Hybrid robust predictive optimization method of power system dispatch
Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY
2011-08-02
A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.
Heuristic Optimization for the Discrete Virtual Power Plant Dispatch Problem
DEFF Research Database (Denmark)
Petersen, Mette Kirschmeyer; Hansen, Lars Henrik; Bendtsen, Jan Dimon
2014-01-01
We consider a Virtual Power Plant, which is given the task of dispatching a fluctuating power supply to a portfolio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the Discrete Virtual Power Plant Dispatch...... Problem. First NP-completeness of the Discrete Virtual Power Plant Dispatch Problem is proved formally. We then proceed to develop tailored versions of the meta-heuristic algorithms Hill Climber and Greedy Randomized Adaptive Search Procedure (GRASP). The algorithms are tuned and tested on portfolios...... of varying sizes. We find that all the tailored algorithms perform satisfactorily in the sense that they are able to find sub-optimal, but usable, solutions to very large problems (on the order of 10 5 units) at computation times on the scale of just 10 seconds, which is far beyond the capabilities...
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
which are related to electrical system topology. This paper proposed an optimized power dispatch strategy (OPD) for minimizing the levelized production cost (LPC) of a wind farm. Particle swarm optimization (PSO) is employed to obtain final solution for the optimization problem. Both regular shape......Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...... and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy....
Virtual power plant mid-term dispatch optimization
International Nuclear Information System (INIS)
Pandžić, Hrvoje; Kuzle, Igor; Capuder, Tomislav
2013-01-01
Highlights: ► Mid-term virtual power plant dispatching. ► Linear modeling. ► Mixed-integer linear programming applied to mid-term dispatch scheduling. ► Operation profit maximization combining bilateral contracts and the day-ahead market. -- Abstract: Wind power plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind power plants and other non-dispatchable power sources are combined with dispatchable power sources forming a virtual power plant. This paper considers a weekly self-scheduling of a virtual power plant composed of intermittent renewable sources, storage system and a conventional power plant. On the one hand, the virtual power plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly virtual power plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind power and solar power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional power plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
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Kanagasabai Lenin
2015-03-01
Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Energy and ancillary service dispatch through dynamic optimal power flow
International Nuclear Information System (INIS)
Costa, A.L.; Costa, A. Simoes
2007-01-01
This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system. (author)
Optimal dispatch strategy for the agile virtual power plant
DEFF Research Database (Denmark)
Petersen, Mette Højgaard; Bendtsen, Jan Dimon; Stoustrup, Jakob
2012-01-01
The introduction of large ratios of renewable energy into the existing power system is complicated by the inherent variability of production technologies, which harvest energy from wind, sun and waves. Fluctuations of renewable power production can be predicted to some extent, but the assumption...... of perfect prediction is unrealistic. This paper therefore introduces the Agile Virtual Power Plant. The Agile Virtual Power Plant assumes that the base load production planning based on best available knowledge is already given, so imbalances cannot be predicted. Consequently the Agile Virtual Power Plant...... attempts to preserve maneuverability (stay agile) rather than optimize performance according to predictions. In this paper the imbalance compensation problem for an Agile Virtual Power Plant is formulated. It is proved formally, that when local units are power and energy constrained integrators a dispatch...
Chinese National Condition Based Power Dispatching Optimization in Microgrids
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Gang Chen
2018-01-01
Full Text Available This paper proposed a study on the power dispatching optimization in the microgrid aiming at Chinese national condition based on PSO algorithm. The whole work is on the basis of the weighted factor variation of the objective function due to different weather conditions. Three cases including the good contamination-diffusing weather condition, the smog weather condition, and the normal condition are considered, respectively. In the case of smog weather, the new energy generation and the battery system will be all out to use as less power as possible from the primary grid so that the pollution produced by coal consumption in the thermal power plants can be upmost reduced. However, in the case of perfect contamination-diffusing weather, the battery is not used to reserve its lifetime, while a large amount of exchanged power from the primary grid is used to obtain a most economic-efficient effect. In normal condition, the power dispatching is performed in a most balanced way considering not only the cost but also the environmental management. The case study in Suzhou Industrial Part confirms the effectiveness of the proposed method in this paper.
Optimal dispatch in dynamic security constrained open power market
International Nuclear Information System (INIS)
Singh, S.N.; David, A.K.
2002-01-01
Power system security is a new concern in the competitive power market operation, because the integration of the system controller and the generation owner has been broken. This paper presents an approach for dynamic security constrained optimal dispatch in restructured power market environment. The transient energy margin using transient energy function (TEF) approach has been used to calculate the stability margin of the system and a hybrid method is applied to calculate the approximate unstable equilibrium point (UEP) that is used to calculate the exact UEP and thus, the energy margin using TEF. The case study results illustrated on two systems shows that the operating mechanisms are compatible with the new business environment. (author)
Reactive power dispatch considering voltage stability with seeker optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Dai, Chaohua; Chen, Weirong; Zhang, Xuexia [The School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031 (China); Zhu, Yunfang [Department of Computer and Communication Engineering, E' mei Campus, Southwest Jiaotong University, E' mei 614202 (China)
2009-10-15
Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (GAs), differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of GAs, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem. (author)
A Three-Stage Optimal Approach for Power System Economic Dispatch Considering Microgrids
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Wei-Tzer Huang
2016-11-01
Full Text Available The inclusion of microgrids (MGs in power systems, especially distribution-substation-level MGs, significantly affects power systems because of the large volumes of import and export power flows. Consequently, power dispatch has become complicated, and finding an optimal solution is difficult. In this study, a three-stage optimal power dispatch model is proposed to solve such dispatch problems. In the proposed model, the entire power system is divided into two parts, namely, the main power grid and MGs. The optimal power dispatch problem is resolved on the basis of multi-area concepts. In stage I, the main power system economic dispatch (ED problem is solved by sensitive factors. In stage II, the optimal power dispatches of the local MGs are addressed via an improved direct search method. In stage III, the incremental linear models for the entire power system can be established on the basis of the solutions of the previous two stages and can be subjected to linear programming to determine the optimal reschedules from the original dispatch solutions. The proposed method is coded using Matlab and tested by utilizing an IEEE 14-bus test system to verify its feasibility and accuracy. Results demonstrated that the proposed approach can be used for the ED of power systems with MGs as virtual power plants.
Optimized dispatch of wind farms with power control capability for power system restoration
DEFF Research Database (Denmark)
Xie, Yunyun; Liu, Changsheng; Wu, Qiuwei
2017-01-01
As the power control technology of wind farms develops, the output power of wind farms can be constant, which makes it possible for wind farms to participate in power system restoration. However, due to the uncertainty of wind energy, the actual output power can’t reach a constant dispatch power...... in all time intervals, resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits. Therefore, it is necessary to optimize the dispatch of wind farms participating in power system restoration. Considering that the probability...... distribution function (PDF) of transient power sags is hard to obtain, a robust optimization model is proposed in this paper, which can maximize the output power of wind farms participating in power system restoration. Simulation results demonstrate that the security constraints of the restored system can...
The Optimal Dispatch of a Power System Containing Virtual Power Plants under Fog and Haze Weather
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Yajing Gao
2016-01-01
Full Text Available With the growing influence of fog and haze (F-H weather and the rapid development of distributed energy resources (DERs and smart grids, the concept of the virtual power plant (VPP employed in this study would help to solve the dispatch problem caused by multiple DERs connected to the power grid. The effects of F-H weather on photovoltaic output forecast, load forecast and power system dispatch are discussed according to real case data. The wavelet neural network (WNN model was employed to predict photovoltaic output and load, considering F-H weather, based on the idea of “similar days of F-H”. The multi-objective optimal dispatch model of a power system adopted in this paper contains several VPPs and conventional power plants, under F-H weather, and the mixed integer linear programming (MILP and the Yalmip toolbox of MATLAB were adopted to solve the dispatch model. The analysis of the results from a case study proves the validity and feasibility of the model and the algorithms.
Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem
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Kanagasabai Lenin
2015-04-01
Full Text Available In this paper, a novel approach Modified Monkey optimization (MMO algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Parallel dispatch: a new paradigm of electrical power system dispatch
Energy Technology Data Exchange (ETDEWEB)
Zhang, Jun Jason; Wang, Fei-Yue; Wang, Qiang; Hao, Dazhi; Yang, Xiaojing; Gao, David Wenzhong; Zhao, Xiangyang; Zhang, Yingchen
2018-01-01
Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus, the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids, extend system operators U+02BC capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.
A fast and optimized dynamic economic load dispatch for large scale power systems
International Nuclear Information System (INIS)
Musse Mohamud Ahmed; Mohd Ruddin Ab Ghani; Ismail Hassan
2000-01-01
This paper presents Lagrangian Multipliers (LM) and Linear Programming (LP) based dynamic economic load dispatch (DELD) solution for large-scale power system operations. It is to minimize the operation cost of power generation. units subject to the considered constraints. After individual generator units are economically loaded and periodically dispatched, fast and optimized DELD has been achieved. DELD with period intervals has been taken into consideration The results found from the algorithm based on LM and LP techniques appear to be modest in both optimizing the operation cost and achieving fast computation. (author)
Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements
International Nuclear Information System (INIS)
Liu, Fan; Bie, Zhaohong; Liu, Shiyu; Ding, Tao
2017-01-01
Highlights: • Analyzing zonal reserve requirements for wind integrated power system. • Modeling day-ahead optimal dispatch solved by chance constrained programming theory. • Determining optimal zonal reserve demand with minimum confidence interval. • Analyzing numerical results on test and large-scale real-life power systems. - Abstract: Large-scale integration of renewable power presents a great challenge for day-ahead dispatch to manage renewable resources while provide available reserve for system security. Considering zonal reserve is an effective way to ensure reserve deliverability when network congested, a random day-ahead dispatch optimization of wind integrated power system for a least operational cost is modeled including zonal reserve requirements and N − 1 security constraints. The random model is transformed into a deterministic one based on the theory of chance constrained programming and a determination method of optimal zonal reserve demand is proposed using the minimum confidence interval. After solving the deterministic model, the stochastic simulation is conducted to verify the validity of solution. Numerical tests and results on the IEEE 39 bus system and a large-scale real-life power system demonstrate the optimal day-ahead dispatch scheme is available and the proposed method is effective for improving reserve deliverability and reducing load shedding after large-capacity power outage.
Optimal Dispatch of Unreliable Electric Grid-Connected Diesel Generator-Battery Power Systems
Xu, D.; Kang, L.
2015-06-01
Diesel generator (DG)-battery power systems are often adopted by telecom operators, especially in semi-urban and rural areas of developing countries. Unreliable electric grids (UEG), which have frequent and lengthy outages, are peculiar to these regions. DG-UEG-battery power system is an important kind of hybrid power system. System dispatch is one of the key factors to hybrid power system integration. In this paper, the system dispatch of a DG-UEG-lead acid battery power system is studied with the UEG of relatively ample electricity in Central African Republic (CAR) and UEG of poor electricity in Congo Republic (CR). The mathematical models of the power system and the UEG are studied for completing the system operation simulation program. The net present cost (NPC) of the power system is the main evaluation index. The state of charge (SOC) set points and battery bank charging current are the optimization variables. For the UEG in CAR, the optimal dispatch solution is SOC start and stop points 0.4 and 0.5 that belong to the Micro-Cycling strategy and charging current 0.1 C. For the UEG in CR, the optimal dispatch solution is of 0.1 and 0.8 that belongs to the Cycle-Charging strategy and 0.1 C. Charging current 0.1 C is suitable for both grid scenarios compared to 0.2 C. It makes the dispatch strategy design easier in commercial practices that there are a few very good candidate dispatch solutions with system NPC values close to that of the optimal solution for both UEG scenarios in CAR and CR.
Directory of Open Access Journals (Sweden)
Jun Yang
2015-08-01
Full Text Available The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.
Optimization Strategy for Economic Power Dispatch Utilizing Retired EV Batteries as Flexible Loads
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Shubo Hu
2018-06-01
Full Text Available With the increasing penetration of new and renewable energy, incorporating variable adjustable power elements on the demand side is of particular interest. The utilization of batteries as flexible loads is a hot research topic. Lithium-ion batteries are key components in electric vehicles (EVs in terms of capital cost, mass and size. They are retired after around 5 years of service, but still retain up to 80% of their nominal capacity. Disposal of waste batteries will become a significant issue for the automotive industry in the years to come. This work proposes the use of the second life of these batteries as flexible loads to participate in the economic power dispatch. The characteristics of second life batteries (SLBs are varied and diverse, requiring a new optimization strategy for power dispatch at the system level. In this work, SLBs are characterized and their operating curves are obtained analytically for developing an economic power dispatch model involving wind farms and second life batteries. In addition, a dispatch strategy is developed to reduce the dispatch complex brought by the disperse spatial and time distribution of EVs and decrease the system operating cost by introducing incentive and penalty costs in regulating the EV performance. In theory, SLBs are utilized to reduce the peak-valley difference of power loads and to stabilize the power system. Test results based on a ten-unit power system have verified the effectiveness of the proposed dispatch model and the economic benefit of utilizing SLBs as flexible loads in power systems. This work may provide a viable solution to the disposal of waste batteries from EVs and to the stable operation of fluctuating power systems incorporating stochastic renewable energy.
Optimized dispatch in a first-principles concentrating solar power production model
Energy Technology Data Exchange (ETDEWEB)
Wagner, Michael J.; Newman, Alexandra M.; Hamilton, William T.; Braun, Robert J.
2017-10-01
Concentrating solar power towers, which include a steam-Rankine cycle with molten salt thermal energy storage, is an emerging technology whose maximum effectiveness relies on an optimal operational and dispatch policy. Given parameters such as start-up and shut-down penalties, expected electricity price profiles, solar availability, and system interoperability requirements, this paper seeks a profit-maximizing solution that determines start-up and shut-down times for the power cycle and solar receiver, and the times at which to dispatch stored and instantaneous quantities of energy over a 48-h horizon at hourly fidelity. The mixed-integer linear program (MIP) is subject to constraints including: (i) minimum and maximum rates of start-up and shut-down, (ii) energy balance, including energetic state of the system as a whole and its components, (iii) logical rules governing the operational modes of the power cycle and solar receiver, and (iv) operational consistency between time periods. The novelty in this work lies in the successful integration of a dispatch optimization model into a detailed techno-economic analysis tool, specifically, the National Renewable Energy Laboratory's System Advisor Model (SAM). The MIP produces an optimized operating strategy, historically determined via a heuristic. Using several market electricity pricing profiles, we present comparative results for a system with and without dispatch optimization, indicating that dispatch optimization can improve plant profitability by 5-20% and thereby alter the economics of concentrating solar power technology. While we examine a molten salt power tower system, this analysis is equally applicable to the more mature concentrating solar parabolic trough system with thermal energy storage.
A simple two stage optimization algorithm for constrained power economic dispatch
International Nuclear Information System (INIS)
Huang, G.; Song, K.
1994-01-01
A simple two stage optimization algorithm is proposed and investigated for fast computation of constrained power economic dispatch control problems. The method is a simple demonstration of the hierarchical aggregation-disaggregation (HAD) concept. The algorithm first solves an aggregated problem to obtain an initial solution. This aggregated problem turns out to be classical economic dispatch formulation, and it can be solved in 1% of overall computation time. In the second stage, linear programming method finds optimal solution which satisfies power balance constraints, generation and transmission inequality constraints and security constraints. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that the two stage method obtains average speedup ratio 10.64 as compared to classical LP-based method
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors...... leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...... the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find...
Fatigue Load Sensitivity Based Optimal Active Power Dispatch For Wind Farms
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun
2017-01-01
This paper proposes an optimal active power dispatch algorithm for wind farms based on Wind Turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power...... sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions...
DAILY SCHEDULING OF SMALL HYDRO POWER PLANTS DISPATCH WITH MODIFIED PARTICLES SWARM OPTIMIZATION
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Sinvaldo Rodrigues Moreno
2015-04-01
Full Text Available This paper presents a new approach for short-term hydro power scheduling of reservoirs using an algorithm-based Particle Swarm Optimization (PSO. PSO is a population-based algorithm designed to find good solutions to optimization problems, its characteristics have encouraged its adoption to tackle a variety of problems in different fields. In this paper the authors consider an optimization problem related to a daily scheduling of small hydro power dispatch. The goal is construct a feasible solution that maximize the cascade electricity production, following the environmental constraints and water balance. The paper proposes an improved Particle Swarm Optimization (PSO algorithm, which takes advantage of simplicity and facility of implementation. The algorithm was successfully applied to the optimization of the daily schedule strategies of small hydro power plants, considering maximum water utilization and all constraints related to simultaneous water uses. Extensive computational tests and comparisons with other heuristics methods showed the effectiveness of the proposed approach.
Networked and Distributed Control Method with Optimal Power Dispatch for Islanded Microgrids
DEFF Research Database (Denmark)
Li, Qiang; Peng, Congbo; Chen, Minyou
2017-01-01
of controllable agents. The distributed control laws derived from the first subgraph guarantee the supply-demand balance, while further control laws from the second subgraph reassign the outputs of controllable distributed generators, which ensure active and reactive power are dispatched optimally. However...... according to our proposition. Finally, the method is evaluated over seven cases via simulation. The results show that the system performs as desired, even if environmental conditions and load demand fluctuate significantly. In summary, the method can rapidly respond to fluctuations resulting in optimal...
Optimal economic dispatch of FC-CHP based heat and power micro-grids
International Nuclear Information System (INIS)
Nazari-Heris, Morteza; Abapour, Saeed; Mohammadi-Ivatloo, Behnam
2017-01-01
Highlights: • The multi objective economic/environmental heat and power MG dispatch is solved. • The heat and power MG include FC, CHP, boiler, storage system, and heat buffer tank. • Multi objective scheduling of heat and power MG is solved using ε-constraint method. • DR program is employed in the stochastic programming of heat and power MG dispatch. • The uncertainties for load demand and price signals are taken into account. - Abstract: Micro-grids (MGs) are introduced as a solution for distributed energy resource (DER) units and energy storage systems (ESSs) to participate in providing the required electricity demand of controllable and non-controllable loads. In this paper, the authors study the short-term scheduling of grid-connected industrial heat and power MG which contains a fuel cell (FC) unit, combined heat and power (CHP) generation units, power-only unit, boiler, battery storage system, and heat buffer tank. The paper is aimed to solve the multi-objective MG dispatch problem containing cost and emission minimization with the considerations of demand response program and uncertainties. A probabilistic framework based on a scenario method, which is considered for load demand and price signals, is employed to overcome the uncertainties in the optimal energy management of the MG. In order to reduce operational cost, time-of-use rates of demand response programs have been modeled, and the effects of such programs on the load profile have been discussed. To solve the multi-objective optimization problem, the ε-constraint method is used and a fuzzy satisfying approach has been employed to select the best compromise solution. Three cases are studied in this research to confirm the performance of the proposed method: islanded mode, grid-connected mode, and the impact of time of the use-demand response program on MG scheduling.
Directory of Open Access Journals (Sweden)
Jie Yu
2015-01-01
Full Text Available Virtual power plant (VPP is an aggregation of multiple distributed generations, energy storage, and controllable loads. Affected by natural conditions, the uncontrollable distributed generations within VPP, such as wind and photovoltaic generations, are extremely random and relative. Considering the randomness and its correlation of uncontrollable distributed generations, this paper constructs the chance constraints stochastic optimal dispatch of VPP including stochastic variables and its random correlation. The probability distributions of independent wind and photovoltaic generations are described by empirical distribution functions, and their joint probability density model is established by Frank-copula function. And then, sample average approximation (SAA is applied to convert the chance constrained stochastic optimization model into a deterministic optimization model. Simulation cases are calculated based on the AIMMS. Simulation results of this paper mathematic model are compared with the results of deterministic optimization model without stochastic variables and stochastic optimization considering stochastic variables but not random correlation. Furthermore, this paper analyzes how SAA sampling frequency and the confidence level influence the results of stochastic optimization. The numerical example results show the effectiveness of the stochastic optimal dispatch of VPP considering the randomness and its correlations of distributed generations.
A Parallel Adaptive Particle Swarm Optimization Algorithm for Economic/Environmental Power Dispatch
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Jinchao Li
2012-01-01
Full Text Available A parallel adaptive particle swarm optimization algorithm (PAPSO is proposed for economic/environmental power dispatch, which can overcome the premature characteristic, the slow-speed convergence in the late evolutionary phase, and lacking good direction in particles’ evolutionary process. A search population is randomly divided into several subpopulations. Then for each subpopulation, the optimal solution is searched synchronously using the proposed method, and thus parallel computing is realized. To avoid converging to a local optimum, a crossover operator is introduced to exchange the information among the subpopulations and the diversity of population is sustained simultaneously. Simulation results show that the proposed algorithm can effectively solve the economic/environmental operation problem of hydropower generating units. Performance comparisons show that the solution from the proposed method is better than those from the conventional particle swarm algorithm and other optimization algorithms.
Solving multiobjective optimal reactive power dispatch using modified NSGA-II
Energy Technology Data Exchange (ETDEWEB)
Jeyadevi, S.; Baskar, S.; Babulal, C.K.; Willjuice Iruthayarajan, M. [Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu 625 015 (India)
2011-02-15
This paper addresses an application of modified NSGA-II (MNSGA-II) by incorporating controlled elitism and dynamic crowding distance (DCD) strategies in NSGA-II to multiobjective optimal reactive power dispatch (ORPD) problem by minimizing real power loss and maximizing the system voltage stability. To validate the Pareto-front obtained using MNSGA-II, reference Pareto-front is generated using multiple runs of single objective optimization with weighted sum of objectives. For simulation purposes, IEEE 30 and IEEE 118 bus test systems are considered. The performance of MNSGA-II, NSGA-II and multiobjective particle swarm optimization (MOPSO) approaches are compared with respect to multiobjective performance measures. TOPSIS technique is applied on obtained non-dominated solutions to determine best compromise solution (BCS). Karush-Kuhn-Tucker (KKT) conditions are also applied on the obtained non-dominated solutions to substantiate a claim on optimality. Simulation results are quite promising and the MNSGA-II performs better than NSGA-II in maintaining diversity and authenticates its potential to solve multiobjective ORPD effectively. (author)
Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties
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Vahid Amir
2017-11-01
Full Text Available A microgrid (MG is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.
Jihong, Qu
2014-01-01
Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear nature involved in the complex multiobjective scheduling model; therefore, to achieve accurate solution to such complex problem is a very difficult task. This paper presents an interval programming model with 2-step optimization algorithm to solve multiobjective dispatching. Initially, we represented the future data into interval numbers and simplified the object function to a linear programming problem to search the feasible and preliminary solutions to construct the Pareto set. Then the simulated annealing method was used to search the optimal solution of initial model. Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision. PMID:24895663
Ren, Kun; Jihong, Qu
2014-01-01
Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear nature involved in the complex multiobjective scheduling model; therefore, to achieve accurate solution to such complex problem is a very difficult task. This paper presents an interval programming model with 2-step optimization algorithm to solve multiobjective dispatching. Initially, we represented the future data into interval numbers and simplified the object function to a linear programming problem to search the feasible and preliminary solutions to construct the Pareto set. Then the simulated annealing method was used to search the optimal solution of initial model. Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision.
Commitment and dispatch of heat and power units via affinely adjustable robust optimization
DEFF Research Database (Denmark)
Zugno, Marco; Morales González, Juan Miguel; Madsen, Henrik
2016-01-01
compromising computational tractability. We perform an extensive numerical study based on data from the Copenhagen area in Denmark, which highlights important features of the proposed model. Firstly, we illustrate commitment and dispatch choices that increase conservativeness in the robust optimization...... and conservativeness of the solution. Finally, we perform a thorough comparison with competing models based on deterministic optimization and stochastic programming. (C) 2016 Elsevier Ltd. All rights reserved....
Optimal dynamic economic dispatch of generation: A review
International Nuclear Information System (INIS)
Xia, X.; Elaiw, A.M.
2010-01-01
This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported. (author)
Srikantha, Pirathayini
Today's electric grid is rapidly evolving to provision for heterogeneous system components (e.g. intermittent generation, electric vehicles, storage devices, etc.) while catering to diverse consumer power demand patterns. In order to accommodate this changing landscape, the widespread integration of cyber communication with physical components can be witnessed in all tenets of the modern power grid. This ubiquitous connectivity provides an elevated level of awareness and decision-making ability to system operators. Moreover, devices that were typically passive in the traditional grid are now `smarter' as these can respond to remote signals, learn about local conditions and even make their own actuation decisions if necessary. These advantages can be leveraged to reap unprecedented long-term benefits that include sustainable, efficient and economical power grid operations. Furthermore, challenges introduced by emerging trends in the grid such as high penetration of distributed energy sources, rising power demands, deregulations and cyber-security concerns due to vulnerabilities in standard communication protocols can be overcome by tapping onto the active nature of modern power grid components. In this thesis, distributed constructs in optimization and game theory are utilized to design the seamless real-time integration of a large number of heterogeneous power components such as distributed energy sources with highly fluctuating generation capacities and flexible power consumers with varying demand patterns to achieve optimal operations across multiple levels of hierarchy in the power grid. Specifically, advanced data acquisition, cloud analytics (such as prediction), control and storage systems are leveraged to promote sustainable and economical grid operations while ensuring that physical network, generation and consumer comfort requirements are met. Moreover, privacy and security considerations are incorporated into the core of the proposed designs and these
International Nuclear Information System (INIS)
Ji, Ling; Huang, Guo-He; Huang, Lu-Cheng; Xie, Yu-Lei; Niu, Dong-Xiao
2016-01-01
High penetration of wind power generation and deregulated electricity market brings a great challenge to the electricity system operators. It is crucial to make optimal strategy among various generation units and spinning reserve for supporting the system safety operation. By integrating interval two-stage programming and stochastic robust programming, this paper proposes a novel robust model for day-ahead dispatch and risk-aversion management under uncertainties. In the proposed model, the uncertainties are expressed as interval values with different scenario probability. The proposed method requires low computation, and still retains the complete information. A case study is to validate the effectiveness of this approach. Facing the uncertainties of future demand and electricity price, the system operators need to make optimal dispatch strategy for thermal power units and wind turbine, and arrange proper spinning reserve and flexible demand response program to mitigate wind power forecasting error. The optimal strategies provide the system operators with better trade-off between the maximum benefits and the minimum system risk. In additional, two different market rules are compared. The results show that extra financial penalty for the wind power dispatch deviation is another efficient way to enhance the risk consciousness of decision makers and lead to more conservative strategy. - Highlights: • An inexact two-stage stochastic robust programming model for electricity system with wind power penetration. • Uncertainties expressed as discrete intervals and probability distributions. • Demand response program was introduced to adjust the deviation in real-time market. • Financial penalty for imbalance risk from wind power generation was evaluated.
International Nuclear Information System (INIS)
Liao, H.L.; Wu, Q.H.; Li, Y.Z.; Jiang, L.
2014-01-01
Highlights: • Apply multi-objective optimization by learning automata to power system. • Sequentially dimensional search and state memory are incorporated. • Track dispatch under significant variations of wind power and load demand. • Good performance in terms of accuracy, distribution and computation time. - Abstract: This paper is concerned with using multi-objective optimization by learning automata (MOLA) for economic emission dispatching in the environment where wind power and loads vary. With its capabilities of sequentially dimensional search and state memory, MOLA is able to find accurate solutions while satisfying two objectives: fuel cost coupled with environmental emission and voltage stability. Its searching quality and efficiency are measured using the hypervolume indicator for investigating the quality of Pareto front, and demonstrated by tracking the dispatch solutions under significant variations of wind power and load demand. The simulation studies are carried out on the modified midwestern American electric power system and the IEEE 118-bus test system, in which wind power penetration and load variations present. Evaluated on these two power systems, MOLA is fully compared with multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm II (NSGA-II). The simulation results have shown the superiority of MOLA over NAGA-II and MOEA/D, as it is able to obtain more accurate and widely distributed Pareto fronts. In the dynamic environment where the operation condition of both wind speed and load demand varies, MOLA outperforms the other two algorithms, with respect to the tracking ability and accuracy of the solutions
International Nuclear Information System (INIS)
Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan
2014-01-01
Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a
Economic dispatch optimization algorithm based on particle diffusion
International Nuclear Information System (INIS)
Han, Li; Romero, Carlos E.; Yao, Zheng
2015-01-01
Highlights: • A dispatch model that considers fuel, emissions control and wind power cost is built. • An optimization algorithm named diffusion particle optimization (DPO) is proposed. • DPO was used to analyze the impact of wind power risk and emissions on dispatch. - Abstract: Due to the widespread installation of emissions control equipment in fossil fuel-fired power plants, the cost of emissions control needs to be considered, together with the plant fuel cost, in providing economic power dispatch of those units to the grid. On the other hand, while using wind power decreases the overall power generation cost for the power grid, it poses a risk to a traditional grid, because of its inherent stochastic characteristics. Therefore, an economic dispatch optimization model needs to consider all of the fuel cost, emissions control cost and wind power cost for each of the generating unit conforming the fleet that meets the required grid power demand. In this study, an optimization algorithm referred as diffusion particle optimization (DPO) is proposed to solve such complex optimization problem. In this algorithm, Brownian motion theory is used to guide the movement of particles so that the particles can search for an optimal solution over the entire definition region. Several benchmark functions and power grid system data were used to test the performance of DPO, and compared to traditional algorithms used for economic dispatch optimization, such as, particle swarm optimization and artificial bee colony algorithm. It was found that DPO has less probability to be trapped in local optimums. According to results of different power systems DPO was able to find economic dispatch solutions with lower costs. DPO was also used to analyze the impact of wind power risk and fossil unit emissions coefficients on power dispatch. The result are encouraging for the use of DPO as a dynamic tool for economic dispatch of the power grid.
Optimized Power Dispatch in Wind Farms for Power Maximizing Considering Fatigue Loads
DEFF Research Database (Denmark)
Zhang, Baohua; N. Soltani, Mohsen; Hu, Weihao
2018-01-01
Wake effects in a wind farm (WF) include the wind velocity deficit and added turbulence. The wind velocity deficit may bring significant loss of the wind power and the added turbulence may cause extra fatigue load on the wind turbines (WTs). Inclusion of the wake effects in the wind farm control...... at a series of turbulence intensity, mean wind speed and active power reference to form a lookup table, which is used for the WF control. The proposed strategy is compared with WT MPPT control strategy and WF MPPT control strategy. The simulation results show the effectiveness of the proposed strategy....
Directory of Open Access Journals (Sweden)
Umamaheswari Krishnasamy
2014-01-01
Full Text Available Dynamic economic dispatch problem (DEDP for a multiple fuel power plant is a nonlinear and nonsmooth optimization problem when valve-point effects, multifuel effects, and ramp-rate limits are considered. Additionally wind energy is also integrated with the DEDP to supply the load for effective utilization of the renewable energy. Since the wind power may not be predicted, a radial basis function network (RBFN is presented to forecast a one-hour-ahead wind power to plan and ensure a reliable power supply. In this paper, a refined teaching-learning based optimization (TLBO is applied to minimize the overall cost of operation of wind-thermal power system. The TLBO is refined by integrating the sequential quadratic programming (SQP method to fine-tune the better solutions whenever discovered by the former method. To demonstrate the effectiveness of the proposed hybrid TLBO-SQP method, a standard DEDP and one practical DEDP with wind power forecasted are tested based on the practical information of wind speed. Simulation results validate the proposed methodology which is reasonable by ensuring quality solution throughout the scheduling horizon for secure operation of the system.
Opposition-Based Improved PSO for Optimal Reactive Power Dispatch and Voltage Control
Directory of Open Access Journals (Sweden)
Shengrang Cao
2015-01-01
Full Text Available An opposition-based improved particle swarm optimization algorithm (OIPSO is presented for solving multiobjective reactive power optimization problem. OIPSO uses the opposition learning to improve search efficiency, adopts inertia weight factors to balance global and local exploration, and takes crossover and mutation and neighborhood model strategy to enhance population diversity. Then, a new multiobjective model is built, which includes system network loss, voltage dissatisfaction, and switching operation. Based on the market cost prices, objective functions are converted to least-cost model. In modeling process, switching operation cost is described according to the life cycle cost of transformer, and voltage dissatisfaction penalty is developed considering different voltage quality requirements of customers. The experiment is done on the new mathematical model. Through the simulation of IEEE 30-, 118-bus power systems, the results prove that OIPSO is more efficient to solve reactive power optimization problems and the model is more accurate to reflect the real power system operation.
Multi-objective optimal dispatch of distributed energy resources
Longe, Ayomide
This thesis is composed of two papers which investigate the optimal dispatch for distributed energy resources. In the first paper, an economic dispatch problem for a community microgrid is studied. In this microgrid, each agent pursues an economic dispatch for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, a simple market structure is introduced as a framework for energy trades in a small community microgrid such as the Solar Village. It was found that both sellers and buyers benefited by participating in this market. In the second paper, Semidefinite Programming (SDP) for convex relaxation of power flow equations is used for optimal active and reactive dispatch for Distributed Energy Resources (DER). Various objective functions including voltage regulation, reduced transmission line power losses, and minimized reactive power charges for a microgrid are introduced. Combinations of these goals are attained by solving a multiobjective optimization for the proposed ORPD problem. Also, both centralized and distributed versions of this optimal dispatch are investigated. It was found that SDP made the optimal dispatch faster and distributed solution allowed for scalability.
Directory of Open Access Journals (Sweden)
Mehmet KURBAN
2007-03-01
Full Text Available In this paper, the economic dispatch and optimal power flow (OPF methods for the purpose of supplying the load demand with minimum cost is used for 22-bus 380-kV power system in Turkey which consists of 8 thermal plants operated by EUAS (Electricity Generation Co. Inc.and the results found are analyzed comparatively. The results of analysis are given in tables and figures. The analysis made is implemented by the software using MATLAB®. Furthermore, the software can be used for different power systems by using the graphical user interface (GUI. All data used in this study is taken from TEIAS (Transmission System Operator of Turkey and EUAS.
Dispatchable Solar Power Plant Project
Energy Technology Data Exchange (ETDEWEB)
Price, Henry [Solar Dynamics LLC, Broomfield, CO (United States)
2018-01-31
As penetration of intermittent renewable power increases, grid operators must manage greater variability in the supply and demand on the grid. One result is that utilities are planning to build many new natural gas peaking power plants that provide added flexibility needed for grid management. This report discusses the development of a dispatchable solar power (DSP) plant that can be used in place of natural gas peakers. Specifically, a new molten-salt tower (MST) plant has been developed that is designed to allow much more flexible operation than typically considered in concentrating solar power plants. As a result, this plant can provide most of the capacity and ancillary benefits of a conventional natural gas peaker plant but without the carbon emissions. The DSP system presented was designed to meet the specific needs of the Arizona Public Service (APS) utility 2017 peaking capacity request for proposals (RFP). The goal of the effort was to design a MST peaker plant that had the operational capabilities required to meet the peaking requirements of the utility and be cost competitive with the natural gas alternative. The effort also addresses many perceived barriers facing the commercial deployment of MST technology in the US today. These include MST project development issues such as permitting, avian impacts, visual impacts of tower CSP projects, project schedule, and water consumption. The DSP plant design is based on considerable analyses using sophisticated solar system design tools and in-depth preliminary engineering design. The resulting DSP plant design uses a 250 MW steam power cycle, with solar field designed to fit on a square mile plot of land that has a design point thermal rating of 400 MWt. The DSP plant has an annual capacity factor of about 16% tailored to deliver greater than 90% capacity during the critical Arizona summer afternoon peak. The table below compares the All-In energy cost and capacity payment of conventional combustion turbines
Economic dispatch using particle swarm optimization. A review
International Nuclear Information System (INIS)
Mahor, Amita; Rangnekar, Saroj; Prasad, Vishnu
2009-01-01
Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Meta-heuristic optimization techniques especially particle swarm optimization (PSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of PSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper. (author)
Energy network dispatch optimization under emergency of local energy shortage
International Nuclear Information System (INIS)
Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang
2012-01-01
The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.
Coordinated Active Power Dispatch for a Microgrid via Distributed Lambda Iteration
DEFF Research Database (Denmark)
Hu, Jianqiang; Z. Q. Chen, Michael; Cao, Jinde
2017-01-01
A novel distributed optimal dispatch algorithm is proposed for coordinating the operation of multiple micro units in a microgrid, which has incorporated the distributed consensus algorithm in multi-agent systems and the -iteration optimization algorithm in economic dispatch of power systems. Spec...
Distributed Generation Dispatch Optimization under Various Electricity Tariffs
Firestone, Ryan; Marnay, Chris
2007-01-01
The on-site generation of electricity can offer building owners and occupiers financial benefits as well as social benefits such as reduced grid congestion, improved energy efficiency, and reduced greenhouse gas emissions. Combined heat and power (CHP), or cogeneration, systems make use of the waste heat from the generator for site heating needs. Real-time optimal dispatch of CHP systems is difficult to determine because of complicated electricity tariffs and uncertainty in CHP equipment...
A Method for Optimal Load Dispatch of a Multi-zone Power System with Zonal Exchange Constraints
Hazarika, Durlav; Das, Ranjay
2018-04-01
This paper presented a method for economic generation scheduling of a multi-zone power system having inter zonal operational constraints. For this purpose, the generator rescheduling for a multi area power system having inter zonal operational constraints has been represented as a two step optimal generation scheduling problem. At first, the optimal generation scheduling has been carried out for the zone having surplus or deficient generation with proper spinning reserve using co-ordination equation. The power exchange required for the deficit zones and zones having no generation are estimated based on load demand and generation for the zone. The incremental transmission loss formulas for the transmission lines participating in the power transfer process among the zones are formulated. Using these, incremental transmission loss expression in co-ordination equation, the optimal generation scheduling for the zonal exchange has been determined. Simulation is carried out on IEEE 118 bus test system to examine the applicability and validity of the method.
Directory of Open Access Journals (Sweden)
Chunlai Li
2017-07-01
Full Text Available This paper proposes an energy and reserve joint dispatch model based on a robust optimization approach in real-time electricity markets, considering wind power generation uncertainties as well as zonal reserve constraints under both normal and N-1 contingency conditions. In the proposed model, the operating reserves are classified as regulating reserve and spinning reserve according to the response performance. More specifically, the regulating reserve is usually utilized to reduce the gap due to forecasting errors, while the spinning reserve is commonly adopted to enhance the ability for N-1 contingencies. Since the transmission bottlenecks may inhibit the deliverability of reserve, the zonal placement of spinning reserve is considered in this paper to improve the reserve deliverability under the contingencies. Numerical results on the IEEE 118-bus test system show the effectiveness of the proposed model.
Yang, Chunhua; Deconinck, G; Gui, Weihua; Li, Yonggang
2002-01-01
Depending on varying prices of electricity, an optimal power-dispatching system (OPDS) is developed to minimize the cost of power consumption in the electrochemical process of zinc (EPZ). Due to the complexity of the EPZ, the main factors influencing the power consumption are determined by qualitative analysis, and a series of conditional experiments is conducted to acquire sufficient data, then two backpropagation neural networks are used to describe these relationships quantitatively. An equivalent Hopfield neural network is constructed to solve the optimization problem where a penalty function is introduced into the network energy function so as to meet the equality constraints, and inequality constraints are removed by alteration of the Sigmoid function. This OPDS was put into service in a smeltery in 1998. The cost of power consumption has decreased significantly, the total electrical energy consumption is reduced, and it is also beneficial to balancing the load of the power grid. The actual results show the effectiveness of the OPDS. This paper introduces a successful industrial application and mainly presents how to utilize neural networks to solve particular problems for the real world.
Directory of Open Access Journals (Sweden)
Suresh Chintalapudi Venkata
2015-09-01
Full Text Available In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC. This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
International Nuclear Information System (INIS)
Bahmani-Firouzi, Bahman; Farjah, Ebrahim; Azizipanah-Abarghooee, Rasoul
2013-01-01
Renewable energy resources such as wind power plants are playing an ever-increasing role in power generation. This paper extends the dynamic economic emission dispatch problem by incorporating wind power plant. This problem is a multi-objective optimization approach in which total electrical power generation costs and combustion emissions are simultaneously minimized over a short-term time span. A stochastic approach based on scenarios is suggested to model the uncertainty associated with hourly load and wind power forecasts. A roulette wheel technique on the basis of probability distribution functions of load and wind power is implemented to generate scenarios. As a result, the stochastic nature of the suggested problem is emancipated by decomposing it into a set of equivalent deterministic problem. An improved multi-objective particle swarm optimization algorithm is applied to obtain the best expected solutions for the proposed stochastic programming framework. To enhance the overall performance and effectiveness of the particle swarm optimization, a fuzzy adaptive technique, θ-search and self-adaptive learning strategy for velocity updating are used to tune the inertia weight factor and to escape from local optima, respectively. The suggested algorithm goes through the search space in the polar coordinates instead of the Cartesian one; whereby the feasible space is more compact. In order to evaluate the efficiency and feasibility of the suggested framework, it is applied to two test systems with small and large scale characteristics. - Highlights: ► Formulates multi-objective DEED problem under a stochastic programming framework. ► Considers uncertainties related to forecasted values of load demand and wind power. ► Proposes an interactive fuzzy satisfying method based on the novel FSALPSO. ► Presents a new self-adaptive learning strategy to improve original PSO algorithm
Combined heat and power economic dispatch by harmony search algorithm
Energy Technology Data Exchange (ETDEWEB)
Vasebi, A.; Bathaee, S.M.T. [Power System Research Laboratory, Department of Electrical and Electronic Engineering, K.N.Toosi University of Technology, 322-Mirdamad Avenue West, 19697 Tehran (Iran); Fesanghary, M. [Department of Mechanical Engineering, Amirkabir University of Technology, 424-Hafez Avenue, Tehran (Iran)
2007-12-15
The optimal utilization of multiple combined heat and power (CHP) systems is a complicated problem that needs powerful methods to solve. This paper presents a harmony search (HS) algorithm to solve the combined heat and power economic dispatch (CHPED) problem. The HS algorithm is a recently developed meta-heuristic algorithm, and has been very successful in a wide variety of optimization problems. The method is illustrated using a test case taken from the literature as well as a new one proposed by authors. Numerical results reveal that the proposed algorithm can find better solutions when compared to conventional methods and is an efficient search algorithm for CHPED problem. (author)
Evolution of China's power dispatch principle and the new energy saving power dispatch policy
International Nuclear Information System (INIS)
Ciwei, Gao; Yang, Li
2010-01-01
With social economic reform in the past decades, the power industry of China is gradually evolving from a highly integrated one toward an electricity market, which can be characterized based on the transition of the power dispatch principle. To attract investment in the power generating industry, China introduced non-state-owned power plants to the original system of a highly vertically integrated power industry with annual power generation quota guarantees, which makes the traditional economic dispatch principle not applicable. The newly debuted energy saving power dispatch (ESPD) is an attempt to fully exploit the maximum energy savings and was implemented by an administrative code. Starting in August 2007, the pilot operation of the ESPD was implemented in five provinces, but after two years, it is still not widely applied all over the country. This paper details the transition of China's power dispatch principle with particular attention to its origin and content. Moreover, the factors that influence the ESPD's actual energy saving effect are discussed, as well as the sustainability of the policy. (author)
Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium
Directory of Open Access Journals (Sweden)
Xiao Han
2017-12-01
Full Text Available This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE generation, energy storage systems (ESSs, and thermostatically controlled loads (TCLs. This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibrium of the load curve. Accordingly, we propose a concept of load equilibrium entropy to quantify the overall equilibrium of the load curve and reflect the allocation optimization of electric energy. Based on this entropy, we built a novel multi-objective optimal dispatching model to minimize the operational cost and maximize the load curve equilibrium. To aggregate TCLs into the optimization objective, we introduced the concept of a virtual power plant (VPP and proposed a calculation method for VPP operating characteristics based on the equivalent thermal parameter model and the state-queue control method. The Particle Swarm Optimization algorithm was employed to solve the optimization problems. The simulation results illustrated that the proposed dispatching model can achieve cost reductions of system operations, peak load curtailment, and efficiency improvements, and also verified that the load equilibrium entropy can be used as a novel index of load characteristics.
Dynamic multi-stage dispatch of isolated wind–diesel power systems
DEFF Research Database (Denmark)
Hu, Yu; Morales González, Juan Miguel; Pineda, Salvador
2015-01-01
-stage decision-making model is proposed to determine the diesel power output that minimizes the cost of running and maintaining the wind–diesel power system. Optimized operational decisions for each time period are generated dynamically considering the path-dependent nature of the optimal dispatch policy, given......An optimal dispatch strategy is crucial for an isolated wind–diesel power system to save diesel fuel and maintain the system stability. The uncertainty associated with the stochastic character of the wind is, though, a challenging problem for this optimization. In this paper, a dynamic multi...
Directory of Open Access Journals (Sweden)
Jianwen Ren
2018-04-01
Full Text Available This paper proposes a distributed robust dispatch approach to solve the economic dispatch problem of the interconnected systems with a high proportion of wind power penetration. First of all, the basic principle of synchronous alternating direction method of multipliers (SADMM is introduced to solve the economic dispatch problem of the two interconnected regions. Next, the polyhedron set of the robust optimization method is utilized to describe the wind power output. To adjust the conservativeness of the polyhedron set, an adjustment factor of robust conservativeness is introduced. Subsequently, considering the operation characteristics of the DC tie line between the interconnected regions, an economic dispatch model with a high proportion of wind power penetration is established and parallel iteration based on SADMM is used to solve the model. In each iteration, the optimized power of DC tie lines is exchanged between the regions without requiring the participation of the superior dispatch center. Finally, the validity of the proposed model is verified by the examples of the 2-area 6-node interconnected system and the interconnection of several modified New England 39-node systems. The results show that the proposed model can meet the needs of the independent dispatch of regional power grids, effectively deal with the uncertainty of wind power output, and maximize the wind power consumption under the condition of ensuring the safe operation of the interconnected systems.
Active Power Dispatch Method for a Wind Farm Central Controller Considering Wake Effect
DEFF Research Database (Denmark)
Tian, Jie; Su, Chi; N. Soltani, Mohsen
2014-01-01
With the increasing integration of the wind power into the power system, wind farm are required to be controlled as a single unit and have all the same control tasks as conventional power plants. The wind farm central controller receives control orders from Transmission System Operator (TSO), the...... Optimization (PSO) is used to obtain the optimal wind power for each wind turbine. A case study is carried out. The available wind power of the wind farm was compared between the traditional dispatch method and the proposed dispatch method with the consideration of the wake effect....
Harmony search algorithm for solving combined heat and power economic dispatch problems
Energy Technology Data Exchange (ETDEWEB)
Khorram, Esmaile, E-mail: eskhor@aut.ac.i [Department of Applied Mathematics, Faculty of Mathematics and Computer Science, Amirkabir University of Technology, No. 424, Hafez Ave., 15914 Tehran (Iran, Islamic Republic of); Jaberipour, Majid, E-mail: Majid.Jaberipour@gmail.co [Department of Applied Mathematics, Faculty of Mathematics and Computer Science, Amirkabir University of Technology, No. 424, Hafez Ave., 15914 Tehran (Iran, Islamic Republic of)
2011-02-15
Economic dispatch (ED) is one of the key optimization problems in electric power system operation. The problem grows complex if one or more units produce both power and heat. Combined heat and power economic dispatch (CHPED) problem is a complicated problem that needs powerful methods to solve. This paper presents a harmony search (EDHS) algorithm to solve CHPED. Some standard examples are presented to demonstrate the effectiveness of this algorithm in obtaining the optimal solution. In all cases, the solutions obtained using EDHS algorithm are better than those obtained by other methods.
Directory of Open Access Journals (Sweden)
Abdellatif HAMOUDA
2011-12-01
Full Text Available Economic power dispatch (EPD is one of the main tools for optimal operation and planning of modern power systems. To solve effectively the EPD problem, most of the conventional calculus methods rely on the assumption that the fuel cost characteristic of a generating unit is a continuous and convex function, resulting in inaccurate dispatch. This paper presents the design and application of efficient adaptive differential evolution (ADE algorithm for the solution of the economic power dispatch problem, where the non-convex characteristics of the generators, such us prohibited operating zones and ramp rate limits of the practical generator operation are considered. The 26 bus benchmark test system with 6 units having prohibited operating zones and ramp rate limits was used for testing and validation purposes. The results obtained demonstrate the effectiveness of the proposed method for solving the non-convex economic dispatch problem.
Wind power generation, load management and dispatch
International Nuclear Information System (INIS)
Canazza, V.; Cirillo, M.
2007-01-01
The renewed commitment of the United States and European Union for the promotion of renewable energy sources makes some reflections on the appropriate management of dispatch priority of renewable energy in Italy [it
Risk reserve constrained economic dispatch model with wind power penetration
Energy Technology Data Exchange (ETDEWEB)
Zhou, W.; Sun, H.; Peng, Y. [Department of Electrical and Electronics Engineering, Dalian University of Technology, Dalian, 116024 (China)
2010-12-15
This paper develops a modified economic dispatch (ED) optimization model with wind power penetration. Due to the uncertain nature of wind speed, both overestimation and underestimation of the available wind power are compensated using the up and down spinning reserves. In order to determine both of these two reserve demands, the risk-based up and down spinning reserve constraints are presented considering not only the uncertainty of available wind power, but also the load forecast error and generator outage rates. The predictor-corrector primal-dual interior point method is utilized to solve the proposed ED model. Simulation results of a system with ten conventional generators and one wind farm demonstrate the effectiveness of the proposed method. (authors)
A Wind Farm Active Power Dispatch Strategy for Fatigue Load Reduction
DEFF Research Database (Denmark)
Zhang, Baohua; N. Soltani, Mohsen; Hu, Weihao
2016-01-01
One of the biggest challenges in wind farm management is to cope with requirements from the grid companies and to optimize efficiency and minimize wear on wind turbines. This paper addresses an optimized active power dispatch strategy of a wind farm to reduce the fatigue load of wind turbines, wh...
Dynamic multi-stage dispatch of isolated wind–diesel power systems
International Nuclear Information System (INIS)
Hu, Yu; Morales, Juan M.; Pineda, Salvador; Sánchez, María Jesús; Solana, Pablo
2015-01-01
Highlights: • Optimal decision-making model for isolated hybrid wind–diesel power system is proposed. • Wind power uncertainty and conditional operating cost are considered. • Battery wear cost of the energy storage system is included in the model. • The results are compared with deterministic dispatch strategies. - Abstract: An optimal dispatch strategy is crucial for an isolated wind–diesel power system to save diesel fuel and maintain the system stability. The uncertainty associated with the stochastic character of the wind is, though, a challenging problem for this optimization. In this paper, a dynamic multi-stage decision-making model is proposed to determine the diesel power output that minimizes the cost of running and maintaining the wind–diesel power system. Optimized operational decisions for each time period are generated dynamically considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. A numerical case study is analyzed and it is demonstrated that the proposed stochastic dynamic optimization model significantly outperforms the traditional deterministic dispatch strategies
Directory of Open Access Journals (Sweden)
Sheng Siqing
2015-01-01
Full Text Available Carbon emission characteristics of all kinds of power units are analyzed against the background of the low carbon economy. This paper introduces carbon trading in the dispatching model, gives full consideration to the benefit or cost of carbon emission and introduces carbon emission in the dispatching model as a decision variable so as to achieve the unity of the economy and the environmental protection of the dispatching model. A low carbon economic dispatching model is established based on multiple objectives, such as the lowest thermal power generation cost, the lowest carbon trading cost and the lowest carbon capture power plant operation cost. Load equalization, output constraint of power unit, ramping constraint, spinning reserve constraint and carbon capture efficiency constraint should be taken into account in terms of constraint conditions. The model is solved by the particle swarm optimization based on dynamic exchange and density distance. The fact that the introduction of carbon trading can effectively reduce the level of carbon emission and increase the acceptance level of wind power is highlighted through the comparison of the results of three models’ computational examples. With the carbon trading mechanism, carbon capture power plants with new technologies are able to give full play to the advantage of reducing carbon emission and wind curtailment so as to promote the development of the energy conservation and emission reduction technology and reduce the total cost of the dispatching system.
Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch
Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.
2014-10-01
The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.
Song, Lei; Zhang, Bo
2017-07-01
Nowadays, the grid faces much more challenges caused by wind power and the accessing of electric vehicles (EVs). Based on the potentiality of coordinated dispatch, a model of wind-EVs coordinated dispatch was developed. Then, A bi-level particle swarm optimization algorithm for solving the model was proposed in this paper. The application of this algorithm to 10-unit test system carried out that coordinated dispatch can benefit the power system from the following aspects: (1) Reducing operating costs; (2) Improving the utilization of wind power; (3) Stabilizing the peak-valley difference.
Combined emission economic dispatch of power system including solar photo voltaic generation
International Nuclear Information System (INIS)
Khan, Naveed Ahmed; Awan, Ahmed Bilal; Mahmood, Anzar; Razzaq, Sohail; Zafar, Adnan; Sidhu, Guftaar Ahmed Sardar
2015-01-01
Highlights: • Combined Emission Economic Dispatch Problem has been solved with inclusion of solar power plants. • Mixed Integer Optimization Problem has been solved using Particle Swarm Optimization. • Static and dynamic case studies have been considered. • Clouds effect with 15% and 30% reduced radiations has also been taken into account. • Simulation results prove the effectiveness of proposed model. - Abstract: Reliable and inexpensive electricity provision is one of the significant research objectives since decades. Various Economic Dispatch (ED) methods have been developed in order to address the challenge of continuous and sustainable electricity provision at optimized cost. Rapid escalation of fuel prices, depletion of fossil fuel reserves and environmental concerns have compelled us to incorporate the Renewable Energy (RE) resources in the energy mix. This paper presents Combined Emission Economic Dispatch (CEED) models developed for a system consisting of multiple Photo Voltaic (PV) plants and thermal units. Based on the nature of decision variables, our proposed model is essentially a Mixed Integer Optimization Problem (MIOP). Particle Swarm Optimization (PSO) is used to solve the optimization problem for a scenario involving six conventional and thirteen PV plants. Two test cases, Combined Static Emission Economic Dispatch (SCEED) and Combined Dynamic Emission Economic Dispatch (DCEED), have been considered. SCEED is performed for full solar radiation level as well as for reduced radiation level due to clouds effect. Simulation results have proved the effectiveness of the proposed model
A Benders decomposition approach for a combined heat and power economic dispatch
International Nuclear Information System (INIS)
Abdolmohammadi, Hamid Reza; Kazemi, Ahad
2013-01-01
Highlights: • Benders decomposition algorithm to solve combined heat and power economic dispatch. • Decomposing the CHPED problem into master problem and subproblem. • Considering non-convex heat-power feasible region efficiently. • Solving 4 units and 5 units system with 2 and 3 co-generation units, respectively. • Obtaining better or as well results in terms of objective values. - Abstract: Recently, cogeneration units have played an increasingly important role in the utility industry. Therefore the optimal utilization of multiple combined heat and power (CHP) systems is an important optimization task in power system operation. Unlike power economic dispatch, which has a single equality constraint, two equality constraints must be met in combined heat and power economic dispatch (CHPED) problem. Moreover, in the cogeneration units, the power capacity limits are functions of the unit heat productions and the heat capacity limits are functions of the unit power generations. Thus, CHPED is a complicated optimization problem. In this paper, an algorithm based on Benders decomposition (BD) is proposed to solve the economic dispatch (ED) problem for cogeneration systems. In the proposed method, combined heat and power economic dispatch problem is decomposed into a master problem and subproblem. The subproblem generates the Benders cuts and master problem uses them as a new inequality constraint which is added to the previous constraints. The iterative process will continue until upper and lower bounds of the objective function optimal values are close enough and a converged optimal solution is found. Benders decomposition based approach is able to provide a good framework to consider the non-convex feasible operation regions of cogeneration units efficiently. In this paper, a four-unit system with two cogeneration units and a five-unit system with three cogeneration units are analyzed to exhibit the effectiveness of the proposed approach. In all cases, the
An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment
Directory of Open Access Journals (Sweden)
Whei-Min Lin
2018-06-01
Full Text Available This paper presents the scheduling dispatch of a microgrid (MG, while considering renewable energy, battery storage systems, and time-of-use price. For the risk evaluation of an MG, the Value-at-Risk (VAR is calculated by using the Historical Simulation Method (HSM. By considering the various confidence levels of the VAR, a scheduling dispatch model of the MG is formulated to achieve a reasonable trade-off between the risk and cost. An Improved Bee Swarm Optimization (IBSO is proposed to solve the scheduling dispatch model of the MG. In the IBSO procedure, the Sin-wave Weight Factor (SWF and Forward-Backward Control Factor (FBCF are embedded in the bee swarm of the BSO to improve the movement behaviors of each bee, specifically, its search efficiency and accuracy. The effectiveness of the IBSO is demonstrated via a real MG case and the results are compared with other methods. In either a grid-connected scenario or a stand-alone scenario, an optimal scheduling dispatch of MGs is carried out, herein, at various confidence levels of risk. The simulation results provide more information for handling uncertain environments when analyzing the VAR of MGs.
Optimal Real-time Dispatch for Integrated Energy Systems
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Guerrero, Josep M.; Rahimi-Kian, Ashkan
2016-01-01
With the emerging of small-scale integrated energy systems (IESs), there are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy and typical implementation of building-level distributed energy resources (DERs). By integrating DSM and DERs...... into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems, and integrated communications architectures, it is possible to efficiently manage energy and comfort at the end-use location. In this paper, an ontology-driven multi......-agent control system with intelligent optimizers is proposed for optimal real-time dispatch of an integrated building and microgrid system considering coordinated demand response (DR) and DERs management. The optimal dispatch problem is formulated as a mixed integer nonlinear programing problem (MINLP...
International Nuclear Information System (INIS)
Coelho, Leandro dos Santos; Mariani, Viviana Cocco
2007-01-01
Global optimization based on evolutionary algorithms can be used as the important component for many engineering optimization problems. Evolutionary algorithms have yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization problems in the power systems area. Differential evolution (DE) is a simple and efficient evolutionary algorithm for function optimization over continuous spaces. It has reportedly outperformed search heuristics when tested over both benchmark and real world problems. This paper proposes improved DE algorithms for solving economic load dispatch problems that take into account nonlinear generator features such as ramp rate limits and prohibited operating zones in the power system operation. The DE algorithms and its variants are validated for two test systems consisting of 6 and 15 thermal units. Various DE approaches outperforms other state of the art algorithms reported in the literature in solving load dispatch problems with generator constraints
Optimal Real-time Dispatch for Integrated Energy Systems
Energy Technology Data Exchange (ETDEWEB)
Firestone, Ryan Michael [Univ. of California, Berkeley, CA (United States)
2007-05-31
This report describes the development and application of a dispatch optimization algorithm for integrated energy systems (IES) comprised of on-site cogeneration of heat and electricity, energy storage devices, and demand response opportunities. This work is intended to aid commercial and industrial sites in making use of modern computing power and optimization algorithms to make informed, near-optimal decisions under significant uncertainty and complex objective functions. The optimization algorithm uses a finite set of randomly generated future scenarios to approximate the true, stochastic future; constraints are included that prevent solutions to this approximate problem from deviating from solutions to the actual problem. The algorithm is then expressed as a mixed integer linear program, to which a powerful commercial solver is applied. A case study of United States Postal Service Processing and Distribution Centers (P&DC) in four cities and under three different electricity tariff structures is conducted to (1) determine the added value of optimal control to a cogeneration system over current, heuristic control strategies; (2) determine the value of limited electric load curtailment opportunities, with and without cogeneration; and (3) determine the trade-off between least-cost and least-carbon operations of a cogeneration system. Key results for the P&DC sites studied include (1) in locations where the average electricity and natural gas prices suggest a marginally profitable cogeneration system, optimal control can add up to 67% to the value of the cogeneration system; optimal control adds less value in locations where cogeneration is more clearly profitable; (2) optimal control under real-time pricing is (a) more complicated than under typical time-of-use tariffs and (b) at times necessary to make cogeneration economic at all; (3) limited electric load curtailment opportunities can be more valuable as a compliment to the cogeneration system than alone; and
Decentralized Economic Dispatch Scheme With Online Power Reserve for Microgrids
DEFF Research Database (Denmark)
Nutkani, I. U.; Loh, Poh Chiang; Wang, P.
2017-01-01
Decentralized economic operation schemes have several advantages when compared with the traditional centralized management system for microgrids. Specifically, decentralized schemes are more flexible, less computationally intensive, and easier to implement without relying on communication...... costs, their power ratings, and other necessary constraints, before deciding the DG dispatch priorities and droop characteristics. The proposed scheme also allows online power reserve to be set and regulated within the microgrid. This, together with the generation cost saved, has been verified...... infrastructure. Economic operation of existing decentralized schemes is also usually achieved by either tuning the droop characteristics of distributed generators (DGs) or prioritizing their dispatch order. For the latter, an earlier scheme has tried to prioritize the DG dispatch based on their no...
Chaotic particle swarm optimization for economic dispatch considering the generator constraints
International Nuclear Information System (INIS)
Cai, Jiejin; Ma, Xiaoqian; Li, Lixiang; Haipeng, Peng
2007-01-01
Chaotic particle swarm optimization (CPSO) methods are optimization approaches based on the proposed particle swarm optimization (PSO) with adaptive inertia weight factor (AIWF) and chaotic local search (CLS). In this paper, two CPSO methods based on the logistic equation and the Tent equation are presented to solve economic dispatch (ED) problems with generator constraints and applied in two power system cases. Compared with the traditional PSO method, the convergence iterative numbers of the CPSO methods are reduced, and the solutions generation costs decrease around 5 $/h in the six unit system and 24 $/h in the 15 unit system. The simulation results show that the CPSO methods have good convergence property. The generation costs of the CPSO methods are lower than those of the traditional particle swarm optimization algorithm, and hence, CPSO methods can result in great economic effect. For economic dispatch problems, the CPSO methods are more feasible and more effective alternative approaches than the traditional particle swarm optimization algorithm
Neural-net based real-time economic dispatch for thermal power plants
Energy Technology Data Exchange (ETDEWEB)
Djukanovic, M.; Milosevic, B. [Inst. Nikola Tesla, Belgrade (Yugoslavia). Dept. of Power Systems; Calovic, M. [Univ. of Belgrade (Yugoslavia). Dept. of Electrical Engineering; Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States)
1996-12-01
This paper proposes the application of artificial neural networks to real-time optimal generation dispatch of thermal units. The approach can take into account the operational requirements and network losses. The proposed economic dispatch uses an artificial neural network (ANN) for generation of penalty factors, depending on the input generator powers and identified system load change. Then, a few additional iterations are performed within an iterative computation procedure for the solution of coordination equations, by using reference-bus penalty-factors derived from the Newton-Raphson load flow. A coordination technique for environmental and economic dispatch of pure thermal systems, based on the neural-net theory for simplified solution algorithms and improved man-machine interface is introduced. Numerical results on two test examples show that the proposed algorithm can efficiently and accurately develop optimal and feasible generator output trajectories, by applying neural-net forecasts of system load patterns.
Stochastic reactive power dispatch in hybrid power system with intermittent wind power generation
International Nuclear Information System (INIS)
Taghavi, Reza; Seifi, Ali Reza; Samet, Haidar
2015-01-01
Environmental concerns besides fuel costs are the predominant reasons for unprecedented escalating integration of wind turbine on power systems. Operation and planning of power systems are affected by this type of energy due to the intermittent nature of wind speed inputs with high uncertainty in the optimization output variables. Consequently, in order to model this high inherent uncertainty, a PRPO (probabilistic reactive power optimization) framework should be devised. Although MC (Monte-Carlo) techniques can solve the PRPO with high precision, PEMs (point estimate methods) can preserve the accuracy to attain reasonable results when diminishing the computational effort. Also, this paper introduces a methodology for optimally dispatching the reactive power in the transmission system, while minimizing the active power losses. The optimization problem is formulated as a LFP (linear fuzzy programing). The core of the problem lay on generation of 2m + 1 point estimates for solving PRPO, where n is the number of input stochastic variables. The proposed methodology is investigated using the IEEE-14 bus test system equipped with HVDC (high voltage direct current), UPFC (unified power flow controller) and DFIG (doubly fed induction generator) devices. The accuracy of the method is demonstrated in the case study. - Highlights: • This paper uses stochastic loads in optimization process. • AC–DC load flow is modified to use some advantages of DC part in optimization process. • UPFC and DFIG are simulated in a way that could be effective in optimization process. • Fuzzy set has been used as an uncertainty analysis tool in the optimization
An optimization approach for wind turbine commitment and dispatch in a wind park
Energy Technology Data Exchange (ETDEWEB)
Moyano, Carlos F. [School of Engineering Systems, Faculty of Built Environment and Engineering, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001 (Australia); Pecas Lopes, Joao A. [Instituto de Engenharia de Sistemas e Computadores do Porto (Portugal); Faculdade de Engenharia da Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, 378 4200-465 Porto (Portugal)
2009-01-15
This paper describes an operational optimization strategy to be adopted at the wind park control level, that enables defining the commitment of wind turbines and their active and reactive power outputs following requests from Wind Park Dispatch Centers, assuming that individual wind turbines short-term wind speed forecasts are known and are expressed as power availability. This operational strategy was also developed with a concern on the minimization of the connection/disconnection changes of the individual wind generators, for a given time horizon. When identifying the active/reactive dispatching policies, wind generators loading capabilities are also taken in account. This optimization tool is especially suited to manage large wind parks. (author)
Review of reactive power dispatch strategies for loss minimization in a DFIG-based wind farm
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Hou, Peng
2017-01-01
power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle......This paper reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and fourWind Turbine (WT) level reactive...... Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations on a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake...
A new honey bee mating optimization algorithm for non-smooth economic dispatch
International Nuclear Information System (INIS)
Niknam, Taher; Mojarrad, Hasan Doagou; Meymand, Hamed Zeinoddini; Firouzi, Bahman Bahmani
2011-01-01
The non-storage characteristics of electricity and the increasing fuel costs worldwide call for the need to operate the systems more economically. Economic dispatch (ED) is one of the most important optimization problems in power systems. ED has the objective of dividing the power demand among the online generators economically while satisfying various constraints. The importance of economic dispatch is to get maximum usable power using minimum resources. To solve the static ED problem, honey bee mating algorithm (HBMO) can be used. The basic disadvantage of the original HBMO algorithm is the fact that it may miss the optimum and provide a near optimum solution in a limited runtime period. In order to avoid this shortcoming, we propose a new method that improves the mating process of HBMO and also, combines the improved HBMO with a Chaotic Local Search (CLS) called Chaotic Improved Honey Bee Mating Optimization (CIHBMO). The proposed algorithm is used to solve ED problems taking into account the nonlinear generator characteristics such as prohibited operation zones, multi-fuel and valve-point loading effects. The CIHBMO algorithm is tested on three test systems and compared with other methods in the literature. Results have shown that the proposed method is efficient and fast for ED problems with non-smooth and non-continuous fuel cost functions. Moreover, the optimal power dispatch obtained by the algorithm is superior to previous reported results. -- Research highlights: →Economic dispatch. →Reducing electrical energy loss. →Saving electrical energy. →Optimal operation.
Economic/Environmental power dispatch for power systems including wind farms
Directory of Open Access Journals (Sweden)
Imen BEN JAOUED
2015-05-01
Full Text Available This paper presents the problem of the Economic/Environmental power Dispatching (EED of hybrid power system including wind energies. The power flow model for a stall regulated fixed speed wind generator (SR-FSWG system is discussed to assess the steady-state condition of power systems with wind farms. Modified Newton-Raphson algorithm including SR-FSWG is used to solve the load flow equations in which the state variables of the wind generators are combined with the nodal voltage magnitudes and angles of the entire network. The EED problem is a nonlinear constrained multi-objective optimization problem, two competing fuel cost and pollutant emission objectives should be minimized simultaneously while satisfying certain system constraints. In this paper, the resolution is done by the algorithm multi-objective particle swarm optimization (MOPSO. The effectiveness of the proposed method has been verified on IEEE 6-generator 30-bus test system and using MATLAB software package.
Load allocation of power plant using multi echelon economic dispatch
Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad
2017-11-01
In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.
(ajst) on optimum dispatch of electric power
African Journals Online (AJOL)
same time satisfy the load flow equation without violating the inequality constraints. Key Words: Generation ... variables, including real and reactive power generations, phase – shifter ... variable u and the operating limits on the power system bus voltage ... soft” limits (i.e. small violation is tolerable, e. g. voltage limit at load ...
A Hybrid Multilevel Storage Architecture for Electric Power Dispatching Big Data
Yan, Hu; Huang, Bibin; Hong, Bowen; Hu, Jing
2017-10-01
Electric power dispatching is the center of the whole power system. In the long run time, the power dispatching center has accumulated a large amount of data. These data are now stored in different power professional systems and form lots of information isolated islands. Integrating these data and do comprehensive analysis can greatly improve the intelligent level of power dispatching. In this paper, a hybrid multilevel storage architecture for electrical power dispatching big data is proposed. It introduces relational database and NoSQL database to establish a power grid panoramic data center, effectively meet power dispatching big data storage needs, including the unified storage of structured and unstructured data fast access of massive real-time data, data version management and so on. It can be solid foundation for follow-up depth analysis of power dispatching big data.
Energy Technology Data Exchange (ETDEWEB)
Mather, Barry A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cho, Gyu-Jung [Sungkyunkwan University; Oh, Yun-Sik [Sungkyunkwan University; Kim, Min-Sung [Sungkyunkwan University; Kim, Ji-Soo [Sungkyunkwan University; Kim, Chul-Hwan [Sungkyunkwan University
2017-06-29
Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation of the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.
Dispatchable Renewable Energy Model for Microgrid Power System
Energy Technology Data Exchange (ETDEWEB)
Chiou, Fred; Gentle, Jake P.; McJunkin, Timothy R.
2017-04-01
Over the years, many research projects have been performed and focused on finding out the effective ways to balance the power demands and supply on the utility grid. The causes of the imbalance could be the increasing demands from the end users, the loss of power generation (generators down), faults on the transmission lines, power tripped due to overload, and weather conditions, etc. An efficient Load Frequency Control (LFC) can assure the desired electricity quality provided to the residential, commercial and industrial end users. A simulation model is built in this project to investigate the contribution of the modeling of dispatchable energy such as solar energy, wind power, hydro power and energy storage to the balance of the microgrid power system. An analysis of simplified feedback control system with proportional, integral, and derivative (PID) controller was performed. The purpose of this research is to investigate a simulation model that achieves certain degree of the resilient control for the microgrid.
International Nuclear Information System (INIS)
Liao, Gwo-Ching
2011-01-01
An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. -- Research highlights: → Quantum Genetic Algorithm can effectively improve the global search ability. → It can achieve the real objective of the global optimal solutions. → The CPU computation time is less than that other algorithms adopted in this paper.
Economic dispatch optimization for system integrating renewable energy sources
Jihane, Kartite; Mohamed, Cherkaoui
2018-05-01
Nowadays, the use of energy is growing especially in transportation and electricity industries. However this energy is based on conventional sources which pollute the environment. Multi-source system is seen as the best solution to sustainable development. This paper proposes the Economic Dispatch (ED) of hybrid renewable power system. The hybrid system is composed of ten thermal generators, photovoltaic (PV) generator and wind turbine generator. To show the importance of renewable energy sources (RES) in the energy mix we have ran the simulation for system integrated PV only and PV plus wind. The result shows that the system with renewable energy sources (RES) is more compromising than the system without RES in terms of fuel cost.
Optimization of power system operation
Zhu, Jizhong
2015-01-01
This book applies the latest applications of new technologies topower system operation and analysis, including new and importantareas that are not covered in the previous edition. Optimization of Power System Operation covers both traditional andmodern technologies, including power flow analysis, steady-statesecurity region analysis, security constrained economic dispatch,multi-area system economic dispatch, unit commitment, optimal powerflow, smart grid operation, optimal load shed, optimalreconfiguration of distribution network, power system uncertaintyanalysis, power system sensitivity analysis, analytic hierarchicalprocess, neural network, fuzzy theory, genetic algorithm,evolutionary programming, and particle swarm optimization, amongothers. New topics such as the wheeling model, multi-areawheeling, the total transfer capability computation in multipleareas, are also addressed. The new edition of this book continues to provide engineers andac demics with a complete picture of the optimization of techn...
Wind power generation and dispatch in competitive power markets
Abreu, Lisias
Wind energy is currently the fastest growing type of renewable energy. The main motivation is led by more strict emission constraints and higher fuel prices. In addition, recent developments in wind turbine technology and financial incentives have made wind energy technically and economically viable almost anywhere. In restructured power systems, reliable and economical operation of power systems are the two main objectives for the ISO. The ability to control the output of wind turbines is limited and the capacity of a wind farm changes according to wind speeds. Since this type of generation has no production costs, all production is taken by the system. Although, insufficient operational planning of power systems considering wind generation could result in higher system operation costs and off-peak transmission congestions. In addition, a GENCO can participate in short-term power markets in restructured power systems. The goal of a GENCO is to sell energy in such a way that would maximize its profitability. However, due to market price fluctuations and wind forecasting errors, it is essential for the wind GENCO to keep its financial risk at an acceptable level when constituting market bidding strategies. This dissertation discusses assumptions, functions, and methodologies that optimize short-term operations of power systems considering wind energy, and that optimize bidding strategies for wind producers in short-term markets. This dissertation also discusses uncertainties associated with electricity market environment and wind power forecasting that can expose market participants to a significant risk level when managing the tradeoff between profitability and risk.
International Nuclear Information System (INIS)
Daud, Muhamad Zalani; Mohamed, Azah; Hannan, M.A.
2013-01-01
Highlights: • Control of BES for smoothing and hourly dispatch of a PV farm output is developed. • Optimal control strategy for SOC and size of BES are evaluated using GA. • Effectiveness of the control system has been investigated for the case of Malaysia. • The proposed optimal SOC feedback controller has been found effective. • Payback calculations of BES investment is given to highlight the economic benefits. - Abstract: The effects of intermittent cloud and changes in temperature cause a randomly fluctuated output of a photovoltaic (PV) system. To mitigate the PV system impacts particularly on a weak electricity network, battery energy storage (BES) system is an effective means to smooth out the power fluctuations. Consequently, the net power injected to the electricity grid by PV and BES (PV/BES) systems can be dispatched smoothly such as on an hourly basis. This paper presents an improved control strategy for a grid-connected hybrid PV/BES systems for mitigating PV farm output power fluctuations. A feedback controller for BES state of charge is proposed, where the control parameters are optimized using genetic algorithm (GA). GA-based multi objective optimization utilizes the daily average PV farm output power profile which was obtained from simulation using the historical PV system input data of Malaysia. In this way, the optimal size for the BES is also determined to hourly dispatch a 1.2 MW PV farm. A case study for Malaysia is carried out to evaluate the effectiveness of the proposed control scheme using PSCAD/EMTDC software package. Furthermore, the validation of results of the proposed controller and BES size on the actual PV system output data are also given. Finally, a simple payback calculation is presented to study the economical aspects of the BES investment on the proposed mitigation strategy under Malaysian Feed-in Tariff program
Intelligent Anti Misoperation System for Power Grid Dispatching of Regions and Counties
Ji, Yuan; Zhang, Yunju; Zhou, Siming; Wang, Xiangdong; Ma, Jianwei
2018-01-01
With the power system of large capacity, large units, high voltage development trend, dispatching operations becoming more frequent, complex, and probability of mistakes are increasing. For the existing grid dispatching integrated system loss of anti-error function, single dispatching function, low efficiency, according to the existing conditions of Anshun Power Supply Bureau, the Intelligent anti misoperation system for power grid dispatching of regions and counties is designed, introduced the technologies such as the intelligent anti misoperation analysis, automatic process control, and interactive constraint, the system has the advantages of scientific, reasonable and efficient, and providing the technical support for anti misoperation of regions and counties.
An improved harmony search algorithm for power economic load dispatch
Energy Technology Data Exchange (ETDEWEB)
Santos Coelho, Leandro dos [Pontifical Catholic University of Parana, PUCPR, Industrial and Systems Engineering Graduate Program, PPGEPS, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)], E-mail: leandro.coelho@pucpr.br; Mariani, Viviana Cocco [Pontifical Catholic University of Parana, PUCPR, Department of Mechanical Engineering, PPGEM, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)], E-mail: viviana.mariani@pucpr.br
2009-10-15
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature.
An improved harmony search algorithm for power economic load dispatch
Energy Technology Data Exchange (ETDEWEB)
Coelho, Leandro dos Santos [Pontifical Catholic Univ. of Parana, PUCPR, Industrial and Systems Engineering Graduate Program, PPGEPS, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil); Mariani, Viviana Cocco [Pontifical Catholic Univ. of Parana, PUCPR, Dept. of Mechanical Engineering, PPGEM, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)
2009-10-15
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature. (author)
An improved harmony search algorithm for power economic load dispatch
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos; Mariani, Viviana Cocco
2009-01-01
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature.
A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch
International Nuclear Information System (INIS)
Niknam, Taher; Azizipanah-Abarghooee, Rasoul; Roosta, Alireza; Amiri, Babak
2012-01-01
Combined heat and power units are playing an ever increasing role in conventional power stations due to advantages such as reduced emissions and operational cost savings. This paper investigates a more practical formulation of the complex non-convex, non-smooth and non-linear multi-objective dynamic economic emission dispatch that incorporates combined heat and power units. Integrating these types of units, and their power ramp constraints, require an efficient tool to cope with the joint characteristics of power and heat. Unlike previous approaches, the spinning reserve requirements of this system are clearly formulated in the problem. In this way, a new multi-objective optimisation based on an enhanced firefly algorithm is proposed to achieve a set of non-dominated (Pareto-optimal) solutions. A new tuning parameter based on a chaotic mechanism and novel self adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The numerical results demonstrate how the proposed framework was applied in real time studies. -- Highlights: ► Investigate a practical formulation of the DEED (Dynamic Economic Emission Dispatch). ► Consider combined heat and power units. ► Consider power ramp constraints. ► Consider the system spinning reserve requirements. ► Present a new multi-objective optimization firefly.
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Hou, Peng
2015-01-01
Inclusion of the wake effect in the wind farm control design (WF) can increase the total captured power by wind turbines (WTs), which is usually implemented by derating upwind WTs. However, derating the WT without a proper control strategy will increase the structural loads, caused by operation...... in stall mode. Therefore, the WT control strategy for derating operation should be considered in the attempt at maximizing the total captured power while reducing structural loads. Moreover, electrical power loss on the transmission system inside a WF is also not negligible for maximizing the total output...... power of the WF. In this paper, an optimal active power dispatch strategy based on a WT derating strategy and considering the transmission loss is proposed for maximizing the total output power. The active power reference of each WT is chosen as the optimization variable. A partial swarm optimizing...
An Approximate Dynamic Programming Mode for Optimal MEDEVAC Dispatching
2015-03-26
over the myopic policy. This indicates the ADP policy is efficiently managing resources by 28 not immediately sending the nearest available MEDEVAC...DISPATCHING THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology...medical evacuation (MEDEVAC) dispatch policies. To solve the MDP, we apply an ap- proximate dynamic programming (ADP) technique. The problem of deciding
Energy Technology Data Exchange (ETDEWEB)
Fesanghary, M. [Department of Mechanical Engineering, Louisiana State University, 2508 Patrick Taylor Hall, Baton Rouge, LA 70808 (United States); Ardehali, M.M. [Energy Research Center, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424-Hafez Avenue, 15875-4413 Tehran (Iran)
2009-06-15
The increasing costs of fuel and operation of thermal power generating units warrant development of optimization methodologies for economic dispatch (ED) problems. Optimization methodologies that are based on meta-heuristic procedures could assist power generation policy analysts to achieve the goal of minimizing the generation costs. In this context, the objective of this study is to present a novel approach based on harmony search (HS) algorithm for solving ED problems, aiming to provide a practical alternative for conventional methods. To demonstrate the efficiency and applicability of the proposed method and for the purposes of comparison, various types of ED problems are examined. The results of this study show that the new proposed approach is able to find more economical loads than those determined by other methods. (author)
Energy Technology Data Exchange (ETDEWEB)
Maknouninejad, Ali; Lin, Wei; Harno, Hendra G.; Qu, Zhihua; Simaan, Marwan A. [University of Central Florida, Department of EECS, Orlando, FL (United States)
2012-03-15
The small size, extensively dispersed and decentralized, and high penetration level of renewable energy sources in the future smart grids make the application of conventional optimal power flow (OPF) neither practical nor economical. In this paper, a practical approach is proposed to realize high penetration of distributed generators (DGs) by organizing them in some groups within a microgrid and dispatching the generated power aggregately. Each group may have virtual leaders which define the power policy of the group, and all other DGs cooperatively follow that policy. A fair utilization ratio is defined and will be introduced to the group by the virtual leaders. The utilization ratio indicates what percentage of the available power each DG has to feed to the grid, and this ratio will also be propagated within the group using cooperative control. As such, a smartgrid may treat microgrids as individually dispatchable loads or generators. Meanwhile, the interaction between each microgrid and the main grid can be formulated as a Stackelberg game. The main grid as the leader, by offering proper energy price to the micro grid, minimizes its cost and secures the power supply that the microgrid, as the follower, is willing to dispatch. It is shown that this game theoretic approach not only guarantees profit optimization, but also provides a convenient technique to optimize power flow from microgrids to the main grid. Numerical and simulation results for a case of study are provided to demonstrate the effectiveness of the proposed techniques. (orig.)
Data-adaptive Robust Optimization Method for the Economic Dispatch of Active Distribution Networks
DEFF Research Database (Denmark)
Zhang, Yipu; Ai, Xiaomeng; Fang, Jiakun
2018-01-01
Due to the restricted mathematical description of the uncertainty set, the current two-stage robust optimization is usually over-conservative which has drawn concerns from the power system operators. This paper proposes a novel data-adaptive robust optimization method for the economic dispatch...... of active distribution network with renewables. The scenario-generation method and the two-stage robust optimization are combined in the proposed method. To reduce the conservativeness, a few extreme scenarios selected from the historical data are used to replace the conventional uncertainty set....... The proposed extreme-scenario selection algorithm takes advantage of considering the correlations and can be adaptive to different historical data sets. A theoretical proof is given that the constraints will be satisfied under all the possible scenarios if they hold in the selected extreme scenarios, which...
A solution to the economic dispatch using EP based SA algorithm on large scale power system
Energy Technology Data Exchange (ETDEWEB)
Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605 014 (India)
2010-07-15
This paper develops a new approach for solving the Economic Load Dispatch (ELD) using an integrated algorithm based on Evolutionary Programming (EP) and Simulated Annealing (SA) on large scale power system. Classical methods employed for solving Economic Load Dispatch are calculus-based. For generator units having quadratic fuel cost functions, the classical techniques ignore or flatten out the portions of the incremental fuel cost curves and so may be have difficulties in the determination of the global optimum solution for non-differentiable fuel cost functions. To overcome these problems, the intelligent techniques, namely, Evolutionary Programming and Simulated Annealing are employed. The above said optimization techniques are capable of determining the global or near global optimum dispatch solutions. The validity and effectiveness of the proposed integrated algorithm has been tested with 66-bus Indian utility system, IEEE 5-bus, 30-bus, 118-bus system. And the test results are compared with the results obtained from other methods. Numerical results show that the proposed integrated algorithm can provide accurate solutions within reasonable time for any type of fuel cost functions. (author)
On optimization of power production
Energy Technology Data Exchange (ETDEWEB)
Feltenmark, S.
1997-01-01
Short-term optimization of power production is treated. It concerns the problem of determining a production schedule for a power system, which minimizes the total cost of production, while satisfying various constraints. The thesis consists of an introductory chapter, four chapters that each concerns a specific problem area (economic dispatch, unit commitment, hydro power planning and cogeneration optimization), plus a chapter with relevant theory. The emphasis of the thesis is on the mathematical structures that arise in problems in this field, and how to exploit them algorithmically. A recurring theme is convexification, either implicit, by dualization, or explicit, as in our approach to hydro power optimization. 134 refs
Chang, Hung-Chieh; Lin, Pei-Chun
2014-02-01
Economic dispatch is the short-term determination of the optimal output from a number of electricity generation facilities to meet the system load while providing power. As such, it represents one of the main optimization problems in the operation of electrical power systems. This article presents techniques to substantially improve the efficiency of the canonical coordinates method (CCM) algorithm when applied to nonlinear combined heat and power economic dispatch (CHPED) problems. The improvement is to eliminate the need to solve a system of nonlinear differential equations, which appears in the line search process in the CCM algorithm. The modified algorithm was tested and the analytical solution was verified using nonlinear CHPED optimization problems, thereby demonstrating the effectiveness of the algorithm. The CCM methods proved numerically stable and, in the case of nonlinear programs, produced solutions with unprecedented accuracy within a reasonable time.
Solution of optimal power flow using evolutionary-based algorithms
African Journals Online (AJOL)
It aims to estimate the optimal settings of real generator output power, bus voltage, ...... Lansey, K. E., 2003, Optimization of water distribution network design using ... Pandit, M., 2016, Economic load dispatch of wind-solar-thermal system using ...
Directory of Open Access Journals (Sweden)
T. Bouktir
2005-06-01
Full Text Available This paper presents solution of optimal power flow (OPF problem of electrical power system via a genetic algorithm of real type. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units and also maintain an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. CPU times can be reduced by decomposing the optimization constraints to active constraints that affect directly the cost function manipulated directly the GA, and passive constraints such as generator bus voltages and transformer tap setting maintained in their soft limits using a conventional constraint load flow. The algorithm was developed in an Object Oriented fashion, in the C++ programming language. This option satisfies the requirements of flexibility, extensibility, maintainability and data integrity. The economic power dispatch is applied to IEEE 30-bus model system (6-generator, 41-line and 20-load. The numerical results have demonstrate the effectiveness of the stochastic search algorithms because its can provide accurate dispatch solutions with reasonable time. Further analyses indicate that this method is effective for large-scale power systems.
International Nuclear Information System (INIS)
Kumar, Ashwani; Gao, Wenzhong
2009-01-01
This paper proposes a new method for secure bilateral transactions determination ensuring economic power dispatch of the generators using new AC distribution factors for pool and bilateral coordinated markets. The new optimization problem considers simultaneous minimization of deviations from scheduled transactions and fuel cost of the generators in the network. The fuel cost has been obtained for hybrid market model and impact of different percentage of bilateral demand on fuel cost, generation share, and pattern of transactions has also been determined. The impact of optimally located unified power flow controller (UPFC) on the bilateral transactions, fuel cost and generation pattern has also been studied. The results have also been obtained for pool market model. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS). (author)
International Nuclear Information System (INIS)
Jin, Jingliang; Zhou, Dequn; Zhou, Peng; Qian, Shuqu; Zhang, Mingming
2016-01-01
Wind power plays a significant role in economic and environmental operation of electric power system. Meanwhile, the variability and uncertainty characteristics of wind power generation bring technical and economical challenges for power system operation. In order to harmonize the relationship between environmental protection and risk management in power dispatching, this paper presents a stochastic dynamic economic emission dispatch model combining risk perception with environmental awareness of decision-makers by following the principle of chance-constrained programming. In this power dispatching model, the description of wind power uncertainty is derived from the probability statistic character of wind speed. Constraints-handling techniques as a heuristic strategy are embedded into non-dominated sorting genetic algorithm-II. In addition, more information is digested from the Pareto optimum solution set by cluster analysis and fuzzy set theory. The simulation results eventually demonstrate that the increase of the share of wind power output will bring higher risk, though it is beneficial for economic cost and environmental protection. Since different risk perception and environmental awareness can possibly lead to diverse non-dominated solutions, decision-makers may choose an appropriate dispatching strategy according to their specific risk perception and environmental awareness. - Highlights: • A dispatch model combining environmental awareness and risk perception is proposed. • The uncertain characteristic of available wind power is determined. • Constraints-handling techniques are embedded into genetic algorithm. • An appropriate decision-making method is designed. • Dispatching strategies can be coordinated by the proposed model and method.
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Hou, Peng
2016-01-01
The energy loss in a wind farm (WF) caused by wake interaction between wind turbines (WTs) is quite high, which can be reduced by proper active power dispatch. The electrical loss inside a WF by improper active power and reactive power dispatch is also considerable. In this paper, a coordinated...... active power and reactive power dispatch strategy is proposed for a Permanent magnet synchronous generator (PMSG) based WF, in order to maximize the total output power by reducing the wake effect and losses inside the devices of the WF, including the copper loss and iron loss of PMSGs, losses inside...
Energy Technology Data Exchange (ETDEWEB)
Piperagkas, G.S.; Anastasiadis, A.G.; Hatziargyriou, N.D. [National Technical University of Athens, School of Electrical and Computer Engineering, Electric Power Division, 9, Iroon Polytechneiou Str., GR-15773 Zografou, Athens (Greece)
2011-01-15
In this paper an extended stochastic multi-objective model for economic dispatch (ED) is proposed, that incorporates in the optimization process heat and power from CHP units and expected wind power. Stochastic restrictions for the CO{sub 2}, SO{sub 2} and NO{sub x} emissions are used as inequality constraints. The ED problem is solved using a multi-objective particle swarm optimization technique. The available wind power is estimated from a transformation of the wind speed considered as a random variable to wind power. Simulations are performed on the modified IEEE 30 bus network with 2 cogeneration units and actual wind data. Results concerning minimum cost and emissions reduction options are finally drawn. (author)
Combining of Direct Search and Signal-to-Noise Ratio for economic dispatch optimization
International Nuclear Information System (INIS)
Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang
2011-01-01
This paper integrated the ideas of Direct Search and Signal-to-Noise Ratio (SNR) to develop a Novel Direct Search (NDS) method for solving the non-convex economic dispatch problems. NDS consists of three stages: Direct Search (DS), Global SNR (GSNR) and Marginal Compensation (MC) stages. DS provides a basic solution. GSNR searches the point with optimization strategy. MC fulfills the power balance requirement. With NDS, the infinite solution space becomes finite. Furthermore, a same optimum solution can be repeatedly reached. Effectiveness of NDS is demonstrated with three examples and the solutions were compared with previously published results. Test results show that the proposed method is simple, robust, and more effective than many other previously developed algorithms.
Directory of Open Access Journals (Sweden)
Boyang Qu
2017-12-01
Full Text Available The intermittency of wind power and the large-scale integration of electric vehicles (EVs bring new challenges to the reliability and economy of power system dispatching. In this paper, a novel multi-objective dynamic economic emission dispatch (DEED model is proposed considering the EVs and uncertainties of wind power. The total fuel cost and pollutant emission are considered as the optimization objectives, and the vehicle to grid (V2G power and the conventional generator output power are set as the decision variables. The stochastic wind power is derived by Weibull probability distribution function. Under the premise of meeting the system energy and user’s travel demand, the charging and discharging behavior of the EVs are dynamically managed. Moreover, we propose a two-step dynamic constraint processing strategy for decision variables based on penalty function, and, on this basis, the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D algorithm is improved. The proposed model and approach are verified by the 10-generator system. The results demonstrate that the proposed DEED model and the improved MOEA/D algorithm are effective and reasonable.
A novel hybrid particle swarm optimization for economic dispatch with valve-point loading effects
Energy Technology Data Exchange (ETDEWEB)
Niknam, Taher, E-mail: niknam@sutech.ac.i [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Mojarrad, Hasan Doagou, E-mail: hasan_doagou@yahoo.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Meymand, Hamed Zeinoddini, E-mail: h.zeinaddini@gmail.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of)
2011-04-15
Economic dispatch (ED) is one of the important problems in the operation and management of the electric power systems which is formulated as an optimization problem. Modern heuristics stochastic optimization techniques appear to be efficient in solving ED problem without any restriction because of their ability to seek the global optimal solution. One of modern heuristic algorithms is particle swarm optimization (PSO). In PSO algorithm, particles change place to get close to the best position and find the global minimum point. Also, differential evolution (DE) is a robust statistical method for solving non-linear and non-convex optimization problem. The fast convergence of DE degrades its performance and reduces its search capability that leads to a higher probability towards obtaining a local optimum. In order to overcome this drawback a hybrid method is presented to solve the ED problem with valve-point loading effect by integrating the variable DE with the fuzzy adaptive PSO called FAPSO-VDE. DE is the main optimizer and the PSO is used to maintain the population diversity and prevent leading to misleading local optima for every improvement in the solution of the DE run. The parameters of proposed hybrid algorithm such as inertia weight, mutation and crossover factors are adaptively adjusted. The feasibility and effectiveness of the proposed hybrid algorithm is demonstrated for two case studies and results are compared with those of other methods. It is shown that FAPSO-VDE has high quality solution, superior convergence characteristics and shorter computation time.
DEFF Research Database (Denmark)
Ding, Tao; Li, Cheng; Yang, Yongheng
2017-01-01
Optimally dispatching Photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most...... nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust optimization model is proposed in this paper to achieve a robust optimal solution to the PV inverter dispatch, which can hedge...... against any possible realization within the uncertain PV outputs. In addition, the conic relaxation-based branch flow formulation and second-order cone programming based column-and-constraint generation algorithm are employed to deal with the proposed robust optimization model. Case studies on a 33-bus...
Distributed Strategy for Optimal Dispatch of Unbalanced Three-Phase Islanded Microgrids
DEFF Research Database (Denmark)
Vergara Barrios, Pedro Pablo; Rey-López, Juan Manuel; Shaker, Hamid Reza
2018-01-01
This paper presents a distributed strategy for the optimal dispatch of islanded microgrids, modeled as unbalanced three-phase electrical distribution systems (EDS). To set the dispatch of the distributed generation (DG) units, an optimal generation problem is stated and solved distributively based......-phase microgrid. According to the obtained results, the proposed strategy achieves a lower cost solution when compared with a centralized approach based on a static droop framework, with a considerable reduction on the communication system complexity. Additionally, it corrects the mismatch between generation...
Wang, Tiancai; He, Xing; Huang, Tingwen; Li, Chuandong; Zhang, Wei
2017-09-01
The economic emission dispatch (EED) problem aims to control generation cost and reduce the impact of waste gas on the environment. It has multiple constraints and nonconvex objectives. To solve it, the collective neurodynamic optimization (CNO) method, which combines heuristic approach and projection neural network (PNN), is attempted to optimize scheduling of an electrical microgrid with ten thermal generators and minimize the plus of generation and emission cost. As the objective function has non-derivative points considering valve point effect (VPE), differential inclusion approach is employed in the PNN model introduced to deal with them. Under certain conditions, the local optimality and convergence of the dynamic model for the optimization problem is analyzed. The capability of the algorithm is verified in a complicated situation, where transmission loss and prohibited operating zones are considered. In addition, the dynamic variation of load power at demand side is considered and the optimal scheduling of generators within 24 h is described. Copyright © 2017 Elsevier Ltd. All rights reserved.
Combined heat and power economic dispatch by a fish school search algorithm
Energy Technology Data Exchange (ETDEWEB)
Santos, Leonardo Trigueiro dos; Costa e Silva, Marsil de Athayde [Undergraduate in Mechatronics Engineering, Pontifical Catholic University of Parana, Curitiba, PR (Brazil); Coelho, Leandro dos Santos [Industrial and Systems Engineering Graduate Program, PPGEPS, Pontifical Catholic University of Parana, Curitiba, PR (Brazil)], e-mail: leandro.coelho@pucpr.br
2010-07-01
The conversion of primary fossil fuels, such as coal and gas, to electricity is a a relatively inefficient process. Even the most modern combined cycle plants can only achieve efficiencies of between 50-60%. A great portion of the energy wasted in this conversion process is released to the environment as waste heat. The principle of combined heat and power, also known as cogeneration, is to recover and make beneficial use of this heat, significantly raising the overall efficiency of the conversion process. However, the optimal utilization of multiple combined heat and power systems is a complicated problem which needs powerful methods to solve. This paper presents a fish school search (FSS) algorithm to solve the combined heat and power economic dispatch problem. FSS is a novel approach recently proposed to perform search in complex optimization problems. Some simulations presented in the literature indicated that FSS can outperform many bio-inspired algorithms, mainly in multimodal functions. The search process in FSS is carried out by a population of limited-memory individuals - the fishes. Each fish represents a possible solution to the problem. Similarly to particle swarm optimization or genetic algorithm, search guidance in FSS is driven by the success of some individual members of the population. A four-unit system proposed recently which is a benchmark case in the power systems field has been validated as a case study in this paper. (author)
Kamphuis, I.G.; Roossien, B.; Eijgelaar, M.; De Heer, H.; Van der Noort, A.; Velden, van der Jorgen
2013-01-01
An automated Virtual Power Plant using software agents bidding in an electronic market has been set-up in a living lab environment in Hoogkerk near Groningen using the PowerMatcher approach. The optimization goal of the cluster was to support trade dispatch of a commercial portfolio on the market. A
A markov decision process model for the optimal dispatch of military medical evacuation assets.
Keneally, Sean K; Robbins, Matthew J; Lunday, Brian J
2016-06-01
We develop a Markov decision process (MDP) model to examine aerial military medical evacuation (MEDEVAC) dispatch policies in a combat environment. The problem of deciding which aeromedical asset to dispatch to each service request is complicated by the threat conditions at the service locations and the priority class of each casualty event. We assume requests for MEDEVAC support arrive sequentially, with the location and the priority of each casualty known upon initiation of the request. The United States military uses a 9-line MEDEVAC request system to classify casualties as being one of three priority levels: urgent, priority, and routine. Multiple casualties can be present at a single casualty event, with the highest priority casualty determining the priority level for the casualty event. Moreover, an armed escort may be required depending on the threat level indicated by the 9-line MEDEVAC request. The proposed MDP model indicates how to optimally dispatch MEDEVAC helicopters to casualty events in order to maximize steady-state system utility. The utility gained from servicing a specific request depends on the number of casualties, the priority class for each of the casualties, and the locations of both the servicing ambulatory helicopter and casualty event. Instances of the dispatching problem are solved using a relative value iteration dynamic programming algorithm. Computational examples are used to investigate optimal dispatch policies under different threat situations and armed escort delays; the examples are based on combat scenarios in which United States Army MEDEVAC units support ground operations in Afghanistan.
International Nuclear Information System (INIS)
Sun Jun; Fang Wei; Wang Daojun; Xu Wenbo
2009-01-01
In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO-DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO-DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm.
Energy Technology Data Exchange (ETDEWEB)
Jun Sun; Wei Fang; Daojun Wang; Wenbo Xu [School of Information Technology, Jiangnan Univ., Wuxi, Jiangsu 214122 (China)
2009-12-15
In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO-DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO-DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm. (author)
DEFF Research Database (Denmark)
Vlachogiannis, Ioannis (John); Lee, KY
2009-01-01
In this paper an improved coordinated aggregation-based particle swarm optimization (ICA-PSO) algorithm is introduced for solving the optimal economic load dispatch (ELD) problem in power systems. In the ICA-PSO algorithm each particle in the swarm retains a memory of its best position ever...... encountered, and is attracted only by other particles with better achievements than its own with the exception of the particle with the best achievement, which moves randomly. Moreover, the population size is increased adaptively, the number of search intervals for the particles is selected adaptively...
Study of Flexible Load Dispatch to Improve the Capacity of Wind Power Absorption
Yunlei, Yang; Shifeng, Zhang; Xiao, Chang; Da, Lei; Min, Zhang; Jinhao, Wang; Shengwen, Li; Huipeng, Li
2017-05-01
The dispatch method which track the trend of load demand by arranging the generation scheme of controllable hydro or thermal units faces great difficulties and challenges. With the increase of renewable energy sources such as wind power and photovoltaic power introduced to grid, system has to arrange much more spinning reserve units to compensate the unbalanced power. How to exploit the peak-shaving potential of flexible load which can be shifted with time or storage energy has become many scholars’ research direction. However, the modelling of different kinds of load and control strategy is considerably difficult, this paper choose the Air Conditioner with compressor which can storage energy in fact to study. The equivalent thermal parameters of Air Conditioner has been established. And with the use of “loop control” strategies, we can predict the regulated power of Air Conditioner. Then we established the Gen-Load optimal scheduling model including flexible load based on traditional optimal scheduling model. At last, an improved IEEE-30 case is used to verify. The result of simulation shows that flexible load can fast-track renewable power changes. More than that, with flexible load and reasonable incentive method to consumers, the operating cost of the system can be greatly cut down.
Evaluating the CO 2 emissions reduction potential and cost of power sector re-dispatch
Energy Technology Data Exchange (ETDEWEB)
Steinberg, Daniel C.; Bielen, David A.; Townsend, Aaron
2018-01-01
Prior studies of the U.S. electricity sector have recognized the potential to reduce carbon dioxide (CO2) emissions by substituting generation from coal-fired units with generation from under-utilized and lower-emitting natural gas-fired units; in fact, this type of 're-dispatch' was invoked as one of the three building blocks used to set the emissions targets under the Environmental Protection Agency's Clean Power Plan. Despite the existence of surplus natural gas capacity in the U.S., power system operational constraints not often considered in power sector policy analyses, such as transmission congestion, generator ramping constraints, minimum generation constraints, planned and unplanned generator outages, and ancillary service requirements, could limit the potential and increase the cost of coal-to-gas re-dispatch. Using a highly detailed power system unit commitment and dispatch model, we estimate the maximum potential for re-dispatch in the Eastern Interconnection, which accounts for the majority of coal capacity and generation in the U.S. Under our reference assumptions, we find that maximizing coal-to-gas re-dispatch yields emissions reductions of 230 million metric tons (Mt), or 13% of power sector emissions in the Eastern Interconnection, with a corresponding average abatement cost of $15-$44 per metric ton of CO2, depending on the assumed supply elasticity of natural gas.
Alemadi, Nasser Ahmed
Deregulation has brought opportunities for increasing efficiency of production and delivery and reduced costs to customers. Deregulation has also bought great challenges to provide the reliability and security customers have come to expect and demand from the electrical delivery system. One of the challenges in the deregulated power system is voltage instability. Voltage instability has become the principal constraint on power system operation for many utilities. Voltage instability is a unique problem because it can produce an uncontrollable, cascading instability that results in blackout for a large region or an entire country. In this work we define a system of advanced analytical methods and tools for secure and efficient operation of the power system in the deregulated environment. The work consists of two modules; (a) contingency selection module and (b) a Security Constrained Optimization module. The contingency selection module to be used for voltage instability is the Voltage Stability Security Assessment and Diagnosis (VSSAD). VSSAD shows that each voltage control area and its reactive reserve basin describe a subsystem or agent that has a unique voltage instability problem. VSSAD identifies each such agent. VS SAD is to assess proximity to voltage instability for each agent and rank voltage instability agents for each contingency simulated. Contingency selection and ranking for each agent is also performed. Diagnosis of where, why, when, and what can be done to cure voltage instability for each equipment outage and transaction change combination that has no load flow solution is also performed. A security constrained optimization module developed solves a minimum control solvability problem. A minimum control solvability problem obtains the reactive reserves through action of voltage control devices that VSSAD determines are needed in each agent to obtain solution of the load flow. VSSAD makes a physically impossible recommendation of adding reactive
Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch
Xie, Le
2014-01-01
We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.
Directory of Open Access Journals (Sweden)
Abouzar Samimi
2016-01-01
Full Text Available One of the most significant control schemes in optimal operation of distribution networks is Volt/Var control (VVC. Owing to the radial structure of distribution systems and distribution lines with a small X/R ratio, the active power scheduling affects the VVC issue. A Distribution System Operator (DSO procures its active and reactive power requirements from Distributed Generations (DGs along with the wholesale electricity market. This paper proposes a new operational scheduling method based on a joint day-ahead active/reactive power market at the distribution level. To this end, based on the capability curve, a generic reactive power cost model for DGs is developed. The joint active/reactive power dispatch model presented in this paper motivates DGs to actively participate not only in the energy markets, but also in the VVC scheme through a competitive market. The proposed method which will be performed in an offline manner aims to optimally determine (i the scheduled active and reactive power values of generation units; (ii reactive power values of switched capacitor banks; and (iii tap positions of transformers for the next day. The joint active/reactive power dispatch model for daily VVC is modeled in GAMS and solved with the DICOPT solver. Finally, the plausibility of the proposed scheduling framework is examined on a typical 22-bus distribution test network over a 24-h period.
International Nuclear Information System (INIS)
Chen, C.-L.
2005-01-01
With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator's bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market
International Nuclear Information System (INIS)
Chun Lung Chen
2005-01-01
With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator's bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market. (author)
Directory of Open Access Journals (Sweden)
Xianyong Zhang
2018-03-01
Full Text Available Due to the complex configuration and control framework, the conventional microgrid is not cost-effective for engineering applications with small or medium capacity. A stand-alone modular microgrid with separated AC bus and decentralized control strategy is proposed in this paper. Each module is a self-powered system, which consists of wind and solar power, a storage battery, load and three-port converter. The modules are interconnected by three-port converters to form the microgrid. Characteristics, operation principle, control of the modular microgrid and the three-port converter are analyzed in detail. Distributed storage batteries enable power exchanges among modules to enhance economic returns. Economic dispatch of the stand-alone modular microgrid is a mixed-integer programming problem. A day-ahead operation optimization model including fuel cost, battery operation cost, and power transmission cost is established. Because there are so many constraints, it is difficult to produce a feasible solution and even more difficult to have an improved solution. An improved simplified swarm optimization (iSSO method is therefore proposed. The iSSO scheme designs the new update mechanism and survival of the fittest policy. The experimental results from the demonstration project on DongAo Island reflect the effectiveness of the stand-alone modular microgrid and the economic dispatch strategy based on the iSSO method.
Energy Technology Data Exchange (ETDEWEB)
Wang, Hong [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wang, Shaobu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fan, Rui [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhang, Zhuanfang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2016-09-30
This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it has been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.
Research on wind power grid-connected operation and dispatching strategies of Liaoning power grid
Han, Qiu; Qu, Zhi; Zhou, Zhi; He, Xiaoyang; Li, Tie; Jin, Xiaoming; Li, Jinze; Ling, Zhaowei
2018-02-01
As a kind of clean energy, wind power has gained rapid development in recent years. Liaoning Province has abundant wind resources and the total installed capacity of wind power is in the forefront. With the large-scale wind power grid-connected operation, the contradiction between wind power utilization and peak load regulation of power grid has been more prominent. To this point, starting with the power structure and power grid installation situation of Liaoning power grid, the distribution and the space-time output characteristics of wind farm, the prediction accuracy, the curtailment and the off-grid situation of wind power are analyzed. Based on the deep analysis of the seasonal characteristics of power network load, the composition and distribution of main load are presented. Aiming at the problem between the acceptance of wind power and power grid adjustment, the scheduling strategies are given, including unit maintenance scheduling, spinning reserve, energy storage equipment settings by the analysis of the operation characteristics and the response time of thermal power units and hydroelectric units, which can meet the demand of wind power acceptance and provide a solution to improve the level of power grid dispatching.
International Nuclear Information System (INIS)
Cheng, Chuntian; Li, Shushan; Li, Gang
2014-01-01
The energy-saving generation dispatch (ESGD) policy released by Chinese Government in 2007 is a new code for optimally dispatching electric power generation portfolio in the country with the dual objectives of improving energy efficiency and reducing environmental pollution. The ESGD is substantially different from the competitive market in the developed economies, the traditional economic dispatching or the rational dispatching principle implemented in China prior to the new policy. This paper develops a hybrid method that integrates the extended priority list (EPL), the equal incremental principle (EIP) and a heuristic method to optimize daily generation schedules under ESGD. The EPL is presented to search desirable units set that satisfies the complicated duration period requirements based on thermal unit generation priority list. The EIP is developed to allocate load among the committed units within the combined set. A heuristic method is proposed to deal with inequality constraints, which usually result in difficulty for power allocation, and used to improve these results. The algorithm has been embedded into a newly developed decision support system that is currently being used by operators of the Guizhou Province Power Grid to make day-ahead quarter-hourly generation schedules. - Highlights: • Electric power industry is one of key and important fields for energy conservation and emission reduction in China. • The energy-saving generation dispatch policy was released by Chinese government in 2007. • A Hybrid algorithm for energy-saving generation dispatch scheduling of thermal power system is presented. • The algorithm has been embedded into a newly developed decision support system
International Nuclear Information System (INIS)
Cheng Chuntian; Liao Shengli; Tang Zitian; Zhao Mingyan
2009-01-01
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.
Energy Technology Data Exchange (ETDEWEB)
Cheng Chuntian, E-mail: ctcheng@dlut.edu.c [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Liao Shengli; Tang Zitian [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Zhao Mingyan [Department of Environmental Science and Engineering, Tsinghua University, 100084 Beijing (China)
2009-12-15
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.
Energy Technology Data Exchange (ETDEWEB)
Chun-tian Cheng; Sheng-li Liao; Zi-Tian Tang [Dept. of Civil and Hydraulic Engineering, Dalian Univ. of Technology, 116024 Dalian (China); Ming-yan Zhao [Dept. of Environmental Science and Engineering, Tsinghua Univ., 100084 Beijing (China)
2009-12-15
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations. (author)
Solar hybrid power plants: Solar energy contribution in reaching full dispatchability and firmness
Servert, Jorge F.; López, Diego; Cerrajero, Eduardo; Rocha, Alberto R.; Pereira, Daniel; Gonzalez, Lucía
2016-05-01
Renewable energies for electricity generation have always been considered as a risk for the electricity system due to its lack of dispatchability and firmness. Renewable energies penetration is constrained to strong grids or else its production must be limited to ensure grid stability, which is kept by the usage of hydropower energy or fossil-fueled power plants. CSP technology has an opportunity to arise not only as a dispatchable and firm technology, but also as an alternative that improves grid stability. To achieve that objective, solar hybrid configurations are being developed, being the most representative three different solutions: SAPG, ISCC and HYSOL. A reference scenario in Kingdom of Saudi Arabia (KSA) has been defined to compare these solutions, which have been modelled, simulated and evaluated in terms of dispatchability and firmness using ratios defined by the authors. The results show that: a) SAPG obtains the highest firmness KPI values, but no operation constraints have been considered for the coal boiler and the solar energy contribution is limited to 1.7%, b) ISCC provides dispatchable and firm electricity production but its solar energy contribution is limited to a 6.4%, and c) HYSOL presents the higher solar energy contribution of all the technologies considered: 66.0% while providing dispatchable and firm generation in similar conditions as SAPG and ISCC.
Space-time wind speed forecasting for improved power system dispatch
Zhu, Xinxin; Genton, Marc G.; Gu, Yingzhong; Xie, Le
2014-01-01
direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast
International Nuclear Information System (INIS)
Jeddi, Babak; Vahidinasab, Vahid
2014-01-01
Highlights: • A combined economic and emission load dispatch (CEELD) model is proposed. • The proposed model considers practical constraints of real-world power systems. • A new modified harmony search algorithm proposed to solve non-convex CEELD. • The proposed algorithm is tested by applying it to solve seven test systems. - Abstract: Economic load dispatch (ELD) problem is one of the basic and important optimization problems in a power system. However, considering practical constraints of real-world power systems such as ramp rate limits, prohibited operating zones, valve loading effects, multi-fuel options, spinning reserve and transmission system losses in ELD problem makes it a non-convex optimization problem, which is a challenging one and cannot be solved by traditional methods. Moreover, considering environmental issues, results in combined economic and emission load dispatch (CEELD) problem that is a multiobjective optimization model with two non-commensurable and contradictory objectives. In this paper, a modified harmony search algorithm (MHSA) proposed and applied to solve ELD and CEELD problem considering the abovementioned constraints. In the proposed MHSA, a new improvising method based on wavelet mutation together with a new memory consideration scheme based on the roulette wheel mechanism are proposed which improves the accuracy, convergence speed, and robustness of the classical HSA. Performance of the proposed algorithm is investigated by applying it to solve various test systems having non-convex solution spaces. To Show the effectiveness of the proposed method, obtained results compared with classical harmony search algorithm (HSA) and some of the most recently published papers in the area
Framework for the analysis of reactive power dispatch in energy pools
International Nuclear Information System (INIS)
Salgado, R.S.; Irving, M.R.
2004-01-01
This paper proposes a framework for the simulation and analysis of the reactive power distribution in electric energy markets of the pool type. Firstly, the analytical formulation of the OPF problem, with three optional performance indexes for the reactive power dispatch, is discussed. These OPF objectives are used to determine the reactive power distribution for a given active power dispatch (obtained through merit-order strategy, for instance). An allocation strategy is used to assess the participation of each power system agent in the loss/reactive power distribution. This strategy uses the premise of co-operative game theory. Numerical results obtained with the Ward-Hale 6-bus test system illustrate the main aspects of the proposed methodology. (author)
A study on economic power dispatch grid connected PV power plant in educational institutes
Singh, Kuldip; Kumar, M. Narendra; Mishra, Satyasis
2018-04-01
India has main concerns on environment and escalation of fuel prices with respect to diminution of fossil fuel reserves and the major focus on renewable Energy sources for power generation to fulfill the present and future energy demand. Installation of PV power plants in the Educational Institutions has grown up drastically throughout India. More PV power plant are integrated with load and grid through net metering. Therefore, this paper is an analysis of the 75kWp PV plant at chosen buses, considering the need of minimum demand from the grid. The case study is carried out for different generation level throughout the day and year w.r.t load and climate changes, load sharing on grid. The economic dispatch model developed for PV plant integrated with Grid.
International Nuclear Information System (INIS)
Nagl, Stephan; Fuersch, Michaela; Lindenberger, Dietmar
2012-01-01
Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.
Optimized Dispatch Schedule for Autonomous Grids in Isolated Islands
Directory of Open Access Journals (Sweden)
Fan Liuyang
2016-01-01
Full Text Available The rapid development of wind power provides a new solution for power supply of isolated island. However, due to the intermittent and stochastic nature of renewable energy resources (RES, the energy storage unit (ESU is required for power grid reliability. This paper proposed an automatic programming method for autonomous grid in isolated islands. The sea water pumped storage plant serves as ESU to counter-balance the fluctuations of RESs. The penetration level of RES and the profit of the Island system operator (ISO increase significantly. With the geographical and historical data of an island in China, the effectiveness of the proposed method is testified.
International Nuclear Information System (INIS)
Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen
2017-01-01
Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.
Directory of Open Access Journals (Sweden)
Changsun Ahn
2013-12-01
Full Text Available Microgrids can deploy traditional and/or renewable power sources to support remote sites. Utilizing renewable power sources requires more complicated control strategies to achieve acceptable power quality and maintain grid stability. In this research, we assume that the grid stability problem is already solved. As a next step, we focus on how the power can be dispatched from multiple power sources for improved grid efficiency. Isolated microgrids frequently require reconfigurations because of the grid expansion or component failures. Therefore, the control strategies ideally should be implemented in a plug-and-play fashion. Moreover, these strategies ideally require no pre-knowledge of the grid structure, and as little communication with neighboring power sources as possible. The control objective is to minimize a cost function that can be adjusted to reflect the desire to minimize energy cost and/or losses. An algorithm is designed to satisfy a derived necessary condition of function optimality. Such conditions are obtained by formulating Lagrange functions. An equivalent grid model approximates the grid structure which was later confirmed to represent the grid behavior adequately. For decentralized operations, we execute the distributed control sequentially using a simple token communication protocol. The performance of the combined system identification-Lagrange function minimization algorithm is demonstrated through simulations.
Robust optimization-based DC optimal power flow for managing wind generation uncertainty
Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn
2012-11-01
Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.
International Nuclear Information System (INIS)
Xiong, Guojiang; Li, Yinhong; Chen, Jinfu; Shi, Dongyuan; Duan, Xianzhong
2014-01-01
Highlights: • New method for dynamic economic dispatch problem using POLBBO. • Considering valve-point effects, ramp rate limits, transmission network losses. • POLBBO is able to balance the global exploration and the local exploitation. • An effective simultaneous constraints handling technique is proposed. • The achieved results by POLBBO are better than those reported in other literatures. - Abstract: Shortage of energy resources, rising power generation cost, and increasing electric energy demand make the dynamic economic dispatch (DED) increasingly necessary in today’s competitive electricity market. In this paper, an enhanced biogeography-based optimization (BBO) referred to as POLBBO is proposed to solve the DED problem with valve-point effects. BBO is a relatively new powerful population-based meta-heuristic algorithm inspired by biogeography and has been extensively applied to many scientific and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess good local exploitation ability but lack enough global exploration ability. To remedy the defect, on one hand, an efficient operator named polyphyletic migration operator is proposed to enhance the search ability of POLBBO. This operator can not only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is presented. The OL strategy can quickly discover useful information from the search experiences and effectively utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. In addition, an effective simultaneous constraints handling technique without penalty factor settings is developed to handle various complicated constraints of the DED problem. Finally, four test
International Nuclear Information System (INIS)
Gu, Wei; Lu, Shuai; Wu, Zhi; Zhang, Xuesong; Zhou, Jinhui; Zhao, Bo; Wang, Jun
2017-01-01
Highlights: •A bilateral transaction mode for the residential CCHP microgrid is proposed. •An energy pricing strategy for the residential CCHP system is proposed. •A novel integrated demand response for the residential loads is proposed. •Two-stage operation optimization model for the CCHP microgrid is proposed. •Operations of typical days and annual scale of the CCHP microgrid are studied. -- Abstract: As the global energy crisis, environmental pollution, and global warming grow in intensity, increasing attention is being paid to combined cooling, heating, and power (CCHP) systems that realize high-efficiency cascade utilization of energy. This paper proposes a bilateral transaction mechanism between a residential CCHP system and a load aggregator (LA). The variable energy cost of the CCHP system is analyzed, based on which an energy pricing strategy for the CCHP system is proposed. Under this pricing strategy, the electricity price is constant, while the heat/cool price is ladder-shaped and dependent on the relationship between the electrical, heat, and cool loads. For the LA, an integrated demand response program is proposed that combines electricity-load shifting and a flexible heating/cooling supply, in which a thermodynamic model of buildings is used to determine the appropriate range of heating/cooling supply. Subsequently, a two-stage optimal dispatch model is proposed for the energy system that comprises the CCHP system and the LA. Case studies consisting of three scenarios (winter, summer, and excessive seasons) are delivered to demonstrate the effectiveness of the proposed approach, and the performance of the proposed pricing strategy is also evaluated by annual operation simulations.
The Optimization dispatching of Micro Grid Considering Load Control
Zhang, Pengfei; Xie, Jiqiang; Yang, Xiu; He, Hongli
2018-01-01
This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.
Optimize-and-Dispatch Architecture for Expressive Ad Auctions
Parkes, David C.; Sandholm, Tuomas
2005-01-01
Ad auctions are generating massive amounts of revenue for online search engines such as Google. Yet, the level of expressiveness provided to participants in ad auctions could be significantly enhanced. An advantage of this could be improved competition and thus improved revenue to a seller of the right to advertise to a stream of search queries. In this paper, we outline the kinds of expressiveness that one might expect to be useful for ad auctions and introduce a high-level “optimize-and-...
International Nuclear Information System (INIS)
Engels, Klaus; Harasta, Michaela; Braitsch, Werner; Moser, Albert; Schaefer, Andreas
2012-01-01
In Germany's energy markets of today, pumped-storage power plants offer excellent business opportunities due to their outstanding flexibility. However, the energy-economic simulation of pumped-storage plants, which is necessary to base the investment decision on a sound business case, is a highly complex matter since the plant's capacity must be optimized in a given plant portfolio and between two relevant markets: the scheduled wholesale and the reserve market. This mathematical optimization problem becomes even more complex when the question is raised as to which type of machine should be used for a pumped-storage new build option. For the first time, it has been proven possible to simulate the optimum dispatch of different pumped-storage machine concepts within two relevant markets - the scheduled wholesale and the reserve market - thereby greatly supporting the investment decision process. The methodology and findings of a cooperation study between E.ON and RWTH Aachen University in respect of the German pumped-storage extension project 'Waldeck 2+' are described, showing the latest development in dispatch simulation for generation portfolios. (authors)
Directory of Open Access Journals (Sweden)
Ming Zhang
2016-01-01
Full Text Available Aviation emergency rescue is an effective means of nature disaster relief that is widely used in many countries. The dispatching plan of aviation emergency rescue guarantees the efficient implementation of this relief measure. The conventional dispatching plan that does not consider random wind factors leads to a nonprecise quick-responsive scheme and serious safety issues. In this study, an aviation emergency rescue framework that considers the influence of random wind at flight trajectory is proposed. In this framework, the predicted wind information for a disaster area is updated by using unscented Kalman filtering technology. Then, considering the practical scheduling problem of aircraft emergency rescue at present, a multiobjective model is established in this study. An optimization model aimed at maximizing the relief supply satisfaction, rescue priority satisfaction, and minimizing total rescue flight distance is formulated. Finally, the transport times of aircraft with and without the influence of random wind are analyzed on the basis of the data of an earthquake disaster area. Results show that the proposed dispatching plan that considers the constraints of updated wind speed and direction is highly applicable in real operations.
Novel Controls for Time-Dependent Economic Dispatch of Combined Cooling Heating and Power (CCHP)
Energy Technology Data Exchange (ETDEWEB)
Samuelsen, Scott; Brouwer, Jack
2013-08-31
The research and development effort detailed in this report directly addresses the challenge of reducing U.S. industrial energy and carbon intensity by contributing to an increased understanding of potential CCHP technology, the CCHP market and the challenges of widespread adoption. This study developed a number of new tools, models, and approaches for the design, control, and optimal dispatch of various CCHP technologies. The UC Irvine campus served as a ‘living laboratory’ of new CCHP technologies and enabled the design and demonstration of several novel control methods. In particular, the integration of large scale thermal energy storage capable of shifting an entire day of cooling demand required a novel approach to the CCHP dispatch optimization. The thermal energy storage proved an economically viable resource which reduced both costs and emissions by enabling generators and chillers to operate under steady high efficiency conditions at all times of the day.
Zhang, Yunju; Chen, Zhongyi; Guo, Ming; Lin, Shunsheng; Yan, Yinyang
2018-01-01
With the large capacity of the power system, the development trend of the large unit and the high voltage, the scheduling operation is becoming more frequent and complicated, and the probability of operation error increases. This paper aims at the problem of the lack of anti-error function, single scheduling function and low working efficiency for technical support system in regional regulation and integration, the integrated construction of the error prevention of the integrated architecture of the system of dispatching anti - error of dispatching anti - error of power network based on cloud computing has been proposed. Integrated system of error prevention of Energy Management System, EMS, and Operation Management System, OMS have been constructed either. The system architecture has good scalability and adaptability, which can improve the computational efficiency, reduce the cost of system operation and maintenance, enhance the ability of regional regulation and anti-error checking with broad development prospects.
International Nuclear Information System (INIS)
Al-Othman, A.K.; El-Naggar, K.M.
2008-01-01
Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED) with non-smooth cost function. Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using three different test systems. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED). In addition, valve-point effect loading and total system losses are considered to further investigate the potential of the PS technique. Based on the results, it can be concluded that the PS has demonstrated ability in handling highly nonlinear discontinuous non-smooth cost function of the SCED. (author)
Directory of Open Access Journals (Sweden)
Yuan Bo
2018-01-01
Full Text Available According to different operating characteristics of pumped storage fixed speed unit and variable speed unit, a joint dispatching model of pumped storage unit and other types of units based on mixed integer linear optimization is constructed. The model takes into account the operating conditions, reservoir capacity, cycle type and other pumped storage unit constraints, but also consider the frequent start and stop and the stability of the operation of the unit caused by the loss. Using the Cplex solver to solve the model, the empirical example of the provincial power grid shows that the model can effectively arrange the pumping storage speed and the dispatching operation of the variable speed unit under the precondition of economic life of the unit, and give full play to the function of peak shaving and accommodating new energy. Because of its more flexible regulation characteristics of power generation and pumping conditions, the variable speed unit can better improve the operating conditions of other units in the system and promote the new energy dissipation.
Yuan, Bo; Zong, Jin; Xu, Zhicheng
2018-06-01
According to different operating characteristics of pumped storage fixed speed unit and variable speed unit, a joint dispatching model of pumped storage unit and other types of units based on mixed integer linear optimization is constructed. The model takes into account the operating conditions, reservoir capacity, cycle type and other pumped storage unit constraints, but also consider the frequent start and stop and the stability of the operation of the unit caused by the loss. Using the Cplex solver to solve the model, the empirical example of the provincial power grid shows that the model can effectively arrange the pumping storage speed and the dispatching operation of the variable speed unit under the precondition of economic life of the unit, and give full play to the function of peak shaving and accommodating new energy. Because of its more flexible regulation characteristics of power generation and pumping conditions, the variable speed unit can better improve the operating conditions of other units in the system and promote the new energy dissipation.
International Nuclear Information System (INIS)
Azadani, E. Nasr; Hosseinian, S.H.; Moradzadeh, B.
2010-01-01
Competitive bidding for energy and ancillary services is increasingly recognized as an important part of electricity markets. In addition, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on constrained particle swarm optimization (CPSO) is developed to deal with the multi-product (energy and reserve) and multi-area electricity market dispatch problem. Constraint handling is based on particle ranking and uniform distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive electricity market considering the system constraints. The proposed technique shows promising performance for smooth and non smooth cost function as well. Three different systems are examined to demonstrate the effectiveness and the accuracy of the proposed algorithm. (author)
Genetic algorithm based reactive power dispatch for voltage stability improvement
Energy Technology Data Exchange (ETDEWEB)
Devaraj, D. [Department of Electrical and Electronics, Kalasalingam University, Krishnankoil 626 190 (India); Roselyn, J. Preetha [Department of Electrical and Electronics, SRM University, Kattankulathur 603 203, Chennai (India)
2010-12-15
Voltage stability assessment and control form the core function in a modern energy control centre. This paper presents an improved Genetic algorithm (GA) approach for voltage stability enhancement. The proposed technique is based on the minimization of the maximum of L-indices of load buses. Generator voltages, switchable VAR sources and transformer tap changers are used as optimization variables of this problem. The proposed approach permits the optimization variables to be represented in their natural form in the genetic population. For effective genetic processing, the crossover and mutation operators which can directly deal with the floating point numbers and integers are used. The proposed algorithm has been tested on IEEE 30-bus and IEEE 57-bus test systems and successful results have been obtained. (author)
Artificial bee colony algorithm for economic load dispatch with wind power energy
Directory of Open Access Journals (Sweden)
Safari Amin
2016-01-01
Full Text Available This paper presents an efficient Artificial Bee Colony (ABC algorithm for solving large scale economic load dispatch (ELD problems in power networks. To realize the ELD, the valve-point loading effect, system load demand, power losses, ramp rate limits and prohibited operation zones are considered here. Simulations were performed on four different power systems with 3, 6, 15 and 40 generating units and the results are compared with two forms of power systems, one power system is with a wind power generator and other power system is without a wind power generator. The results of this study reveal that the proposed approach is able to find appreciable ELD solutions than those of previous algorithms.
International Nuclear Information System (INIS)
Zou, Dexuan; Li, Steven; Li, Zongyan; Kong, Xiangyong
2017-01-01
Highlights: • A new global particle swarm optimization (NGPSO) is proposed. • NGPSO has strong convergence and desirable accuracy. • NGPSO is used to handle the economic emission dispatch with or without transmission losses. • The equality constraint can be satisfied by solving a quadratic equation. • The inequality constraints can be satisfied by using penalty function method. - Abstract: A new global particle swarm optimization (NGPSO) algorithm is proposed to solve the economic emission dispatch (EED) problems in this paper. NGPSO is different from the traditional particle swarm optimization (PSO) algorithm in two aspects. First, NGPSO uses a new position updating equation which relies on the global best particle to guide the searching activities of all particles. Second, it uses the randomization based on the uniform distribution to slightly disturb the flight trajectories of particles during the late evolutionary process. The two steps enable NGPSO to effectively execute a number of global searches, and thus they increase the chance of exploring promising solution space, and reduce the probabilities of getting trapped into local optima for all particles. On the other hand, the two objective functions of EED are normalized separately according to all candidate solutions, and then they are incorporated into one single objective function. The transformation steps are very helpful in eliminating the difference caused by the different dimensions of the two functions, and thus they strike a balance between the fuel cost and emission. In addition, a simple and common penalty function method is employed to facilitate the satisfactions of EED’s constraints. Based on these improvements in PSO, objective functions and constraints handling, high-quality solutions can be obtained for EED problems. Five examples are chosen to testify the performance of three improved PSOs on solving EED problems with or without transmission losses. Experimental results show that
DEFF Research Database (Denmark)
Faria, Pedro; Soares, Tiago; Vale, Zita
2014-01-01
Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets’ environment, with deep concerns at the efficiency level. In this context, grid operators, market...... proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources’ participation can be performed in both energy and reserve contexts. This methodology contemplates...
Energy Technology Data Exchange (ETDEWEB)
Sriyanyong, P. [King Mongkut' s Univ. of Technology, Bangkok (Thailand). Dept. of Teacher Training in Electrical Engineering
2008-07-01
This paper described the use of an enhanced particle swarm optimization (PSO) model to address the problem of dynamic economic dispatch (DED). A modified heuristic search method was incorporated into the PSO model. Both smooth and non-smooth cost functions were considered. The enhanced PSO model not only utilized the basic PSO algorithm in order to seek the optimal solution for the DED problem, but it also used a modified heuristic method to deal with constraints and increase the possibility of finding a feasible solution. In order to validate the enhanced PSO model, it was used and tested on 10-unit systems considering both smooth and non-smooth cost functions characteristics. The experimental results were also compared to other methods. The proposed technique was found to be better than other approaches. The enhanced PSO model outperformed others with respect to quality, stability and reliability. 23 refs., 1 tab., 8 figs.
Anti-predatory particle swarm optimization: Solution to nonconvex economic dispatch problems
Energy Technology Data Exchange (ETDEWEB)
Selvakumar, A. Immanuel [Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore 641114, Tamilnadu (India); Thanushkodi, K. [Department of Electronics and Instrumentation Engineering, Government College of Technology, Coimbatore 641013, Tamilnadu (India)
2008-01-15
This paper proposes a new particle swarm optimization (PSO) strategy namely, anti-predatory particle swarm optimization (APSO) to solve nonconvex economic dispatch problems. In the classical PSO, the movement of a particle (bird) is governed by three behaviors: inertial, cognitive and social. The cognitive and social behaviors are the components of the foraging activity, which help the swarm of birds to locate food. Another activity that is observed in birds is the anti-predatory nature, which helps the swarm to escape from the predators. In this work, the anti-predatory activity is modeled and embedded in the classical PSO to form APSO. This inclusion enhances the exploration capability of the swarm. To validate the proposed APSO model, it is applied to two test systems having nonconvex solution spaces. Satisfactory results are obtained when compared with previous approaches. (author)
Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch
Xie, Le; Gu, Yingzhong; Zhu, Xinxin; Genton, Marc G.
2014-01-01
forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24
Directory of Open Access Journals (Sweden)
Ming-Tse Kuo
2013-07-01
Full Text Available Taiwan’s power system is isolated and not supported by other interconnected systems. Consequently, the system frequency immediately reflects changes in the system loads. Pumped storage units are crucial for controlling power frequency. These units provide main or auxiliary capacities, reducing the allocation of frequency-regulating reserve (FRR and further reducing generation costs in system operations. Taiwan’s Longmen Nuclear Power Plant is set to be converted for commercial operations, which will significantly alter the spinning reserves in the power system. Thus, this study proposes a safe and economic pumped storage unit dispatch strategy. This strategy is used to determine the optimal FRR capacity and 1-min recovery frequency in a generator failure occurrence at the Longmen Power Plant. In addition, this study considered transmission capacity constraints and conducted power flow analysis of the power systems in Northern, Central, and Southern Taiwan. The results indicated that, in the event of a failure at Longmen Power Plant, the proposed strategy can not only recover the system frequency to an acceptable range to prevent underfrequency load-shedding, but can also mitigate transmission line overloading.
International Nuclear Information System (INIS)
Neves, Diana; Silva, Carlos A.
2015-01-01
The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs
International Nuclear Information System (INIS)
Lu Youlin; Zhou Jianzhong; Qin Hui; Wang Ying; Zhang Yongchuan
2011-01-01
An enhanced multi-objective differential evolution algorithm (EMODE) is proposed in this paper to solve environmental/economic dispatch (EED) problem by considering the minimal of fuel cost and emission effects synthetically. In the proposed algorithm, an elitist archive technique is adopted to retain the non-dominated solutions obtained during the evolutionary process, and the operators of DE are modified according to the characteristics of multi-objective optimization problems. Moreover, in order to avoid premature convergence, a local random search (LRS) operator is integrated with the proposed method to improve the convergence performance. In view of the difficulties of handling the complicated constraints of EED problem, a new heuristic constraints handling method without any penalty factor settings is presented. The feasibility and effectiveness of the proposed EMODE method is demonstrated for a test power system. Compared with other methods, EMODE can get higher quality solutions by reducing the fuel cost and the emission effects synthetically.
An effortless hybrid method to solve economic load dispatch problem in power systems
International Nuclear Information System (INIS)
Pourakbari-Kasmaei, M.; Rashidi-Nejad, M.
2011-01-01
Highlights: → We proposed a fast method to get feasible solution and avoid futile search. → The method dramatically improves search efficiency and solution quality. → Applied to solve constrained ED problems of power systems with 6 and 15 unit. → Superiority of this method in both aspects of financial and CPU time is remarkable. - Abstract: This paper proposes a new approach and coding scheme for solving economic dispatch problems (ED) in power systems through an effortless hybrid method (EHM). This novel coding scheme can effectively prevent futile searching and also prevents obtaining infeasible solutions through the application of stochastic search methods, consequently dramatically improves search efficiency and solution quality. The dominant constraint of an economic dispatch problem is power balance. The operational constraints, such as generation limitations, ramp rate limits, prohibited operating zones (POZ), network loss are considered for practical operation. Firstly, in the EHM procedure, the output of generator is obtained with a lambda iteration method and without considering POZ and later in a genetic based algorithm this constraint is satisfied. To demonstrate its efficiency, feasibility and fastness, the EHM algorithm was applied to solve constrained ED problems of power systems with 6 and 15 units. The simulation results obtained from the EHM were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time.
DEFF Research Database (Denmark)
Juul, Nina; Mullane, Alan; Meibom, Peter
plants. For the future transport system, electric drive vehicles are expected to be one of the solutions. Introducing different electric drive vehicle penetrations in a power system with a large amount of wind power, changes the usage of the predefined power system. This work presents investigations......Increased focus on global warming and CO2 emissions imply increased focus on the energy system, consisting of the heat, power, and transport systems. Solutions for the heat and power system are increasing penetrations of renewable heat and power generation plants such as wind power and biomass heat...... of different charging regimes’ influence of the power dispatch in the Irish power system. Analyses show an overall cost decrease and CO2 emission increase in the heat and power system with the introduction of electric drive vehicles. Furthermore, increased intelligence in the electric drive vehicle charging...
Stochastic model of wind-fuel cell for a semi-dispatchable power generation
DEFF Research Database (Denmark)
Alvarez-Mendoza, Fernanda; Bacher, Peder; Madsen, Henrik
2017-01-01
electrolyte membrane fuel cell, which are embedded in one complete system with the wind power. This study uses historic wind speed data from Mexico; the forecasts are obtained using the recursive least square algorithm with a forgetting factor. The proposed approach provides probabilistic information......Hybrid systems are implemented to improve the efficiency of individual generation technologies by complementing each other. Intermittence is a challenge to overcome especially for renewable energy sources for electric generation, as in the case of wind power. This paper proposes a hybrid system...... for short-term wind power generation and electric generation as the outcome of the hybrid system. A method for a semi-dispatchable electric generation based on time series analysis is presented, and the implementation of wind power and polymer electrolyte membrane fuel cell models controlled by a model...
A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch
Energy Technology Data Exchange (ETDEWEB)
Niknam, Taher; Mojarrad, Hassan Doagou; Nayeripour, Majid [Electrical and Electronic Engineering Department, Shiraz University of Technology, Shiraz (Iran)
2010-04-15
This paper proposes a novel method for solving the Non-convex Economic Dispatch (NED) problems, by the Fuzzy Adaptive Modified Particle Swarm Optimization (FAMPSO). Practical ED problems have non-smooth cost functions with equality and inequality constraints when generator valve-point loading effects are taken into account. Modern heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution for ED problems. PSO is one of modern heuristic algorithms, in which particles change place to get close to the best position and find the global minimum point. However, the classic PSO may converge to a local optimum solution and the performance of the PSO highly depends on the internal parameters. To overcome these drawbacks, in this paper, a new mutation is proposed to improve the global searching capability and prevent the convergence to local minima. Also, a fuzzy system is used to tune its parameters such as inertia weight and learning factors. In order to evaluate the performance of the proposed algorithm, it is applied to a system consisting of 13 and 40 thermal units whose fuel cost function is calculated by taking account of the effect of valve-point loading. Simulation results demonstrate the superiority of the proposed algorithm compared to other optimization algorithms presented in literature. (author)
Zhang, Huifeng; Lei, Xiaohui; Wang, Chao; Yue, Dong; Xie, Xiangpeng
2017-01-01
Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications.
Directory of Open Access Journals (Sweden)
Chintalapudi V. Suresh
2015-09-01
Full Text Available This paper presents an attempt to analyze the effect of multi-fuel and practical constraints on economic load dispatch problem using a novel uniform distributed two-stage particle swarm optimization (UDTPSO algorithm without and with unified power flow controller (UPFC while satisfying equality, inequality, practical constraints such as ramp-rate and prohibited operating zone (POZ limits and device operating limits. A Novel severity function is formulated based on the transmission line overloads and bus voltage violations to identify an optimal location to install UPFC. A multi-objective optimization problem is solved for multi-fuel non-convex cost and transmission power loss objectives. Obtained results for considered standard test functions and electrical systems indicate the effectiveness of the proposed algorithm and can obtain efficient solution when compared to existing methods. Hence, the proposed method is a promising method and can be easily applied to optimize the power system objectives.
International Nuclear Information System (INIS)
Azizipanah-Abarghooee, Rasoul; Golestaneh, Faranak; Gooi, Hoay Beng; Lin, Jeremy; Bavafa, Farhad; Terzija, Vladimir
2016-01-01
Highlights: • Suggesting a new UC mixing a probabilistic security and incentive demand response. • Investigating the effects of uncertainty on UC using chance-constraint programming. • Proposing an efficient spinning reserve satisfaction based on a new ED correction. • Presenting a new operational cycles way to convert binary variable to discrete one. - Abstract: We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers’ benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n − 1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved Jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems.
Wind Farm-LA Coordinated Operation Mode and Dispatch Model in Wind Power Accommodation Promotion
Directory of Open Access Journals (Sweden)
Li Lin
2018-05-01
Full Text Available With the support of a smart grid, a load aggregator (LA that aggregates the demand response resources of small- and medium-sized customers to participate in the electricity market would be a novel way to promote wind power accommodation. This paper proposes a wind farm–LA coordinated operation mode (WLCOM, which enables LAs to deal with wind farms directly at an agreement price. Afterwards, according to the accommodation demand of the wind farm, a coordinated dispatch model taking advantage of the various response capabilities of different flexible loads is set up to maximize the revenue of the LA. A case study was conducted to demonstrate the effectiveness of the proposed WLCOM and the coordinated dispatch model. The demonstration indicates that: (a load fluctuations and wind curtailment were obviously reduced; and (b both the LA and the wind farm participating in coordinated operation obtained higher revenues. Factors that influence the accommodation level, as well as revenues of wind farms and LA, are also investigated.
Economic Dispatch for Power System Included Wind and Solar Thermal Energy
Directory of Open Access Journals (Sweden)
Saoussen BRINI
2009-07-01
Full Text Available With the fast development of technologies of alternative energy, the electric power network can be composed of several renewable energy resources. The energy resources have various characteristics in terms of operational costs and reliability. In this study, the problem is the Economic Environmental Dispatching (EED of hybrid power system including wind and solar thermal energies. Renewable energy resources depend on the data of the climate such as the wind speed for wind energy, solar radiation and the temperature for solar thermal energy. In this article it proposes a methodology to solve this problem. The resolution takes account of the fuel costs and reducing of the emissions of the polluting gases. The resolution is done by the Strength Pareto Evolutionary Algorithm (SPEA method and the simulations have been made on an IEEE network test (30 nodes, 8 machines and 41 lines.
International Nuclear Information System (INIS)
Nwulu, Nnamdi I.; Xia, Xiaohua
2015-01-01
Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model
Energy Technology Data Exchange (ETDEWEB)
Miller, R.J.; Najaf-Zadeh, K.; Darlington, H.T.; McNair, H.D.; Seidenstein, S.; Williams, A.R.
1982-10-01
Human factors is a systems-oriented interdisciplinary specialty concerned with the design of systems, equipment, facilities and the operational environment. An important aspect leading to the design requirements is the determination of the information requirements for electric power dispatch control centers. There are significant differences between the system operator's actions during normal and degraded states of power system operation, and power system restoration. This project evaluated the information the operator requires for normal power system and control system operations and investigates the changes of information required by the operator as the power system and/or the control system degrades from a normal operating state. The Phase II study, published in two volumes, defines power system states and control system conditions to which operator information content can be related. This volume presents detailed data concerning operator information needs that identify the needs for and the uses of power system information by a system operator in conditions ranging from normal through degraded operation. The study defines power system states and control system conditions to which operator information content can be related, and it identifies the requisite information as consistent with current industry practice so as to aid control system designers. Training requirements are also included for planning entry-level and follow-on training for operators.
International Nuclear Information System (INIS)
Despres, Jacques
2015-12-01
Renewable sources of electricity production are strongly increasing in many parts of the world. The production costs are going down quickly, thus accelerating the deployment of new solar and wind electricity generation. In the long-term, these variable sources of electricity could represent a high share of the power system. However, long-term foresight energy models have difficulties describing precisely the integration challenges of Variable Renewable Energy Sources (VRES) such as wind or solar. They just do not represent the short-term technical constraints of the power sector. The objective of this paper is to show a new approach of the representation of the challenges of variability in the long-term foresight energy model POLES (Prospective Outlook on Long-term Energy Systems). We develop a short-term optimization model for the power sector operation, EUCAD (European Unit Commitment and Dispatch) and we couple it to POLES year after year. The direct coupling, with bi-directional exchanges of information, brings technical precision to the long-term coherence of energy scenarios. (author)
A Decomposition Method for Security Constrained Economic Dispatch of a Three-Layer Power System
Yang, Junfeng; Luo, Zhiqiang; Dong, Cheng; Lai, Xiaowen; Wang, Yang
2018-01-01
This paper proposes a new decomposition method for the security-constrained economic dispatch in a three-layer large-scale power system. The decomposition is realized using two main techniques. The first is to use Ward equivalencing-based network reduction to reduce the number of variables and constraints in the high-layer model without sacrificing accuracy. The second is to develop a price response function to exchange signal information between neighboring layers, which significantly improves the information exchange efficiency of each iteration and results in less iterations and less computational time. The case studies based on the duplicated RTS-79 system demonstrate the effectiveness and robustness of the proposed method.
Space-time wind speed forecasting for improved power system dispatch
Zhu, Xinxin
2014-02-27
To support large-scale integration of wind power into electric energy systems, state-of-the-art wind speed forecasting methods should be able to provide accurate and adequate information to enable efficient, reliable, and cost-effective scheduling of wind power. Here, we incorporate space-time wind forecasts into electric power system scheduling. First, we propose a modified regime-switching, space-time wind speed forecasting model that allows the forecast regimes to vary with the dominant wind direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast models. This, in turn, leads to cost-effective scheduling of system-wide wind generation. Potential economic benefits arise from the system-wide generation of cost savings and from the ancillary service cost savings. We illustrate the economic benefits using a test system in the northwest region of the United States. Compared with persistence and autoregressive models, our model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars annually in regions with high wind penetration, such as Texas and the Pacific northwest. © 2014 Sociedad de Estadística e Investigación Operativa.
Transmission tariffs based on optimal power flow
International Nuclear Information System (INIS)
Wangensteen, Ivar; Gjelsvik, Anders
1998-01-01
This report discusses transmission pricing as a means of obtaining optimal scheduling and dispatch in a power system. This optimality includes consumption as well as generation. The report concentrates on how prices can be used as signals towards operational decisions of market participants (generators, consumers). The main focus is on deregulated systems with open access to the network. The optimal power flow theory, with demand side modelling included, is briefly reviewed. It turns out that the marginal costs obtained from the optimal power flow gives the optimal transmission tariff for the particular load flow in case. There is also a correspondence between losses and optimal prices. Emphasis is on simple examples that demonstrate the connection between optimal power flow results and tariffs. Various cases, such as open access and single owner are discussed. A key result is that the location of the ''marketplace'' in the open access case does not influence the net economical result for any of the parties involved (generators, network owner, consumer). The optimal power flow is instantaneous, and in its standard form cannot deal with energy constrained systems that are coupled in time, such as hydropower systems with reservoirs. A simplified example of how the theory can be extended to such a system is discussed. An example of the influence of security constraints on prices is also given. 4 refs., 24 figs., 7 tabs
International Nuclear Information System (INIS)
Saber, Ahmed Yousuf; Chakraborty, Shantanu; Abdur Razzak, S.M.; Senjyu, Tomonobu
2009-01-01
This paper presents a modified particle swarm optimization (MPSO) for constrained economic load dispatch (ELD) problem. Real cost functions are more complex than conventional second order cost functions when multi-fuel operations, valve-point effects, accurate curve fitting, etc., are considering in deregulated changing market. The proposed modified particle swarm optimization (PSO) consists of problem dependent variable number of promising values (in velocity vector), unit vector and error-iteration dependent step length. It reliably and accurately tracks a continuously changing solution of the complex cost function and no extra concentration/effort is needed for the complex higher order cost polynomials in ELD. Constraint management is incorporated in the modified PSO. The modified PSO has balance between local and global searching abilities, and an appropriate fitness function helps to converge it quickly. To avoid the method to be frozen, stagnated/idle particles are reset. Sensitivity of the higher order cost polynomials is also analyzed visually to realize the importance of the higher order cost polynomials for the optimization of ELD. Finally, benchmark data sets and methods are used to show the effectiveness of the proposed method. (author)
Energy Technology Data Exchange (ETDEWEB)
Costa, Geraldo R.M. da [Sao Paulo Univ., Sao Carlos, SP (Brazil). Escola de Engenharia
1994-12-31
This paper discusses, partially, the advantages and the disadvantages of the optimal power flow. It shows some of the difficulties of implementation and proposes solutions. An analysis is made comparing the power flow, BIGPOWER/CESP, and the optimal power flow, FPO/SEL, developed by the author, when applied to the CEPEL-ELETRONORTE and CESP systems. (author) 8 refs., 5 tabs.
Optimal Regulation of Virtual Power Plants
Energy Technology Data Exchange (ETDEWEB)
Dall Anese, Emiliano; Guggilam, Swaroop S.; Simonetto, Andrea; Chen, Yu Christine; Dhople, Sairaj V.
2018-03-01
This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence and tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.
Directory of Open Access Journals (Sweden)
Y.N. Vijay Kumar
2016-05-01
Full Text Available Now a day, non-uniform increase of demand on a power system turns the research toward the dynamic analysis. In this paper, to perform dynamic analysis and to solve economic load dispatch problem using optimal power flow (OPF, four realistic load levels are considered. Further, the effectiveness of the objective has been enhanced in the presence of interline power flow controller (IPFC. An optimal location identification methodology for IPFC based on line stability index (LSI is also presented. The effect of ramp-rate limits on generations and the effect of dynamic loads on generation fuel cost and transmission losses are also analyzed on standard IEEE-30 bus and real time 23 bus test systems with supporting validations, numerical and graphical results.
Wang, Yan; Huang, Song; Ji, Zhicheng
2017-07-01
This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.
International Nuclear Information System (INIS)
Krieger, Elena M.; Casey, Joan A.; Shonkoff, Seth B.C.
2016-01-01
Emerging grid resources such as energy storage and demand response have the potential to provide numerous environmental and societal benefits, but are primarily sited and operated to provide grid-specific services without optimizing these co-benefits. We present a four-metric framework to identify priority regions to deploy and dispatch these technologies to displace marginal grid air emissions with high environmental and health impacts. To the standard metrics of total mass and rate of air pollutant emissions we add location and time, to prioritize emission displacement near densely populated areas with poor air quality, especially at times when air pollutant concentrations exceed regulatory standards. We illustrate our framework with a case study using storage, demand response, and other technologies to displace peaker power plants, the highest-rate marginal emitters on the California grid. We combine spatial-temporal data on plant electricity generation, air quality standard exceedance days, and population characteristics available from environmental justice screening tool CalEnviroScreen 2.0 to determine where emissions reductions may have the greatest marginal benefit. This screening approach can inform grid siting decisions, such as storage in lieu of peaker plants in high impact regions, or dispatch protocol, such as triggering demand response instead of peaker plants on poor air quality days. - Highlights: •We develop a health and environmental framework for siting clean energy resources. •Metrics include total mass, time, rate and location of displaced marginal emissions. •Emission displacement is prioritized near dense populations on poor air quality days. •We apply our framework to the displacement of peaker power plant generation in CA. •We identify optimal places and times to site and dispatch storage and demand response.
Yu, Yang; Rajagopal, Ram
2015-02-17
Two dispatch protocols have been adopted by electricity markets to deal with the uncertainty of wind power but the effects of the selection between the dispatch protocols have not been comprehensively analyzed. We establish a framework to compare the impacts of adopting different dispatch protocols on the efficacy of using wind power and implementing a carbon tax to reduce emissions. We suggest that a market has high potential to achieve greater emission reduction by adopting the stochastic dispatch protocol instead of the static protocol when the wind energy in the market is highly uncertain or the market has enough adjustable generators, such as gas-fired combustion generators. Furthermore, the carbon-tax policy is more cost-efficient for reducing CO2 emission when the market operates according to the stochastic protocol rather than the static protocol. An empirical study, which is calibrated according to the data from the Electric Reliability Council of Texas market, confirms that using wind energy in the Texas market results in a 12% CO2 emission reduction when the market uses the stochastic dispatch protocol instead of the 8% emission reduction associated with the static protocol. In addition, if a 6$/ton carbon tax is implemented in the Texas market operated according to the stochastic protocol, the CO2 emission is similar to the emission level from the same market with a 16$/ton carbon tax operated according to the static protocol. Correspondingly, the 16$/ton carbon tax associated with the static protocol costs 42.6% more than the 6$/ton carbon tax associated with the stochastic protocol.
International Nuclear Information System (INIS)
Mueller, N.P.; Meyer, C.E.
1984-01-01
A pressurized water reactor (PWR) nuclear fueled, electric power generating unit is controlled through the use of on-line calculations of the rapid, step and ramp, power change capabilities of the unit made from measured values of power level, axial offset, coolant temperature and rod position taking into account operator generated, safety and control, and balance of plant limits. The power change capabilities so generated may be fed to an automatic dispatch system which provides closed loop control of a power grid system. (author)
Energy Technology Data Exchange (ETDEWEB)
Subbaraj, P. [Kalasalingam University, Srivilliputhur, Tamilnadu 626 190 (India); Rengaraj, R. [Electrical and Electronics Engineering, S.S.N. College of Engineering, Old Mahabalipuram Road, Thirupporur (T.K), Kalavakkam, Kancheepuram (Dist.) 603 110, Tamilnadu (India); Salivahanan, S. [S.S.N. College of Engineering, Old Mahabalipuram Road, Thirupporur (T.K), Kalavakkam, Kancheepuram (Dist.) 603 110, Tamilnadu (India)
2009-06-15
In this paper, a self adaptive real-coded genetic algorithm (SARGA) is implemented to solve the combined heat and power economic dispatch (CHPED) problem. The self adaptation is achieved by means of tournament selection along with simulated binary crossover (SBX). The selection process has a powerful exploration capability by creating tournaments between two solutions. The better solution is chosen and placed in the mating pool leading to better convergence and reduced computational burden. The SARGA integrates penalty parameterless constraint handling strategy and simultaneously handles equality and inequality constraints. The population diversity is introduced by making use of distribution index in SBX operator to create a better offspring. This leads to a high diversity in population which can increase the probability towards the global optimum and prevent premature convergence. The SARGA is applied to solve CHPED problem with bounded feasible operating region which has large number of local minima. The numerical results demonstrate that the proposed method can find a solution towards the global optimum and compares favourably with other recent methods in terms of solution quality, handling constraints and computation time. (author)
A coordinated dispatch model for electricity and heat in a Microgrid via particle swarm optimization
DEFF Research Database (Denmark)
Xu, Lizhong; Yang, Guangya; Xu, Zhao
2013-01-01
This paper develops a coordinated electricity and heat dispatching model for Microgrid under day-ahead environment. In addition to operational constraints, network loss and physical limits are addressed in this model, which are always ignored in previous work. As an important component of Microgrid...
A Robust Optimization Approach to Energy and Reserve Dispatch in Electricity Markets
DEFF Research Database (Denmark)
Zugno, Marco; Conejo, Antonio J.
To a large extent, electricity markets worldwide still rely on deterministic procedures for clearing energy and reserve auctions. However, larger and larger shares of the production mix consist of renewable sources whose nature is stochastic and non-dispatchable, as their output is not known...
A robust optimization approach to energy and reserve dispatch in electricity markets
DEFF Research Database (Denmark)
Zugno, Marco; Conejo, Antonio J.
2015-01-01
To a large extent, electricity markets worldwide still rely on deterministic procedures for clearing energy and reserve auctions. However, increasing shares of the production mix consist of renewable sources whose nature is stochastic and non-dispatchable, as their output is uncertain and cannot...
Directory of Open Access Journals (Sweden)
Saroj Kumar Dash
2016-07-01
Full Text Available The basic objective of economic load dispatch (ELD is to optimize the total fuel cost of hybrid solar thermal electric power plant (HSTP. In ELD problems the cost function for each generator has been approximated by a single quadratic cost equation. As cost of coal increases, it becomes even more important have a good model for the production cost of each generator for the solar thermal hybrid system. A more accurate formulation is obtained for the ELD problem by expressing the generation cost function as a piece wise quadratic cost function. However, the solution methods for ELD problem with piece wise quadratic cost function requires much complicated algorithms such as the hierarchical structure approach along with evolutionary computations (ECs. A test system comprising of 10 units with 29 different fuel [7] cost equations is considered in this paper. The applied genetic algorithm method will provide optimal solution for the given load demand.
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Simonetto, Andrea
2018-03-01
This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall, the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.
Directory of Open Access Journals (Sweden)
Douglas Halamay
2014-09-01
Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.
Directory of Open Access Journals (Sweden)
Hong-Yun Zhang
2012-09-01
Full Text Available Quantum-behaved particle swarm optimization (QPSO is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE, particle swarm optimization (PSO and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems.
Lesmana, E.; Chaerani, D.; Khansa, H. N.
2018-03-01
Energy-Saving Generation Dispatch (ESGD) is a scheme made by Chinese Government in attempt to minimize CO2 emission produced by power plant. This scheme is made related to global warming which is primarily caused by too much CO2 in earth’s atmosphere, and while the need of electricity is something absolute, the power plants producing it are mostly thermal-power plant which produced many CO2. Many approach to fulfill this scheme has been made, one of them came through Minimum Cost Flow in which resulted in a Quadratically Constrained Quadratic Programming (QCQP) form. In this paper, ESGD problem with Minimum Cost Flow in QCQP form will be solved using Lagrange’s Multiplier Method
DEFF Research Database (Denmark)
Faria, Pedro; Soares, Tiago; Pinto, Tiago
2013-01-01
are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart......The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets...... grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve...
International Nuclear Information System (INIS)
He Dakuo; Dong Gang; Wang Fuli; Mao Zhizhong
2011-01-01
A chaotic sequence based differential evolution (DE) approach for solving the dynamic economic dispatch problem (DEDP) with valve-point effect is presented in this paper. The proposed method combines the DE algorithm with the local search technique to improve the performance of the algorithm. DE is the main optimizer, while an approximated model for local search is applied to fine tune in the solution of the DE run. To accelerate convergence of DE, a series of constraints handling rules are adopted. An initial population obtained by using chaotic sequence exerts optimal performance of the proposed algorithm. The combined algorithm is validated for two test systems consisting of 10 and 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other algorithms reported in literatures for DEDP considering valve-point effects.
Directory of Open Access Journals (Sweden)
Chong Chen
2018-04-01
Full Text Available In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP, and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL, are still imperfect, which make it difficult for the active distribution network (ADN to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.
International Nuclear Information System (INIS)
Stoilov, D.
2001-01-01
The first part of the parer considers the general problem of optimal yearly unit commitment in the new economical conditions in Bulgaria. The second part deals with non-convex problem , taking into account some costs for starting and stopping of power systems. The transition from yearly commitment to weekly or daily dispatching is commented
International Nuclear Information System (INIS)
Bogdan, Zeljko; Cehil, Mislav
2007-01-01
Long-term gas purchase contracts usually determine delivery and payment for gas on the regular hourly basis, independently of demand side consumption. In order to use fuel gas in an economically viable way, optimization of gas distribution for covering consumption must be introduced. In this paper, a mathematical model of the electric utility system which is used for optimization of gas distribution over electric generators is presented. The utility system comprises installed capacity of 1500 MW of thermal power plants, 400 MW of combined heat and power plants, 330 MW of a nuclear power plant and 1600 MW of hydro power plants. Based on known demand curve the optimization model selects plants according to the prescribed criteria. Firstly it engages run-of-river hydro plants, then the public cogeneration plants, the nuclear plant and thermal power plants. Storage hydro plants are used for covering peak load consumption. In case of shortage of installed capacity, the cross-border purchase is allowed. Usage of dual fuel equipment (gas-oil), which is available in some thermal plants, is also controlled by the optimization procedure. It is shown that by using such a model it is possible to properly plan the amount of fuel gas which will be contracted. The contracted amount can easily be distributed over generators efficiently and without losses (no breaks in delivery). The model helps in optimizing of fuel gas-oil ratio for plants with combined burners and enables planning of power plants overhauls over a year in a viable and efficient way. (author)
Solving unit commitment and economic load dispatch problems ...
African Journals Online (AJOL)
Economic Load Dispatch (ELD) and Unit Commitment (UC) are very important applications to predict the optimized cost of load in a power system. UC determines working states for existing generating units under some operational constraints and then optimizing the operation cost for all running units w.r.t. load demand ...
Economic Power Dispatch of Distributed Generators in a Grid-Connected Microgrid
DEFF Research Database (Denmark)
Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Andrade, Fabio
2015-01-01
Grid-connected microgrids with storage systems are reliable configurations for critical loads which can not tolerate interruptions of energy supply. In such cases, some of the energy resources should be scheduled in order to coordinate optimally the power generation according to a defined objective...
Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method
Wen-Yeau Chang
2013-01-01
High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO) based hybrid forecasting method for short-term wi...
A multi-objective chaotic particle swarm optimization for environmental/economic dispatch
International Nuclear Information System (INIS)
Cai Jiejin; Ma Xiaoqian; Li Qiong; Li Lixiang; Peng Haipeng
2009-01-01
A multi-objective chaotic particle swarm optimization (MOCPSO) method has been developed to solve the environmental/economic dipatch (EED) problems considering both economic and environmental issues. The proposed MOCPSO method has been applied in two test power systems. Compared with the conventional multi-objective particle swarm optimization (MOPSO) method, for the compromising minimum fuel cost and emission case, the fuel cost and pollutant emission obtained from MOCPSO method can be reduced about 50.08 $/h and 2.95 kg/h, respectively, in test system 1, about 0.02 $/h and 1.11 kg/h, respectively, in test system 2. The MOCPSO method also results in higher quality solutions for the minimum fuel cost case and the minimum emission case in both of the test power systems. Hence, MOCPSO method can result in great environmental and economic effects. For EED problems, the MOCPSO method is more feasible and more effective alternative approach than the conventional MOPSO method.
Sanders, Kelly T; Blackhurst, Michael F; King, Carey W; Webber, Michael E
2014-06-17
We utilize a unit commitment and dispatch model to estimate how water use fees on power generators would affect dispatching and water requirements by the power sector in the Electric Reliability Council of Texas' (ERCOT) electric grid. Fees ranging from 10 to 1000 USD per acre-foot were separately applied to water withdrawals and consumption. Fees were chosen to be comparable in cost to a range of water supply projects proposed in the Texas Water Development Board's State Water Plan to meet demand through 2050. We found that these fees can reduce water withdrawals and consumption for cooling thermoelectric power plants in ERCOT by as much as 75% and 23%, respectively. To achieve these water savings, wholesale electricity generation costs might increase as much as 120% based on 2011 fuel costs and generation characteristics. We estimate that water saved through these fees is not as cost-effective as conventional long-term water supply projects. However, the electric grid offers short-term flexibility that conventional water supply projects do not. Furthermore, this manuscript discusses conditions under which the grid could be effective at "supplying" water, particularly during emergency drought conditions, by changing its operational conditions.
International Nuclear Information System (INIS)
Coelho, Leandro dos Santos; Mariani, Viviana Cocco
2009-01-01
Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed PSO introduces chaos mapping using Henon map sequences which increases its convergence rate and resulting precision. The chaotic PSO approach is used to produce good potential solutions, and the IF is used to fine-tune of final solution of PSO. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results are promising and show the effectiveness of the proposed approach.
A dynamic approach for the optimal electricity dispatch in the deregulated market
International Nuclear Information System (INIS)
Carraretto, Cristian; Lazzaretto, Andrea
2004-01-01
The electricity market has been experiencing the deregulation process in many countries. Effective approaches to the management of single power plants or groups of plants are therefore becoming crucial for the competitiveness of energy utilities. A dynamic programming approach is presented in this paper for the optimal plant management in the new Italian deregulated market. A thorough description of the method is given in cases of free or fixed production over time (e.g. when the overall production is limited by bilateral contracts or cogeneration). Analysis of market characteristics, detailed thermodynamic models of plant operation and reliable price forecasts over the time period of interest are required. The suggested approach is useful for both long-term scheduling and planning daily offers in the market
Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid
Directory of Open Access Journals (Sweden)
Xiaogang Guo
2018-01-01
Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.
Environmental dispatch: Minimum cost generation planning for acid rain compliance
International Nuclear Information System (INIS)
Qadri, S.S.; Weinstein, R.E.
1991-01-01
Passage of Public Law 101-549, the 1990 Clean Air Act Amendments, requires reductions in SO 2 and NO x emissions from many power generation stations by 1995, and by an electric utility company's entire generation system by year 2000. Another option to reduce the total environmental emissions is to dispatch generating units with lower emission rates prior to dispatching units with high emission rates. This option may not lower the emission levels to the desired limits, but can reduce emissions. This is practical as long as the added operating cost is modest compared to the cost of alternatives to meet the same levels of emission reduction. This cost can be optimized to provide the best compromise between reduced emissions and operating cost increase. An environmental dispatch algorithm developed by Gilbert/Commonwealth for its eVOLVE-p trademark production costing program makes this optimization possible. The algorithm modifies the traditional economic dispatch order of utility generation to include the impact of the Clean Air Act Amendments. The dispatch order is based on emissions in excess of Clean Air Act compliance limits. A cost is assigned to the excess emissions, and these costs are distributed to the individual generating units in proportion to their emission rates. This paper discusses how this environmental dispatch algorithm is applied for utility generation compliance planning
A Hybrid Harmony Search Algorithm Approach for Optimal Power Flow
Directory of Open Access Journals (Sweden)
Mimoun YOUNES
2012-08-01
Full Text Available Optimal Power Flow (OPF is one of the main functions of Power system operation. It determines the optimal settings of generating units, bus voltage, transformer tap and shunt elements in Power System with the objective of minimizing total production costs or losses while the system is operating within its security limits. The aim of this paper is to propose a novel methodology (BCGAs-HSA that solves OPF including both active and reactive power dispatch It is based on combining the binary-coded genetic algorithm (BCGAs and the harmony search algorithm (HSA to determine the optimal global solution. This method was tested on the modified IEEE 30 bus test system. The results obtained by this method are compared with those obtained with BCGAs or HSA separately. The results show that the BCGAs-HSA approach can converge to the optimum solution with accuracy compared to those reported recently in the literature.
Power, control and optimization
Vasant, Pandian; Barsoum, Nader
2013-01-01
The book consists of chapters based on selected papers of international conference „Power, Control and Optimization 2012”, held in Las Vegas, USA. Readers can find interesting chapters discussing various topics from the field of power control, its distribution and related fields. Book discusses topics like energy consumption impacted by climate, mathematical modeling of the influence of thermal power plant on the aquatic environment, investigation of cost reduction in residential electricity bill using electric vehicle at peak times or allocation and size evaluation of distributed generation using ANN model and others. Chapter authors are to the best of our knowledge the originators or closely related to the originators of presented ideas and its applications. Hence, this book certainly is one of the few books discussing the benefit from intersection of those modern and fruitful scientific fields of research with very tight and deep impact on real life and industry. This book is devoted to the studies o...
Energy Technology Data Exchange (ETDEWEB)
Miller, R.J.; Najaf-Zadeh, K.; Darlington, H.T.; McNair, H.D.; Seidenstein, S.; Williams, A.R.
1982-10-01
Human factors is a systems-oriented interdisciplinary specialty concerned with the design of systems, equipment, facilities and the operational environment. An important aspect leading to the design requirements is the determination of the information requirements for electric power dispatch control centers. There are significant differences between the system operator's actions during normal and degraded states of power system operation, and power system restoration. This project evaluated the information the operator requires for normal power system and control system operations and investigates the changes of information required by the operator as the power system and/or the control system degrades from a normal operating state. The Phase II study, published in two volumes, defines power system states and control system conditions to which operator information content can be related. This volume presents a summary of operator information needs, identifying the needs for and the uses of power system information by a system operator in conditions ranging from normal through degraded operation. Training requirements are also included for planning entry-level and follow-on training for operators.
Energy Technology Data Exchange (ETDEWEB)
Colnago, Glauber R.; Correia, Paulo B. [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil). Faculdade de Engenharia Mecanica]. E-mails: grcolnago@fem.unicamp.br; pcorreia@fem.unicamp.br
2006-07-01
This work proposes a mixed integer nonlinear programming model to pre-dispatch of a hydroelectric power plant. In the model we want to minimize the losses in the electricity generation with conditions of electricity demand, operational prohibited zones and units' efficiency data. The Xingo Hydroelectric Power Plant was utilized in the mode tests. The solver used was Lingo 8.0. (author)
Economic environmental dispatch using BSA algorithm
Jihane, Kartite; Mohamed, Cherkaoui
2018-05-01
Economic environmental dispatch problem (EED) is an important issue especially in the field of fossil fuel power plant system. It allows the network manager to choose among different units the most optimized in terms of fuel costs and emission level. The objective of this paper is to minimize the fuel cost with emissions constrained; the test is conducted for two cases: six generator unit and ten generator unit for the same power demand 1200Mw. The simulation has been computed in MATLAB and the result shows the robustness of the Backtracking Search optimization Algorithm (BSA) and the impact of the load demand on the emission.
Thermodynamic optimization of power plants
Haseli, Y.
2011-01-01
Thermodynamic Optimization of Power Plants aims to establish and illustrate comparative multi-criteria optimization of various models and configurations of power plants. It intends to show what optimization objectives one may define on the basis of the thermodynamic laws, and how they can be applied
Wang, Lingfeng; Singh, Chanan
2007-01-01
Source: Swarm Intelligence: Focus on Ant and Particle Swarm Optimization, Book edited by: Felix T. S. Chan and Manoj Kumar Tiwari, ISBN 978-3-902613-09-7, pp. 532, December 2007, Itech Education and Publishing, Vienna, Austria
Klyuev, R. V.; Bosikov, I. I.; Madaeva, M. Z.; A-V Turluev, R.
2018-03-01
The structural scheme of the automated control system of power consumption at the industrial enterprise is developed in the article. At the non-ferrous metallurgy enterprise, an energy inspection and a rank analysis of the electrical energy consumption of the main processing equipment were carried out. It is established that the enterprises of non-ferrous metallurgy are a complex process system consisting of a set of thousands of jointly functioning technological facilities. For the most effective estimation of power consumption of enterprises, it is reasonable to use the automated system of dispatching control of power consumption (ASDCPC). The paper presents the results of the development of the ASDCPC structural diagram that allows one to perform on-line control and management of the energy and process parameters of the main production units and the enterprise as a whole. As a result of the introduction of ASDCPC at the non-ferrous metallurgy enterprise, the consumed active power was reduced during the peak hours of the load by 20%, the specific electricity consumption - by 14%, the cost of the energy component in the cost of production of hard alloys - by 3%.
Solving Multi-Pollutant Emission Dispatch Problem Using Computational Intelligence Technique
Directory of Open Access Journals (Sweden)
Nur Azzammudin Rahmat
2016-06-01
Full Text Available Economic dispatch is a crucial process conducted by the utilities to correctly determine the satisfying amount of power to be generated and distributed to the consumers. During the process, the utilities also consider pollutant emission as the consequences of fossil-fuel consumption. Fossil-fuel includes petroleum, coal, and natural gas; each has its unique chemical composition of pollutants i.e. sulphur oxides (SOX, nitrogen oxides (NOX and carbon oxides (COX. This paper presents multi-pollutant emission dispatch problem using computational intelligence technique. In this study, a novel emission dispatch technique is formulated to determine the amount of the pollutant level. It utilizes a pre-developed optimization technique termed as differential evolution immunized ant colony optimization (DEIANT for the emission dispatch problem. The optimization results indicated high level of COX level, regardless of any type of fossil fuel consumed.
DEFF Research Database (Denmark)
Ding, Tao; Kou, Yu; Yang, Yongheng
2017-01-01
. However, the intermittency of solar PV energy (e.g., due to passing clouds) may affect the PV generation in the district distribution network. To address this issue, the voltage magnitude constraints under the cloud shading conditions should be taken into account in the optimization model, which can......As photovoltaic (PV) integration increases in distribution systems, to investigate the maximum allowable PV integration capacity for a district distribution system becomes necessary in the planning phase, an optimization model is thus proposed to evaluate the maximum PV integration capacity while...
Metaheuristic optimization in power engineering
Radosavljević, Jordan
2018-01-01
This book describes the principles of solving various problems in power engineering via the application of selected metaheuristic optimization methods including genetic algorithms, particle swarm optimization, and the gravitational search algorithm.
Optimal Dispatch of an Industrial Microgrid with a Mixed Portfolio of Distributed Energy Resources
DEFF Research Database (Denmark)
You, Shi; Zong, Yi; Bindner, Henrik W.
2014-01-01
Local brownouts are a nuisance and have driven consumers to take greater responsibility for their electricity supply – particularly industries and communities with a critical need for reliable and safe power. By deploying a Microgrid on their own site, the consumers could benefit from having...... this interoperable grid solution with respect to improved energy efficiency, system reliability and power quality. When the on-site generation is from renewables, external incentives and system sustainability could make the Microgrid solution even more attractive...
Real-time Distributed Economic Dispatch forDistributed Generation Based on Multi-Agent System
DEFF Research Database (Denmark)
Luo, Kui; Wu, Qiuwei; Nielsen, Arne Hejde
2015-01-01
The distributed economic dispatch for distributed generation is formulated as a optimization problem with equality and inequality constraints. An effective distributed approach based on multi-agent system is proposed for solving the economic dispatch problem in this paper. The proposed approach...... consists of two stages. In the first stage, an adjacency average allocation algorithm is proposed to ensure the generation-demand equality. In the second stage, a local replicator dynamics algorithm is applied to achieve nash equilibrium for the power dispatch game. The approach is implemented in a fully...
DEFF Research Database (Denmark)
Ding, Tao; Kou, Yu; Yang, Yongheng
2017-01-01
. However, the intermittency of solar PV energy (e.g., due to passing clouds) may affect the PV generation in the district distribution network. To address this issue, the voltage magnitude constraints under the cloud shading conditions should be taken into account in the optimization model, which can...
Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming
DEFF Research Database (Denmark)
Shuai, Hang; Fang, Jiakun; Ai, Xiaomeng
2018-01-01
slope updating strategy is employed for the proposed method. With sufficient information extracted from these scenarios and embedded in the PLF function, the proposed ADPED algorithm can not only be used in day-ahead scheduling but also the intra-day optimization process. The algorithm can make full use......-ahead and intra-day operation under uncertainty....
Load flow optimization and optimal power flow
Das, J C
2017-01-01
This book discusses the major aspects of load flow, optimization, optimal load flow, and culminates in modern heuristic optimization techniques and evolutionary programming. In the deregulated environment, the economic provision of electrical power to consumers requires knowledge of maintaining a certain power quality and load flow. Many case studies and practical examples are included to emphasize real-world applications. The problems at the end of each chapter can be solved by hand calculations without having to use computer software. The appendices are devoted to calculations of line and cable constants, and solutions to the problems are included throughout the book.
Energy Technology Data Exchange (ETDEWEB)
Mehos, Mark [National Renewable Energy Lab. (NREL), Golden, CO (United States); Turchi, Craig [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ho, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Armijo, Kenneth [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-05-01
This report examines the remaining challenges to achieving the competitive concentrating solar power (CSP) costs and large-scale deployment envisioned under the U.S. Department of Energy's SunShot Initiative. Although CSP costs continue to decline toward SunShot targets, CSP acceptance and deployment have been hindered by inexpensive photovoltaics (PV). However, a recent analysis found that thermal energy storage (TES) could increase CSP's value--based on combined operational and capacity benefits--by up to 6 cents/kWh compared to variable-generation PV, under a 40% renewable portfolio standard in California. Thus, the high grid value of CSP-TES must be considered when evaluating renewable energy options. An assessment of net system cost accounts for the difference between the costs of adding new generation and the avoided cost from displacing other resources providing the same level of energy and reliability. The net system costs of several CSP configurations are compared with the net system costs of conventional natural-gas-fired combustion-turbine (CT) and combined-cycle plants. At today's low natural gas prices and carbon emission costs, the economics suggest a peaking configuration for CSP. However, with high natural gas prices and emission costs, each of the CSP configurations compares favorably against the conventional alternatives, and systems with intermediate to high capacity factors become the preferred alternatives. Another analysis compares net system costs for three configurations of CSP versus PV with batteries and PV with CTs. Under current technology costs, the least-expensive option is a combination of PV and CTs. However, under future cost assumptions, the optimal configuration of CSP becomes the most cost-effective option.
Directory of Open Access Journals (Sweden)
Ping Li
2017-06-01
Full Text Available The strong coupling between electric power and heat supply highly restricts the electric power generation range of combined heat and power (CHP units during heating seasons. This makes the system operational flexibility very low, which leads to heavy wind power curtailment, especially in the region with a high percentage of CHP units and abundant wind power energy such as northeastern China. The heat storage capacity of pipelines and buildings of the district heating system (DHS, which already exist in the urban infrastructures, can be exploited to realize the power and heat decoupling without any additional investment. We formulate a combined heat and power dispatch model considering both the pipelines’ dynamic thermal performance (PDTP and the buildings’ thermal inertia (BTI, abbreviated as the CPB-CHPD model, emphasizing the coordinating operation between the electric power and district heating systems to break the strong coupling without impacting end users’ heat supply quality. Simulation results demonstrate that the proposed CPB-CHPD model has much better synergic benefits than the model considering only PDTP or BTI on wind power integration and total operation cost savings.
Optimization of a Virtual Power Plant to Provide Frequency Support.
Energy Technology Data Exchange (ETDEWEB)
Neely, Jason C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gonzalez, Sigifredo [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lave, Matthew Samuel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Delhotal, Jarod James [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-12-01
Increasing the penetration of distributed renewable sources, including photovoltaic (PV) sources, poses technical challenges for grid management. The grid has been optimized over decades to rely upon large centralized power plants with well-established feedback controls, but now non-dispatchable, renewable sources are displacing these controllable generators. This one-year study was funded by the Department of Energy (DOE) SunShot program and is intended to better utilize those variable resources by providing electric utilities with the tools to implement frequency regulation and primary frequency reserves using aggregated renewable resources, known as a virtual power plant. The goal is to eventually enable the integration of 100s of Gigawatts into US power systems.
Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor
PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu
2018-03-01
In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.
International Nuclear Information System (INIS)
Al-Muhawesh, Tareq A.; Qamber, Isa S.
2008-01-01
A current trend in electric power industries is the deregulation around the world. One of the questions arise during any deregulation process is: where will be the future generation expansion? In the present paper, the study is concentrated on the wheeling computational method as a part of mega watt (MW) linear programming-based optimal power flow (LP-based OPF) method. To observe the effects of power wheeling on the power system operations, the paper uses linear interactive and discrete optimizer (LINDO) optimizer software as a powerful tool for solving linear programming problems to evaluate the influence of the power wheeling. As well, the paper uses the optimization tool to solve the economic generation dispatch and transmission management problems. The transmission line flow was taken in consideration with some constraints discussed in this paper. The complete linear model of the MW LP-based OPF, which is used to know the future generation potential areas in any utility is proposed. The paper also explains the available economic load dispatch (ELD) as the basic optimization tool to dispatch the power system. It can be concluded in the present study that accuracy is expensive in terms of money and time and in the competitive market enough accuracy is needed without paying much
Distributionally robust hydro-thermal-wind economic dispatch
International Nuclear Information System (INIS)
Chen, Yue; Wei, Wei; Liu, Feng; Mei, Shengwei
2016-01-01
Highlights: • A two-stage distributionally robust hydro-thermal-wind model is proposed. • A semi-definite programing equivalent and its algorithm are developed. • Cases that demonstrate the effectiveness of the proposed model are included. - Abstract: With the penetration of wind energy increasing, uncertainty has become a major challenge in power system dispatch. Hydro power can change rapidly and is regarded as one promising complementary energy resource to mitigate wind power fluctuation. Joint scheduling of hydro, thermal, and wind energy is attracting more and more attention nowadays. This paper proposes a distributionally robust hydro-thermal-wind economic dispatch (DR-HTW-ED) method to enhance the flexibility and reliability of power system operation. In contrast to the traditional stochastic optimization (SO) and adjustable robust optimization (ARO) method, distributionally robust optimization (DRO) method describes the uncertain wind power output by all possible probability distribution functions (PDFs) with the same mean and variance recovered from the forecast data, and optimizes the expected operation cost in the worst distribution. Traditional DRO optimized the random parameter in entire space, which is sometimes contradict to the actual situation. In this paper, we restrict the wind power uncertainty in a bounded set, and derive an equivalent semi-definite programming (SDP) for the DR-HTW-ED using S-lemma. A delayed constraint generation algorithm is suggested to solve it in a tractable manner. The proposed DR-HTW-ED is compared with the existing ARO based hydro-thermal-wind economic dispatch (AR-HTW-ED). Their respective features are shown from the perspective of computational efficiency and conservativeness of dispatch strategies.
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun
2015-01-01
This paper proposes algorithms for optimal sitingand sizing of Energy Storage System (ESS) for the operationplanning of power systems with large scale wind power integration.The ESS in this study aims to mitigate the wind powerfluctuations during the interval between two rolling Economic......Dispatches (EDs) in order to maintain generation-load balance.The charging and discharging of ESS is optimized consideringoperation cost of conventional generators, capital cost of ESSand transmission losses. The statistics from simulated systemoperations are then coupled to the planning process to determinethe...
Rejoinder on: Space-time wind speed forecasting for improved power system dispatch
Zhu, Xinxin
2014-02-27
We are thankful to the four reviewers for providing very valuable and insightful comments. We have divided our rejoinder into two main parts: (1) the rotating RSTD model; and (2) the integration of wind power into a power system. In each part, we present our views on the various comments of the discussants and provide further discussion. © 2014 Sociedad de Estadística e Investigación Operativa.
Rejoinder on: Space-time wind speed forecasting for improved power system dispatch
Zhu, Xinxin; Genton, Marc G.; Gu, Yingzhong; Xie, Le
2014-01-01
We are thankful to the four reviewers for providing very valuable and insightful comments. We have divided our rejoinder into two main parts: (1) the rotating RSTD model; and (2) the integration of wind power into a power system. In each part, we present our views on the various comments of the discussants and provide further discussion. © 2014 Sociedad de Estadística e Investigación Operativa.
Energy Technology Data Exchange (ETDEWEB)
Wang, Yishen [Univ. of Washington, Seattle, WA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Zhou, Zhi [Argonne National Lab. (ANL), Argonne, IL (United States); Liu, Cong [Argonne National Lab. (ANL), Argonne, IL (United States); Electric Reliability Council of Texas (ERCOT), Austin, TX (United States); Botterud, Audun [Argonne National Lab. (ANL), Argonne, IL (United States)
2016-08-01
As more wind power and other renewable resources are being integrated into the electric power grid, the forecast uncertainty brings operational challenges for the power system operators. In this report, different operational strategies for uncertainty management are presented and evaluated. A comprehensive and consistent simulation framework is developed to analyze the performance of different reserve policies and scheduling techniques under uncertainty in wind power. Numerical simulations are conducted on a modified version of the IEEE 118-bus system with a 20% wind penetration level, comparing deterministic, interval, and stochastic unit commitment strategies. The results show that stochastic unit commitment provides a reliable schedule without large increases in operational costs. Moreover, decomposition techniques, such as load shift factor and Benders decomposition, can help in overcoming the computational obstacles to stochastic unit commitment and enable the use of a larger scenario set to represent forecast uncertainty. In contrast, deterministic and interval unit commitment tend to give higher system costs as more reserves are being scheduled to address forecast uncertainty. However, these approaches require a much lower computational effort Choosing a proper lower bound for the forecast uncertainty is important for balancing reliability and system operational cost in deterministic and interval unit commitment. Finally, we find that the introduction of zonal reserve requirements improves reliability, but at the expense of higher operational costs.
Power system operational security analysis to obtain sustainable, strategic and economic dispatch
International Nuclear Information System (INIS)
Khan, R.A.J.; Alemadi, N.; Mulla, Y.A.; Choudhry, T.M.
2006-01-01
This paper addresses the most critical question that is static/online security system n power system operation and managements. Therefore, we do originated couple of models with their operational scenarios. How to identify the main security constraints and their most suitable reinforcements needed to maintain the system security as per determine boundary. It would also render instrumental approach to enhance the security operational constraints. Therefore, it will also provide the system operator to take preventive action or formulate the action plan prior to contingencies occurred In past the both demand side management system and load shedding have been used for to provide reliable power system under normal or emergency operation and control [4,5 J.) (author)
Energy Technology Data Exchange (ETDEWEB)
Greitzer, Frank L.; Podmore, Robin
2008-11-17
The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration of a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.
A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.
Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie
2018-06-04
Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.
Directory of Open Access Journals (Sweden)
Abouzar Samimi
2015-11-01
Full Text Available One of the most important Distribution System Operators (DSO schemes addresses the Volt/Var control (VVC problem. Developing a cost-based reactive power dispatch model for distribution systems, in which the reactive powers are appropriately priced, can motivate Distributed Energy Resources (DERs to participate actively in VVC. In this paper, new reactive power cost models for DERs, including synchronous machine-based DGs and wind turbines (WTs, are formulated based on their capability curves. To address VVC in the context of competitive electricity markets in distribution systems, first, in a day-ahead active power market, the initial active power dispatch of generation units is estimated considering environmental and economic aspects. Based on the results of the initial active power dispatch, the proposed VVC model is executed to optimally allocate reactive power support among all providers. Another novelty of this paper lies in the pricing scheme that rewards transformers and capacitors for tap and step changing, respectively, while incorporating the reactive power dispatch model. A Benders decomposition algorithm is employed as a solution method to solve the proposed reactive power dispatch, which is a mixed integer non-linear programming (MINLP problem. Finally, a typical 22-bus distribution network is used to verify the efficiency of the proposed method.
Directory of Open Access Journals (Sweden)
Y.N. Vijay Kumar
2016-12-01
Full Text Available The utilization of electrical energy due to urbanization and industrialization is increasing day by day, and due to this, there is chance of increasing the uncertainties in a given power system and that affects the economy of the country. The conventional power system in the presence of flexible AC transmission system (FACTS controllers is an alternative to solve this problem and can increase the power system capability to handle rapid changes in operating conditions of the system. In general, multi-line FACTS controllers are effective than single line FACTS controllers. In this paper, a detailed mathematical modeling of IPFC is presented and the effect of an optimal location is also analyzed. A novel optimization algorithm i.e. modified BAT algorithm is proposed to solve optimal power flow problem in the presence of IPFC including system constraints and device limits. The proposed methodology has been tested on standard test systems.
Energy Technology Data Exchange (ETDEWEB)
Mehos, Mark [National Renewable Energy Lab. (NREL), Golden, CO (United States); Turchi, Craig [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ho, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Armijo, Kenneth [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-05-01
Energy storage will help enable CSP compete by adding flexibility value to a high-variable-generation (solar plus wind) power system (see Mehos et al. 2016). Compared with PV, CSP systems are more complex to develop, design, construct, and operate, and they require a much larger minimum effective scale—typically at least 50 MW, compared with PV systems that can be as small as a few kilowatts. In recent years, PV’s greater modularity and lower LCOE have made it more attractive to many solar project developers, and some large projects that were originally planned for CSP have switched to PV. However, the ability of CSP to use thermal energy storage—and thus provide continuous power for long periods when the sun is not shining—could give CSP a vital role in evolving electricity systems. Because CSP with storage can store energy when net demand is low and release that energy when demand is high, it increases the electricity system’s ability to balance supply and demand over multiple time scales. Such flexibility becomes increasingly important as more variable-generation renewable energy is added to the system. For example, one analysis suggests that, under a 40% renewable portfolio standard in California, CSP with storage could provide more than twice as much value to the electricity system as variable-generation PV. For this reason, enhanced thermal energy storage is a critical component of the SunShot Initiative’s 2020 CSP technology-improvement roadmap.
Enhanced GSA-Based Optimization for Minimization of Power Losses in Power System
Directory of Open Access Journals (Sweden)
Gonggui Chen
2015-01-01
Full Text Available Gravitational Search Algorithm (GSA is a heuristic method based on Newton’s law of gravitational attraction and law of motion. In this paper, to further improve the optimization performance of GSA, the memory characteristic of Particle Swarm Optimization (PSO is employed in GSAPSO for searching a better solution. Besides, to testify the prominent strength of GSAPSO, GSA, PSO, and GSAPSO are applied for the solution of optimal reactive power dispatch (ORPD of power system. Conventionally, ORPD is defined as a problem of minimizing the total active power transmission losses by setting control variables while satisfying numerous constraints. Therefore ORPD is a complicated mixed integer nonlinear optimization problem including many constraints. IEEE14-bus, IEEE30-bus, and IEEE57-bus test power systems are used to implement this study, respectively. The obtained results of simulation experiments using GSAPSO method, especially the power loss reduction rates, are compared to those yielded by the other modern artificial intelligence-based techniques including the conventional GSA and PSO methods. The results presented in this paper reveal the potential and effectiveness of the proposed method for solving ORPD problem of power system.
A Hierarchical Dispatch Structure for Distribution Network Pricing
Yuan, Zhao; Hesamzadeh, Mohammad Reza
2015-01-01
This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...
A review on economic emission dispatch problems using quantum computational intelligence
Mahdi, Fahad Parvez; Vasant, Pandian; Kallimani, Vish; Abdullah-Al-Wadud, M.
2016-11-01
Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI) in solving Economic Emission Dispatch problems. QCI techniques like Quantum Genetic Algorithm (QGA) and Quantum Particle Swarm Optimization (QPSO) algorithm are discussed here. This paper will encourage the researcher to use more QCI based algorithm to get better optimal result for solving EED problems.
Directory of Open Access Journals (Sweden)
Thang Diep Thanh
2017-12-01
Full Text Available In environmental uncertainties, the power flow problem in islanded microgrid (MG becomes complex and non-trivial. The optimal power flow (OPL problem is described in this paper by using the energy balance between the power generation and load demand. The paper also presents the hierarchical control structure which consists of primary, secondary, tertiary, and emergency controls. Clearly, optimal power flow (OPL which implements a distributed tertiary control in hierarchical control. MG consists of diesel engine generator (DEG, wind turbine generator (WTG, and photovoltaic (PV power. In the control system considered, operation planning is realized based on profiles such that the MG, load, wind and photovoltaic power must be forecasted in short-period, meanwhile the dispatch source (i.e., DEG needs to be scheduled. The aim of the control problem is to find the dispatch output power by minimizing the total cost of energy that leads to the Hamilton-Jacobi-Bellman equation. Experimental results are presented, showing the effectiveness of optimal control such that the generation allows demand profile.
Directory of Open Access Journals (Sweden)
Toly Chen
2012-01-01
Full Text Available A nonlinear programming and artificial neural network approach is presented in this study to optimize the performance of a job dispatching rule in a wafer fabrication factory. The proposed methodology fuses two existing rules and constructs a nonlinear programming model to choose the best values of parameters in the two rules by dynamically maximizing the standard deviation of the slack, which has been shown to benefit scheduling performance by several studies. In addition, a more effective approach is also applied to estimate the remaining cycle time of a job, which is empirically shown to be conducive to the scheduling performance. The efficacy of the proposed methodology was validated with a simulated case; evidence was found to support its effectiveness. We also suggested several directions in which it can be exploited in the future.
Study on optimal configuration of the grid-connected wind-solar-battery hybrid power system
Ma, Gang; Xu, Guchao; Ju, Rong; Wu, Tiantian
2017-08-01
The capacity allocation of each energy unit in the grid-connected wind-solar-battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind-solar-battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind-solar-battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.
Economic dispatch using chaotic bat algorithm
International Nuclear Information System (INIS)
Adarsh, B.R.; Raghunathan, T.; Jayabarathi, T.; Yang, Xin-She
2016-01-01
This paper presents the application of a new metaheuristic optimization algorithm, the chaotic bat algorithm for solving the economic dispatch problem involving a number of equality and inequality constraints such as power balance, prohibited operating zones and ramp rate limits. Transmission losses and multiple fuel options are also considered for some problems. The chaotic bat algorithm, a variant of the basic bat algorithm, is obtained by incorporating chaotic sequences to enhance its performance. Five different example problems comprising 6, 13, 20, 40 and 160 generating units are solved to demonstrate the effectiveness of the algorithm. The algorithm requires little tuning by the user, and the results obtained show that it either outperforms or compares favorably with several existing techniques reported in literature. - Highlights: • The chaotic bat algorithm, a new metaheuristic optimization algorithm has been used. • The problem solved – the economic dispatch problem – is nonlinear, discontinuous. • It has number of equality and inequality constraints. • The algorithm has been demonstrated to be applicable on high dimensional problems.
A direct Newton-Raphson economic dispatch
International Nuclear Information System (INIS)
Lin, C.E.; Chen, S.T.; Huang, C.L.
1992-01-01
This paper presents a new method to solve the real-time economic dispatch problem using an alternative Jacobian matrix considering system constraints. The transition loss is approximately expressed in terms of generating powers and the generalized generation shift distribution factor. Based on this expression, a set of simultaneous equations of Jacobian matrix is formulated and solved by the Newton-Raphson method. The proposed method eliminates the penalty factor calculation, and solves the economic dispatch directly. The proposed method obtains very fast solution speed and maintains good accuracy from test examples. It is good approach to solve the economic dispatch problem
Transmission dispatch and congestion management in open market systems
Fang, Risheng
This thesis is located in the domain of electricity supply industry restructuring. It deals with emerging issues, whose understanding is essential to advancing knowledge of open access transmission theory and proceeds to develop approaches for solving the transmission dispatch and congestion management problem. An overview of current trends and experiences in utility restructuring and the main models for restructuring, as well as the classifications of system operators, is first presented. A fully unbundled competitive electricity market model, called the bilateral/multilateral trades model, is then developed. A survey of current research in transmission dispatch and congestion management is included with discussion of transmission capacity and ancillary services. A methodology for the power dispatch problem in a structure dominated by bilateral and multilateral transmission contracts is presented. Group structures are mathematically formulated and explored and three basic types of curtailment strategies proposed for use by market participants. A more complex model is then developed, which takes into account the co-existence of bilateral and multilateral contracts with pool type dynamic supplies and demands based on bids and market clearing prices. An integrated dispatch strategy to reconcile all three types of transactions (bilateral, multilateral and pool) is then developed. Prioritization of electricity transactions and related curtailment strategies are explored and a mechanism for coordination between market participants to achieve additional economic advantages is described. A theory of security based rescheduling is presented in order to investigate the security-related aspects of operation in an unbundled and deregulated system. The impact of post-contingency corrective capability on optimal rescheduling results has been identified and the advantage of incorporating post-contingency corrective rescheduling into the objective function demonstrated. Finally
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
generator operating point in the P-Q plane. Four computer programs were developed to automatically perform the market auction simulations using the equal incremental cost rule. The software calculates the payoffs for the two competing competitors, dispatches six generators, and allocates ancillary services for 64 combinations of bidding strategies, three levels of system demand, and three different types of competitors. Matrix Game theory was utilized to calculate Nash Equilibrium solutions and mixed-strategy Nash solutions as the optimal generator bidding strategies. A method to incorporate ancillary services into the generation bidding strategy, to assure an adequate supply of ancillary services, and to allocate these necessary resources to the on-line units was devised. The optimal generator bid strategy in a power auction was shown to be the Nash Equilibrium solution found in two-player variable-sum matrix games.
Annealed Demon Algorithms Solving the Environmental / Economic Dispatch Problem
Directory of Open Access Journals (Sweden)
Aristidis VLACHOS
2013-06-01
Full Text Available This paper presents an efficient and reliable Annealed Demon (AD algorithm for the Environmental/Economic Dispatch (EEB problem. The EED problem is a multi-objective non-linear optimization problem with constraints. This problem is one of the fundamentals issues in power system operation. The system of generation associates thermal generators and emissions which involves sulphur oxides (SO2 and nitrogen oxides (NOx. The aim is to minimize total fuel cost of the system and control emission. The proposed AD algorithm is applied for EED of a simple power system.
Real-Time Dispatch of Petroleum Tank Trucks
Gerald G. Brown; Glenn W. Graves
1981-01-01
A highly automated, real-time dispatch system is described which uses embedded optimization routines to replace extensive manual operations and to reduce substantially operating costs for a nation-wide fleet of petroleum tank trucks. The system is currently used in daily operations by the Order Entry and Dispatch segment of the Chevron U.S.A. Marketing System. Refined petroleum products valued at several billion dollars per year are dispatched from more than 80 bulk terminals on a fleet excee...
Congestion management by determining optimal location of TCSC in deregulated power systems
International Nuclear Information System (INIS)
Besharat, Hadi; Taher, Seyed Abbas
2008-01-01
In a deregulated electricity market, it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. The ongoing power system restructuring requires an opening of unused potentials of transmission system due to environmental, right-of-way and cost problems which are major hurdles for power transmission network expansion. Flexible AC transmission systems (FACTSs) devices can be an alternative to reduce the flows in heavily loaded lines, resulting in an increased loadability, low system loss, improved stability of the network, reduced cost of production and fulfilled contractual requirement by controlling the power flows in the network. A method to determine the optimal location of thyristor controlled series compensators (TCSCs) has been suggested in this paper based on real power performance index and reduction of total system VAR power losses. (author)
Security constrained optimal power flow by modern optimization tools
African Journals Online (AJOL)
Security constrained optimal power flow by modern optimization tools. ... International Journal of Engineering, Science and Technology ... If you would like more information about how to print, save, and work with PDFs, Highwire Press ...
Security constrained optimal power flow by modern optimization tools
African Journals Online (AJOL)
The main objective of an optimal power flow (OPF) functions is to optimize .... It is characterized as propagation of plants and this happens by gametes union. ... ss and different variables, for example, wind, nearby fertilization can have a critic.
Electric power system applications of optimization
Momoh, James A
2008-01-01
Introduction Structure of a Generic Electric Power System Power System Models Power System Control Power System Security Assessment Power System Optimization as a Function of Time Review of Optimization Techniques Applicable to Power Systems Electric Power System Models Complex Power Concepts Three-Phase Systems Per Unit Representation Synchronous Machine Modeling Reactive Capability Limits Prime Movers and Governing Systems Automatic Gain Control Transmission Subsystems Y-Bus Incorporating the Transformer Effect Load Models Available Transfer Capability Illustrative Examples Power
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Dragicevic, Tomislav; Meng, Lexuan
2016-01-01
Next generation power management at all scales is highly relying on the efficient scheduling and operation of different energy sources to maximize efficiency and utility. The ability to schedule and modulate the energy storage options within energy systems can also lead to more efficient use...... of the generating units. This optimal planning and operation management strategy becomes increasingly important for off-grid systems that operate independently of the main utility, such as microgrids or power systems on marine vessels. This work extends the principles of optimal planning and economic dispatch...... for the proposed plan is derived based on the solution from a mixed-integer nonlinear programming (MINLP) problem. Simulation results showed that including well-sized energy storage options together with optimal operation management of generating units can improve the economic operation of the test system while...
Directory of Open Access Journals (Sweden)
Akanksha Mishra
2017-05-01
Full Text Available In a deregulated electricity market it may at times become difficult to dispatch all the required power that is scheduled to flow due to congestion in transmission lines. An Interline Power Flow Controller (IPFC can be used to reduce the system loss and power flow in the heavily loaded line, improve stability and loadability of the system. This paper proposes a Disparity Line Utilization Factor for the optimal placement and Gravitational Search algorithm based optimal tuning of IPFC to control the congestion in transmission lines. DLUF ranks the transmission lines in terms of relative line congestion. The IPFC is accordingly placed in the most congested and the least congested line connected to the same bus. Optimal sizing of IPFC is carried using Gravitational Search algorithm. A multi-objective function has been chosen for tuning the parameters of the IPFC. The proposed method is implemented on an IEEE-30 bus test system. Graphical representations have been included in the paper showing reduction in LUF of the transmission lines after the placement of an IPFC. A reduction in active power and reactive power loss of the system by about 6% is observed after an optimally tuned IPFC has been included in the power system. The effectiveness of the proposed tuning method has also been shown in the paper through the reduction in the values of the objective functions.
Dispatch Strategy Development for Grid-tied Household Energy Systems
Cardwell, Joseph
The prevalence of renewable generation will increase in the next several decades and offset conventional generation more and more. Yet this increase is not coming without challenges. Solar, wind, and even some water resources are intermittent and unpredictable, and thereby create scheduling challenges due to their inherent "uncontrolled" nature. To effectively manage these distributed renewable assets, new control algorithms must be developed for applications including energy management, bridge power, and system stability. This can be completed through a centralized control center though efforts are being made to parallel the control architecture with the organization of the renewable assets themselves--namely, distributed controls. Building energy management systems are being employed to control localized energy generation, storage, and use to reduce disruption on the net utility load. One such example is VOLTTRONTM, an agent-based platform for building energy control in real time. In this thesis, algorithms developed in VOLTTRON simulate a home energy management system that consists of a solar PV array, a lithium-ion battery bank, and the grid. Dispatch strategies are implemented to reduce energy charges from overall consumption (/kWh) and demand charges (/kW). Dispatch strategies for implementing storage devices are tuned on a month-to-month basis to provide a meaningful economic advantage under simulated scenarios to explore algorithm sensitivity to changing external factors. VOLTTRON agents provide automated real-time optimization of dispatch strategies to efficiently manage energy supply and demand, lower consumer costs associated with energy usage, and reduce load on the utility grid.
Energy Technology Data Exchange (ETDEWEB)
Jacob Raglend, I. [School of Electrical Sciences, Noorul Islam University, Kumaracoil 629 180 (India); Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B. [School of Electrical Sciences, Vellore Institute of Technology, Vellore 632 004 (India); Kothari, D.P. [FNAE, FNASC, SMIEEE, Vellore Institute of Technology University, Vellore 632 014 (India)
2010-07-15
A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)
International Nuclear Information System (INIS)
Jacob Raglend, I.; Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B.; Kothari, D.P.
2010-01-01
A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)
Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm
Directory of Open Access Journals (Sweden)
Qunli Wu
2015-12-01
Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.
Optimal power flow by particle swarm optimization with an aging ...
African Journals Online (AJOL)
In this paper, a particle swarm optimization (PSO) with an aging leader and challengers (ALC-PSO) is applied for the solution of OPF problem of power system. This study is implemented on modified IEEE 30-bus test power system with different objectives that reflect minimization of either fuel cost or active power loss or sum ...
Ant colony search algorithm for optimal reactive power optimization
Directory of Open Access Journals (Sweden)
Lenin K.
2006-01-01
Full Text Available The paper presents an (ACSA Ant colony search Algorithm for Optimal Reactive Power Optimization and voltage control of power systems. ACSA is a new co-operative agents’ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called "Ants" co-operates to find good solution for Reactive Power Optimization problem. The ACSA is applied for optimal reactive power optimization is evaluated on standard IEEE, 30, 57, 191 (practical test bus system. The proposed approach is tested and compared to genetic algorithm (GA, Adaptive Genetic Algorithm (AGA.
International Nuclear Information System (INIS)
Chen, Gonggui; Liu, Lilan; Song, Peizhu; Du, Yangwei
2014-01-01
Highlights: • New method for MOORPD problem using MOCIPSO and MOIPSO approaches. • Constrain-prior Pareto-dominance method is proposed to meet the constraints. • The limits of the apparent power flow of transmission line are considered. • MOORPD model is built up for MOORPD problem. • The achieved results by MOCIPSO and MOIPSO approaches are better than MOPSO method. - Abstract: Multi-objective optimal reactive power dispatch (MOORPD) seeks to not only minimize power losses, but also improve the stability of power system simultaneously. In this paper, the static voltage stability enhancement is achieved through incorporating L index in MOORPD problem. Chaotic improved PSO-based multi-objective optimization (MOCIPSO) and improved PSO-based multi-objective optimization (MOIPSO) approaches are proposed for solving complex multi-objective, mixed integer nonlinear problems such as minimization of power losses and L index in power systems simultaneously. In MOCIPSO and MOIPSO based optimization approaches, crossover operator is proposed to enhance PSO diversity and improve their global searching capability, and for MOCIPSO based optimization approach, chaotic sequences based on logistic map instead of random sequences is introduced to PSO for enhancing exploitation capability. In the two approaches, constrain-prior Pareto-dominance method (CPM) is proposed to meet the inequality constraints on state variables, the sorting and crowding distance methods are considered to maintain a well distributed Pareto optimal solutions, and moreover, fuzzy set theory is employed to extract the best compromise solution over the Pareto optimal curve. The proposed approaches have been examined and tested in the IEEE 30 bus and the IEEE 57 bus power systems. The performances of MOCIPSO, MOIPSO, and multi-objective PSO (MOPSO) approaches are compared with respect to multi-objective performance measures. The simulation results are promising and confirm the ability of MOCIPSO and
Artificial intelligence in power system optimization
Ongsakul, Weerakorn
2013-01-01
With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.
International Nuclear Information System (INIS)
Sanjari, M.J.; Karami, H.; Gooi, H.B.
2016-01-01
Highlights: • Combination of day-ahead and hour-ahead optimizations to design online controller. • Investigating the effect of load forecast error on the system operating cost. • Proposing effective method for hour-ahead resource re-dispatch. • Using the HSS algorithm as a powerful and effective optimization method. • Combining long-term and short-term strategies for optimal dispatch of resources. - Abstract: This paper deals with a residential hybrid thermal/electrical grid-connected home energy system incorporating real data for the load demand. A day-ahead scheduling (DAS) algorithm for dispatching different resources has been developed in previous studies to determine the optimal operation scheduling for the distributed energy resources at each time interval so that the operational cost of a smart house is minimized. However, demand of houses may be changed in each hour and cannot be exactly predicted one day ahead. System complexity caused by nonlinear dynamics of the fuel cell, as a combined heat and power device, and battery charging and discharging time make it difficult to find the optimal operating point of the system by using the optimization algorithms quickly in online applications. In this paper, the demand forecast error is studied and a near-optimal dispatch strategy by using artificial neural network (ANN) is proposed for the residential energy system when the demand changes are known one hour ahead with respect to the predicted day-ahead values. The day-ahead and hour-ahead optimizations are combined and ANN training inputs are adjusted according to the problem such that the economic dispatch of different energy resources can be achieved by the proposed method compared with previous studies. Using the model of the fuel cell extracted from experimental measurement and real data for the load demand makes the results more applicable in real residential energy systems.
Joint energy and spinning reserve dispatching and pricing
International Nuclear Information System (INIS)
Rashidinejad, M.; Song, Y.-H.; Javidi Dasht-Bayaz, M.H.
2000-01-01
Unpredictable load demand variations, and also sudden generation interruption, may cause imbalance in power systems. To prevent any blackout and to reduce such total power imbalance, spinning reserve can provide electric power system ability to respond. Adequate amount of spinning reserve should be based on economy and risk as an optimal decision making. This paper uses Quadratic Programming (QP) method to solve Joint Energy and Spinning Reserve Dispatch (JESRD) problem and derives the optimal price of spinning reserve. In JESRD, Unserved Energy Cost (UEC) is considered as an Opportunity Cost of Spinning Reserve (OCSR). To distribute the System Reserve Requirements (SRR) among generation units, two different models, Fixed Reserve Percentage (FRP) or fixed allocation model and Non-Fixed Reserve Percentage (NFRP) or flexible allocation model has been investigated. Numerical results on a 5-bus test system and the 30-bus IEEE standard system, considering FRP and NFRP models are included. (author)
International Nuclear Information System (INIS)
Athayde Costa e Silva, Marsil de; Klein, Carlos Eduardo; Mariani, Viviana Cocco; Santos Coelho, Leandro dos
2013-01-01
The environmental/economic dispatch (EED) is an important daily optimization task in the operation of many power systems. It involves the simultaneous optimization of fuel cost and emission objectives which are conflicting ones. The EED problem can be formulated as a large-scale highly constrained nonlinear multiobjective optimization problem. In recent years, many metaheuristic optimization approaches have been reported in the literature to solve the multiobjective EED. In terms of metaheuristics, recently, scatter search approaches are receiving increasing attention, because of their potential to effectively explore a wide range of complex optimization problems. This paper proposes an improved scatter search (ISS) to deal with multiobjective EED problems based on concepts of Pareto dominance and crowding distance and a new scheme for the combination method. In this paper, we have considered the standard IEEE (Institute of Electrical and Electronics Engineers) 30-bus system with 6-generators and the results obtained by proposed ISS algorithm are compared with the other recently reported results in the literature. Simulation results demonstrate that the proposed ISS algorithm is a capable candidate in solving the multiobjective EED problems. - Highlights: ► Economic dispatch. ► We solve the environmental/economic economic power dispatch problem with scatter search. ► Multiobjective scatter search can effectively improve the global search ability
Economic Dispatch for Microgrid Containing Electric Vehicles via Probabilistic Modeling: Preprint
Energy Technology Data Exchange (ETDEWEB)
Yao, Yin; Gao, Wenzhong; Momoh, James; Muljadi, Eduard
2016-02-11
In this paper, an economic dispatch model with probabilistic modeling is developed for a microgrid. The electric power supply in a microgrid consists of conventional power plants and renewable energy power plants, such as wind and solar power plants. Because of the fluctuation in the output of solar and wind power plants, an empirical probabilistic model is developed to predict their hourly output. According to different characteristics of wind and solar power plants, the parameters for probabilistic distribution are further adjusted individually for both. On the other hand, with the growing trend in plug-in electric vehicles (PHEVs), an integrated microgrid system must also consider the impact of PHEVs. The charging loads from PHEVs as well as the discharging output via the vehicle-to-grid (V2G) method can greatly affect the economic dispatch for all of the micro energy sources in a microgrid. This paper presents an optimization method for economic dispatch in a microgrid considering conventional power plants, renewable power plants, and PHEVs. The simulation results reveal that PHEVs with V2G capability can be an indispensable supplement in a modern microgrid.
DEFF Research Database (Denmark)
Li, Chendan; Federico, de Bosio; Chen, Fang
2017-01-01
In this paper, an economic dispatch problem for total operation cost minimization in DC microgrids is formulated. An operating cost is associated with each generator in the microgrid, including the utility grid, combining the cost-efficiency of the system with demand response requirements...... achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic method. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used in the case studies. Simulation results show that under variable renewable energy generation, load...... of the utility. The power flow model is included in the optimization problem, thus the transmission losses can be considered for generation dispatch. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to this control level, thus...
The value of dispatchability of CSP plants in the electricity systems of Morocco and Algeria
International Nuclear Information System (INIS)
Brand, Bernhard; Boudghene Stambouli, Amine; Zejli, Driss
2012-01-01
This paper examines the effects of an increased integration of concentrated solar power (CSP) into the conventional electricity systems of Morocco and Algeria. A cost-minimizing linear optimization tool was used to calculate the best CSP plant configuration for Morocco's coal-dominated power system as well as for Algeria, where flexible gas-fired power plants prevail. The results demonstrate that in both North African countries, storage-based CSP plants offer significant economic advantages over non-storage, low-dispatchable CSP configurations. However, in a generalized renewable integration scenario, where CSP has to compete with other renewable generation technologies, like wind or photovoltaic (PV) power, it was found that the cost advantages of dispatchability only justify CSP investments when a relatively high renewable penetration is targeted in the electricity mix. - Highlights: ► Market model to optimize CSP plant configuration in North African power systems. ► Value of storage-based CSP plants compared to non-dispatchable configurations: 28–55 €/MWh. ► Assessment of Morocco's and Algeria's renewable electricity targets until 2030. ► CSP becomes more competitive with intermittent technologies when high RES-E quota are targeted.
The Optimization of power reactor control system
International Nuclear Information System (INIS)
Danupoyo, S.D.
1997-01-01
A power reactor is an important part in nuclear powered electrical plant systems. Success in controlling the power reactor will establish safety of the whole power plant systems. Until now, the power reactor has been controlled by a classical control system that was designed based on output feedback method. To meet the safety requirements that are now more restricted, the recently used power reactor control system should be modified. this paper describes a power reactor control system that is designed based on a state feedback method optimized with LQG (Linear-quadrature-gaussian) method and equipped with a state estimator. A pressurized-water type reactor has been used as the model. by using a point kinetics method with one group delayed neutrons. the result of simulation testing shows that the optimized control system can control the power reactor more effective and efficient than the classical control system
Economic load dispatch of wind-solar-thermal system using ...
African Journals Online (AJOL)
Economic load dispatch (ELD) problem is an essential optimization problem ..... The data for radiation and average ambient temperature is adopted as per (Solar Radiation Hand Book, et al.,2008) ..... Reference temperature for cell efficiency.
Simulated annealing approach for solving economic load dispatch ...
African Journals Online (AJOL)
user
thermodynamics to solve economic load dispatch (ELD) problems. ... evolutionary programming algorithm has been successfully applied for solving the ... concept behind the simulated annealing (SA) optimization is discussed in Section 3.
Optimization of photovoltaic power systems
Rekioua, Djamila
2012-01-01
Photovoltaic generation is one of the cleanest forms of energy conversion available. One of the advantages offered by solar energy is its potential to provide sustainable electricity in areas not served by the conventional power grid. Optimisation of Photovoltaic Power Systems details explicit modelling, control and optimisation of the most popular stand-alone applications such as pumping, power supply, and desalination. Each section is concluded by an example using the MATLAB(R) and Simulink(R) packages to help the reader understand and evaluate the performance of different photovoltaic syste
A two-stage optimal planning and design method for combined cooling, heat and power microgrid system
International Nuclear Information System (INIS)
Guo, Li; Liu, Wenjian; Cai, Jiejin; Hong, Bowen; Wang, Chengshan
2013-01-01
Highlights: • A two-stage optimal method is presented for CCHP microgrid system. • Economic and environmental performance are considered as assessment indicators. • Application case demonstrates its good economic and environmental performance. - Abstract: In this paper, a two-stage optimal planning and design method for combined cooling, heat and power (CCHP) microgrid system was presented. The optimal objective was to simultaneously minimize the total net present cost and carbon dioxide emission in life circle. On the first stage, multi-objective genetic algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) was applied to solve the optimal design problem including the optimization of equipment type and capacity. On the second stage, mixed-integer linear programming (MILP) algorithm was used to solve the optimal dispatch problem. The approach was applied to a typical CCHP microgrid system in a hospital as a case study, and the effectiveness of the proposed method was verified
Directory of Open Access Journals (Sweden)
Junpeng Zhu
2014-07-01
Full Text Available The coming interaction between a growing electrified vehicle fleet and the desired growth in renewable energy provides new insights into the economic dispatch (ED problem. This paper presents an economic dispatch model that considers electric vehicle charging, battery exchange stations, and wind farms. This ED model is a high-dimensional, non-linear, and stochastic problem and its solution requires powerful methods. A new finite action-set learning automata (FALA-based approach that has the ability to adapt to a stochastic environment is proposed. The feasibility of the proposed approach is demonstrated in a modified IEEE 30 bus system. It is compared with continuous action-set learning automata and particle swarm optimization-based approaches in terms of convergence characteristics, computational efficiency, and solution quality. Simulation results show that the proposed FALA-based approach was indeed capable of more efficiently obtaining the approximately optimal solution. In addition, by using an optimal dispatch schedule for the interaction between electric vehicle stations and power systems, it is possible to reduce the gap between demand and power generation at different times of the day.
Optimal Control of Wind Power Generation
Directory of Open Access Journals (Sweden)
Pawel Pijarski
2018-03-01
Full Text Available Power system control is a complex task, which is strongly related to the number and kind of generating units as well as to the applied technologies, such as conventional coal fired power plants or wind and photovoltaic farms. Fast development of wind generation that is considered as unstable generation sets new strong requirements concerning remote control and data hubs cooperating with SCADA systems. Considering specific nature of the wind power generation, the authors analyze the problem of optimal control for wind power generation in farms located over a selected remote-controlled part of the Operator grid under advantageous wind conditions. This article presents an original stepwise method for tracing power flows that makes possible to eliminate current (power overloading of power grid branches. Its core idea is to consider the discussed problem as an optimization task.
Directory of Open Access Journals (Sweden)
Fei Wang
2017-11-01
Full Text Available The optimal dispatching model for a stand-alone microgrid (MG is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL and multi-distributed generations (DGs. The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend and weather categories (sunny or rainy to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation.
Optimal control applications in electric power systems
Christensen, G S; Soliman, S A
1987-01-01
Significant advances in the field of optimal control have been made over the past few decades. These advances have been well documented in numerous fine publications, and have motivated a number of innovations in electric power system engineering, but they have not yet been collected in book form. Our purpose in writing this book is to provide a description of some of the applications of optimal control techniques to practical power system problems. The book is designed for advanced undergraduate courses in electric power systems, as well as graduate courses in electrical engineering, applied mathematics, and industrial engineering. It is also intended as a self-study aid for practicing personnel involved in the planning and operation of electric power systems for utilities, manufacturers, and consulting and government regulatory agencies. The book consists of seven chapters. It begins with an introductory chapter that briefly reviews the history of optimal control and its power system applications and also p...
Optimal control systems in hydro power plants
International Nuclear Information System (INIS)
Babunski, Darko L.
2012-01-01
The aim of the research done in this work is focused on obtaining the optimal models of hydro turbine including auxiliary equipment, analysis of governors for hydro power plants and analysis and design of optimal control laws that can be easily applicable in real hydro power plants. The methodology of the research and realization of the set goals consist of the following steps: scope of the models of hydro turbine, and their modification using experimental data; verification of analyzed models and comparison of advantages and disadvantages of analyzed models, with proposal of turbine model for design of control low; analysis of proportional-integral-derivative control with fixed parameters and gain scheduling and nonlinear control; analysis of dynamic characteristics of turbine model including control and comparison of parameters of simulated system with experimental data; design of optimal control of hydro power plant considering proposed cost function and verification of optimal control law with load rejection measured data. The hydro power plant models, including model of power grid are simulated in case of island ing and restoration after breakup and load rejection with consideration of real loading and unloading of hydro power plant. Finally, simulations provide optimal values of control parameters, stability boundaries and results easily applicable to real hydro power plants. (author)
Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem
International Nuclear Information System (INIS)
Malik, T.N.; Asar, A.U.
2009-01-01
ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
The Mathematics of Dispatchability Revisited
Morris, Paul
2016-01-01
Dispatchability is an important property for the efficient execution of temporal plans where the temporal constraints are represented as a Simple Temporal Network (STN). It has been shown that every STN may be reformulated as a dispatchable STN, and dispatchability ensures that the temporal constraints need only be satisfied locally during execution. Recently it has also been shown that Simple Temporal Networks with Uncertainty, augmented with wait edges, are Dynamically Controllable provided every projection is dispatchable. Thus, the dispatchability property has both theoretical and practical interest. One thing that hampers further work in this area is the underdeveloped theory. The existing definitions are expressed in terms of algorithms, and are less suitable for mathematical proofs. In this paper, we develop a new formal theory of dispatchability in terms of execution sequences. We exploit this to prove a characterization of dispatchability involving the structural properties of the STN graph. This facilitates the potential application of the theory to uncertainty reasoning.
Consumption Behavior Analytics-Aided Energy Forecasting and Dispatch
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yang, Rui [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Kaiqing [University of Illinois Urbana-Champaign; Zhang, Jun Jason [University of Denver
2017-08-17
For decades, electricity customers have been treated as mere recipients of electricity in vertically integrated power systems. However, as customers have widely adopted distributed energy resources and other forms of customer participation in active dispatch (such as demand response) have taken shape, the value of mining knowledge from customer behavior patterns and using it for power system operation is increasing. Further, the variability of renewable energy resources has been considered a liability to the grid. However, electricity consumption has shown the same level of variability and uncertainty, and this is sometimes overlooked. This article investigates data analytics and forecasting methods to identify correlations between electricity consumption behavior and distributed photovoltaic (PV) output. The forecasting results feed into a predictive energy management system that optimizes energy consumption in the near future to balance customer demand and power system needs.
A Modified Artificial Bee Colony Algorithm Application for Economic Environmental Dispatch
Tarafdar Hagh, M.; Baghban Orandi, Omid
2018-03-01
In conventional fossil-fuel power systems, the economic environmental dispatch (EED) problem is a major problem that optimally determines the output power of generating units in a way that cost of total production and emission level be minimized simultaneously, and at the same time all the constraints of units and system are satisfied properly. To solve EED problem which is a non-convex optimization problem, a modified artificial bee colony (MABC) algorithm is proposed in this paper. This algorithm by implementing weighted sum method is applied on two test systems, and eventually, obtained results are compared with other reported results. Comparison of results confirms superiority and efficiency of proposed method clearly.
Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method
Directory of Open Access Journals (Sweden)
Wen-Yeau Chang
2013-09-01
Full Text Available High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO based hybrid forecasting method for short-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network, and the radial basis function (RBF neural network. The EPSO algorithm is employed to optimize the weight coefficients in the hybrid forecasting method. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a wind energy conversion system (WECS installed on the Taichung coast of Taiwan. Comparisons of forecasting performance are made with the individual forecasting methods. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.
Optimal Control of Wind Farms for Coordinated TSO-DSO Reactive Power Management
Directory of Open Access Journals (Sweden)
David Sebastian Stock
2018-01-01
Full Text Available The growing importance of renewable generation connected to distribution grids requires an increased coordination between transmission system operators (TSOs and distribution system operators (DSOs for reactive power management. This work proposes a practical and effective interaction method based on sequential optimizations to evaluate the reactive flexibility potential of distribution networks and to dispatch them along with traditional synchronous generators, keeping to a minimum the information exchange. A modular optimal power flow (OPF tool featuring multi-objective optimization is developed for this purpose. The proposed method is evaluated for a model of a real German 110 kV grid with 1.6 GW of installed wind power capacity and a reduced order model of the surrounding transmission system. Simulations show the benefit of involving wind farms in reactive power support reducing losses both at distribution and transmission level. Different types of setpoints are investigated, showing the feasibility for the DSO to fulfill also individual voltage and reactive power targets over multiple connection points. Finally, some suggestions are presented to achieve a fair coordination, combining both TSO and DSO requirements.
Economic dispatch of a single micro-gas turbine under CHP operation
International Nuclear Information System (INIS)
Rist, Johannes F.; Dias, Miguel F.; Palman, Michael; Zelazo, Daniel; Cukurel, Beni
2017-01-01
Highlights: •Economic dispatch of a micro gas turbine is considered for smart grid integration. •A detailed thermodynamic cycle analysis is conducted for variable load CHP operation. •Benefits are shown for case studies with real demand profiles and energy tariffs. •Optimal unit schedule can be electricity, heat, revenue or maintenance-cost driven. -- Abstract: This work considers the economic dispatch of a single micro-gas turbine under combined heat and power (CHP) operation. A detailed thermodynamic cycle analysis is conducted on a representative micro-gas turbine unit with non-constant component efficiencies and recuperator bypass. Based on partial and full load configurations, an accurate optimization model is developed for solving the economic dispatch problem of integrating the turbine into the grid. The financial benefit and viability of this approach is then examined on four detailed scenarios using real data on energy demand profiles and electricity tariffs. The analysis considers the optimal operation in a large hotel, a full-service restaurant, a small hotel, and a residential neighborhood during various seasons. The optimal schedule follows four fundamental economic drivers which are electricity, heat, revenue, and maintenance-cost driven.
Gas Dispatching and Management
International Nuclear Information System (INIS)
Schoettker, R.; Spiecker, U.
1995-01-01
Activities in large dispatch centres are usually divided into volume planning and contract management as well as grid control. Volume planning and contract management require high-performance computers for contractual and technical optimisation models, for contract handling models and communication with partner companies. For grid control, the use of computers for SCADA systems and for grid simulation and optimisation has become a fundamental requirement. In 1992, Ruhrgas replaced the hardware by a modern hardware concept featuring a fault-tolerant process computer for SCADA system interface processing. The work-place computers were substituted by sophisticated workstations integrated into a computer network and an X-Windows user interface based on the MOTIF standard was introduced. Effective cooperation between the dispatch centres of European gas companies is of paramount importance. One example of good cooperation is the contractual and physical handling of North Sea gas supplies at Emden. 4 figs
Optimization and Control of Electric Power Systems
Energy Technology Data Exchange (ETDEWEB)
Lesieutre, Bernard C. [Univ. of Wisconsin, Madison, WI (United States); Molzahn, Daniel K. [Univ. of Wisconsin, Madison, WI (United States)
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Modeling and Optimization of the Medium-Term Units Commitment of Thermal Power
Directory of Open Access Journals (Sweden)
Shengli Liao
2015-11-01
Full Text Available Coal-fired thermal power plants, which represent the largest proportion of China’s electric power system, are very sluggish in responding to power system load demands. Thus, a reasonable and feasible scheme for the medium-term optimal commitment of thermal units (MOCTU can ensure that the generation process runs smoothly and minimizes the start-up and shut-down times of thermal units. In this paper, based on the real-world and practical demands of power dispatch centers in China, a flexible mathematical model for MOCTU that uses equal utilization hours for the installed capacity of all thermal power plants as the optimization goal and that considers the award hours for MOCTU is developed. MOCTU is a unit commitment (UC problem with characteristics of large-scale, high dimensions and nonlinearity. For optimization, an improved progressive optimality algorithm (IPOA offering the advantages of POA is adopted to overcome the drawback of POA of easily falling into the local optima. In the optimization process, strategies of system operating capacity equalization and single station operating peak combination are introduced to move the target solution from the boundary constraints along the target isopleths into the feasible solution’s interior to guarantee the global optima. The results of a case study consisting of nine thermal power plants with 27 units show that the presented algorithm can obtain an optimal solution and is competent in solving the MOCTU with high efficiency and accuracy as well as that the developed simulation model can be applied to practical engineering needs.
Optimization of IGCT for pulsed power
International Nuclear Information System (INIS)
Chen Fanglin; Tang Longgu; Chen Yongmin; Pan Xuejun
2014-01-01
In order to develop high-performance IGCT devices applied in pulse power, cathode finger layout is optimized, the finger structure is modified, minority carrier lifetime is properly controlled and gate triggering characteristics is improved. As a result of these measures, the IGCT turn -on di/dt is improved, current handling capability is enhanced and switching response speed is increased. The feasibility and validity of the optimization study on the IGCT is verified by simulation and experimental results. (authors)
Optimization of a wearable power system
Energy Technology Data Exchange (ETDEWEB)
Kovacevic, I.; Round, S. D.; Kolar, J. W.; Boulouchos, K.
2008-07-01
In this paper the optimization of wearable power system comprising of an internal combustion engine, motor/generator, inverter/rectifier, Li-battery pack, DC/DC converters, and controller is performed. The Wearable Power System must have the capability to supply an average 20 W for 4 days with peak power of 200 W and have a system weight less then 4 kg. The main objectives are to select the engine, fuel and battery type, to match the weight of fuel and the number of battery cells, to find the optimal working point of engine and minimizing the system weight. The minimization problem is defined in Matlab as a nonlinear constrained optimization task. The optimization procedure returns the optimal system design parameters: the Li-polymer battery with eight cells connected in series for a 28 V DC output voltage, the selection of gasoline/oil fuel mixture and the optimal engine working point of 12 krpm for a 4.5 cm{sup 3} 4-stroke engine. (author)
Power Consumption Optimization in Tooth Gears Processing
Kanatnikov, N.; Harlamov, G.; Kanatnikova, P.; Pashmentova, A.
2018-01-01
The paper reviews the issue of optimization of technological process of tooth gears production of the power consumption criteria. The authors dwell on the indices used for cutting process estimation by the consumed energy criteria and their applicability in the analysis of the toothed wheel production process. The inventors proposed a method for optimization of power consumptions based on the spatial modeling of cutting pattern. The article is aimed at solving the problem of effective source management in order to achieve economical and ecological effect during the mechanical processing of toothed gears. The research was supported by Russian Science Foundation (project No. 17-79-10316).
Power and performance software analysis and optimization
Kukunas, Jim
2015-01-01
Power and Performance: Software Analysis and Optimization is a guide to solving performance problems in modern Linux systems. Power-efficient chips are no help if the software those chips run on is inefficient. Starting with the necessary architectural background as a foundation, the book demonstrates the proper usage of performance analysis tools in order to pinpoint the cause of performance problems, and includes best practices for handling common performance issues those tools identify. Provides expert perspective from a key member of Intel's optimization team on how processors and memory
Real-Time Dispatch of Petroleum Tank Trucks
Brown, Gerald G.; Graves, Glenn W.
1981-01-01
Management Science, 27, 1, pp. 19-32. (1982 International Management Science Achievement Award Finalist). A highly automated, real-time dispatch system is described which uses embedded optimization routines to replace extensive manual operations and to reduce substantially operating costs for a nation-wide fleet of petroleum tank trucks. The system is currently used in daily operations by the Order Entry and Dispatch segment of the Chevron U.S.A. Marketing System. Refined petroleum produ...
Hydrothermal optimal power flow using continuation method
International Nuclear Information System (INIS)
Raoofat, M.; Seifi, H.
2001-01-01
The problem of optimal economic operation of hydrothermal electric power systems is solved using powerful continuation method. While in conventional approach, fixed generation voltages are used to avoid convergence problems, in the algorithm, they are treated as variables so that better solutions can be obtained. The algorithm is tested for a typical 5-bus and 17-bus New Zealand networks. Its capabilities and promising results are assessed
International Nuclear Information System (INIS)
Ghasemi, Mojtaba; Ghavidel, Sahand; Aghaei, Jamshid; Gitizadeh, Mohsen; Falah, Hasan
2014-01-01
Highlights: • Chaotic invasive weed optimization techniques based on chaos. • Nonlinear environmental OPF problem considering non-smooth fuel cost curves. • A comparative study of CIWO techniques for environmental OPF problem. - Abstract: This paper presents efficient chaotic invasive weed optimization (CIWO) techniques based on chaos for solving optimal power flow (OPF) problems with non-smooth generator fuel cost functions (non-smooth OPF) with the minimum pollution level (environmental OPF) in electric power systems. OPF problem is used for developing corrective strategies and to perform least cost dispatches. However, cost based OPF problem solutions usually result in unattractive system gaze emission issue (environmental OPF). In the present paper, the OPF problem is formulated by considering the emission issue. The total emission can be expressed as a non-linear function of power generation, as a multi-objective optimization problem, where optimal control settings for simultaneous minimization of fuel cost and gaze emission issue are obtained. The IEEE 30-bus test power system is presented to illustrate the application of the environmental OPF problem using CIWO techniques. Our experimental results suggest that CIWO techniques hold immense promise to appear as efficient and powerful algorithm for optimization in the power systems
Exploration of dispatch model integrating wind generators and electric vehicles
International Nuclear Information System (INIS)
Haque, A.N.M.M.; Ibn Saif, A.U.N.; Nguyen, P.H.; Torbaghan, S.S.
2016-01-01
Highlights: • A novel business model for the BRPs is analyzed. • Imbalance cost of wind generation is considered in the UC-ED model. • Smart charging of EVs is included into the UC-ED problem to mitigate the imbalance cost. • Effects of smart charging on generation cost, CO 2 emissions and total network load are assessed. - Abstract: In recent years, the share of renewable energy sources (RES) in the electricity generation mix has been expanding rapidly. However, limited predictability of the RES poses challenges for traditional scheduling and dispatching mechanisms based on unit commitment (UC) and economic dispatch (ED). This paper presents an advanced UC-ED model to incorporate wind generators as RES-based units alongside conventional centralized generators. In the proposed UC-ED model, an imbalance cost is introduced reflecting the wind generation uncertainty along with the marginal generation cost. The proposed UC-ED model aims to utilize the flexibility of fleets of plug-in electric vehicles (PEVs) to optimally compensate for the wind generation uncertainty. A case study with 15 conventional units and 3 wind farms along with a fixed-sized PEV fleet demonstrates that shifting of PEV fleets charging at times of high wind availability realizes generation cost savings. Nevertheless, the operational cost saving incurred by controlled charging appears to diminish when dispatched wind energy becomes considerably larger than the charging energy of PEV fleets. Further analysis of the results reveals that the effectiveness of PEV control strategy in terms of CO 2 emission reduction is strongly coupled with generation mix and the proposed control strategy is favored in cases where less pollutant-based plants like nuclear and hydro power are profoundly dominant.
Fuel optimization of Qinshan nuclear power plant
International Nuclear Information System (INIS)
Liao Zejun; Li Zhuoqun; Kong Deping; Xue Xincai; Wang Shiwei
2010-01-01
Based on the design practice of the fuel replacement of Qin Shan nuclear power plant, this document effectively analyzes the shortcomings of current replacement design of Qin Shan. To address these shortcomings, this document successfully implements the 300 MW fuel optimization program from fuel replacement. fuel improvement and experimentation ,and achieves great economic results. (authors)
Wind Farm Dispatch Control for Demand Tracking and Minimized Fatigue
DEFF Research Database (Denmark)
Juelsgaard, Morten; Schiøler, Henrik; Leth, John-Josef
2012-01-01
This work presents a strategy for dispatching production references to the individual turbines in a wind farm, such that an overall production demand for the farm is obeyed, while the fatigue experienced by the turbines is minimized. Using a turbine fatigue model for simulating the aging across...... the farm, we show that a 17 % reduction of the turbine aging can be obtained compared to a commonly employed industrial dispatcher, without degrading the power demand tracking....
Energy Technology Data Exchange (ETDEWEB)
Barragan Gomez, Sergio Baruch
2004-05-15
The changes in the structures of the electric systems of vertical schemes to horizontal schemes have caused systems to be formed by four segments: generation, transmission, distribution and commercialization. Under this scheme the system operator is the one in charge of guaranteeing an economic and secure administration-operation. One of the main tasks of this organization together with the transmission net is achieving the movement of power from the generation centers until the consumption points, however in order to make this activity possible, a group of auxiliary service is needed. In a horizontal scheme, the voltage support of the generators is considered as an auxiliary service, which is necessary for the operation of the system. Although compensation of reactive power should be achieved in a local way through shunt compensation, static compensators, synchronous condensers and transformers with under load tap changer, because transmitting reactive power flow from generators causes an increment in the transmission system losses, however although the main function of the synchronous generators is the production of active power, in an implicit way these generate reactive power under certain operation conditions. Therefore the need of determining a cost for the voltage support of the generators exists, since this action is considered as an auxiliary service and it is rewarded in an independent way. In this work, the gradient method is used to solve the reactive power dispatch and determine the cost for voltage support of each participant generator in the system. The reactive power dispatch is subject to equality restrictions that represent the balance equations of active and reactive power of each node and to inequality restrictions that correspond to limits in the voltage profiles of all the system nodes. The equality restrictions are considered with the Lagrange multipliers method and the inequality restrictions with quadratic penalty functions. The total cost
Banka, John Czeslaw
The world strives for more clean and renewable energy, but the amount of dispatchable energy in river networks is not accurately known and difficult to assess. When wind is integrated with water, the dispatchable yield can be greatly increased, but the uncertainty of the wind further degrades predictability. This thesis demonstrates how simulating the flows is a river network integrated with wind over a long time domain yields a solution. Time-shifting the freshet and pumped storage will ameliorate the seasonal summer drought; the risk of ice jams and uncontrolled flooding is reduced. An artificial market eliminates the issue of surplus energy from wind at night. Furthermore, this thesis shows how the necessary infrastructure can be built to accomplish the goals of the intended research. While specific to Northern Ontario and sensitive to the lives of the Native peoples living there, it indicates where the research might be applicable elsewhere in the world.
International Nuclear Information System (INIS)
Perera, A.T.D.; Nik, Vahid M.; Mauree, Dasaraden; Scartezzini, Jean-Louis
2017-01-01
Highlights: • A novel method introduced to optimize Electrical Hubs. • Novel dispatch based on fuzzy control and finite state machines. • Evaluating sensitivity of three performance indices for system autonomy. • Multi objective optimization considering system autonomy-cost. • Electrical Hubs can cover above 60% of the demand using wind and Solar PV. - Abstract: A paradigm change in energy system design tools, energy market, and energy policy is required to attain the target levels in renewable energy integration and in minimizing pollutant emissions in power generation. Integrating non-dispatchable renewable energy sources such as solar and wind energy is vital in this context. Distributed generation has been identified as a promising method to integrate Solar PV (SPV) and wind energy into grid in recent literature. Distributed generation using grid-tied electrical hubs, which consist of Internal Combustion Generator (ICG), non-dispatchable energy sources (i.e., wind turbines and SPV panels) and energy storage for providing the electricity demand in Sri Lanka is considered in this study. A novel dispatch strategy is introduced to address the limitations in the existing methods in optimizing grid-integrated electrical hubs considering real time pricing of the electricity grid and curtailments in grid integration. Multi-objective optimization is conducted for the system design considering grid integration level and Levelized Energy Cost (LEC) as objective functions to evaluate the potential of electrical hubs to integrate SPV and wind energy. The sensitivity of grid curtailments, energy market, price of wind turbines and SPV panels on Pareto front is evaluated subsequently. Results from the Pareto analysis demonstrate the potential of electrical hubs to cover more than 60% of the annual electricity demand from SPV and wind energy considering stringent grid curtailments. Such a share from SPV and wind energy is quite significant when compared to direct grid
DEFF Research Database (Denmark)
Michalitsakos, Panagiotis; Mihet-Popa, Lucian; Xydis, George
2017-01-01
-CAM (Distributed Energy Resources Customer Adoption Model) decision support tool was used for the multi-objective analysis conducted, which proposes a set of optimal solutions defining the appropriate Distributed Generation (DG) technologies, the capacities of storage and other technologies and the optimal......The possibility of replacing the existing autonomous thermal power plants by Distributed Energy Resources (DER) based on renewable energy sources (RES), along with the appropriate energy storage technologies in order to deal with the major problems that autonomous islands usually face...... was investigated. A case study of a small Greek island, which is confronted by various energy and water shortages, was studied for assessing the feasibility of DER deployment. The main objectives investigated were cost minimization, CO2 emissions minimization and DER reliability maximization. The DER...
Optimal Power Flow Control by Rotary Power Flow Controller
Directory of Open Access Journals (Sweden)
KAZEMI, A.
2011-05-01
Full Text Available This paper presents a new power flow model for rotary power flow controller (RPFC. RPFC injects a series voltage into the transmission line and provides series compensation and phase shifting simultaneously. Therefore, it is able to control the transmission line impedance and the active power flow through it. An RPFC is composed mainly of two rotary phase shifting transformers (RPST and two conventional (series and shunt transformers. Structurally, an RPST consists of two windings (stator and rotor windings. The rotor windings of the two RPSTs are connected in parallel and their stator windings are in series. The injected voltage is proportional to the vector sum of the stator voltages and so its amplitude and angle are affected by the rotor position of the two RPSTs. This paper, describes the steady state operation and single-phase equivalent circuit of the RPFC. Also in this paper, a new power flow model, based on power injection model of flexible ac transmission system (FACTS controllers, suitable for the power flow analysis is introduced. Proposed model is used to solve optimal power flow (OPF problem in IEEE standard test systems incorporating RPFC and the optimal settings and location of the RPFC is determined.
Wheeling rates evaluation using optimal power flows
International Nuclear Information System (INIS)
Muchayi, M.; El-Hawary, M. E.
1998-01-01
Wheeling is the transmission of electrical power and reactive power from a seller to a buyer through a transmission network owned by a third party. The wheeling rates are then the prices charged by the third party for the use of its network. This paper proposes and evaluates a strategy for pricing wheeling power using a pricing algorithm that in addition to the fuel cost for generation incorporates the optimal allocation of the transmission system operating cost, based on time-of-use pricing. The algorithm is implemented for the IEEE standard 14 and 30 bus system which involves solving a modified optimal power flow problem iteratively. The base of the proposed algorithm is the hourly spot price. The analysis spans a total time period of 24 hours. Unlike other algorithms that use DC models, the proposed model captures wheeling rates of both real and reactive power. Based on the evaluation, it was concluded that the model has the potential for wide application in calculating wheeling rates in a deregulated competitive power transmission environment. 9 refs., 3 tabs
Burning peat in Ireland: An electricity market dispatch perspective
International Nuclear Information System (INIS)
Tuohy, Aidan; Bazilian, Morgan; Doherty, Ronan; Gallachoir, Brian O; O'Malley, Mark
2009-01-01
This paper examines peat power production in Ireland under the three pillars of energy policy-security, competitiveness and environment. Peat contributes to energy security-as an indigenous fuel, it reduces dependency on imports. During a period of low capacity margins, the operation of the peat plants is useful from a system security perspective. Peat generation is being financially supported by consumers through an electricity levy. The fuel also has high carbon intensity. It is not politically viable to consider peat on equal economic criteria to other plant types because of history and location. This paper reviews electricity generation through combustion of peat in Ireland, and quantifies the costs of supporting peat utilising economic dispatch tools, finding the subsidy is not insignificant from a cost or carbon perspective. It shows that while peat is beneficial for one pillar of energy policy (security), the current usage of peat is not optimal from a competitiveness or environmental perspective. By switching from the current 'must-run' mode of operation for peat to the 'dispatched' mode used for the other generation, significant societal savings (in the range Euro 21 m per annum) can be achieved, as well as reducing system emissions by approximately 5% per year.
The political economy of electricity dispatch reform in China
International Nuclear Information System (INIS)
Kahrl, Fredrich; Williams, James H.; Hu, Junfeng
2013-01-01
The transition to a cleaner and more cost-efficient electricity system in China is political-economic as well as technological. An example is the reform of China's method of dispatching power plants, which potentially affects the economic relationships between consumers and producers, between grid and generating companies, and between central and provincial governments. Historically, coal-fired power plants in China all received roughly the same number of operating hours, regardless of efficiency or cost. In 2007, Chinese government agencies began to pilot “energy efficient dispatch,” which requires that generators be dispatched on the basis of thermal efficiency. Using a case study of Guangxi Zhuang Autonomous Region in southern China, we evaluated potential energy and cost savings from a change to energy efficient dispatch. We found that the savings are at best relatively small, because large, efficient generators already account for a significant share of total generation. Moreover, as an administrative policy that does not change economic incentives, energy efficient dispatch exacerbates imbalances and center-provincial tensions in the current system. We argue that incentive-based dispatch reform is likely to produce better outcomes, and that the keys to this reform are empowering an independent regulator with pricing authority and establishing a formal, transparent ratemaking process. - Highlights: ► Savings from China's energy efficient dispatch (EED) policy are at best relatively small. ► EED exacerbates imbalances and center-provincial tensions in China's current power system. ► Incentive-based dispatch reform is likely to produce better outcomes than EED. ► Keys to reform are independent regulation and a formal, transparent ratemaking process. ► Transition to cleaner, cost-efficient electricity system in China is political-economic as well as technological.
DEFF Research Database (Denmark)
Petersen, Mette Højgaard; Edlund, Kristian; Hansen, Lars Henrik
2013-01-01
The word flexibility is central to Smart Grid literature, but still a formal definition of flexibility is pending. This paper present a taxonomy for flexibility modeling denoted Buckets, Batteries and Bakeries. We consider a direct control Virtual Power Plant (VPP), which is given the task...... of servicing a portfolio of flexible consumers by use of a fluctuating power supply. Based on the developed taxonomy we first prove that no causal optimal dispatch strategies exist for the considered problem. We then present two heuristic algorithms for solving the balancing task: Predictive Balancing...
Time-optimal control of reactor power
International Nuclear Information System (INIS)
Bernard, J.A.
1987-01-01
Control laws that permit adjustments in reactor power to be made in minimum time and without overshoot have been formulated and demonstrated. These control laws which are derived from the standard and alternate dynamic period equations, are closed-form expressions of general applicability. These laws were deduced by noting that if a system is subject to one or more operating constraints, then the time-optimal response is to move the system along these constraints. Given that nuclear reactors are subject to limitations on the allowed reactor period, a time-optimal control law would step the period from infinity to the minimum allowed value, hold the period at that value for the duration of the transient, and then step the period back to infinity. The change in reactor would therefore be accomplished in minimum time. The resulting control laws are superior to other forms of time-optimal control because they are general-purpose, closed-form expressions that are both mathematically tractable and readily implanted. Moreover, these laws include provisions for the use of feedback. The results of simulation studies and actual experiments on the 5 MWt MIT Research Reactor in which these time-optimal control laws were used successfully to adjust the reactor power are presented
International Nuclear Information System (INIS)
Mohammadi, A.; Varahram, M.H.
2007-01-01
In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been Shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for Convergence is considerably smaller compared to classical methods. (author)
Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method
International Nuclear Information System (INIS)
Azizipanah-Abarghooee, Rasoul; Niknam, Taher; Roosta, Alireza; Malekpour, Ahmad Reza; Zare, Mohsen
2012-01-01
In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies. -- Highlights: ► WPGs are being incorporated in the multiobjective economic emission dispatch problem. ► 2m PEM handles the system uncertainties. ► A MTLBO is proposed to determine the set of non-dominated (Pareto) optimal solutions. ► A fuzzy-based clustering technique is implemented to control the size of the repository.
A train dispatching model based on fuzzy passenger demand forecasting during holidays
Directory of Open Access Journals (Sweden)
Fei Dou Dou
2013-03-01
Full Text Available Abstract: Purpose: The train dispatching is a crucial issue in the train operation adjustment when passenger flow outbursts. During holidays, the train dispatching is to meet passenger demand to the greatest extent, and ensure safety, speediness and punctuality of the train operation. In this paper, a fuzzy passenger demand forecasting model is put up, then a train dispatching optimization model is established based on passenger demand so as to evacuate stranded passengers effectively during holidays. Design/methodology/approach: First, the complex features and regularity of passenger flow during holidays are analyzed, and then a fuzzy passenger demand forecasting model is put forward based on the fuzzy set theory and time series theory. Next, the bi-objective of the train dispatching optimization model is to minimize the total operation cost of the train dispatching and unserved passenger volume during holidays. Finally, the validity of this model is illustrated with a case concerned with the Beijing-Shanghai high-speed railway in China. Findings: The case study shows that the fuzzy passenger demand forecasting model can predict outcomes more precisely than ARIMA model. Thus train dispatching optimization plan proves that a small number of trains are able to serve unserved passengers reasonably and effectively. Originality/value: On the basis of the passenger demand predictive values, the train dispatching optimization model is established, which enables train dispatching to meet passenger demand in condition that passenger flow outbursts, so as to maximize passenger demand by offering the optimal operation plan.
Problems of the power plant shield optimization
International Nuclear Information System (INIS)
Abagyan, A.A.; Dubinin, A.A.; Zhuravlev, V.I.; Kurachenko, Yu.A.; Petrov, Eh.E.
1981-01-01
General approaches to the solution of problems on the nuclear power plant radiation shield optimization are considered. The requirements to the shield parameters are formulated in a form of restrictions on a number of functionals, determined by the solution of γ quantum and neutron transport equations or dimensional and weight characteristics of shield components. Functional determined by weight-dimensional parameters (shield cost, mass and thickness) and functionals, determined by radiation fields (equivalent dose rate, produced by neutrons and γ quanta, activation functional, radiation functional, heat flux, integral heat flux in a particular part of the shield volume, total energy flux through a particular shield surface are considered. The following methods of numerical solution of simplified optimization problems are discussed: semiempirical methods using radiation transport physical leaks, numerical solution of approximate transport equations, numerical solution of transport equations for the simplest configurations making possible to decrease essentially a number of variables in the problem. The conclusion is drawn that the attained level of investigations on the problem of nuclear power plant shield optimization gives the possibility to pass on at present to the solution of problems with a more detailed account of the real shield operating conditions (shield temperature field account, its strength and other characteristics) [ru
Directory of Open Access Journals (Sweden)
Wanxing Sheng
2016-05-01
Full Text Available In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.
Centralized versus distributed systems to reschedule trains in two dispatching areas
Corman, F.; D'Ariano, A.; Pacciarelli, D.; Pranzo, M.
2010-01-01
Railway dispatchers are in charge of rescheduling trains during operations in order to limit propagation of disturbances occurring in real-time. To help the dispatchers in such task, an advanced decision support system, ROMA (Railway traffic Optimization by Means of Alternative graphs), has been
Construction and assembling optimization of power equipment
Directory of Open Access Journals (Sweden)
Marius Groza
2005-10-01
Full Text Available The main purpose of this paper is to elaborate a calculation program in Pascal language, using Delphi environment. This calculation program is designed to solve the power engineering optimization problems using the critical path method. For illustrating the use of the algorithm and the calculation program we propose an application from power engineering: a 400 kV electrical overhead line section realization. This paper is structured in 4 parts. In the first part of the paper we present the application as a problem of critic path. In the second part of the paper, we determine the critic path in a program graph and time reserves. In the third part of the paper we present a representative numerical application. In the fourth part of the paper it is described the calculation program.
Pipe support optimization in nuclear power plants
International Nuclear Information System (INIS)
Cleveland, A.B.; Kalyanam, N.
1984-01-01
A typical 1000 MWe nuclear power plant consists of 80,000 to 100,000 feet of piping which must be designed to withstand earthquake shock. For the required ground motion, seismic response spectra are developed for safety-related structures. These curves are used in the dynamic analysis of piping systems with pipe-stress analysis computer codes. To satisfy applicable Code requirements, the piping systems also require analysis for weight, thermal and possibly other lasting conditions. Bechtel Power Corporation has developed a design program called SLAM (Support Location Algorithm) for optimizing pipe support locations and types (rigid, spring, snubber, axial, lateral, etc.) while satisfying userspecified parameters such as locations, load combinations, stress and load allowables, pipe displacement and cost. This paper describes SLAM, its features, applications and benefits
Continuous grasp algorithm applied to economic dispatch problem of thermal units
Energy Technology Data Exchange (ETDEWEB)
Vianna Neto, Julio Xavier [Pontifical Catholic University of Parana - PUCPR, Curitiba, PR (Brazil). Undergraduate Program at Mechatronics Engineering; Bernert, Diego Luis de Andrade; Coelho, Leandro dos Santos [Pontifical Catholic University of Parana - PUCPR, Curitiba, PR (Brazil). Industrial and Systems Engineering Graduate Program, LAS/PPGEPS], e-mail: leandro.coelho@pucpr.br
2010-07-01
The economic dispatch problem (EDP) is one of the fundamental issues in power systems to obtain benefits with the stability, reliability and security. Its objective is to allocate the power demand among committed generators in the most economical manner, while all physical and operational constraints are satisfied. The cost of power generation, particularly in fossil fuel plants, is very high and economic dispatch helps in saving a significant amount of revenue. Recently, as an alternative to the conventional mathematical approaches, modern heuristic optimization techniques such as simulated annealing, evolutionary algorithms, neural networks, ant colony, and tabu search have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. On other hand, continuous GRASP (C-GRASP) is a stochastic local search meta-heuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints. Like a greedy randomized adaptive search procedure (GRASP), a C-GRASP is a multi-start procedure where a starting solution for local improvement is constructed in a greedy randomized fashion. The C-GRASP algorithm is validated for a test system consisting of fifteen units, test system that takes into account spinning reserve and prohibited operating zones constrains. (author)
Multiobjective Optimization Model for Wind Power Allocation
Directory of Open Access Journals (Sweden)
Juan Alemany
2017-01-01
Full Text Available There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solutions for the location of new wind power resources. It is based on the augmented ε-constrained methodology. Two competitive objectives are considered: maximization of preexisting energy injection and maximization of new wind energy injection, both embedded, in the maximization of load supply. The results show that the location of new renewable generation units affects considerably the transmission network flows, the load supply, and the preexisting energy injection. Moreover, there are diverse opportunities to benefit the preexisting generation, contrarily to the expected effect where renewable generation displaces conventional power. The proposed methodology produces a diverse range of equivalent solutions, expanding and enriching the horizon of options and giving flexibility to the decision-making process.
Stochastic maintenance optimization at Candu power plants
International Nuclear Information System (INIS)
Doyle, E.K.; Duchesne, T.; Lee, C.G.; Cho, D.I.
2004-01-01
The use of various innovative maintenance optimization techniques at Bruce has lead to cost effective preventive maintenance applications for complex systems as previously reported at ICONE 6 in New Orleans (1996). Further refinement of the station maintenance strategy was evaluated via the applicability of statistical analysis of historical failure data. The viability of stochastic methods in Candu maintenance was illustrated at ICONE 10 in Washington DC (2002). The next phase consists of investigating the validity of using subjective elicitation techniques to obtain component lifetime distributions. This technique provides access to the elusive failure statistics, the lack of which is often referred to in the literature as the principal impediment preventing the use of stochastic methods in large industry. At the same time the technique allows very valuable information to be captured from the fast retiring 'baby boom generation'. Initial indications have been quite positive. The current reality of global competition necessitates the pursuit of all financial optimizers. The next construction phase in the power generation industry will soon begin on a worldwide basis. With the relatively high initial capital cost of new nuclear generation all possible avenues of financial optimization must be evaluated and implemented. (authors)
High performance magnet power supply optimization
International Nuclear Information System (INIS)
Jackson, L.T.
1988-01-01
The power supply system for the joint LBL--SLAC proposed accelerator PEP provides the opportunity to take a fresh look at the current techniques employed for controlling large amounts of dc power and the possibility of using a new one. A basic requirement of +- 100 ppM regulation is placed on the guide field of the bending magnets and quadrupoles placed around the 2200 meter circumference of the accelerator. The optimization questions to be answered by this paper are threefold: Can a firing circuit be designed to reduce the combined effects of the harmonics and line voltage combined effects of the harmonics and line voltage unbalance to less than 100 ppM in the magnet field. Given the ambiguity of the previous statement, is the addition of a transistor bank to a nominal SCR controlled system the way to go or should one opt for an SCR chopper system running at 1 KHz where multiple supplies are fed from one large dc bus and the cost--performance evaluation of the three possible systems
Optimal sizing and control strategy of isolated grid with wind power and energy storage system
International Nuclear Information System (INIS)
Luo, Yi; Shi, Lin; Tu, Guangyu
2014-01-01
Highlights: • An energy storage sizing scheme for wind powered isolated grid is developed. • A bi-level control strategy for wind-battery isolated grid is proposed. • The energy storage type selection method for Nan’ao island grid is presented. • The sizing method and the control strategy are verified based on the Nan’ao island. • The wind-battery demonstration system has great benefit for remote areas. - Abstract: Integrating renewable energy and energy storage system provides a prospective way for power supply of remote areas. Focused on the isolated grids comprising renewable energy generation and energy storage, an energy storage sizing method for taking account of the reliability requirement and a bi-level control strategy of the isolated grids are presented in this paper. Based on comparative analysis of current energy storage characteristics and practicability, Sodium–sulfur battery is recommended for power balance control in the isolated grids. The optimal size of the energy storage system is determined by genetic algorithm and sequential simulation. The annualized cost considering the compensation cost of curtailed wind power and load is minimized when the reliability requirement can be satisfied. The sizing method emphasizes the tradeoff between energy storage size and reliability of power supply. The bi-level control strategy is designed as upper level wide area power balance control in dispatch timescale and lower level battery energy storage system V/f control in real-time range for isolated operation. The mixed timescale simulation results of Nan’ao Island grid verify the effectiveness of the proposed sizing method and control strategy
Secured Economic Dispatch Algorithm using GSDF Matrix
Directory of Open Access Journals (Sweden)
Slimane SOUAG
2014-02-01
Full Text Available In this paper we present a new method for solving the secured power flow problem by the economic dispatch using DC power flow method and Generation Shift Distribution Factor (GSDF. A graphical interface in LabVIEW has been created as a virtual instrument. Hence the DC power flow reduces the power flow problem to a set of linear equations, which make the iterative calculation very fast and the GSFD matrix present the effects of single and multiple generator MW change on the transmission line. The effectiveness of the method developed is identified through its application to an IEEE-14 bus test system. The calculation results show excellent performance of the proposed method, in regard to computation time and quality of results.
Alhajeri, Nawaf S.; Donohoo, Pearl; Stillwell, Ashlynn S.; King, Carey W.; Webster, Mort D.; Webber, Michael E.; Allen, David T.
2011-10-01
The possibility of using electricity dispatching strategies to achieve a 50% nitrogen oxide (NOx) emission reduction from electricity generating units was examined using the grid of the Electricity Reliability Council of Texas as a case study. Simulations of a hypothetical policy demonstrate that imposing higher NOx prices induces a switch from some coal-fired generation to natural gas generation, lowering NOx emissions. The simulation is for a day with relatively high electricity demand and accounts for transmission constraints. In addition to the lowering of the NOx emissions, there are co-benefits of the redispatching of generation from coal to natural gas, including reductions in the emissions of sulfur oxides (24%-71%), Hg (16%-82%) and CO2 (8.8%-22%). Water consumption was also decreased, by 4.4%-8.7%. Substantial reductions of NOx emissions can be achieved for an increased generation cost of 4-13%, which is due to the higher fuel price of gas relative to coal (assuming a price of 3.87 per MMBTU (MMBTU: million British thermal units) for natural gas, and 1.89 per MMBTU for coal). However, once the system has reduced NOx emissions by approximately 50%, there is little incremental reduction in emissions due to further increases in NOx prices.
Optimal configuration of power grid sources based on optimal particle swarm algorithm
Wen, Yuanhua
2018-04-01
In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.
Genetic Algorithm Based Economic Dispatch with Valve Point Effect
Energy Technology Data Exchange (ETDEWEB)
Park, Jong Nam; Park, Kyung Won; Kim, Ji Hong; Kim, Jin O [Hanyang University (Korea, Republic of)
1999-03-01
This paper presents a new approach on genetic algorithm to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through improved death penalty method, generation-apart elitism, atavism and sexual selection with sexual distinction. Numerical results on a test system consisting of 13 thermal units show that the proposed approach is faster, more robust and powerful than conventional genetic algorithms. (author). 8 refs., 10 figs.
A qualitative approach to economic-environmental dispatch
International Nuclear Information System (INIS)
Gjengedal, T.; Hansen, O.; Johansen, S.
1992-01-01
This paper describes the principles, and suggests a methodology for expanding the dispatch of electrical power production systems for involving a pure minimum cost dispatch, to also include environmental objectives. The approach is qualitative in that no attempt is made as to assign a specific monetary value to environmental impacts, but rather maintaining the physical value of the impact through the decision process. However, the initial relative weights assigned to environmental impacts in the methodology are based on the many recent attempts to monetize environmental damages. The main contribution of the approach is to analyze how dispatch changes as a function of the total environmental weight, and as a function of the relative weighing of individual environmental insults, e.g., SO 2 , NO x and CO 2 . The methodology is illustrated with a sample production system involving environmental coast estimates from major US studies
Economic Dispatch of Demand Response Balancing through Asymmetric Block Offers
DEFF Research Database (Denmark)
O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik
2015-01-01
This paper proposes a method of describing the load shifting ability of flexible electrical loads in a manner suitable for existing power system dispatch frameworks. The concept of an asymmetric block offer for flexible loads is introduced. This offer structure describes the ability of a flexible...
Optimal offering strategy for a concentrating solar power plant
International Nuclear Information System (INIS)
Dominguez, R.; Baringo, L.; Conejo, A.J.
2012-01-01
Highlights: ► Concentrating solar power (CSP) plants are becoming economically viable. ► CSP production is positively correlated with the demand. ► CSP plants can be made dispatchable by using molten salt storage facilities. ► Integrating CSP plants in a market constitutes a relevant challenge. -- Abstract: This paper provides a methodology to build offering curves for a concentrating solar power plant. This methodology takes into account the uncertainty in the thermal production from the solar field and the volatility of market prices. The solar plant owner is a price-taker producer that participates in a pool-based electricity market with the aim of maximizing its expected profit. To enhance the value of the concentrating solar power plant, a molten salt heat storage is considered, which allows producing electricity during periods without availability of the solar resource. To derive offering curves, a mixed-integer linear programming model is proposed, which is robust from the point of view of the uncertainty associated with the thermal production of the solar field and stochastic from the point of view of the uncertain market prices.
Static economic dispatch incorporating wind farm using Flower pollination algorithm
Directory of Open Access Journals (Sweden)
Suresh Velamuri
2016-09-01
Full Text Available Renewable energy is one of the clean and cheapest forms of energy which helps in minimizing the carbon foot print. Due to the less environmental impact and economic issues integration of renewable energy sources with the existing network gained attention. In this paper, the impact of wind energy is analysed in a power system network using static economic dispatch (SED. The wind energy is integrated with the existing thermal systems. Here, the generation scheduling is optimized using Flower pollination algorithm (FPA due to its robustness in solving nonlinear problems. Integration of wind power in the existing system increases the complexity due to its stochastic nature. Weibull distribution function is used for solving the stochastic nature of wind. Scenarios without and with wind power penetration are discussed in detail. The analysis is carried out by considering the losses and installing the wind farm at different locations in the system. The proposed methodology is tested and validated on a standard IEEE 30 bus system.
Optimal integration of linear Fresnel reflector with gas turbine cogeneration power plant
International Nuclear Information System (INIS)
Dabwan, Yousef N.; Mokheimer, Esmail M.A.
2017-01-01
Highlights: • A LFR integrated solar gas turbine cogeneration plant (ISGCPP) has been simulated. • The optimally integrated LFR with gas turbine cogeneration plant can achieve an annual solar share of 23%. • Optimal integration of LFR with gas turbine cogeneration system can reduce CO 2 emission by 18%. • Compared to a fully-solar-powered LFR plant, the optimal ISGCPP reduces the LEC by 83%. • ISGCPP reduces the LEC by 50% compared to plants integrated with carbon capture technology. - Abstract: Solar energy is an abundant resource in many countries in the Sunbelt, especially in the middle east, countries, where recent expansion in the utilization of natural gas for electricity generation has created a significant base for introducing integrated solar‐natural gas power plants (ISGPP) as an optimal solution for electricity generation in these countries. ISGPP reduces the need for thermal energy storage in traditional concentrated solar thermal plants and results in dispatchable power on demand at lower cost than stand-alone concentrated thermal power and much cheaper than photovoltaic plants. Moreover, integrating concentrated solar power (CSP) with conventional fossil fuel based thermal power plants is quite suitable for large-scale central electric power generation plants and it can be implemented in the design of new installed plants or during retrofitting of existing plants. The main objective of the present work is to investigate the possible modifications of an existing gas turbine cogeneration plant, which has a gas turbine of 150 MWe electricity generation capacity and produces steam at a rate of 81.4 at 394 °C and 45.88 bars for an industrial process, via integrating it with concentrated solar power system. In this regard, many simulations have been carried out using Thermoflow software to explore the thermo-economic performance of the gas turbine cogeneration plant integrated with LFR concentrated solar power field. Different electricity
optimal location of distributed generation on the nigerian power ...
African Journals Online (AJOL)
user
optimal sizing and placement of DG in the Nigerian power network for active power loss minimization. The ..... costs, resulting to low or over voltage in the network contrary to the desired ... Through Capabilities of a Wind Farm” Paper ID 99,.
An Improved Differential Evolution Based Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function
Directory of Open Access Journals (Sweden)
R. Balamurugan
2007-09-01
Full Text Available Dynamic economic dispatch (DED is one of the major operational decisions in electric power systems. DED problem is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. This paper presents an improved differential evolution (IDE method to solve the DED problem of generating units considering valve-point effects. Heuristic crossover technique and gene swap operator are introduced in the proposed approach to improve the convergence characteristic of the differential evolution (DE algorithm. To illustrate the effectiveness of the proposed approach, two test systems consisting of five and ten generating units have been considered. The results obtained through the proposed method are compared with those reported in the literature.
Directory of Open Access Journals (Sweden)
Xiaohong Duan
2018-01-01
Full Text Available The traditional method for solving the dynamic emergency vehicle dispatching problem can only get a local optimal strategy in each horizon. In order to obtain the dispatching strategy that can better respond to changes in road conditions during the whole dispatching process, the real-time and time-dependent link travel speeds are fused, and a time-dependent polygonal-shaped link travel speed function is set up to simulate the predictable changes in road conditions. Response times, accident severity, and accident time windows are taken as key factors to build an emergency vehicle dispatching model integrating dynamic emergency vehicle routing and selection. For the unpredictable changes in road conditions caused by accidents, the dispatching strategy is adjusted based on the real-time link travel speed. In order to solve the dynamic emergency vehicle dispatching model, an improved shuffled frog leaping algorithm (ISFLA is proposed. The global search of the improved algorithm uses the probability model of estimation of distribution algorithm to avoid the partial optimal solution. Based on the Beijing expressway network, the efficacy of the model and the improved algorithm were tested from three aspects. The results have shown the following: (1 Compared with SFLA, the optimization performance of ISFLA is getting better and better with the increase of the number of decision variables. When the possible emergency vehicle selection strategies are 815, the objective function value of optimal selection strategies obtained by the base algorithm is 210.10% larger than that of ISFLA. (2 The prediction error of the travel speed affects the accuracy of the initial emergency vehicle dispatching. The prediction error of ±10 can basically meet the requirements of the initial dispatching. (3 The adjustment of emergency vehicle dispatching strategy can successfully bypassed road sections affected by accidents and shorten the response time.
Optimal power flow based on glow worm-swarm optimization for three-phase islanded microgrids
DEFF Research Database (Denmark)
Quang, Ninh Nguyen; Sanseverino, Eleonora Riva; Di Silvestre, Maria Luisa
2014-01-01
This paper presents an application of the Glowworm Swarm Optimization method (GSO) to solve the optimal power flow problem in three-phase islanded microgrids equipped with power electronics dc-ac inverter interfaced distributed generation units. In this system, the power injected by the distribut...
Robot dispatching Scenario for Accident Condition Monitoring of NPP
International Nuclear Information System (INIS)
Kim, Jongseog
2013-01-01
In March of 2011, unanticipated big size of tsunami attacks Fukushima NPP, this accident results in explosion of containment building. Tokyo electric power of Japan couldn't dispatch a robot for monitoring of containment inside. USA Packbot robot used for desert war in Iraq was supplied to Fukushima NPP for monitoring of high radiation area. Packbot also couldn't reach deep inside of Fukushima NPP due to short length of power cable. Japanese robot 'Queens' also failed to complete a mission due to communication problem between robot and operator. I think major reason of these robot failures is absence of robot dispatching scenario. If there was a scenario and a rehearsal for monitoring during or after accident, these unanticipated obstacles could be overcome. Robot dispatching scenario studied for accident of nuclear power plant was described herein. Study on scenario of robot dispatching is performed. Flying robot is regarded as good choice for accident monitoring. Walking robot with arm equipped is good for emergency valve close. Short time work and shift work by several robots can be a solution for high radiation area. Thin and soft cable with rolling reel can be a good solution for long time work and good communication
International Nuclear Information System (INIS)
Sood, Yog Raj; Singh, Randhir
2010-01-01
In the competitive electricity market it becomes very much important to give special consideration for development of renewable energy sources (RESs) due to environmental and other social problems related with conventional generations. So this paper presents an optimal model of congestion management with special emphasis for promotion of RES in competitive electricity market. This paper presents a generalized optimal model of congestion management for deregulated power sector that dispatches the pool in combination with privately negotiated bilateral and multilateral contracts while maximizing social benefit. This model determines the locational marginal pricing (LMP) based on marginal cost theory. It also determines the size of non-firm transactions as well as pool demand and generations. Both firms as well as non-firm transactions are considered in this model. The proposed model has been applied to IEEE-30 bus test system with addition of some RES for analysis of the proposed model. The RES supplies its power to load either through the firm transaction or through power pool. The power from RES is not subjected to any curtailment in proposed model of congestion management. (author)
Dispatches - electricity and cancer
International Nuclear Information System (INIS)
Snyder, P.
1996-01-01
This Channel 4 Television booklet on 'Electricity and Cancer' provides the content of such a programme broadcast in 1996. This programme explored the possible links between electric power lines, radon in our homes and childhood cancer. This link is based on research showing that electromagnetic fields such as those surrounding power lines increase the concentration of radon decay products in the immediate vicinity. Because radon is known to cause cancer, this may be a key part of the puzzle of why there is a higher incidence of cancers near power lines. (UK)
DEFF Research Database (Denmark)
Vlachogiannis, Ioannis (John); Lee, K. Y.
2010-01-01
a memory of its best position ever encountered, and is attracted only by other particles with better achievements than its own with the exception of the particle with the best achievement, which moves randomly.The ICA-PSO algorithm is tested on a number of power systems, including the systems with 6, 13...
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos; Mariani, Viviana Cocco
2009-01-01
The economic dispatch problem (EDP) is an optimization problem useful in power systems operation. The objective of the EDP of electric power generation, whose characteristics are complex and highly non-linear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying system constraints. Recently, as an alternative to the conventional mathematical approaches, modern heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. As special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used as optimization technique in EDPs. Based on the chaos theory, this paper discusses the design and validation of an optimization procedure based on a chaotic artificial immune network approach based on Zaslavsky's map. The optimization approach based on chaotic artificial immune network is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results and comparisons show that the chaotic artificial immune network approach is competitive in performance with other optimization approaches presented in literature and is also an attractive tool to be used on applications in the power systems field.
Joint optimization of regional water-power systems
DEFF Research Database (Denmark)
Cardenal, Silvio Javier Pereira; Mo, Birger; Gjelsvik, Anders
2016-01-01
using stochastic dual dynamic programming. The results showed that current water allocation to hydropower producers in basins with high irrigation productivity, and to irrigation users in basins with high hydropower productivity was sub-optimal. Optimal allocation was achieved by managing reservoirs...... for joint optimization of water and electric power systems was developed in order to identify methodologies to assess the broader interactions between water and energy systems. The proposed method is to include water users and power producers into an economic optimization problem that minimizes the cost...... of power production and maximizes the benefits of water allocation, subject to constraints from the power and hydrological systems. The method was tested on the Iberian Peninsula using simplified models of the seven major river basins and the power market. The optimization problem was successfully solved...
A solution to the optimal power flow using multi-verse optimizer
Directory of Open Access Journals (Sweden)
Bachir Bentouati
2016-12-01
Full Text Available In this work, the most common problem of the modern power system named optimal power flow (OPF is optimized using the novel meta-heuristic optimization Multi-verse Optimizer(MVO algorithm. In order to solve the optimal power flow problem, the IEEE 30-bus and IEEE 57-bus systems are used. MVO is applied to solve the proposed problem. The problems considered in the OPF problem are fuel cost reduction, voltage profile improvement, voltage stability enhancement. The obtained results are compared with recently published meta-heuristics. Simulation results clearly reveal the effectiveness and the rapidity of the proposed algorithm for solving the OPF problem.
Optimization Criteria of Power Transformer Operation
Directory of Open Access Journals (Sweden)
A. A. Gonchar
2006-01-01
Full Text Available It has been shown that minimum losses in active power of a power transformer do not correspond to its maximum efficiency. For a transformer being operated there are no so called «zones of its economical operation». In this case strictly specified value of active power losses corresponds to a particular current of the winding.
Optimal power flow by particle swarm optimization with an aging ...
African Journals Online (AJOL)
DR OKE
2002), evolutionary programming (EP) (Somasundaram et al. ... concepts, a modified PSO called as PSO with aging leader and challenges (ALC-PSO) is ... system is adopted as standard power network whose OPF problem is solved with the ...
Optimization of the triple-pressure combined cycle power plant
Directory of Open Access Journals (Sweden)
Alus Muammer
2012-01-01
Full Text Available The aim of this work was to develop a new system for optimization of parameters for combined cycle power plants (CCGTs with triple-pressure heat recovery steam generator (HRSG. Thermodynamic and thermoeconomic optimizations were carried out. The objective of the thermodynamic optimization is to enhance the efficiency of the CCGTs and to maximize the power production in the steam cycle (steam turbine gross power. Improvement of the efficiency of the CCGT plants is achieved through optimization of the operating parameters: temperature difference between the gas and steam (pinch point P.P. and the steam pressure in the HRSG. The objective of the thermoeconomic optimization is to minimize the production costs per unit of the generated electricity. Defining the optimal P.P. was the first step in the optimization procedure. Then, through the developed optimization process, other optimal operating parameters (steam pressure and condenser pressure were identified. The developed system was demonstrated for the case of a 282 MW CCGT power plant with a typical design for commercial combined cycle power plants. The optimized combined cycle was compared with the regular CCGT plant.
Techno-economic design optimization of solar thermal power plants
Morin, G.
2011-01-01
A holistic view is essential in the engineering of technical systems. This thesis presents an integrative approach for designing solar thermal power plants. The methodology is based on a techno-economic plant model and a powerful optimization algorithm. Typically, contemporary design methods treat technical and economic parameters and sub-systems separately, making it difficult or even impossible to realize the full optimization potential of power plant systems. The approach presented here ov...
Optimal Power Flow by Interior Point and Non Interior Point Modern Optimization Algorithms
Directory of Open Access Journals (Sweden)
Marcin Połomski
2013-03-01
Full Text Available The idea of optimal power flow (OPF is to determine the optimal settings for control variables while respecting various constraints, and in general it is related to power system operational and planning optimization problems. A vast number of optimization methods have been applied to solve the OPF problem, but their performance is highly dependent on the size of a power system being optimized. The development of the OPF recently has tracked significant progress both in numerical optimization techniques and computer techniques application. In recent years, application of interior point methods to solve OPF problem has been paid great attention. This is due to the fact that IP methods are among the fastest algorithms, well suited to solve large-scale nonlinear optimization problems. This paper presents the primal-dual interior point method based optimal power flow algorithm and new variant of the non interior point method algorithm with application to optimal power flow problem. Described algorithms were implemented in custom software. The experiments show the usefulness of computational software and implemented algorithms for solving the optimal power flow problem, including the system model sizes comparable to the size of the National Power System.
Parameters optimization for magnetic resonance coupling wireless power transmission.
Li, Changsheng; Zhang, He; Jiang, Xiaohua
2014-01-01
Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.
Optimization design for drain to nuclear power condenser
International Nuclear Information System (INIS)
Ding Jiapeng; Jiang Chengren
2010-01-01
Characters and varieties of drain to nuclear power condenser are discussed in this paper. Take the main steam system of a nuclear power as an example, normal and detailed optimization design are introduced, related expatiate are used as a reference for the drain of other systems. According to the characters of nuclear power instant operation, the influence and needed actions related with the optimization design are also analyzed. Based on the above research, the scheme has been carried out in a nuclear power station and safety for the condenser operation of the nuclear power has been improved largely. (authors)
International Nuclear Information System (INIS)
MacCormack, John; Hollis, Aidan; Zareipour, Hamidreza; Rosehart, William
2010-01-01
This work examines the effects of large-scale integration of wind powered electricity generation in a deregulated energy-only market on loads (in terms of electricity prices and supply reliability) and dispatchable conventional power suppliers. Hourly models of wind generation time series, load and resultant residual demand are created. From these a non-chronological residual demand duration curve is developed that is combined with a probabilistic model of dispatchable conventional generator availability, a model of an energy-only market with a price cap, and a model of generator costs and dispatch behavior. A number of simulations are performed to evaluate the effect on electricity prices, overall reliability of supply, the ability of a dominant supplier acting strategically to profitably withhold supplies, and the fixed cost recovery of dispatchable conventional power suppliers at different levels of wind generation penetration. Medium and long term responses of the market and/or regulator in the long term are discussed.
A decoupled power flow algorithm using particle swarm optimization technique
International Nuclear Information System (INIS)
Acharjee, P.; Goswami, S.K.
2009-01-01
A robust, nondivergent power flow method has been developed using the particle swarm optimization (PSO) technique. The decoupling properties between the power system quantities have been exploited in developing the power flow algorithm. The speed of the power flow algorithm has been improved using a simple perturbation technique. The basic power flow algorithm and the improvement scheme have been designed to retain the simplicity of the evolutionary approach. The power flow is rugged, can determine the critical loading conditions and also can handle the flexible alternating current transmission system (FACTS) devices efficiently. Test results on standard test systems show that the proposed method can find the solution when the standard power flows fail.
A thermal storage capacity market for non dispatchable renewable energies
Bennouna, El Ghali; Mouaky, Ammar; Arrad, Mouad; Ghennioui, Abdellatif; Mimet, Abdelaziz
2017-06-01
Due to the increasingly high capacity of wind power and solar PV in Germany and some other European countries and the high share of variable renewable energy resources in comparison to fossil and nuclear capacity, a power reserve market structured by auction systems was created to facilitate the exchange of balance power capacities between systems and even grid operators. Morocco has a large potential for both wind and solar energy and is engaged in a program to deploy 2000MW of wind capacity by 2020 and 3000 MW of solar capacity by 2030. Although the competitiveness of wind energy is very strong, it appears clearly that the wind program could be even more ambitious than what it is, especially when compared to the large exploitable potential. On the other hand, heavy investments on concentrated solar power plants equipped with thermal energy storage have triggered a few years ago including the launching of the first part of the Nour Ouarzazate complex, the goal being to reach stable, dispatchable and affordable electricity especially during evening peak hours. This paper aims to demonstrate the potential of shared thermal storage capacity between dispatchable and non dispatchable renewable energies and particularly CSP and wind power. Thus highlighting the importance of a storage capacity market in parallel to the power reserve market and the and how it could enhance the development of both wind and CSP market penetration.
Multi-objective optimal power flow with FACTS devices
International Nuclear Information System (INIS)
Basu, M.
2011-01-01
This paper presents multi-objective differential evolution to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem is formulated as a multi-objective optimization problem. FACTS devices considered include thyristor controlled series capacitor (TCSC) and thyristor controlled phase shifter (TCPS). The proposed approach has been examined and tested on the modified IEEE 30-bus and 57-bus test systems. The results obtained from the proposed approach have been compared with those obtained from nondominated sorting genetic algorithm-II, strength pareto evolutionary algorithm 2 and pareto differential evolution.
Implementation of Electricity Business Competition Framework with Economic Dispatch Direct Method
Directory of Open Access Journals (Sweden)
Yusra Sabri
2012-12-01
Full Text Available Technically, electricity business under competition structure is more complex than that of vertically integrated one. The main prolems here are how to create an applicable competition framework and to solve electric calculations very quickly to obtain an optimal energi pricing, cost of losses, congestion and transportation costs by less than 15 minutes. This paper proposes a competition framework with the electric calculations, where a bilateral contract has been accommodated. Optimal energy price in the paper is calculated based on direct method of economic dispatch to obtain the result very quickly. The proposed method has been simulated to a 4-bus system. The simulation results show that the method works well and complies with the expectation. Therefore, electric power business under competition structure can be well realized by the proposed method.
International Nuclear Information System (INIS)
Pothiya, Saravuth; Ngamroo, Issarachai; Kongprawechnon, Waree
2008-01-01
This paper presents a new optimization technique based on a multiple tabu search algorithm (MTS) to solve the dynamic economic dispatch (ED) problem with generator constraints. In the constrained dynamic ED problem, the load demand and spinning reserve capacity as well as some practical operation constraints of generators, such as ramp rate limits and prohibited operating zone are taken into consideration. The MTS algorithm introduces additional mechanisms such as initialization, adaptive searches, multiple searches, crossover and restarting process. To show its efficiency, the MTS algorithm is applied to solve constrained dynamic ED problems of power systems with 6 and 15 units. The results obtained from the MTS algorithm are compared to those achieved from the conventional approaches, such as simulated annealing (SA), genetic algorithm (GA), tabu search (TS) algorithm and particle swarm optimization (PSO). The experimental results show that the proposed MTS algorithm approaches is able to obtain higher quality solutions efficiently and with less computational time than the conventional approaches
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies...... the generated power by changing the power reference of the individual wind turbines. We use the optimization setup to compare power production of the wind farm models. This paper shows that for the most frequent wind velocities (below and around the rated values), the generated powers of the wind farms...
Optimized PWR power ascension reload testing
International Nuclear Information System (INIS)
Emery, S.P.; Long, S.W.; Nazareth, V.F.; Herschthal, M.A.
1987-01-01
Reduction in critical path testing time following refueling is actively supported by utilities to increase plant capacity factor and to minimize replacement power costs. Combustion Engineering (C-E) has developed a fast power ascension program (FPAP), which reduces this critical path testing by minimizing holds at intermediate power levels and by automating data acquisition and analysis. A very successful demonstration of the FPAP was performed recently during the cycle 3 startup of Southern California Edison's San Onofre Unit 2 reactor, which resulted in a critical path time savings of ∼ 3 days
Very short-term spatio-temporal wind power prediction using a censored Gaussian field
DEFF Research Database (Denmark)
Baxevani, Anastassia; Lenzi, Amanda
2018-01-01
Wind power is a renewable energy resource, that has relatively cheap installation costs and it is highly possible that will become the main energy resource in the near future. Wind power needs to be integrated efficiently into electricity grids, and to optimize the power dispatch, techniques...
An Optimal Power Flow (OPF) Method with Improved Power System Stability
DEFF Research Database (Denmark)
Su, Chi; Chen, Zhe
2010-01-01
This paper proposes an optimal power flow (OPF) method taking into account small signal stability as additional constraints. Particle swarm optimization (PSO) algorithm is adopted to realize the OPF process. The method is programmed in MATLAB and implemented to a nine-bus test power system which...... has large-scale wind power integration. The results show the ability of the proposed method to find optimal (or near-optimal) operating points in different cases. Based on these results, the analysis of the impacts of wind power integration on the system small signal stability has been conducted....
High performance magnet power supply optimization
International Nuclear Information System (INIS)
Jackson, L.T.
1975-01-01
Three types of magnet power supply systems for the joint LBL-SLAC proposed accelerator PEP are discussed. The systems considered include a firing circuit and six-pulse controlled rectifier, transistor systems, and a chopper system. (U.S.)
Optimal electricity market for wind power
International Nuclear Information System (INIS)
Holttinen, H.
2005-01-01
This paper is about electricity market operation when looking from the wind power producers' point of view. The focus in on market time horizons: how many hours there is between the closing and delivering the bids. The case is for the Nordic countries, the Nordpool electricity market and the Danish wind power production. Real data from year 2001 was used to study the benefits of a more flexible market to wind power producer. As a result of reduced regulating market costs from better hourly predictions to the market, wind power producer would gain up to 8% more if the time between market bids and delivery was shortened from the day ahead Elspot market (hourly bids by noon for 12-36 h ahead). An after sales market where surplus or deficit production could be traded 2 h before delivery could benefit the producer almost as much, gaining 7%
OPF-Based Optimal Location of Two Systems Two Terminal HVDC to Power System Optimal Operation
Directory of Open Access Journals (Sweden)
Mehdi Abolfazli
2013-04-01
Full Text Available In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC-based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore, two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.
Optimal Output of Distributed Generation Based On Complex Power Increment
Wu, D.; Bao, H.
2017-12-01
In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.
Optimal prediction intervals of wind power generation
DEFF Research Database (Denmark)
Wan, Can; Wu, Zhao; Pinson, Pierre
2014-01-01
direct optimization of both the coverage probability and sharpness to ensure the quality. The proposed method does not involve the statistical inference or distribution assumption of forecasting errors needed in most existing methods. Case studies using real wind farm data from Australia have been...
Modeling and optimization of an electric power distribution network ...
African Journals Online (AJOL)
Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems
Directory of Open Access Journals (Sweden)
R Subramanian
2013-12-01
Full Text Available The Economic Load Dispatch (ELD problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA, for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to limits on generator true power output and transmission losses. The MFA is a stochastic, Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of MFA to ELD for six generator test case system. MFA is applied to ELD problem and compared its solution quality and computation efficiency to Genetic algorithm (GA, Differential Evolution (DE, Particle swarm optimization (PSO, Artificial Bee Colony optimization (ABC, Biogeography-Based Optimization (BBO, Bacterial Foraging optimization (BFO, Firefly Algorithm (FA techniques. The simulation result shows that the proposed algorithm outperforms previous optimization methods.
Optimization of the commissioning period of nuclear power plant
International Nuclear Information System (INIS)
Hou Ganglian; Li Chunyue
2014-01-01
Due to current equipment manufacture capacity, construction experience and other factors, commissioning of nuclear power projects was used to be postponed, which could lead to delay of the whole project. Based on the actual situation, optimization of commissioning period and its logic could be an effective way to improve this situation to some extent. Based on previous practice and experience in the schedule management for the commissioning nuclear power projects, this paper analyzes and discusses the characteristics of make commissioning plan and the difficulties of program implementation and strategies of commissioning plan optimization, discusses and presents ways of dynamic plan adjustment and optimization at the vision of entire project, synthesizes the methods of time management through commissioning itself, interface and management, expounds measures for the timing and optimization of commissioning schedule and commissioning period, and sums up the ways of optimization of commissioning period, improving management capabilities and control of optimization principles. (authors)
Directory of Open Access Journals (Sweden)
Susanta Dutta
2018-05-01
Full Text Available This paper presents an efficient quasi-oppositional chemical reaction optimization (QOCRO technique to find the feasible optimal solution of the multi objective optimal reactive power dispatch (RPD problem with flexible AC transmission system (FACTS device. The quasi-oppositional based learning (QOBL is incorporated in conventional chemical reaction optimization (CRO, to improve the solution quality and the convergence speed. To check the superiority of the proposed method, it is applied on IEEE 14-bus and 30-bus systems and the simulation results of the proposed approach are compared to those reported in the literature. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms. Keywords: Quasi-oppositional chemical reaction optimization (QOCRO, Reactive power dispatch (RPD, TCSC, SVC, Multi-objective optimization
Numerical optimization for separation power of gas centrifuge
International Nuclear Information System (INIS)
Jiang Dongjun; Zeng Shi; Liu Bing
2012-01-01
In order to obtain higher separation power of the gas centrifuge, the code was developed to solve the flow-field of the counter-current to acquire the separation power, which was integrated with the iSight software, so a numerical optimization model for separation power was presented, in which the driver conditions and the geometry parameters of the waste baffle were optimized to get the maximum separation power using the sequential quadratic programming arithmetic, and the 12% higher results was acquired, which shows the feasibility of this method. The results also note that the separation power of gas centrifuge is sensitive to the driver conditions and the structure parameters of the waste baffle, so it is necessary to perform the optimization calculation for the certain gas centrifuge model. (authors)
Optimization of the Energy Output of Osmotic Power Plants
Directory of Open Access Journals (Sweden)
Florian Dinger
2013-01-01
Full Text Available On the way to a completely renewable energy supply, additional alternatives to hydroelectric, wind, and solar power have to be investigated. Osmotic power is such an alternative with a theoretical global annual potential of up to 14400 TWh (70% of the global electricity consumption of 2008 per year. It utilizes the phenomenon that upon the mixing of fresh water and oceanic salt water (e.g., at a river mouth, around 2.88 MJ of energy per 1 m3 of fresh water is released. Here, we describe a new approach to derive operational parameter settings for osmotic power plants using a pressure exchanger for optimal performance, either with respect to maximum generated power or maximum extracted energy. Up to now, only power optimization is discussed in the literature, but when considering the fresh water supply as a limiting factor, the energy optimization appears as the challenging task.
Evolutionary Computing for Intelligent Power System Optimization and Control
DEFF Research Database (Denmark)
This new book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization the...... theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems....
Optimal Selective Harmonic Control for Power Harmonics Mitigation
DEFF Research Database (Denmark)
Zhou, Keliang; Yang, Yongheng; Blaabjerg, Frede
2015-01-01
of power harmonics. The proposed optimal SHC is of hybrid structure: all recursive SHC modules with weighted gains are connected in parallel. It bridges the real “nk+-m order RC” and the complex “parallel structure RC”. Compared to other IMP based control solutions, it offers an optimal trade-off among...
Maintenance optimization in nuclear power plants through genetic algorithms
International Nuclear Information System (INIS)
Munoz, A.; Martorell, S.; Serradell, V.
1999-01-01
Establishing suitable scheduled maintenance tasks leads to optimizing the reliability of nuclear power plant safety systems. The articles addresses this subject, whilst endeavoring to tackle an overall optimization process for component availability and safety systems through the use of genetic algorithms. (Author) 20 refs
Stochastic Robust Mathematical Programming Model for Power System Optimization
Energy Technology Data Exchange (ETDEWEB)
Liu, Cong; Changhyeok, Lee; Haoyong, Chen; Mehrotra, Sanjay
2016-01-01
This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.
Optimal sizing method for stand-alone photovoltaic power systems
Energy Technology Data Exchange (ETDEWEB)
Groumpos, P P; Papageorgiou, G
1987-01-01
The total life-cycle cost of stand-alone photovoltaic (SAPV) power systems is mathematically formulated. A new optimal sizing algorithm for the solar array and battery capacity is developed. The optimum value of a balancing parameter, M, for the optimal sizing of SAPV system components is derived. The proposed optimal sizing algorithm is used in an illustrative example, where a more economical life-cycle cost has bene obtained. The question of cost versus reliability is briefly discussed.
Optimal estimation and control in nuclear power plants
International Nuclear Information System (INIS)
Purviance, J.E.; Tylee, J.L.
1982-08-01
Optimal estimation and control theories offer the potential for more precise control and diagnosis of nuclear power plants. The important element of these theories is that a mathematical plant model is used in conjunction with the actual plant data to optimize some performance criteria. These criteria involve important plant variables and incorporate a sense of the desired plant performance. Several applications of optimal estimation and control to nuclear systems are discussed
Optimal control of wind power plants
Steinbuch, M.; Boer, de W.W.; Bosgra, O.H.; Peeters, S.A.W.M.; Ploeg, J.
1988-01-01
The control system design for a wind power plant is investigated. Both theoverall wind farm control and the individual wind turbine control effect thewind farm dynamic performance.For a wind turbine with a synchronous generator and rectifier/invertersystem a multivariable controller is designed.
The effect of work shift configurations on emergency medical dispatch center response.
Montassier, Emmanuel; Labady, Julien; Andre, Antoine; Potel, Gilles; Berthier, Frederic; Jenvrin, Joel; Penverne, Yann
2015-01-01
It has been proved that emergency medical dispatch centers (EMDC) save lives by promoting an appropriate allocation of emergency medical service resources. Indeed, optimal dispatcher call duration is pivotal to reduce the time gap between the time a call is placed and the delivery of medical care. However, little is known about the impact of work shift configurations (i.e., work shift duration and work shift rotation throughout the day) and dispatcher call duration. Thus, the objective of our study was to assess the effect of work shift configurations on dispatcher call duration. During a 1-year study period, we analyzed the dispatcher call durations for medical and trauma calls during the 4 different work shift rotations (day, morning, evening, and night) and during the 10-hour work shift of each dispatcher in the EMDC of Nantes. We extracted dispatcher call durations from our advanced telephone system, configured with CC Pulse + (Genesys, Alcatel Lucent), and collected them in a custom designed database (Excel, Microsoft). Afterward, we analyzed these data using linear mixed effects models. During the study period, our EMDC received 408,077 calls. Globally, the mean dispatcher call duration was 107 ± 45 seconds. Based on multivariate linear mixed effects models, the dispatcher call duration was affected by night work shift and work shift duration greater than 8 hours, increasing it by about 10 ± 1 seconds and 4 ± 1 seconds, respectively (both p work shift rotation and duration, with longer durations seen over night shifts and shifts over 8 hours. While these differences are small and may not have clinical significance, they may have implications for EMDC efficiency.
Energy Technology Data Exchange (ETDEWEB)
Langer, Uwe [EWE NETZ GmbH, Oldenburg (Germany)
2012-10-15
The increasing number of devices for the decentralized integration of gas from renewable energy sources presents new challenges in the dispatching of natural gas networks operators. In the future, beside the supply of biogas there also a supply of hydrogen and synthetic methane will exist. In addition to compliance with the technical regulations for the quality and accountability of these gases the focus is on the optimization of the processes.
Optimized control strategy for crowbarless solid state modular power supply
International Nuclear Information System (INIS)
Upadhyay, R.; Badapanda, M.K.; Tripathi, A.; Hannurkar, P.R.; Pithawa, C.K.
2009-01-01
Solid state modular power supply with series connected IGBT based power modules have been employed as high voltage bias power supply of klystron amplifier. Auxiliary compensation of full wave inverter bridge with ZVS/ZCS operations of all IGBTs over entire operating range is incorporated. An optimized control strategy has been adopted for this power supply needing no output filter, making this scheme crowbarless and is presented in this paper. DSP based fully digital control with same duty cycle for all power modules, have been incorporated for regulating this power supply along with adequate protection features. Input to this power supply is taken directly from 11 kV line and the input system is intentionally made 24 pulsed to reduce the input harmonics, improve the input power factor significantly, there by requiring no line filters. Various steps have been taken to increase the efficiency of major subsystems, so as to improve the overall efficiency of this power supply significantly. (author)
The Oak Ridge Competitive Electricity Dispatch (ORCED) Model Version 9
Energy Technology Data Exchange (ETDEWEB)
Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Baek, Young Sun [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2016-11-01
The Oak Ridge Competitive Electricity Dispatch (ORCED) model dispatches power plants in a region to meet the electricity demands for any single given year up to 2030. It uses publicly available sources of data describing electric power units such as the National Energy Modeling System and hourly demands from utility submittals to the Federal Energy Regulatory Commission that are projected to a future year. The model simulates a single region of the country for a given year, matching generation to demands and predefined net exports from the region, assuming no transmission constraints within the region. ORCED can calculate a number of key financial and operating parameters for generating units and regional market outputs including average and marginal prices, air emissions, and generation adequacy. By running the model with and without changes such as generation plants, fuel prices, emission costs, plug-in hybrid electric vehicles, distributed generation, or demand response, the marginal impact of these changes can be found.
Optimal contracts for wind power producers in electricity markets
Bitar, E.
2010-12-01
This paper is focused on optimal contracts for an independent wind power producer in conventional electricity markets. Starting with a simple model of the uncertainty in the production of power from a wind turbine farm and a model for the electric energy market, we derive analytical expressions for optimal contract size and corresponding expected optimal profit. We also address problems involving overproduction penalties, cost of reserves, and utility of additional sensor information. We obtain analytical expressions for marginal profits from investing in local generation and energy storage. ©2010 IEEE.
DEFF Research Database (Denmark)
Liu, Chengxi; Qin, Nan; Bak, Claus Leth
2015-01-01
This paper proposes a hybrid optimization method to optimally control the voltage and reactive power with minimum power loss in transmission grid. This approach is used for the Danish automatic voltage control (AVC) system which is typically a non-linear non-convex problem mixed with both...
Optimal contracts for wind power producers in electricity markets
Bitar, E.; Giani, A.; Rajagopal, R.; Varagnolo, D.; Khargonekar, P.; Poolla, K.; Varaiya, P.
2010-01-01
This paper is focused on optimal contracts for an independent wind power producer in conventional electricity markets. Starting with a simple model of the uncertainty in the production of power from a wind turbine farm and a model for the electric
Optimal configuration of an integrated power and transport system
DEFF Research Database (Denmark)
Juul, Nina; Meibom, Peter
2011-01-01
optimal investments in both power plants and vehicle technologies is presented in this article. The model includes the interactions between the power system and the transport system including the competition between flexibility measures such as hydrogen storage in combination with electrolysis, heat...... storage in combination with heat pumps and heat boilers, and plug-in electric vehicles....
Direct Fuel Injector Power Drive System Optimization
2014-04-01
solenoid coil to create magnetic field in the stator. Then, the stator pulls the pintle to open the injector nozzle . This pintle movement occurs when the...that typically deal with power strategies to the injector solenoid coil. Numerical simulation codes for diesel injection systems were developed by...Laboratory) for providing the JP-8 test fuel. REFERENCES 1. Digesu, P. and Laforgia D., “ Diesel electro- injector : A numerical simulation code”. Journal of
Dynamic Controllability and Dispatchability Relationships
Morris, Paul Henry
2014-01-01
An important issue for temporal planners is the ability to handle temporal uncertainty. Recent papers have addressed the question of how to tell whether a temporal network is Dynamically Controllable, i.e., whether the temporal requirements are feasible in the light of uncertain durations of some processes. We present a fast algorithm for Dynamic Controllability. We also note a correspondence between the reduction steps in the algorithm and the operations involved in converting the projections to dispatchable form. This has implications for the complexity for sparse networks.
Hansson, Linus; Guédez, Rafael; Larchet, Kevin; Laumert, Bjorn
2017-06-01
The dispatchability offered by thermal energy storage (TES) in concentrated solar power (CSP) and solar hybrid plants based on such technology presents the most important difference compared to power generation based only on photovoltaics (PV). This has also been one reason for recent hybridization efforts of the two technologies and the creation of Power Purchase Agreement (PPA) payment schemes based on offering higher payment multiples during daily hours of higher (peak or priority) demand. Recent studies involving plant-level thermal energy storage control strategies are however to a large extent based on pre-determined approaches, thereby not taking into account the actual dynamics of thermal energy storage system operation. In this study, the implementation of a dynamic dispatch strategy in the form of a TRNSYS controller for hybrid PV-CSP plants in the power-plant modelling tool DYESOPT is presented. In doing this it was attempted to gauge the benefits of incorporating a day-ahead approach to dispatch control compared to a fully pre-determined approach determining hourly dispatch only once prior to annual simulation. By implementing a dynamic strategy, it was found possible to enhance technical and economic performance for CSP-only plants designed for peaking operation and featuring low values of the solar multiple. This was achieved by enhancing dispatch control, primarily by taking storage levels at the beginning of every simulation day into account. The sequential prediction of the TES level could therefore be improved, notably for evaluated plants without integrated PV, for which the predicted storage levels deviated less than when PV was present in the design. While also featuring dispatch performance gains, optimal plant configurations for hybrid PV-CSP was found to present a trade-off in economic performance in the form of an increase in break-even electricity price when using the dynamic strategy which was offset to some extent by a reduction in
Optimal dispatching in a tandem queue
van Leeuwen, D.; Núñez Queija, R.
2017-01-01
We investigate a Markovian tandem queueing model in which service to the first queue is provided in batches. The main goal is to choose the batch sizes so as to minimize a linear cost function of the mean queue lengths. This model can be formulated as a Markov Decision Process (MDP) for which the
Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks
Cho, Hsun-Jung; Lin, Guey-Shii
2007-12-01
The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.
Joint optimization of regional water-power systems
Pereira-Cardenal, Silvio J.; Mo, Birger; Gjelsvik, Anders; Riegels, Niels D.; Arnbjerg-Nielsen, Karsten; Bauer-Gottwein, Peter
2016-06-01
Energy and water resources systems are tightly coupled; energy is needed to deliver water and water is needed to extract or produce energy. Growing pressure on these resources has raised concerns about their long-term management and highlights the need to develop integrated solutions. A method for joint optimization of water and electric power systems was developed in order to identify methodologies to assess the broader interactions between water and energy systems. The proposed method is to include water users and power producers into an economic optimization problem that minimizes the cost of power production and maximizes the benefits of water allocation, subject to constraints from the power and hydrological systems. The method was tested on the Iberian Peninsula using simplified models of the seven major river basins and the power market. The optimization problem was successfully solved using stochastic dual dynamic programming. The results showed that current water allocation to hydropower producers in basins with high irrigation productivity, and to irrigation users in basins with high hydropower productivity was sub-optimal. Optimal allocation was achieved by managing reservoirs in very distinct ways, according to the local inflow, storage capacity, hydropower productivity, and irrigation demand and productivity. This highlights the importance of appropriately representing the water users' spatial distribution and marginal benefits and costs when allocating water resources optimally. The method can handle further spatial disaggregation and can be extended to include other aspects of the water-energy nexus.
Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte
2010-01-01
This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...
A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System
Directory of Open Access Journals (Sweden)
Yanzhe Hu
2017-03-01
Full Text Available As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED model for the wind-thermal-energy storage system (WTESS is developed in this paper. An optimization model with the wind power and the energy storage system (ESS is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG. A Gaussian mixture model (GMM distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.
Optimal Power Flow in Microgrids with Energy Storage
DEFF Research Database (Denmark)
Levron, Yoash; Guerrero, Josep M.; Beck, Yuval
2013-01-01
Energy storage may improve power management in microgrids that include renewable energy sources. The storage devices match energy generation to consumption, facilitating a smooth and robust energy balance within the microgrid. This paper addresses the optimal control of the microgrid’s energy...... storage devices. Stored energy is controlled to balance power generation of renewable sources to optimize overall power consumption at the microgrid point of common coupling. Recent works emphasize constraints imposed by the storage device itself, such as limited capacity and internal losses. However...
Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm
Energy Technology Data Exchange (ETDEWEB)
Chung, Hyeng Hwan; Chung, Dong Il; Chung, Mun Kyu [Dong-AUniversity (Korea); Wang, Yong Peel [Canterbury Univeristy (New Zealand)
1999-06-01
In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer (PSS) with robustness in low frequency oscillation for power system using real variable elitism genetic algorithm (RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristics of PSS, the system eigenvalues criterion and the dynamic characteristics were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory. (author). 20 refs., 15 figs., 8 tabs.
Power Link Optimization for a Neurostimulator in Nasal Cavity
Directory of Open Access Journals (Sweden)
Seunghyun Lee
2017-01-01
Full Text Available This paper examines system optimization for wirelessly powering a small implant embedded in tissue. For a given small receiver in a multilayer tissue model, the transmitter is abstracted as a sheet of tangential current density for which the optimal distribution is analytically found. This proposes a new design methodology for wireless power transfer systems. That is, from the optimal current distribution, the maximum achievable efficiency is derived first. Next, various design parameters are determined to achieve the target efficiency. Based on this design methodology, a centimeter-sized neurostimulator inside the nasal cavity is demonstrated. For this centimeter-sized implant, the optimal distribution resembles that of a coil source and the optimal frequency is around 15 MHz. While the existing solution showed an efficiency of about 0.3 percent, the proposed system could enhance the efficiency fivefold.
UES: an optimization software package for power and energy
International Nuclear Information System (INIS)
Vohryzek, J.; Havlena, V.; Findejs, J.; Jech, J.
2004-01-01
Unified Energy Solutions components are designed to meet specific requirements of the electric utilities, industrial power units, and district heating (combined heat and power) plants. The optimization objective is to operate the plant with maximum process efficiency and operational profit under the constraints imposed by technology and environmental impacts. Software applications for advanced control real-time optimization may provide a low-cost, high return alternative to expensive boiler retrofits for improving operational profit as well as reducing emissions. Unified Energy Solutions (UES) software package is a portfolio of advanced control and optimization components running on top of the standard process regulatory and control system. The objective of the UES is to operate the plant with maximum achievable profit (maximum efficiency) under the constraints imposed by technology (life-time consumption, asset health) and environmental impacts (CO and NO x emissions). Fast responsiveness to varying economic conditions and integration of real-time optimization and operator decision support (off-line) features are critical for operation in real-time economy. Optimization Features are targeted to combustion process, heat and power load allocation to parallel resources, electric power delivery and ancillary services. Optimization Criteria include increased boiler thermal efficiency, maintaining emission limits, economic load allocation of the heat and generation sources. State-of-the-art advanced control algorithms use model based predictive control principles and provide superior response in transient states. Individual software modules support open control platforms and communication protocols. UES can be implemented on a wide range of distributed control systems. Typical achievable benefits include heat and power production costs savings, increased effective boiler operation range, optimized flue gas emissions, optimized production capacity utilization, optimized
Optimal power transaction matrix rescheduling under multilateral open access environment
International Nuclear Information System (INIS)
Moghaddam, M.P.; Raoofat, M.; Haghifam, M.R.
2004-01-01
This paper addresses a new concept for determining optimal transactions between different entities in a multilateral environment while benefits of both buyer and seller entities are taken into account with respect to the rules of the system. At the same time, constraints of the network are met, which leads to an optimal power flow problem. A modified power transaction matrix is proposed for modeling the environment. The optimization method in this paper is the continuation method, which is suited for complex situations of power system studies. This complexity will become more serious when dual interaction between financial and electrical subsystems of competitive power system are taken into account. The proposed approach is tested on a typical network with satisfactory results. (author)
Optimal energy management strategy for battery powered electric vehicles
International Nuclear Information System (INIS)
Xi, Jiaqi; Li, Mian; Xu, Min
2014-01-01
Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios
Olivares, Marcelo A.; Haas, Jannik; Palma-Behnke, Rodrigo; Benavides, Carlos
2015-05-01
Hydrologic alteration due to hydropeaking reservoir operations is a main concern worldwide. Subdaily environmental flow constraints (ECs) on operations can be promising alternatives for mitigating negative impacts. However, those constraints reduce the flexibility of hydropower plants, potentially with higher costs for the power system. To study the economic and environmental efficiency of ECs, this work proposes a novel framework comprising four steps: (i) assessment of the current subdaily hydrologic alteration; (ii) formulation and implementation of a short-term, grid-wide hydrothermal coordination model; (iii) design of ECs in the form of maximum ramping rates (MRRs) and minimum flows (MIFs) for selected hydropower reservoirs; and (iv) identification of Pareto-efficient solutions in terms of grid-wide costs and the Richard-Baker flashiness index for subdaily hydrologic alteration (SDHA). The framework was applied to Chile's main power grid, assessing 25 EC cases, involving five MIFs and five MRRs. Each case was run for a dry, normal, and wet water year type. Three Pareto-efficient ECs are found, with remarkably small cost increase below 2% and a SDHA improvement between 28% and 90%. While the case involving the highest MIF worsens the flashiness of another basin, the other two have no negative effect on other basins and can be recommended for implementation.
Directory of Open Access Journals (Sweden)
Leyzgold D.Yu.
2015-04-01
Full Text Available This article studies the problem of the transmission line conductor heating effect on the active power flows optimization in the local segment of industrial power supply. The purpose is to determine the optimal generation rating of the distributed power sources, in which the power flow values will correspond to the minimum active power losses in the power supply. The timeliness is the need to define the most appropriate rated power values of distributed sources which will be connected to current industrial power supply. Basing on the model of active power flow optimization, authors formulate the description of the nonlinear transportation problem considering the active power losses depending on the transmission line conductor heating. Authors proposed a new approach to the heating model parameters definition based on allowable current loads and nominal parameters of conductors as part of the optimization problem. Analysis of study results showed that, despite the relatively small active power losses reduction to the tune 0,45% due to accounting of the conductors heating effect for the present configuration of power supply, there are significant fluctuations in the required generation rating in nodes of the network to 9,32% within seasonal changes in the outer air temperature. This fact should be taken into account when selecting the optimum power of distributed generation systems, as exemplified by an arbitrary network configuration.
Directory of Open Access Journals (Sweden)
Luis Eduardo Gallego Vega
2010-05-01
Full Text Available This paper presents the results of research about the effect of transmission constraints on both expected electrical energy to be dispatched and power generation companies’ bidding strategies in the Colombian electrical power market. The proposed model simulates the national transmission grid and economic dispatch by means of optimal power flows. The proposed methodology allows structural problems in the power market to be analyzed due to the exclusive effect of trans- mission constraints and the mixed effect of bidding strategies and transmission networks. A new set of variables is proposed for quantifying the impact of each generation company on system operating costs and the change in expected dispatched energy. A correlation analysis of these new variables is presented, revealing some interesting linearities in some generation companies’ bidding patterns.
Dar, Zamiyad
The prices in the electricity market change every five minutes. The prices in peak demand hours can be four or five times more than the prices in normal off peak hours. Renewable energy such as wind power has zero marginal cost and a large percentage of wind energy in a power grid can reduce the price significantly. The variability of wind power prevents it from being constantly available in peak hours. The price differentials between off-peak and on-peak hours due to wind power variations provide an opportunity for a storage device owner to buy energy at a low price and sell it in high price hours. In a large and complex power grid, there are many locations for installation of a storage device. Storage device owners prefer to install their device at locations that allow them to maximize profit. Market participants do not possess much information about the system operator's dispatch, power grid, competing generators and transmission system. The publicly available data from the system operator usually consists of Locational Marginal Prices (LMP), load, reserve prices and regulation prices. In this thesis, we develop a method to find the optimum location of a storage device without using the grid, transmission or generator data. We formulate and solve an optimization problem to find the most profitable location for a storage device using only the publicly available market pricing data such as LMPs, and reserve prices. We consider constraints arising due to storage device operation limitations in our objective function. We use binary optimization and branch and bound method to optimize the operation of a storage device at a given location to earn maximum profit. We use two different versions of our method and optimize the profitability of a storage unit at each location in a 36 bus model of north eastern United States and south eastern Canada for four representative days representing four seasons in a year. Finally, we compare our results from the two versions of our
Optimization of passive low power wireless electromagnetic energy harvesters.
Nimo, Antwi; Grgić, Dario; Reindl, Leonhard M
2012-10-11
This work presents the optimization of antenna captured low power radio frequency (RF) to direct current (DC) power converters using Schottky diodes for powering remote wireless sensors. Linearized models using scattering parameters show that an antenna and a matched diode rectifier can be described as a form of coupled resonator with different individual resonator properties. The analytical models show that the maximum voltage gain of the coupled resonators is mainly related to the antenna, diode and load (remote sensor) resistances at matched conditions or resonance. The analytical models were verified with experimental results. Different passive wireless RF power harvesters offering high selectivity, broadband response and high voltage sensitivity are presented. Measured results show that with an optimal resistance of antenna and diode, it is possible to achieve high RF to DC voltage sensitivity of 0.5 V and efficiency of 20% at -30 dBm antenna input power. Additionally, a wireless harvester (rectenna) is built and tested for receiving range performance.
Optimizing the wireless power transfer over MIMO Channels
Wiedmann, Karsten; Weber, Tobias
2017-09-01
In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.
Optimizing the wireless power transfer over MIMO Channels
Directory of Open Access Journals (Sweden)
K. Wiedmann
2017-09-01
Full Text Available In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.
Energy Technology Data Exchange (ETDEWEB)
Hansen, A D; Bindner, H [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Rebsdorf, A [Vestas Wind Systems A/S, Lem (Denmark)
1999-03-01
The paper summarises and describes the main results of a recently performed study of improving the transition between power optimization and power limitation for variable speed/variable pitch wind turbines. The results show that the capability of varying the generator speed also can be exploited in the transition stage to improve the quality of the generated power. (au)
Energy Technology Data Exchange (ETDEWEB)
Pereira, Luiz Eduardo S.; Ribeiro, Paulo [Universidade Federal de Juiz de Fora (UFJF), MG (Brazil)], Emails: luizeduardo_jf@yahoo.com.br, pfribeiro@ieee.org; Tardin, Thiago V. [Engenho Pesquisa, Desenvolvimento e Consultoria Ltda., Rio de Janeiro, RJ (Brazil)], E-mail: thiago@engenho.com
2009-07-01
The positive and negative impacts of the electric energy generation from biomass of sugar in the Brazilian energy matrix are presented, as well as in the hydrothermal dispatch. Studies on the impacts of the generation sources using sugar cane bagasse in the operational planning and in the composition of the electric energy price are done. Computational implementations using optimized methods, as the stochastic dual dynamic programing, are done, to support the decision making and to compare the obtained results. It is, also presented the commercialization rules for energy in the Free Contracting Environment and in the Regulated Contracting Environment related to the alternative sources of energy, as well as the mechanisms of encouraged energy auction (reserve auction) and the rules for commercialization of energy applied to encouraged sources.
Energy Technology Data Exchange (ETDEWEB)
Fernandes, Jessica Pillon Torralba; Colnago, Glauber Renato; Correia, Paulo de Barros; Ohishi, Takaaki [Universidade Estadual de Campinas (UNICAMP), SP (Brazil). Fac. de Engenharia Mecanica. Dept. de Energia], emails: pillon@fem.unicamp.br, colnago@fem.unicamp.br, pcorreia@fem.unicamp.br, taka@densis.fee.unicamp.br
2010-07-01
This paper presents an optimization model for daily operation of Sao Francisco hydroelectric power plants. The study considers eight power plants - Sobradinho (USB), Luiz Gonzaga (ULG), Apolonio Sales (UAS), Paulo Afonso I, II, III, (UPA), Paulo Afonso IV (USQ) e Xingo (UXG)- belongs to Sao Francisco Hydroelectric Company (CHESF). Its objective is to maximize the power plant efficiency and to minimize the number of startup and shutdowns of generating units (GU), simultaneously. Considering those GU are equal, is determined the number of units to be dispatched and their charge. The optimal dispatch, linear and non-linear programming techniques and genetic algorithms (GA) support this article. (author)
International Nuclear Information System (INIS)
Bouchekara, H.R.E.H.; Abido, M.A.; Chaib, A.E.; Mehasni, R.
2014-01-01
Highlights: • Optimal power flow. • Reducing electrical energy loss. • Saving electrical energy. • Optimal operation. - Abstract: A new efficient optimization method, called the League Championship Algorithm (LCA) is proposed in this paper for solving the optimal power flow problem. This method is inspired by the competition of sport teams in an artificial sport league for several weeks and over a number of seasons. The proposed method has been applied to the Algerian power system network for different objectives. Furthermore, in order to assess the effectiveness of the proposed LCA method the obtained results using this method have been compared to those obtained using other methods reported in the literature. The obtained results and the comparison with other techniques indicate that the league championship algorithm provides effective and high-quality solution when solving the optimal power flow problem
Emission constrained secure economic dispatch
International Nuclear Information System (INIS)
Arya, L.D.; Choube, S.C.; Kothari, D.P.
1997-01-01
This paper describes a methodology for secure economic operation of power system accounting emission constraint areawise as well as in totality. Davidon-Fletcher-Powell's method of optimization has been used. Inequality constraints are accounted for by a penalty function. Sensitivity coefficients have been used to evaluate the gradient vector as well as for the calculation of incremental transmission loss (ITL). AC load flow results are required in the beginning only. The algorithm has been tested on IEEE 14- and 25-bus test systems. (Author)
Optimal Operation of Plug-In Electric Vehicles in Power Systems with High Wind Power Penetrations
DEFF Research Database (Denmark)
Hu, Weihao; Su, Chi; Chen, Zhe
2013-01-01
in the power systems with high wind power penetrations. In this paper, the integration of plug-in electric vehicles in the power systems with high wind power penetrations is proposed and discussed. Optimal operation strategies of PEV in the spot market are proposed in order to decrease the energy cost for PEV......The Danish power system has a large penetration of wind power. The wind fluctuation causes a high variation in the power generation, which must be balanced by other sources. The battery storage based Plug-In Electric Vehicles (PEV) may be a possible solution to balance the wind power variations...... owners. Furthermore, the application of battery storage based aggregated PEV is analyzed as a regulation services provider in the power system with high wind power penetrations. The western Danish power system where the total share of annual wind power production is more than 27% of the electrical energy...
International Nuclear Information System (INIS)
Secui, Dinu Calin
2015-01-01
This paper suggests a chaotic optimizing method, based on the GBABC (global best artificial bee colony algorithm), where the random sequences used in updating the solutions of this algorithm are replaced with chaotic sequences generated by chaotic maps. The new algorithm, called chaotic CGBABC (global best artificial bee colony algorithm), is used to solving the multi-area economic/emission dispatch problem taking into consideration the valve-point effects, the transmission line losses, multi-fuel sources, prohibited operating zones, tie line capacity and power transfer cost between different areas of the system. The behaviour of the CGBABC algorithm is studied considering ten chaotic maps both one-dimensional and bi-dimensional, with various probability density functions. The CGBABC algorithm's performance including a variety of chaotic maps is tested on five systems (6-unit, 10-unit, 16-unit, 40-unit and 120-unit) with different characteristics, constraints and sizes. The results comparison highlights a hierarchy in the chaotic maps included in the CGBABC algorithm and shows that it performs better than the classical ABC algorithm, the GBABC algorithm and other optimization techniques. - Highlights: • A chaotic global best ABC algorithm (CGBABC) is presented. • CGBABC is applied for solving the multi-area economic/emission dispatch problem. • Valve-point effects, multi-fuel sources, POZ, transmission losses were considered. • The algorithm is tested on five systems having 6, 10, 16, 40 and 120 thermal units. • CGBABC algorithm outperforms several optimization techniques.
Modified artificial bee colony algorithm for reactive power optimization
Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani
2015-05-01
Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.
Optimal Power Constrained Distributed Detection over a Noisy Multiaccess Channel
Directory of Open Access Journals (Sweden)
Zhiwen Hu
2015-01-01
Full Text Available The problem of optimal power constrained distributed detection over a noisy multiaccess channel (MAC is addressed. Under local power constraints, we define the transformation function for sensor to realize the mapping from local decision to transmitted waveform. The deflection coefficient maximization (DCM is used to optimize the performance of power constrained fusion system. Using optimality conditions, we derive the closed-form solution to the considered problem. Monte Carlo simulations are carried out to evaluate the performance of the proposed new method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system with low signal-to-noise ratio (SNR. We also show that the proposed new method has a robust detection performance for broad SNR region.
Dynamic ADMM for Real-time Optimal Power Flow: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-02-23
This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.
Optimal pole shifting controller for interconnected power system
International Nuclear Information System (INIS)
Yousef, Ali M.; Kassem, Ahmed M.
2011-01-01
Research highlights: → Mathematical model represents a power system which consists of synchronous machine connected to infinite bus through transmission line. → Power system stabilizer was designed based on optimal pole shifting controller. → The system performances was tested through load disturbances at different operating conditions. → The system performance with the proposed optimal pole shifting controller is compared with the conventional pole placement controller. → The digital simulation results indicated that the proposed controller has a superior performance. -- Abstract: Power system stabilizer based on optimal pole shifting is proposed. An approach for shifting the real parts of the open-loop poles to any desired positions while preserving the imaginary parts is presented. In each step of this approach, it is required to solve a first-order or a second-order linear matrix Lyapunov equation for shifting one real pole or two complex conjugate poles, respectively. This presented method yields a solution, which is optimal with respect to a quadratic performance index. The attractive feature of this method is that it enables solutions of the complex problem to be easily found without solving any non-linear algebraic Riccati equation. The present power system stabilizer is based on Riccati equation approach. The control law depends on finding the feedback gain matrix, and then the control signal is synthesized by multiplying the state variables of the power system with determined gain matrix. The gain matrix is calculated one time only, and it works over wide range of operating conditions. To validate the power of the proposed PSS, a linearized model of a simple power system consisted of a single synchronous machine connected to infinite bus bar through transmission line is simulated. The studied power system is subjected to various operating points and power system parameters changes.
Optimal pole shifting controller for interconnected power system
Energy Technology Data Exchange (ETDEWEB)
Yousef, Ali M., E-mail: drali_yousef@yahoo.co [Electrical Eng. Dept., Faculty of Engineering, Assiut University (Egypt); Kassem, Ahmed M., E-mail: kassem_ahmed53@hotmail.co [Control Technology Dep., Industrial Education College, Beni-Suef University (Egypt)
2011-05-15
Research highlights: {yields} Mathematical model represents a power system which consists of synchronous machine connected to infinite bus through transmission line. {yields} Power system stabilizer was designed based on optimal pole shifting controller. {yields} The system performances was tested through load disturbances at different operating conditions. {yields} The system performance with the proposed optimal pole shifting controller is compared with the conventional pole placement controller. {yields} The digital simulation results indicated that the proposed controller has a superior performance. -- Abstract: Power system stabilizer based on optimal pole shifting is proposed. An approach for shifting the real parts of the open-loop poles to any desired positions while preserving the imaginary parts is presented. In each step of this approach, it is required to solve a first-order or a second-order linear matrix Lyapunov equation for shifting one real pole or two complex conjugate poles, respectively. This presented method yields a solution, which is optimal with respect to a quadratic performance index. The attractive feature of this method is that it enables solutions of the complex problem to be easily found without solving any non-linear algebraic Riccati equation. The present power system stabilizer is based on Riccati equation approach. The control law depends on finding the feedback gain matrix, and then the control signal is synthesized by multiplying the state variables of the power system with determined gain matrix. The gain matrix is calculated one time only, and it works over wide range of operating conditions. To validate the power of the proposed PSS, a linearized model of a simple power system consisted of a single synchronous machine connected to infinite bus bar through transmission line is simulated. The studied power system is subjected to various operating points and power system parameters changes.
Generating optimized stochastic power management strategies for electric car components
Energy Technology Data Exchange (ETDEWEB)
Fruth, Matthias [TraceTronic GmbH, Dresden (Germany); Bastian, Steve [Technische Univ. Dresden (Germany)
2012-11-01
With the increasing prevalence of electric vehicles, reducing the power consumption of car components becomes a necessity. For the example of a novel traffic-light assistance system, which makes speed recommendations based on the expected length of red-light phases, power-management strategies are used to control under which conditions radio communication, positioning systems and other components are switched to low-power (e.g. sleep) or high-power (e.g. idle/busy) states. We apply dynamic power management, an optimization technique well-known from other domains, in order to compute energy-optimal power-management strategies, sometimes resulting in these strategies being stochastic. On the example of the traffic-light assistant, we present a MATLAB/Simulink-implemented framework for the generation, simulation and formal analysis of optimized power-management strategies, which is based on this technique. We study capabilities and limitations of this approach and sketch further applications in the automotive domain. (orig.)
Distributed Economic Dispatch in Microgrids Based on Cooperative Reinforcement Learning.
Liu, Weirong; Zhuang, Peng; Liang, Hao; Peng, Jun; Huang, Zhiwu; Weirong Liu; Peng Zhuang; Hao Liang; Jun Peng; Zhiwu Huang; Liu, Weirong; Liang, Hao; Peng, Jun; Zhuang, Peng; Huang, Zhiwu
2018-06-01
Microgrids incorporated with distributed generation (DG) units and energy storage (ES) devices are expected to play more and more important roles in the future power systems. Yet, achieving efficient distributed economic dispatch in microgrids is a challenging issue due to the randomness and nonlinear characteristics of DG units and loads. This paper proposes a cooperative reinforcement learning algorithm for distributed economic dispatch in microgrids. Utilizing the learning algorithm can avoid the difficulty of stochastic modeling and high computational complexity. In the cooperative reinforcement learning algorithm, the function approximation is leveraged to deal with the large and continuous state spaces. And a diffusion strategy is incorporated to coordinate the actions of DG units and ES devices. Based on the proposed algorithm, each node in microgrids only needs to communicate with its local neighbors, without relying on any centralized controllers. Algorithm convergence is analyzed, and simulations based on real-world meteorological and load data are conducted to validate the performance of the proposed algorithm.
Autonomous power networks based power system
International Nuclear Information System (INIS)
Jokic, A.; Van den Bosch, P.P.J.
2006-01-01
This paper presented the concept of autonomous networks to cope with this increased complexity in power systems while enhancing market-based operation. The operation of future power systems will be more challenging and demanding than present systems because of increased uncertainties, less inertia in the system, replacement of centralized coordinating activities by decentralized parties and the reliance on dynamic markets for both power balancing and system reliability. An autonomous network includes the aggregation of networked producers and consumers in a relatively small area with respect to the overall system. The operation of an autonomous network is coordinated and controlled with one central unit acting as an interface between internal producers/consumers and the rest of the power system. In this study, the power balance problem and system reliability through provision of ancillary services was formulated as an optimization problem for the overall autonomous networks based power system. This paper described the simulation of an optimal autonomous network dispatching in day ahead markets, based on predicted spot prices for real power, and two ancillary services. It was concluded that large changes occur in a power systems structure and operation, most of them adding to the uncertainty and complexity of the system. The introduced concept of an autonomous power network-based power system was shown to be a realistic and consistent approach to formulate and operate a market-based dispatch of both power and ancillary services. 9 refs., 4 figs
PSO Algorithm for an Optimal Power Controller in a Microgrid
Al-Saedi, W.; Lachowicz, S.; Habibi, D.; Bass, O.
2017-07-01
This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency.
Resource-based optimization of electric power production (in Iran)
International Nuclear Information System (INIS)
Sadeghzadeh, Mohammad
1999-01-01
This paper is about electric power production optimization and chiefly discusses on the types of resources available in Iran. The modeling has been based on the marginal cost of different energy resources and types of technologies used. the computed costs are the basic standards for optimization of the production system of energy. the costs associated with environmental pollution and also pollution control are considered. the present paper also studied gas fossil fuel, hydro, nuclear, renewable and co-generation of heat and power. The results are discussed and reported at the last of the paper
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2014-01-01
Consumers may decide to modify the profile of their demand from high price periods to low price periods in order to reduce their electricity costs. This optimal load response to electricity prices for demand side management generates different load profiles and provides an opportunity to achieve...... power loss minimization in distribution systems. In this paper, a new method to achieve power loss minimization in distribution systems by using a price signal to guide the demand side management is proposed. A fuzzy adaptive particle swarm optimization (FAPSO) is used as a tool for the power loss...
Optimal power flow management for distributed energy resources with batteries
International Nuclear Information System (INIS)
Tazvinga, Henerica; Zhu, Bing; Xia, Xiaohua
2015-01-01
Highlights: • A PV-diesel-battery hybrid system is proposed. • Model minimizes fuel and battery wear costs. • Power flows are analysed in a 24-h period. • Results provide a practical platform for decision making. - Abstract: This paper presents an optimal energy management model of a solar photovoltaic-diesel-battery hybrid power supply system for off-grid applications. The aim is to meet the load demand completely while satisfying the system constraints. The proposed model minimizes fuel and battery wear costs and finds the optimal power flow, taking into account photovoltaic power availability, battery bank state of charge and load power demand. The optimal solutions are compared for cases when the objectives are weighted equally and when a larger weight is assigned to battery wear. A considerable increase in system operational cost is observed in the latter case owing to the increased usage of the diesel generator. The results are important for decision makers, as they depict the optimal decisions considered in the presence of trade-offs between conflicting objectives
Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto
2018-01-12
This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.
McLarty, Dustin Fogle
heuristics are discussed using a case study of the UCI central plant. Thermal energy storage introduces a time horizon into the dispatch optimization which requires novel solution strategies. Highly efficient and responsive generators are required to meet the increasingly dynamic loads of today's efficient buildings and intermittent local renewable wind and solar power. Fuel cell gas turbine hybrids will play an integral role in the complex and ever-changing solution to local electricity production.
Modeling work of the dispatching service of high-rise building as queuing system
Dement'eva, Marina; Dement'eva, Anastasiya
2018-03-01
The article presents the results of calculating the performance indicators of the dispatcher service of a high-rise building as a queuing system with an unlimited queue. The calculation was carried out for three models: with a single control room and brigade of service, with a single control room and a specialized service, with several dispatch centers and specialized services. The aim of the work was to investigate the influence of the structural scheme of the organization of the dispatcher service of a high-rise building on the amount of operating costs and the time of processing and fulfilling applications. The problems of high-rise construction and their impact on the complication of exploitation are analyzed. The composition of exploitation activities of high-rise buildings is analyzed. The relevance of the study is justified by the need to review the role of dispatch services in the structure of management of the quality of buildings. Dispatching service from the lower level of management of individual engineering systems becomes the main link in the centralized automated management of the exploitation of high-rise buildings. With the transition to market relations, the criterion of profitability at the organization of the dispatching service becomes one of the main parameters of the effectiveness of its work. A mathematical model for assessing the efficiency of the dispatching service on a set of quality of service indicators is proposed. The structure of operating costs is presented. The algorithm of decision-making is given when choosing the optimal structural scheme of the dispatching service of a high-rise building.
Optimized multi area AGC simulation in restructured power systems
International Nuclear Information System (INIS)
Bhatt, Praghnesh; Roy, Ranjit; Ghoshal, S.P.
2010-01-01
In this paper, the traditional automatic generation control loop with modifications is incorporated for simulating automatic generation control (AGC) in restructured power system. Federal energy regulatory commission (FERC) encourages an open market system for price based operation. FERC has issued a notice for proposed rulemaking of various ancillary services. One of these ancillary services is load following with frequency control which comes broadly under Automatic Generation Control in deregulated regime. The concept of DISCO participation matrix is used to simulate the bilateral contracts in the three areas and four area diagrams. Hybrid particle swarm optimization is used to obtain optimal gain parameters for optimal transient performance. (author)
Online Dispatching Rules For Vehicle-Based Internal Transport Systems
T. Le-Anh (Tuan); M.B.M. de Koster (René)
2004-01-01
textabstractOn-line vehicles dispatching rules are widely used in many facilities such as warehouses to control vehicles' movements. Single-attribute dispatching rules, which dispatch vehicles based on only one parameter, are used commonly. However, multi-attribute dispatching rules prove to be
Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks
Directory of Open Access Journals (Sweden)
M. Hadi Amini
2018-01-01
Full Text Available Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs with competing charging stations, to exchange data such as electricity price, energy demand, and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs’ charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices were communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e., optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks.
DEFF Research Database (Denmark)
Li, Qingnan; Andersen, Michael A. E.; Thomsen, Ole Cornelius
2011-01-01
Nowadays, efficiency and power density are the most important issues for Power Factor Correction (PFC) converters development. However, it is a challenge to reach both high efficiency and power density in a system at the same time. In this paper, taking a Bridgeless PFC (BPFC) as an example......, a useful compromise between efficiency and power density of the Boost inductors on 3.2kW is achieved using an optimized design procedure. The experimental verifications based on the optimized inductor are carried out from 300W to 3.2kW at 220Vac input....
An Effective Framework For Economic Dispatch Using Modified Harmony Search Algorithm
Directory of Open Access Journals (Sweden)
Advik Kumar
2017-09-01
Full Text Available The effects of ever-increasing wind power generation for solving the economic dispatch ED problem have led to high penetration of renewable energy source in new power systems. Continuing search for better utilizing of wind turbine associated with thermal sources to find the optimal allocation of output power is necessary in which pro-vide more reliability and efficiency. Dynamic nature of wind energy has imposed uncertainties characteristics in the poser systems. To deal with this problem an effective probabilistic method to investigate all unpredictability would be a good idea to make more realistic analysis. This paper presents a heuristics optimization method based on harmony search HS algorithm to solve non-convex ED problems while uncertainties effects caused by wind turbines are considered. To involve a realistic analysis as a more practical investigation the proposed probabilistic ED PED approach includes prohibited operating zone POZ system spinning reserve ramp rate limits variety of fuel is considered in this studies. Point Estimate Method PEM as a proposed PED model the uncertainties of wind speed for wind turbines to present better realization to the problem. Optimal solution are presented for vari-ous test system and these solutions demonstrate the benefits of our approach in terms of cost over existing ED techniques.
Optimization of power generation from shrouded wind turbines
Energy Technology Data Exchange (ETDEWEB)
Foote, Tudor; Agarwal, Ramesh [Department of Mechanical Engineering and Materials Science, Washington University in St. Louis (United States)
2013-07-01
In past several years, several studies have shown that the shrouded wind turbines can generate greater power compared to bare turbines. The objective of this study is to determine the potential of shrouded wind turbines for increased power generation by conducting numerical simulations. An analytical/computational study is performed by employing the well-known commercial Computational Fluid Dynamics (CFD) software FLUENT. An actuator disc model is used to model the turbine. The incompressible Navier-Stokes equations and a two equation realizable {kappa}-{epsilon} model are employed in the calculations. The power coefficient Cp and generated power are calculated for a large number of cases for horizontal axis wind turbines (HAWT) of various diameters and wind speeds for both bare and shrouded turbines. The design of the shroud is optimized by employing a single objective genetic algorithm; the objective being the maximization of the power coefficient Cp. It was found that the shroud indeed increases the Cp beyond the Betz’s limit significantly and as a result the generated power; this effect is consistent with that found in the recent literature that the shrouded wind-turbines can generate greater power than the bare turbines. The optimized shape of the shroud or diffuser further increases the generated power and Cp.
Generation of Optimal Basis Functions for Reconstruction of Power Distribution
Energy Technology Data Exchange (ETDEWEB)
Park, Moonghu [Sejong Univ., Seoul (Korea, Republic of)
2014-05-15
This study proposes GMDH to find not only the best functional form but also the optimal parameters those describe the power distribution most accurately. A total of 1,060 cases of axially 1-dimensional core power distributions of 20-nodes are generated by 3-dimensional core analysis code covering BOL to EOL core burnup histories to validate the method. Axially five-point box powers at in-core detectors are considered as measurements. The reconstructed axial power shapes using GMDH method are compared to the reference power shapes. The results show that the proposed method is very robust and accurate compared with spline fitting method. It is shown that the GMDH analysis can give optimal basis functions for core power shape reconstruction. The in-core measurements are the 5 detector snapshots and the 20-node power distribution is successfully reconstructed. The effectiveness of the method is demonstrated by comparing the results of spline fitting for BOL, saddle and top-skewed power shapes.
Optimizing efficiency on conventional transformer based low power AC/DC standby power supplies
DEFF Research Database (Denmark)
Nielsen, Nils
2004-01-01
This article describes the research results for simple and cheap methods to reduce the idle- and load-losses in very low power conventional transformer based power supplies intended for standby usage. In this case "very low power" means 50 Hz/230 V-AC to 5 V-DC@1 W. The efficiency is measured...... on two common power supply topologies designed for this power level. The two described topologies uses either a series (or linear) or a buck regulation approach. Common to the test power supplies is they either are using a standard cheap off-the-shelf transformer, or one, which are loss optimized by very...
Energy Technology Data Exchange (ETDEWEB)
Gunkel, David [TU Dresden (Germany). Lehrstuhl fuer Energiewirtschaft; Hess, Tobias; Schegner, Peter [TU Dresden (Germany). Inst. fuer Elektrische Energieversorgung und Hochspannungstechnik
2011-07-01
The daily operational scheduling of decentralised unit is an important optimization task of power systems. This proceeding deals with planning of small scaled co-generation power units for district heating in a microgrid. This power system can be mathematically formulated and solved by an optimization algorithm. The solution process consists of a unit commitment and dispatch. The starting unit commitment is characterised by a mixed integer nonlinear problem defining the on-off-state of all units. Subsequently, the dispatch distributes the generation requirements to every committed unit considering thermal demand. The dispatching is based on a mixed integer linear problem. Additionally, it presents a way for flexible reducing the outage reserve related to the operational condition. The given microgrid operates in an islanding mode. The method can also be applied in a grid connected model considering the possible requirements of a grid operator. (orig.)
Optimization in the scale of nuclear power generation and the economy of nuclear power
International Nuclear Information System (INIS)
Suzuki, Toshiharu
1983-01-01
In the not too distant future, the economy of nuclear power will have to be restudied. Various conditions and circumstances supporting this economy of nuclear power tend to change, such as the decrease in power demand and supply, the diversification in base load supply sources, etc. The fragility in the economic advantage of nuclear power may thus be revealed. In the above connection, on the basis of the future outlook of the scale of nuclear power generation, that is, the further reduction of the current nuclear power program, and of the corresponding supply and demand of nuclear fuel cycle quantities, the aspect of the economic advantage of nuclear power was examined, for the purpose of optimizing the future scale of nuclear power generation (the downward revision of the scale, the establishment of the schedule of nuclear fuel cycle the stagnation of power demand and nuclear power generation costs). (Mori, K.)
Farrokhseresht, M.; Paterakis, N.G.; Gibescu, M.; Slootweg, J.G.
2017-01-01
This paper presents a stochastic bi-level optimization model to determine the optimal dispatch of energy storage systems controlled directly by the distribution system operator (DSO) in order to achieve minimization of active power losses, taking into account the profit-driven participation of
Optimal pricing of non-utility generated electric power
International Nuclear Information System (INIS)
Siddiqi, S.N.; Baughman, M.L.
1994-01-01
The importance of an optimal pricing policy for pricing non-utility generated power is pointed out in this paper. An optimal pricing policy leads to benefits for all concerned: the utility, industry, and the utility's other customers. In this paper, it is shown that reliability differentiated real-time pricing provides an optimal non-utility generated power pricing policy, from a societal welfare point of view. Firm capacity purchase, and hence an optimal price for purchasing firm capacity, are an integral part of this pricing policy. A case study shows that real-time pricing without firm capacity purchase results in improper investment decisions and higher costs for the system as a whole. Without explicit firm capacity purchase, the utility makes greater investment in capacity addition in order to meet its reliability criteria than is socially optimal. It is concluded that the non-utility generated power pricing policy presented in this paper and implied by reliability differentiated pricing policy results in social welfare-maximizing investment and operation decisions
International Nuclear Information System (INIS)
Derafshian, Mehdi; Amjady, Nima
2015-01-01
This paper presents an evolutionary algorithm-based approach for optimal design of power system stabilizer (PSS) for multi-machine power systems that include doubly fed induction generator wind turbines. The proposed evolutionary algorithm is an improved particle swarm optimization named chaotic particle swarm optimization with passive congregation (CPSO-PC) applied for finding the optimal settings of PSS parameters. Two different eigenvalue-based objectives are combined as the objective function for the optimization problem of tuning PSS parameters. The first objective function comprises the damping factor of lightly damped electro-mechanical modes and the second one includes the damping ratio of these modes. The effectiveness of the proposed method to design PSS for the power systems including DFIG (Doubly Fed Induction Generator) is extensively demonstrated through eigenvalue analysis and time-domain simulations and also by comparing its simulation results with the results of other heuristic optimization approaches. - Highlights: • A new optimization model for design of PSS in power systems including DFIG is proposed. • A detailed and realistic modeling of DFIG is presented. • A new evolutionary algorithm is suggested for solving the optimization problem of designing PSS
Wind Turbine Power Curve Design for Optimal Power Generation in Wind Farms Considering Wake Effect
Directory of Open Access Journals (Sweden)
Jie Tian
2017-03-01
Full Text Available In modern wind farms, maximum power point tracking (MPPT is widely implemented. Using the MPPT method, each individual wind turbine is controlled by its pitch angle and tip speed ratio to generate the maximum active power. In a wind farm, the upstream wind turbine may cause power loss to its downstream wind turbines due to the wake effect. According to the wake model, downstream power loss is also determined by the pitch angle and tip speed ratio of the upstream wind turbine. By optimizing the pitch angle and tip speed ratio of each wind turbine, the total active power of the wind farm can be increased. In this paper, the optimal pitch angle and tip speed ratio are selected for each wind turbine by the exhausted search. Considering the estimation error of the wake model, a solution to implement the optimized pitch angle and tip speed ratio is proposed, which is to generate the optimal control curves for each individual wind turbine off-line. In typical wind farms with regular layout, based on the detailed analysis of the influence of pitch angle and tip speed ratio on the total active power of the wind farm by the exhausted search, the optimization is simplified with the reduced computation complexity. By using the optimized control curves, the annual energy production (AEP is increased by 1.03% compared to using the MPPT method in a case-study of a typical eighty-turbine wind farm.
Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses
Energy Technology Data Exchange (ETDEWEB)
Wendt, Daniel S.; Mines, Gregory L.; Turchi, Craig S.; Zhu, Guangdong; Cohan, Sander; Angelini, Lorenzo; Bizzarri, Fabrizio; Consoli, Daniele; De Marzo, Alessio
2015-09-02
The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error. The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.
Optimization of radiological protection in Spanish nuclear power plants
International Nuclear Information System (INIS)
O'Donnell, P.; Amor, I.; Butragueno, J.L.
1997-01-01
Optimizing the radiological protection of occupationally exposed nuclear power plant workers has become one further item in what is called the safety culture. Spanish facilities are implementing programme with this in mind, grounded on a personal motivation policy with the backing of a suitable organizational structure. (Author)
Using package MESSAGE for optimization studies of nuclear power structures
International Nuclear Information System (INIS)
Andrianov, A.A.; Fedorova, E.V.; Korobejnikov, V.V.; Poplavskaya, E.V.; Rachkova, E.N.
2010-01-01
The results of optimization research of Russia nuclear power strategies, obtained for different assumptions concerning availability of natural uranium resources were presented. The ability of energy planning package MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impacts) application for elaborating breeding parameters requirements of fast sodium reactors and assessing the required scale of nuclear fuel cycle enterprises development was demonstrated [ru
Optimal trajectory control of a CLCC resonant power converter
Huisman, H.; Visser, de I.; Duarte, J.L.
2015-01-01
A CLCC resonant converter to be used in an isolated power supply is operated using optimal trajectory control (OTC). As a consequence, the converter's inner loop behavior is changed to that of a controlled current source. The controller is implemented in an FPGA. Simulation results and recorded
Efficient relaxations for joint chance constrained AC optimal power flow
Energy Technology Data Exchange (ETDEWEB)
Baker, Kyri; Toomey, Bridget
2017-07-01
Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality as an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.
Optimization of the scheduled maintenance on the power units of the nuclear power plants with WWER
International Nuclear Information System (INIS)
Skalozubov, V.I.; Kovrizhkin, Yu.L.; Kolykhanov, V.N.; Kochneva, V.Yu.; Urbanskij, V.V.
2008-01-01
The advanced international and domestic experience in the field of the maintenance optimization of the power units of NPPs, as well, as on the base of the planning optimization, the maintenance organization and carrying out, the technical maintenance and repair control system automatization, the testing and monitoring optimization during the service process, the modernization of the technology and technical tools of the maintenance service and control is represented
Optimal power allocation of a sensor node under different rate constraints
Ayala Solares, Jose Roberto; Rezki, Zouheir; Alouini, Mohamed-Slim
2012-01-01
The optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now
Optimal Power Flow for Distribution Systems under Uncertain Forecasts: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Baker, Kyri; Summers, Tyler
2016-12-01
The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.
Optimal Design of Magnetic ComponentsinPlasma Cutting Power Supply
Jiang, J. F.; Zhu, B. R.; Zhao, W. N.; Yang, X. J.; Tang, H. J.
2017-10-01
Phase-shifted transformer and DC reactor are usually needed in chopper plasma cutting power supply. Because of high power rate, the loss of magnetic components may reach to several kilowatts, which seriously affects the conversion efficiency. Therefore, it is necessary to research and design low loss magnetic components by means of efficient magnetic materials and optimal design methods. The main task in this paper is to compare the core loss of different magnetic material, to analyze the influence of transformer structure, winding arrangement and wire structure on the characteristics of magnetic component. Then another task is to select suitable magnetic material, structure and wire in order to reduce the loss and volume of magnetic components. Based on the above outcome, the optimization design process of transformer and dc reactor are proposed in chopper plasma cutting power supply with a lot of solutions. These solutions are analyzed and compared before the determination of the optimal solution in order to reduce the volume and power loss of the two magnetic components and improve the conversion efficiency of plasma cutting power supply.
The optimization of wireless power transmission: design and realization.
Jia, Zhiwei; Yan, Guozheng; Liu, Hua; Wang, Zhiwu; Jiang, Pingping; Shi, Yu
2012-09-01
A wireless power transmission system is regarded as a practical way of solving power-shortage problems in multifunctional active capsule endoscopes. The uniformity of magnetic flux density, frequency stability and orientation stability are used to evaluate power transmission stability, taking into consideration size and safety constraints. Magnetic field safety and temperature rise are also considered. Test benches are designed to measure the relevent parameters. Finally, a mathematical programming model in which these constraints are considered is proposed to improve transmission efficiency. To verify the feasibility of the proposed method, various systems for a wireless active capsule endoscope are designed and evaluated. The optimal power transmission system has the capability to supply continuously at least 500 mW of power with a transmission efficiency of 4.08%. The example validates the feasibility of the proposed method. Introduction of novel designs enables further improvement of this method. Copyright © 2012 John Wiley & Sons, Ltd.
Power Consumption in Refrigeration Systems - Modeling for Optimization
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Skovrup, Morten Juel
2011-01-01
Refrigeration systems consume a substantial amount of energy. Taking for instance supermarket refrigeration systems as an example they can account for up to 50−80% of the total energy consumption in the supermarket. Due to the thermal capacity made up by the refrigerated goods in the system...... there is a possibility for optimizing the power consumption by utilizing load shifting strategies. This paper describes the dynamics and the modeling of a vapor compression refrigeration system needed for sufficiently realistic estimation of the power consumption and its minimization. This leads to a non-convex function...... with possibly multiple extrema. Such a function can not directly be optimized by standard methods and a qualitative analysis of the system’s constraints is presented. The description of power consumption contains nonlinear terms which are approximated by linear functions in the control variables and the error...
Price-based Optimal Control of Electrical Power Systems
Energy Technology Data Exchange (ETDEWEB)
Jokic, A.
2007-09-10
The research presented in this thesis is motivated by the following issue of concern for the operation of future power systems: Future power systems will be characterized by significantly increased uncertainties at all time scales and, consequently, their behavior in time will be difficult to predict. In Chapter 2 we will present a novel explicit, dynamic, distributed feedback control scheme that utilizes nodal-prices for real-time optimal power balance and network congestion control. The term explicit means that the controller is not based on solving an optimization problem on-line. Instead, the nodal prices updates are based on simple, explicitly defined and easily comprehensible rules. We prove that the developed control scheme, which acts on the measurements from the current state of the system, always provide the correct nodal prices. In Chapter 3 we will develop a novel, robust, hybrid MPC control (model predictive controller) scheme for power balance control with hard constraints on line power flows and network frequency deviations. The developed MPC controller acts in parallel with the explicit controller from Chapter 2, and its task is to enforce the constraints during the transient periods following suddenly occurring power imbalances in the system. In Chapter 4 the concept of autonomous power networks will be presented as a concise formulation to deal with economic, technical and reliability issues in power systems with a large penetration of distributed generating units. With autonomous power networks as new market entities, we propose a novel operational structure of ancillary service markets. In Chapter 5 we will consider the problem of controlling a general linear time-invariant dynamical system to an economically optimal operating point, which is defined by a multiparametric constrained convex optimization problem related with the steady-state operation of the system. The parameters in the optimization problem are values of the exogenous inputs to
Computer-aided dispatching system design specification
Energy Technology Data Exchange (ETDEWEB)
Briggs, M.G.
1997-12-16
This document defines the performance requirements for a graphic display dispatching system to support Hanford Patrol Operations Center. This document reflects the as-built requirements for the system that was delivered by GTE Northwest, Inc. This system provided a commercial off-the-shelf computer-aided dispatching system and alarm monitoring system currently in operations at the Hanford Patrol Operations Center, Building 2721E. This system also provides alarm back-up capability for the Plutonium Finishing Plant (PFP).
Computer-Aided dispatching system design specification
International Nuclear Information System (INIS)
Briggs, M.G.
1996-01-01
This document defines the performance requirements for a graphic display dispatching system to support Hanford Patrol emergency response. This system is defined as a Commercial-Off the-Shelf computer dispatching system providing both text and graphical display information while interfacing with the diverse reporting system within the Hanford Facility. This system also provided expansion capabilities to integrate Hanford Fire and the Occurrence Notification Center and provides back-up capabilities for the Plutonium Processing Facility
Computer-aided dispatching system design specification
International Nuclear Information System (INIS)
Briggs, M.G.
1997-01-01
This document defines the performance requirements for a graphic display dispatching system to support Hanford Patrol Operations Center. This document reflects the as-built requirements for the system that was delivered by GTE Northwest, Inc. This system provided a commercial off-the-shelf computer-aided dispatching system and alarm monitoring system currently in operations at the Hanford Patrol Operations Center, Building 2721E. This system also provides alarm back-up capability for the Plutonium Finishing Plant (PFP)
International Nuclear Information System (INIS)
Secui, Dinu Calin
2016-01-01
This paper proposes a new metaheuristic algorithm, called Modified Symbiotic Organisms Search (MSOS) algorithm, to solve the economic dispatch problem considering the valve-point effects, the prohibited operating zones (POZ), the transmission line losses, multi-fuel sources, as well as other operating constraints of the generating units and power system. The MSOS algorithm introduces, in all of its phases, new relations to update the solutions to improve its capacity of identifying stable and of high-quality solutions in a reasonable time. Furthermore, to increase the capacity of exploring the MSOS algorithm in finding the most promising zones, it is endowed with a chaotic component generated by the Logistic map. The performance of the modified algorithm and of the original algorithm Symbiotic Organisms Search (SOS) is tested on five systems of different characteristics, constraints and dimensions (13-unit, 40-unit, 80-unit, 160-unit and 320-unit). The results obtained by applying the proposed algorithm (MSOS) show that this has a better performance than other techniques of optimization recently used in solving the economic dispatch problem with valve-point effects. - Highlights: • A new modified SOS algorithm (MSOS) is proposed to solve the EcD problem. • Valve-point effects, ramp-rate limits, POZ, multi-fuel sources, transmission losses were considered. • The algorithm is tested on five systems having 13, 40, 80, 160 and 320 thermal units. • MSOS algorithm outperforms many other optimization techniques.
Optimal Operation of Energy Storage in Power Transmission and Distribution
Akhavan Hejazi, Seyed Hossein
In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider
Convex relaxation of Optimal Power Flow in Distribution Feeders with embedded solar power
DEFF Research Database (Denmark)
Hermann, Alexander Niels August; Wu, Qiuwei; Huang, Shaojun
2016-01-01
There is an increasing interest in using Distributed Energy Resources (DER) directly coupled to end user distribution feeders. This poses an array of challenges because most of today’s distribution feeders are designed for unidirectional power flow. Therefore when installing DERs such as solar...... panels with uncontrolled inverters, the upper limit of installable capacity is quickly reached in many of today’s distribution feeders. This problem can often be mitigated by optimally controlling the voltage angles of inverters. However, the optimal power flow problem in its standard form is a large...... scale non-convex optimization problem, and thus can’t be solved precisely and also is computationally heavy and intractable for large systems. This paper examines the use of a convex relaxation using Semi-definite programming to optimally control solar power inverters in a distribution grid in order...
An electric vehicle dispatch module for demand-side energy participation
International Nuclear Information System (INIS)
Zhou, Bowen; Yao, Feng; Littler, Tim; Zhang, Huaguang
2016-01-01
Highlights: • Real-time measurement and assessment to calculate EV initial state-of-charge (SOC). • Flexible EV charging allocation using measured available time duration (ATD). • Owner participation using mobile phone apps and a new EV dispatch module. • Online algorithm for real-time calculation of maximum and minimum adjustable limits. • Business-trading models with data security, trending and commercial impacts of EV. - Abstract: The penetration of the electric vehicle (EV) has increased rapidly in recent years mainly as a consequence of advances in transport technology and power electronics and in response to global pressure to reduce carbon emissions and limit fossil fuel consumption. It is widely acknowledged that inappropriate provision and dispatch of EV charging can lead to negative impacts on power system infrastructure. This paper considers EV requirements and proposes a module which uses owner participation, through mobile phone apps and on-board diagnostics II (OBD-II), for scheduled vehicle charging. A multi-EV reference and single-EV real-time response (MRS2R) online algorithm is proposed to calculate the maximum and minimum adjustable limits of necessary capacity, which forms part of decision-making support in power system dispatch. The proposed EV dispatch module is evaluated in a case study and the influence of the mobile app, EV dispatch trending and commercial impact is explored.
Optimal Power Transmission of Offshore Wind Power Using a VSC-HVdc Interconnection
Directory of Open Access Journals (Sweden)
Miguel E. Montilla-DJesus
2017-07-01
Full Text Available High-voltage dc transmission based on voltage-source converter (VSC-HVdc is quickly increasing its power rating, and it can be the most appropriate link for the connection of offshore wind farms (OWFs to the grid in many locations. This paper presents a steady-state operation model to calculate the optimal power transmission of an OWF connected to the grid through a VSC-HVdc link. The wind turbines are based on doubly fed induction generators (DFIGs, and a detailed model of the internal OWF grid is considered in the model. The objective of the optimization problem is to maximize the active power output of the OWF, i.e., the reduction of losses, by considering the optimal reactive power allocation while taking into account the restrictions imposed by the available wind power, the reactive power capability of the DFIG, the DC link model, and the operating conditions. Realistic simulations are performed to evaluate the proposed model and to execute optimal operation analyses. The results show the effectiveness of the proposed method and demonstrate the advantages of using the reactive control performed by DFIG to achieve the optimal operation of the VSC-HVdc.
International Nuclear Information System (INIS)
Lopez, P. Reche; Reyes, N. Ruiz; Gonzalez, M. Gomez; Jurado, F.
2008-01-01
With sufficient territory and abundant biomass resources Spain appears to have suitable conditions to develop biomass utilization technologies. As an important decentralized power technology, biomass gasification and power generation has a potential market in making use of biomass wastes. This paper addresses biomass fuelled generation of electricity in the specific aspect of finding the best location and the supply area of the electric generation plant for three alternative technologies (gas motor, gas turbine and fuel cell-microturbine hybrid power cycle), taking into account the variables involved in the problem, such as the local distribution of biomass resources, transportation costs, distance to existing electric lines, etc. For each technology, not only optimal location and supply area of the biomass plant, but also net present value and generated electric power are determined by an own binary variant of Particle Swarm Optimization (PSO). According to the values derived from the optimization algorithm, the most profitable technology can be chosen. Computer simulations show the good performance of the proposed binary PSO algorithm to optimize biomass fuelled systems for distributed power generation. (author)
Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer
Yang, Gang; Moghadam, Mohammad R. Vedady; Zhang, Rui
2017-06-01
In magnetic resonant coupling (MRC) enabled multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each with one single coil are used to enhance the efficiency of simultaneous power transfer to multiple single-coil receivers (RXs) by constructively combining their induced magnetic fields at the RXs, a technique termed "magnetic beamforming". In this paper, we study the optimal magnetic beamforming design in a multi-user MIMO MRC-WPT system. We introduce the multi-user power region that constitutes all the achievable power tuples for all RXs, subject to the given total power constraint over all TXs as well as their individual peak voltage and current constraints. We characterize each boundary point of the power region by maximizing the sum-power deliverable to all RXs subject to their minimum harvested power constraints. For the special case without the TX peak voltage and current constraints, we derive the optimal TX current allocation for the single-RX setup in closed-form as well as that for the multi-RX setup. In general, the problem is a non-convex quadratically constrained quadratic programming (QCQP), which is difficult to solve. For the case of one single RX, we show that the semidefinite relaxation (SDR) of the problem is tight. For the general case with multiple RXs, based on SDR we obtain two approximate solutions by applying time-sharing and randomization, respectively. Moreover, for practical implementation of magnetic beamforming, we propose a novel signal processing method to estimate the magnetic MIMO channel due to the mutual inductances between TXs and RXs. Numerical results show that our proposed magnetic channel estimation and adaptive beamforming schemes are practically effective, and can significantly improve the power transfer efficiency and multi-user performance trade-off in MIMO MRC-WPT systems.
Application of Newton's optimal power flow in voltage/reactive power control
Energy Technology Data Exchange (ETDEWEB)
Bjelogrlic, M.; Babic, B.S. (Electric Power Board of Serbia, Belgrade (YU)); Calovic, M.S. (Dept. of Electrical Engineering, University of Belgrade, Belgrade (YU)); Ristanovic, P. (Institute Nikola Tesla, Belgrade (YU))
1990-11-01
This paper considers an application of Newton's optimal power flow to the solution of the secondary voltage/reactive power control in transmission networks. An efficient computer program based on the latest achievements in the sparse matrix/vector techniques has been developed for this purpose. It is characterized by good robustness, accuracy and speed. A combined objective function appropriate for various system load levels with suitable constraints, for treatment of the power system security and economy is also proposed. For the real-time voltage/reactive power control, a suboptimal power flow procedure has been derived by using the reduced set of control variables. This procedure is based on the sensitivity theory applied to the determination of zones for the secondary voltage/reactive power control and corresponding reduced set of regulating sources, whose reactive outputs represent control variables in the optimal power flow program. As a result, the optimal power flow program output becomes a schedule to be used by operators in the process of the real-time voltage/reactive power control in both normal and emergency operating states.
Control strategies for wind farm power optimization: LES study
Ciri, Umberto; Rotea, Mario; Leonardi, Stefano
2017-11-01
Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.
International Nuclear Information System (INIS)
Chen, Fang; Zhou, Jianzhong; Wang, Chao; Li, Chunlong; Lu, Peng
2017-01-01
Wind power is a type of clean and renewable energy, and reasonable utilization of wind power is beneficial to environmental protection and economic development. Therefore, a short-term hydro-thermal-wind economic emission dispatching (SHTW-EED) problem is presented in this paper. The proposed problem aims to distribute the load among hydro, thermal and wind power units to simultaneously minimize economic cost and pollutant emission. To solve the SHTW-EED problem with complex constraints, a modified gravitational search algorithm based on the non-dominated sorting genetic algorithm-III (MGSA-NSGA-III) is proposed. In the proposed MGSA-NSGA-III, a non-dominated sorting approach, reference-point based selection mechanism and chaotic mutation strategy are applied to improve the evolutionary process of the original gravitational search algorithm (GSA) and maintain the distribution diversity of Pareto optimal solutions. Moreover, a parallel computing strategy is introduced to improve the computational efficiency. Finally, the proposed MGSA-NSGA-III is applied to a typical hydro-thermal-wind system to verify its feasibility and effectiveness. The simulation results indicate that the proposed algorithm can obtain low economic cost and small pollutant emission when dealing with the SHTW-EED problem. - Highlights: • A hybrid algorithm is proposed to handle hydro-thermal-wind power dispatching. • Several improvement strategies are applied to the algorithm. • A parallel computing strategy is applied to improve computational efficiency. • Two cases are analyzed to verify the efficiency of the optimize mode.
Optimization of the control of contamination at nuclear power plants
International Nuclear Information System (INIS)
Khan, T.A.; Baum, J.W.
1988-05-01
A methodology is described for the optimization of the actions taken to control contamination. It deals with many aspects of contamination, such as the monetary value assigned to a unit of radiation dose, the treatment of skin and extremity dose, and the inefficiencies introduced from working in a contaminated environemnt. The optimization method is illustrated with two case studies based on cleanup projects at nuclear power plants. Guidelines for the use of protective apparel, and for monitoring radiation and contamination at various levels of contamination are presented. The report concludes that additional research is required to quantify the effect of a contaminated environment on work efficiencies
Optimization of wind farm power production using innovative control strategies
DEFF Research Database (Denmark)
Duc, Thomas
Wind energy has experienced a very significant growth and cost reduction over the past decade, and is now able to compete with conventional power generation sources. New concepts are currently investigated to decrease costs of production of electricity even further. Wind farm coordinated control...... deficit caused by the wake downstream, or yawing the turbine to deflect the wake away from the downwind turbine. Simulation results found in the literature indicate that an increase in overall power production can be obtained. However they underline the high sensitivity of these gains to incoming wind...... aligned wind turbines. The experimental results show that the scenarios implemented during the first measurement campaign did not achieve an increase in overall power production, which confirms the difficulty to realize wind farm power optimization in real operating conditions. In the curtailment field...
Multiperiod hydrothermal economic dispatch by an interior point method
Directory of Open Access Journals (Sweden)
Kimball L. M.
2002-01-01
Full Text Available This paper presents an interior point algorithm to solve the multiperiod hydrothermal economic dispatch (HTED. The multiperiod HTED is a large scale nonlinear programming problem. Various optimization methods have been applied to the multiperiod HTED, but most neglect important network characteristics or require decomposition into thermal and hydro subproblems. The algorithm described here exploits the special bordered block diagonal structure and sparsity of the Newton system for the first order necessary conditions to result in a fast efficient algorithm that can account for all network aspects. Applying this new algorithm challenges a conventional method for the use of available hydro resources known as the peak shaving heuristic.
Mathematical game type optimization of powerful fast reactors
International Nuclear Information System (INIS)
Pavelesku, M.; Dumitresku, Kh.; Adam, S.
1975-01-01
To obtain maximum speed of putting into operation fast breeders it is recommended on the initial stage of putting into operation these reactors to apply lower power which needs less fission materials. That is why there is an attempt to find a configuration of a high-power reactor providing maximum power for minimum mass of fission material. This problem has a structure of the mathematical game with two partners of non-zero-order total and is solved by means of specific aids of theory of games. Optimal distribution of fission and breeding materials in a multizone reactor first is determined by solution of competitive game and then, on its base, by solution of the cooperation game. The second problem the solution for which is searched is developed from remark on the fact that a reactor with minimum coefficient of flux heterogenity has a configuration different from the reactor with power coefficient heterogenity. Maximum burn-up of fuel needs minimum heterogenity of the flux coefficient and the highest power level needs minimum coefficient of power heterogenity. That is why it is possible to put a problem of finding of the reactor configuration having both coefficients with minimum value. This problem has a structure of a mathematical game with two partners of non-zero-order total and is solved analogously giving optimal distribution of fuel from the new point of view. In the report is shown that both these solutions are independent which is a result of the aim put in the problem of optimization. (author)
Optimization of Passive Low Power Wireless Electromagnetic Energy Harvesters
Nimo, Antwi; Grgić, Dario; Reindl, Leonhard M.
2012-01-01
This work presents the optimization of antenna captured low power radio frequency (RF) to direct current (DC) power converters using Schottky diodes for powering remote wireless sensors. Linearized models using scattering parameters show that an antenna and a matched diode rectifier can be described as a form of coupled resonator with different individual resonator properties. The analytical models show that the maximum voltage gain of the coupled resonators is mainly related to the antenna, diode and load (remote sensor) resistances at matched conditions or resonance. The analytical models were verified with experimental results. Different passive wireless RF power harvesters offering high selectivity, broadband response and high voltage sensitivity are presented. Measured results show that with an optimal resistance of antenna and diode, it is possible to achieve high RF to DC voltage sensitivity of 0.5 V and efficiency of 20% at −30 dBm antenna input power. Additionally, a wireless harvester (rectenna) is built and tested for receiving range performance. PMID:23202014
Optimization of Passive Low Power Wireless Electromagnetic Energy Harvesters
Directory of Open Access Journals (Sweden)
Dario Grgić
2012-10-01
Full Text Available This work presents the optimization of antenna captured low power radio frequency (RF to direct current (DC power converters using Schottky diodes for powering remote wireless sensors. Linearized models using scattering parameters show that an antenna and a matched diode rectifier can be described as a form of coupled resonator with different individual resonator properties. The analytical models show that the maximum voltage gain of the coupled resonators is mainly related to the antenna, diode and load (remote sensor resistances at matched conditions or resonance. The analytical models were verified with experimental results. Different passive wireless RF power harvesters offering high selectivity, broadband response and high voltage sensitivity are presented. Measured results show that with an optimal resistance of antenna and diode, it is possible to achieve high RF to DC voltage sensitivity of 0.5 V and efficiency of 20% at −30 dBm antenna input power. Additionally, a wireless harvester (rectenna is built and tested for receiving range performance.
Yan, Rongge; Guo, Xiaoting; Cao, Shaoqing; Zhang, Changgeng
2018-05-01
Magnetically coupled resonance (MCR) wireless power transfer (WPT) system is a promising technology in electric energy transmission. But, if its system parameters are designed unreasonably, output power and transmission efficiency will be low. Therefore, optimized parameters design of MCR WPT has important research value. In the MCR WPT system with designated coil structure, the main parameters affecting output power and transmission efficiency are the distance between the coils, the resonance frequency and the resistance of the load. Based on the established mathematical model and the differential evolution algorithm, the change of output power and transmission efficiency with parameters can be simulated. From the simulation results, it can be seen that output power and transmission efficiency of the two-coil MCR WPT system and four-coil one with designated coil structure are improved. The simulation results confirm the validity of the optimization method for MCR WPT system with designated coil structure.
Optimizing wind farm cable routing considering power losses
DEFF Research Database (Denmark)
Fischetti, Martina; Pisinger, David
2017-01-01
that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. The latter goal has not been addressed in previous work. We present a Mixed-Integer Linear Programming approach to optimize the routing using both exact and math-heuristic methods....... In the power losses computation, wind scenarios are handled eciently as part of the preprocessing, resulting in a MIP model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our...
Electric power systems advanced forecasting techniques and optimal generation scheduling
Catalão, João P S
2012-01-01
Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie
Optimization of heat supply systems employing nuclear power plants
International Nuclear Information System (INIS)
Urbanek, J.
1988-01-01
Decision making on the further development of heat supply systems requires optimization of the parameters. In particular, meeting the demands of peak load ranges is of importance. The heat supply coefficient α and the annual utilization of peak load equipment τ FS have been chosen as the characteristic quantities to describe them. The heat price at the consumer, C V , offers as the optimization criterion. The transport distance, temperature spread of the heating water, and different curves of annual variation of heat consumption on heat supply coefficient and heat price at the consumer. A comparison between heat supply by nuclear power plants and nuclear heating stations verifies the advantage of combined heat and power generation even with longer heat transport distances as compared with local heat supply by nuclear district heating stations based on the criterion of minimum employment of peak load boilers. (author)
AS Migration and Optimization of the Power Integrated Data Network
Zhou, Junjie; Ke, Yue
2018-03-01
In the transformation process of data integration network, the impact on the business has always been the most important reference factor to measure the quality of network transformation. With the importance of the data network carrying business, we must put forward specific design proposals during the transformation, and conduct a large number of demonstration and practice to ensure that the transformation program meets the requirements of the enterprise data network. This paper mainly demonstrates the scheme of over-migrating point-to-point access equipment in the reconstruction project of power data comprehensive network to migrate the BGP autonomous domain to the specified domain defined in the industrial standard, and to smooth the intranet OSPF protocol Migration into ISIS agreement. Through the optimization design, eventually making electric power data network performance was improved on traffic forwarding, traffic forwarding path optimized, extensibility, get larger, lower risk of potential loop, the network stability was improved, and operational cost savings, etc.
Design and optimization of geothermal power generation, heating, and cooling
Kanoglu, Mehmet
Most of the world's geothermal power plants have been built in 1970s and 1980s following 1973 oil crisis. Urgency to generate electricity from alternative energy sources and the fact that geothermal energy was essentially free adversely affected careful designs of plants which would maximize their performance for a given geothermal resource. There are, however, tremendous potentials to improve performance of many existing geothermal power plants by retrofitting, optimizing the operating conditions, re-selecting the most appropriate binary fluid in binary plants, and considering cogeneration such as a district heating and/or cooling system or a system to preheat water entering boilers in industrial facilities. In this dissertation, some representative geothermal resources and existing geothermal power plants in Nevada are investigated to show these potentials. Economic analysis of a typical geothermal resource shows that geothermal heating and cooling may generate up to 3 times as much revenue as power generation alone. A district heating/cooling system is designed for its incorporation into an existing 27 MW air-cooled binary geothermal power plant. The system as designed has the capability to meet the entire heating needs of an industrial park as well as 40% of its cooling needs, generating potential revenues of $14,040,000 per year. A study of the power plant shows that evaporative cooling can increase the power output by up to 29% in summer by decreasing the condenser temperature. The power output of the plant can be increased by 2.8 percent by optimizing the maximum pressure in the cycle. Also, replacing the existing working fluid isobutane by butane, R-114, isopentane, and pentane can increase the power output by up to 2.5 percent. Investigation of some well-known geothermal power generation technologies as alternatives to an existing 12.8 MW single-flash geothermal power plant shows that double-flash, binary, and combined flash/binary designs can increase the
Optimal Wind Power Uncertainty Intervals for Electricity Market Operation
Energy Technology Data Exchange (ETDEWEB)
Wang, Ying; Zhou, Zhi; Botterud, Audun; Zhang, Kaifeng
2018-01-01
It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a twosettlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.
Reference Tracking and Profit Optimization of a Power Plant
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
In this paper we discuss two different methods for implementing reference tracking intro a profit optimization problem of a power plant. It is shown that tracking included as a side constraint results in an significant tracking error only when the reference gradient is large. When tracking...... is included in the cost function, as a quadratic term, the reference is tracked with a small accumulated error. Finally, the two methods are compared both in terms of tracking performance and computational burden....
Optimization criteria for solar and wind power systems
Energy Technology Data Exchange (ETDEWEB)
Salieva, R B
1976-01-01
It is shown that the design of solar and wind power systems requires both the specification of the target function and the optimization of the system with respect to two criteria, namely, the system must be economical (minimum cost to the economy) and it must be reliable (the probability of failure-free operation of the system must be not less than a standard value).
Optimal power and efficiency of quantum Stirling heat engines
Yin, Yong; Chen, Lingen; Wu, Feng
2017-01-01
A quantum Stirling heat engine model is established in this paper in which imperfect regeneration and heat leakage are considered. A single particle which contained in a one-dimensional infinite potential well is studied, and the system consists of countless replicas. Each particle is confined in its own potential well, whose occupation probabilities can be expressed by the thermal equilibrium Gibbs distributions. Based on the Schrödinger equation, the expressions of power output and efficiency for the engine are obtained. Effects of imperfect regeneration and heat leakage on the optimal performance are discussed. The optimal performance region and the optimal values of important parameters of the engine cycle are obtained. The results obtained can provide some guidelines for the design of a quantum Stirling heat engine.
Optimization of ultra-low-power CMOS transistors
International Nuclear Information System (INIS)
Stockinger, M.
2000-01-01
Ultra-low-power CMOS integrated circuits have constantly gained importance due to the fast growing portable electronics market. High-performance applications like mobile telephones ask for high-speed computations and low stand-by power consumption to increase the actual operating time. This means that transistors with low leakage currents and high drive currents have to be provided. Common fabrication methods will soon reach their limits if the on-chip feature size of CMOS technology continues to shrink at this very fast rate. New device architectures will help to keep track with the roadmap of the semiconductor industry. Especially doping profiles offer much freedom for performance improvements as they determine the 'inner functioning' of a transistor. In this work automated doping profile optimization is performed on MOS transistors within the TCAD framework SIESTA. The doping between and under the source/drain wells is discretized on an orthogonal optimization grid facilitating almost arbitrary two-dimensional shapes. A linear optimizer issued to find the optimum doping profile by variation of the doping parameters utilizing numerical device simulations with MINIMOS-NT. Gaussian functions are used in further optimization runs to make the doping profiles smooth. Two device generations are considered, one with 0.25 μm, the other with 0.1 μm gate length. The device geometries and source/drain doping profiles are kept fixed during optimization and supply voltages are chosen suitable for ultra-low-power purposes. In a first optimization study the drive current of NMOS transistors is maximized while keeping the leakage current below a limit of 1 pA/μm. This results in peaking channel doping devices (PCD) with narrow doping peaks placed asymmetrically in the channel. Drive current improvements of 45 % and 71 % for the 0.25 μm and 0.1 μm devices, respectively, are achieved compared to uniformly doped devices. The PCD device is studied in detail and explanations for
Optimized Envelope Tracking Power Supply for Tetra2 Base Station RF Power Amplifier
DEFF Research Database (Denmark)
Høyerby, Mikkel Christian Wendelboe; Andersen, Michael Andreas E.
2008-01-01
An ultra-fast tracking power supply (UFTPS) for envelope tracking in a 50kHz 64-QAM Tetra2 base station power amplification system is demonstrated. A simple method for optimizing the step response of the PID+PD sliding-mode control system is presented and demonstrated, along with a PLL-based scheme...... application. Also demonstrated is the effect of non-zero UFTPS output impedance on envelope tracking performance. At 13W average (156W peak) RF output, a reduction of DC input power consumption from 93W (14% efficiency) to 54W (24% efficiency) is obtained by moving from a fixed RF power amplifier supply...
Thermodynamic performance optimization of a combined power/cooling cycle
International Nuclear Information System (INIS)
Pouraghaie, M.; Atashkari, K.; Besarati, S.M.; Nariman-zadeh, N.
2010-01-01
A combined thermal power and cooling cycle has already been proposed in which thermal energy is used to produce work and to generate a sub-ambient temperature stream that is suitable for cooling applications. The cycle uses ammonia-water mixture as working fluid and is a combination of a Rankine cycle and absorption cycle. The very high ammonia vapor concentration, exiting turbine under certain operating conditions, can provide power output as well as refrigeration. In this paper, the goal is to employ multi-objective algorithms for Pareto approach optimization of thermodynamic performance of the cycle. It has been carried out by varying the selected design variables, namely, turbine inlet pressure (P h ), superheater temperature (T superheat ) and condenser temperature (T condensor ). The important conflicting thermodynamic objective functions that have been considered in this study are turbine work (w T ), cooling capacity (q cool ) and thermal efficiency (η th ) of the cycle. It is shown that some interesting and important relationships among optimal objective functions and decision variables involved in the combined cycle can be discovered consequently. Such important relationships as useful optimal design principles would have not been obtained without the use of a multi-objective optimization approach.
Optimal load allocation of complex ship power plants
International Nuclear Information System (INIS)
Baldi, Francesco; Ahlgren, Fredrik; Melino, Francesco; Gabrielii, Cecilia; Andersson, Karin
2016-01-01
Highlights: • The optimal operation of the prime movers of hybrid ship power plants is addressed. • Both mechanical, electric and thermal power demand are considered. • The problem is modelled as a mixed integer-nonlinear programming problem. • Up to 3% savings can be achieved with hybrid power plants. • Including the thermal power demand improves the solution by up to 4%. - Abstract: In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, the cruise industry is growing in size and impact. In this context, further effort is required for improving the energy efficiency of cruise ship energy systems. In this paper, we propose a generic method for modelling the power plant of an isolated system with mechanical, electric and thermal power demands and for the optimal load allocation of the different components that are able to fulfil the demand. The optimisation problem is presented in the form of a mixed integer linear programming (MINLP) problem, where the number of engines and/or boilers running is represented by the integer variables, while their respective load is represented by the non-integer variables. The individual components are modelled using a combination of first-principle models and polynomial regressions, thus making the system nonlinear. The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea, and used to compare the existing power plant with a hybrid propulsion plant. The results show the benefits brought by using the proposing method, which allow estimating the performance of the hybrid system (for which the load allocation is a non-trivial problem) while also including the contribution of the heat demand. This allows showing that, based on a reference round voyage, up to 3% savings could be achieved by installing the proposed system, compared to the existing one, and that a NPV of 11 kUSD could be achieved already 5 years after the installation of the