An Optimal Control Method for Maximizing the Efficiency of Direct Drive Ocean Wave Energy Extraction System

Science.gov (United States)

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability. PMID:25152913

An optimal control method for maximizing the efficiency of direct drive ocean wave energy extraction system.

Science.gov (United States)

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability.

Feedback control of a Darrieus wind turbine and optimization of the produced energy

Science.gov (United States)

Maurin, T.; Henry, B.; Devos, F.; de Saint Louvent, B.; Gosselin, J.

1984-03-01

A microprocessor-driven control system, applied to the feedback control of a Darrieus wind turbine is presented. The use of a dc machine as a generator to recover the energy and as a motor to start the engine, allows simplified power electronics. The architecture of the control unit is built to ensure four different functions: starting, optimization of the recoverable energy, regulation of the speed, and braking. An experimental study of the system in a wind tunnel allowed optimization of the coefficients of the proportional and integral (pi) control algorithm. The electrical energy recovery was found to be much more efficient using the feedback system than without the control unit. This system allows a better characterization of the wind turbine and a regulation adapted to the wind statistics observed in one given geographical location.

Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

DEFF Research Database (Denmark)

Khoobi, Saeed; Halvaei, Abolfazl; Hajizadeh, Amin

2016-01-01

Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management...... of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy...

Consensus of satellite cluster flight using an energy-matching optimal control method

Science.gov (United States)

Luo, Jianjun; Zhou, Liang; Zhang, Bo

2017-11-01

This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

Energy-Aware Routing Optimization in Dynamic GMPLS Controlled Optical Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Ricciardi, Sergio; Fagertun, Anna Manolova

2012-01-01

In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations...

An optimal control model for load shifting - With application in the energy management of a colliery

International Nuclear Information System (INIS)

Middelberg, Arno; Zhang Jiangfeng; Xia Xiaohua

2009-01-01

This paper presents an optimal control model for the load shifting problem in energy management and its application in a South African colliery. It is illustrated in the colliery scenario that how the optimal control model can be applied to optimize load shifting and improve energy efficiency through the control of conveyor belts. The time-of-use electricity tariff is used as an input to the objective function in order to obtain a solution that minimizes electricity costs and thus maximizes load shifting. The case study yields promising results that show the potential of applying this optimal control model to other industrial Demand Side Management initiatives

Cloud computing-based energy optimization control framework for plug-in hybrid electric bus

International Nuclear Information System (INIS)

Yang, Chao; Li, Liang; You, Sixiong; Yan, Bingjie; Du, Xian

2017-01-01

Considering the complicated characteristics of traffic flow in city bus route and the nonlinear vehicle dynamics, optimal energy management integrated with clustering and recognition of driving conditions in plug-in hybrid electric bus is still a challenging problem. Motivated by this issue, this paper presents an innovative energy optimization control framework based on the cloud computing for plug-in hybrid electric bus. This framework, which includes offline part and online part, can realize the driving conditions clustering in offline part, and the energy management in online part. In offline part, utilizing the operating data transferred from a bus to the remote monitoring center, K-means algorithm is adopted to cluster the driving conditions, and then Markov probability transfer matrixes are generated to predict the possible operating demand of the bus driver. Next in online part, the current driving condition is real-time identified by a well-trained support vector machine, and Markov chains-based driving behaviors are accordingly selected. With the stochastic inputs, stochastic receding horizon control method is adopted to obtain the optimized energy management of hybrid powertrain. Simulations and hardware-in-loop test are carried out with the real-world city bus route, and the results show that the presented strategy could greatly improve the vehicle fuel economy, and as the traffic flow data feedback increases, the fuel consumption of every plug-in hybrid electric bus running in a specific bus route tends to be a stable minimum. - Highlights: • Cloud computing-based energy optimization control framework is proposed. • Driving cycles are clustered into 6 types by K-means algorithm. • Support vector machine is employed to realize the online recognition of driving condition. • Stochastic receding horizon control-based energy management strategy is designed for plug-in hybrid electric bus. • The proposed framework is verified by simulation and hard

Energy optimal control strategies for electro motors; low-cost and sensorless PWM-VSI based induction motor control. Vol. 1: Main report, appendix and annex

Energy Technology Data Exchange (ETDEWEB)

Abrahamsen, F

1998-02-01

When variable speed induction motor drives are used in applications that run at low load for long periods, energy can be saved by reducing the motor flux at low load. In this report the efficiency of 2.2 kW standard and high-efficiency motor drives are investigated experimentally with efficiency optimized and constant flux control, with sinusoidal and PWM voltage supply and with varying switching frequency. Steady-state motor models are developed and verified experimentally, and are used to analyze and develop efficiency optimizing control strategies. Four energy optimal control strategies are tested experimentally: cos({phi}) control, model-based control, off-line calculated airgap flux control and stator current/input power minimising search control. Their dynamical properties and their ability to reject load disturbances are analysed. Their ability to save energy is tested on a water pump system. For a typical predefined test-cycle the energy optimal control reduces the energy consumption with 10% compared with classical constant V/Hz control. (au)

Optimal energy management strategy for self-reconfigurable batteries

International Nuclear Information System (INIS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2017-01-01

This paper proposes a novel energy management strategy for multi-cell high voltage batteries where the current through each cell can be controlled, called self-reconfigurable batteries. An optimized control strategy further enhances the energy efficiency gained by the hardware architecture of those batteries. Currently, achieving cell equalization by using the active balancing circuits is considered as the best way to optimize the energy efficiency of the battery pack. This study demonstrates that optimizing the energy efficiency of self-reconfigurable batteries is no more strongly correlated to the cell balancing. According to the features of this novel battery architecture, the energy management strategy is formulated as nonlinear dynamic optimization problem. To solve this optimal control, an optimization algorithm that generates the optimal discharge policy for a given driving cycle is developed based on dynamic programming and code vectorization. The simulation results show that the designed energy management strategy maximizes the system efficiency across the battery lifetime over conventional approaches. Furthermore, the present energy management strategy can be implemented online due to the reduced complexity of the optimization algorithm. - Highlights: • The energy efficiency of self-reconfigurable batteries is maximized. • The energy management strategy for the battery is formulated as optimal control problem. • Developing an optimization algorithm using dynamic programming techniques and code vectorization. • Simulation studies are conducted to validate the proposed optimal strategy.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

Science.gov (United States)

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

Science.gov (United States)

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach

Optimal control of energy extraction in LES of large wind farms

Science.gov (United States)

Meyers, Johan; Goit, Jay; Munters, Wim

2014-11-01

We investigate the use of optimal control combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large ``infinite'' wind farms and in finite farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with an actuator-disk representation of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in the actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. In a first infinite wind-farm case, we find that farm power is increases by approximately 16% over one hour of operation. This comes at the cost of a deceleration of the outer layer of the boundary layer. A detailed analysis of energy balances is presented, and a comparison is made between infinite and finite farm cases, for which boundary layer entrainment plays an import role. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Govern.

Fuzzy-TLBO optimal reactive power control variables planning for energy loss minimization

International Nuclear Information System (INIS)

Moghadam, Ahmad; Seifi, Ali Reza

2014-01-01

Highlights: • A new approach to the problem of optimal reactive power control variables planning is proposed. • The energy loss minimization problem has been formulated by modeling the load of system as a Load Duration Curve. • To solving the energy loss problem, the classic methods and the evolutionary methods are used. • A new proposed fuzzy teaching–learning based algorithm is applied to energy loss problem. • Simulations are done to show the effectiveness and superiority of the proposed algorithm compared with other methods. - Abstract: This paper offers a new approach to the problem of optimal reactive power control variables planning (ORPVCP). The basic idea is division of Load Duration Curve (LDC) into several time intervals with constant active power demand in each interval and then solving the energy loss minimization (ELM) problem to obtain an optimal initial set of control variables of the system so that is valid for all time intervals and can be used as an initial operating condition of the system. In this paper, the ELM problem has been solved by the linear programming (LP) and fuzzy linear programming (Fuzzy-LP) and evolutionary algorithms i.e. MHBMO and TLBO and the results are compared with the proposed Fuzzy-TLBO method. In the proposed method both objective function and constraints are evaluated by membership functions. The inequality constraints are embedded into the fitness function by the membership function of the fuzzy decision and the problem is modeled by fuzzy set theory. The proposed Fuzzy-TLBO method is performed on the IEEE 30 bus test system by considering two different LDC; and it is shown that using this method has further minimized objective function than original TLBO and other optimization techniques and confirms its potential to solve the ORPCVP problem with considering ELM as the objective function

Optimal Control Method for Wind Farm to Support Temporary Primary Frequency Control with Minimized Wind Energy Cost

DEFF Research Database (Denmark)

Wang, Haijiao; Chen, Zhe; Jiang, Quanyuan

2015-01-01

This study proposes an optimal control method for variable speed wind turbines (VSWTs) based wind farm (WF) to support temporary primary frequency control. This control method consists of two layers: temporary frequency support control (TFSC) of the VSWT, and temporary support power optimal...... dispatch (TSPOD) of the WF. With TFSC, the VSWT could temporarily provide extra power to support system frequency under varying and wide-range wind speed. In the WF control centre, TSPOD optimally dispatches the frequency support power orders to the VSWTs that operate under different wind speeds, minimises...... the wind energy cost of frequency support, and satisfies the support capabilities of the VSWTs. The effectiveness of the whole control method is verified in the IEEE-RTS built in MATLABSimulink, and compared with a published de-loading method....

Online optimal control of variable refrigerant flow and variable air volume combined air conditioning system for energy saving

International Nuclear Information System (INIS)

Zhu, Yonghua; Jin, Xinqiao; Du, Zhimin; Fang, Xing

2015-01-01

The variable refrigerant flow (VRF) and variable air volume (VAV) combined air conditioning system can solve the problem of the VRF system in outdoor air ventilation while taking advantage of its high part load energy efficiency. Energy performance of the combined air conditioning system can also be optimized by joint control of both the VRF and the VAV parts. A model-based online optimal control strategy for the combined air conditioning system is presented. Simplified adaptive models of major components of the combined air conditioning system are firstly developed for predicting system performances. And a cost function in terms of energy consumption and thermal comfort is constructed. Genetic algorithm is used to search for the optimal control sets. The optimal control strategy is tested and evaluated through two case studies based on the simulation platform. Results show that the optimal strategy can effectively reduce energy consumption of the combined air conditioning system while maintaining acceptable thermal comfort. - Highlights: • A VRF and VAV combined system is proposed. • A model-based online optimal control strategy is proposed for the combined system. • The strategy can reduce energy consumption without sacrificing thermal comfort. • Novel simplified adaptive models are firstly developed for the VRF system

Tuning for optimal performance in angle control, uniformity, and energy purity

International Nuclear Information System (INIS)

Liebert, Reuel B.; Olson, Joseph C.; Arevalo, Edwin A.; Downey, Daniel F.

2005-01-01

Advances in reducing the sizes of device structures and line widths place increasing demands on the accuracy of dopant placement and the control of dopant motion during activation anneals. Serial process high current ion implantation systems seek to produce beams in which the angles are controlled to high precision avoiding the angles introduced by conical structures used for holding wafers on spinning discs in batch systems. However, ion optical corrections and control of incident beam angle, dose uniformity, high throughput and energy purity often present apparently contradictory requirements in machine design. Data is presented to illustrate that tuning procedures can be used to simultaneously optimize angle purity in both x and y planes as well as control energy purity and dose uniformity

Energy-economical optimization of industrial sites

International Nuclear Information System (INIS)

Berthold, A.; Saliba, S.; Franke, R.

2015-01-01

The holistic optimization of an industrial estate networks all electrical components of a location and combines energy trading, energy management and production processes. This allows to minimize the energy consumption from the supply network and to relieve the power grid and to maximize the profitability of the industrial self-generation. By analyzing the potential is detected and the cost of optimization solution is estimated. The generation-side optimization is supported through demand-side optimization (demand response). Through a real-time optimization the of Use of fuels is managed, controlled and optimized. [de

Quad-rotor flight path energy optimization

Science.gov (United States)

Kemper, Edward

Quad-Rotor unmanned areal vehicles (UAVs) have been a popular area of research and development in the last decade, especially with the advent of affordable microcontrollers like the MSP 430 and the Raspberry Pi. Path-Energy Optimization is an area that is well developed for linear systems. In this thesis, this idea of path-energy optimization is extended to the nonlinear model of the Quad-rotor UAV. The classical optimization technique is adapted to the nonlinear model that is derived for the problem at hand, coming up with a set of partial differential equations and boundary value conditions to solve these equations. Then, different techniques to implement energy optimization algorithms are tested using simulations in Python. First, a purely nonlinear approach is used. This method is shown to be computationally intensive, with no practical solution available in a reasonable amount of time. Second, heuristic techniques to minimize the energy of the flight path are tested, using Ziegler-Nichols' proportional integral derivative (PID) controller tuning technique. Finally, a brute force look-up table based PID controller is used. Simulation results of the heuristic method show that both reliable control of the system and path-energy optimization are achieved in a reasonable amount of time.

An energy-optimal solution for transportation control of cranes with double pendulum dynamics: Design and experiments

Science.gov (United States)

Sun, Ning; Wu, Yiming; Chen, He; Fang, Yongchun

2018-03-01

Underactuated cranes play an important role in modern industry. Specifically, in most situations of practical applications, crane systems exhibit significant double pendulum characteristics, which makes the control problem quite challenging. Moreover, most existing planners/controllers obtained with standard methods/techniques for double pendulum cranes cannot minimize the energy consumption when fulfilling the transportation tasks. Therefore, from a practical perspective, this paper proposes an energy-optimal solution for transportation control of double pendulum cranes. By applying the presented approach, the transportation objective, including fast trolley positioning and swing elimination, is achieved with minimized energy consumption, and the residual oscillations are suppressed effectively with all the state constrains being satisfied during the entire transportation process. As far as we know, this is the first energy-optimal solution for transportation control of underactuated double pendulum cranes with various state and control constraints. Hardware experimental results are included to verify the effectiveness of the proposed approach, whose superior performance is reflected by being experimentally compared with some comparative controllers.

Information Support of Optimal Control of Modes of Electric Systems with Renewable Energy Sources

Directory of Open Access Journals (Sweden)

Michalina Gryniewicz-Jaworska

2017-12-01

Full Text Available To provide necessary quality of electric energy and reliable supply and reduce environmental contamination as a result of energy units operation, renewable sources of energy (RSE, in particular solar electric stations (SES, wind electric stations (WES and small hydropower stations (SHES are intensively developed. The paper considers the conditions of optimality of renewable sources of energy (RSE functioning in electric systems, controllability of which is limited by the impact of non-stable weather conditions. The influence of control system information support on the efficiency of RSE usage is shown.

Energy Management Strategy in Consideration of Battery Health for PHEV via Stochastic Control and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Yuying Wang

2017-11-01

Full Text Available This paper presents an energy management strategy for plug-in hybrid electric vehicles (PHEVs that not only tries to minimize the energy consumption, but also considers the battery health. First, a battery model that can be applied to energy management optimization is given. In this model, battery health damage can be estimated in the different states of charge (SOC and temperature of the battery pack. Then, because of the inevitability that limiting the battery health degradation will increase energy consumption, a Pareto energy management optimization problem is formed. This multi-objective optimal control problem is solved numerically by using stochastic dynamic programming (SDP and particle swarm optimization (PSO for satisfying the vehicle power demand and considering the tradeoff between energy consumption and battery health at the same time. The optimization solution is obtained offline by utilizing real historical traffic data and formed as mappings on the system operating states so as to implement online in the actual driving conditions. Finally, the simulation results carried out on the GT-SUITE-based PHEV test platform are illustrated to demonstrate that the proposed multi-objective optimal control strategy would effectively yield benefits.

To the Problem of Energy Security and Energy Objects Control Optimization

International Nuclear Information System (INIS)

Gotsiridze, A.; Abzianidze, D.

2004-01-01

One of the method of studying energy security of energy objects is evaluation of character and range of main safety risk influence with the help of indicator analysis. In the work is also reviewed an example of applying modern management theory to the group of tasks, connected with the optimal management of energy objects, which is the basis of their secure functioning. (authors)

Optimization analysis of propulsion motor control efficiency

Directory of Open Access Journals (Sweden)

CAI Qingnan

2017-12-01

Full Text Available [Objectives] This paper aims to strengthen the control effect of propulsion motors and decrease the energy used during actual control procedures.[Methods] Based on the traditional propulsion motor equivalence circuit, we increase the iron loss current component, introduce the definition of power matching ratio, calculate the highest efficiency of a motor at a given speed and discuss the flux corresponding to the power matching ratio with the highest efficiency. In the original motor vector efficiency optimization control module, an efficiency optimization control module is added so as to achieve motor efficiency optimization and energy conservation.[Results] MATLAB/Simulink simulation data shows that the efficiency optimization control method is suitable for most conditions. The operation efficiency of the improved motor model is significantly higher than that of the original motor model, and its dynamic performance is good.[Conclusions] Our motor efficiency optimization control method can be applied in engineering to achieve energy conservation.

Optimally efficient swimming in hyper-redundant mechanisms: control, design, and energy recovery

International Nuclear Information System (INIS)

Wiens, A J; Nahon, M

2012-01-01

Hyper-redundant mechanisms (HRMs), also known as snake-like robots, are highly adaptable during locomotion on land. Researchers are currently working to extend their capabilities to aquatic environments through biomimetic undulatory propulsion. In addition to increasing the versatility of the system, truly biomimetic swimming could also provide excellent locomotion efficiency. Unfortunately, the complexity of the system precludes the development of a functional solution to achieve this. To explore this problem, a rapid optimization process is used to generate efficient HRM swimming gaits. The low computational cost of the approach allows for multiple optimizations over a broad range of system conditions. By observing how these conditions affect optimal kinematics, a number of new insights are developed regarding undulatory swimming in robotic systems. Two key conditions are varied within the study, swimming speed and energy recovery. It is found that the swimmer mimics the speed control behaviour of natural fish and that energy recovery drastically increases the system's efficiency. Remarkably, this efficiency increase is accompanied by a distinct change in swimming kinematics. With energy recovery, the swimmer converges to a clearly anguilliform gait, without, it tends towards the carangiform mode. (paper)

Optimal Active Power Control of A Wind Farm Equipped with Energy Storage System based on Distributed Model Predictive Control

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

2016-01-01

This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...

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...

Probability of Interference-Optimal and Energy-Efficient Analysis for Topology Control in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ning Li

2016-11-01

Full Text Available Because wireless sensor networks (WSNs have been widely used in recent years, how to reduce their energy consumption and interference has become a major issue. Topology control is a common and effective approach to improve network performance, such as reducing the energy consumption and network interference, improving the network connectivity, etc. Many topology control algorithms reduce network interference by dynamically adjusting the node transmission range. However, reducing the network interference by adjusting the transmission range is probabilistic. Therefore, in this paper, we analyze the probability of interference-optimality for the WSNs and prove that the probability of interference-optimality increases with the increasing of the original transmission range. Under a specific transmission range, the probability reaches the maximum value when the transmission range is 0.85r in homogeneous networks and 0.84r in heterogeneous networks. In addition, we also prove that when the network is energy-efficient, the network is also interference-optimal with probability 1 both in the homogeneous and heterogeneous networks.

Energy-optimal electrical excitation of nerve fibers.

Science.gov (United States)

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Optimal control of operation efficiency of belt conveyor systems

International Nuclear Information System (INIS)

Zhang, Shirong; Xia, Xiaohua

2010-01-01

The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study.

Optimal control of operation efficiency of belt conveyor systems

Energy Technology Data Exchange (ETDEWEB)

Zhang, Shirong [Department of Automation, Wuhan University, Wuhan 430072 (China); Xia, Xiaohua [Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002 (South Africa)

2010-06-15

The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study. (author)

Two-objective on-line optimization of supervisory control strategy

Energy Technology Data Exchange (ETDEWEB)

Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal (Canada)

2004-09-01

The set points of supervisory control strategy are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values of zone temperatures, supply duct static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes all the individual component models developed and validated against the monitored data of an existing VAV system. It serves to calculate energy use during the optimization process, whereas the actual energy use is determined by using monitoring data and the appropriate validated component models. A comparison, done for one summer week, of actual and optimal energy use shows that the on-line implementation of a genetic algorithm optimization program to determine the optimal set points of supervisory control strategy could save energy by 19.5%, while satisfying the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy than the application of the one-objective optimization problem. (Author)

Power control based on particle swarm optimization of grid-connected inverter for hybrid renewable energy system

International Nuclear Information System (INIS)

García-Triviño, Pablo; Gil-Mena, Antonio José; Llorens-Iborra, Francisco; García-Vázquez, Carlos Andrés; Fernández-Ramírez, Luis M.; Jurado, Francisco

2015-01-01

Highlights: • Three PSO-based PI controllers for a grid-connected inverter were presented. • Two online PSO-based PI controllers were compared with an offline PSO-tuned PI. • The HRES and the inverter were evaluated under power changes and grid voltage sags. • Online ITAE-based PSO reduced ITAE (current THD) by 15.24% (5.32%) versus offline one. - Abstract: This paper is focused on the study of particle swarm optimization (PSO)-based PI controllers for the power control of a grid-connected inverter supplied from a hybrid renewable energy system. It is composed of two renewable energy sources (wind turbine and photovoltaic – PV – solar panels) and two energy storage systems (battery and hydrogen system, integrated by fuel cell and electrolyzer). Three PSO-based PI controllers are implemented: (1) conventional PI controller with offline tuning by PSO algorithm based on the integral time absolute error (ITAE) index; (2) PI controllers with online self-tuning by PSO algorithm based on the error; and (3) PI controllers with online self-tuning by PSO algorithm based on the ITAE index. To evaluate and compare the three controllers, the hybrid renewable energy system and the grid-connected inverter are simulated under changes in the active and reactive power values, as well as under a grid voltage sag. The results show that the online PSO-based PI controllers that optimize the ITAE index achieves the best response

An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems

International Nuclear Information System (INIS)

Huang, Yanjun; Khajepour, Amir; Ding, Haitao; Bagheri, Farshid; Bahrami, Majid

2017-01-01

Highlights: • A novel two-layer energy-saving controller for automotive A/C-R system is developed. • A set-point optimizer at the outer loop is designed based on the steady state model. • A sliding mode controller in the inner loop is built. • Extensively experiments studies show that about 9% energy can be saving by this controller. - Abstract: This paper presents an energy-saving controller for automotive air-conditioning/refrigeration (A/C-R) systems. With their extensive application in homes, industry, and vehicles, A/C-R systems are consuming considerable amounts of energy. The proposed controller consists of two different time-scale layers. The outer or the slow time-scale layer called a set-point optimizer is used to find the set points related to energy efficiency by using the steady state model; whereas, the inner or the fast time-scale layer is used to track the obtained set points. In the inner loop, thanks to its robustness, a sliding mode controller (SMC) is utilized to track the set point of the cargo temperature. The currently used on/off controller is presented and employed as a basis for comparison to the proposed controller. More importantly, the real experimental results under several disturbed scenarios are analysed to demonstrate how the proposed controller can improve performance while reducing the energy consumption by 9% comparing with the on/off controller. The controller is suitable for any type of A/C-R system even though it is applied to an automotive A/C-R system in this paper.

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...

Optimal control in thermal engineering

CERN Document Server

Badescu, Viorel

2017-01-01

This book is the first major work covering applications in thermal engineering and offering a comprehensive introduction to optimal control theory, which has applications in mechanical engineering, particularly aircraft and missile trajectory optimization. The book is organized in three parts: The first part includes a brief presentation of function optimization and variational calculus, while the second part presents a summary of the optimal control theory. Lastly, the third part describes several applications of optimal control theory in solving various thermal engineering problems. These applications are grouped in four sections: heat transfer and thermal energy storage, solar thermal engineering, heat engines and lubrication.Clearly presented and easy-to-use, it is a valuable resource for thermal engineers and thermal-system designers as well as postgraduate students.

Advanced experimental method for self-optimizing control system to a new energy converce plant

International Nuclear Information System (INIS)

Vasiliev, V.V.

1992-01-01

The progress in the development and studying of new methods of producing electric energy, based on direct conversion of heat, light, fuel or chemical energy into electric energy, raises the problem of more effective use of their power characteristics. In this paper, disclosure is made of a self-optimizing control system for an abject with a unimodal quality function. The system comprises an object, a divider, a band-pass filter, an averaging filter, a multiplier, a final control element, and adder and further includes a search signal generator. The fashion and the system are presented in the USSR No. 684510, in the USA No. 4179730, in France No. 2386854, in Germany No. 2814963, in Japan No. 1369882

Virtual Power Plant and Microgrids controller for Energy Management based on optimization techniques

Directory of Open Access Journals (Sweden)

Maher G. M. Abdolrasol

2017-06-01

Full Text Available This paper discuss virtual power plant (VPP and Microgrid controller for energy management system (EMS based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA and particle swarm optimization algorithm (PSO. The research proposes use of multi Microgrid in the distribution networks to aggregate the power form distribution generation and form it into single Microgrid and let these Microgrid deal directly with the central organizer called virtual power plant. VPP duties are price forecast, demand forecast, weather forecast, production forecast, shedding loads, make intelligent decision and for aggregate & optimizes the data. This huge system has been tested and simulated by using Matlab simulink. These paper shows optimizations of two methods were really significant in the results. But BSA is better than PSO to search for better parameters which could make more power saving as in the results and the discussion.

An Optimal Control Strategy for DC Bus Voltage Regulation in Photovoltaic System with Battery Energy Storage

Directory of Open Access Journals (Sweden)

Muhamad Zalani Daud

2014-01-01

Full Text Available This paper presents an evaluation of an optimal DC bus voltage regulation strategy for grid-connected photovoltaic (PV system with battery energy storage (BES. The BES is connected to the PV system DC bus using a DC/DC buck-boost converter. The converter facilitates the BES power charge/discharge to compensate for the DC bus voltage deviation during severe disturbance conditions. In this way, the regulation of DC bus voltage of the PV/BES system can be enhanced as compared to the conventional regulation that is solely based on the voltage-sourced converter (VSC. For the grid side VSC (G-VSC, two control methods, namely, the voltage-mode and current-mode controls, are applied. For control parameter optimization, the simplex optimization technique is applied for the G-VSC voltage- and current-mode controls, including the BES DC/DC buck-boost converter controllers. A new set of optimized parameters are obtained for each of the power converters for comparison purposes. The PSCAD/EMTDC-based simulation case studies are presented to evaluate the performance of the proposed optimized control scheme in comparison to the conventional methods.

An optimal control strategy for DC bus voltage regulation in photovoltaic system with battery energy storage.

Science.gov (United States)

Daud, Muhamad Zalani; Mohamed, Azah; Hannan, M A

2014-01-01

This paper presents an evaluation of an optimal DC bus voltage regulation strategy for grid-connected photovoltaic (PV) system with battery energy storage (BES). The BES is connected to the PV system DC bus using a DC/DC buck-boost converter. The converter facilitates the BES power charge/discharge to compensate for the DC bus voltage deviation during severe disturbance conditions. In this way, the regulation of DC bus voltage of the PV/BES system can be enhanced as compared to the conventional regulation that is solely based on the voltage-sourced converter (VSC). For the grid side VSC (G-VSC), two control methods, namely, the voltage-mode and current-mode controls, are applied. For control parameter optimization, the simplex optimization technique is applied for the G-VSC voltage- and current-mode controls, including the BES DC/DC buck-boost converter controllers. A new set of optimized parameters are obtained for each of the power converters for comparison purposes. The PSCAD/EMTDC-based simulation case studies are presented to evaluate the performance of the proposed optimized control scheme in comparison to the conventional methods.

Joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids

International Nuclear Information System (INIS)

Baldi, Simone; Karagevrekis, Athanasios; Michailidis, Iakovos T.; Kosmatopoulos, Elias B.

2015-01-01

Highlights: • Energy efficient operation of photovoltaic-equipped interconnected microgrids. • Optimized energy demand for a block of heterogeneous buildings with different sizes. • Multiobjective optimization: matching demand and supply taking into account thermal comfort. • Intelligent control mechanism for heating, ventilating, and air conditioning units. • Optimization of energy consumption and thermal comfort at the aggregate microgrid level. - Abstract: Electrical smart microgrids equipped with small-scale renewable-energy generation systems are emerging progressively as an alternative or an enhancement to the central electrical grid: due to the intermittent nature of the renewable energy sources, appropriate algorithms are required to integrate these two typologies of grids and, in particular, to perform efficiently dynamic energy demand and distributed generation management, while guaranteeing satisfactory thermal comfort for the occupants. This paper presents a novel control algorithm for joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids. Energy demand shaping is achieved via an intelligent control mechanism for heating, ventilating, and air conditioning units. The intelligent control mechanism takes into account the available solar energy, the building dynamics and the thermal comfort of the buildings’ occupants. The control design is accomplished in a simulation-based fashion using an energy simulation model, developed in EnergyPlus, of an interconnected microgrid. Rather than focusing only on how each building behaves individually, the optimization algorithm employs a central controller that allows interaction among the buildings of the microgrid. The control objective is to optimize the aggregate microgrid performance. Simulation results demonstrate that the optimization algorithm efficiently integrates the microgrid with the photovoltaic system that provides free electric energy: in

Optimal Control Development System for Electrical Drives

Directory of Open Access Journals (Sweden)

Marian GAICEANU

2008-08-01

Full Text Available In this paper the optimal electrical drive development system is presented. It consists of both electrical drive types: DC and AC. In order to implement the optimal control for AC drive system an Altivar 71 inverter, a Frato magnetic particle brake (as load, three-phase induction machine, and dSpace 1104 controller have been used. The on-line solution of the matrix Riccati differential equation (MRDE is computed by dSpace 1104 controller, based on the corresponding feedback signals, generating the optimal speed reference for the AC drive system. The optimal speed reference is tracked by Altivar 71 inverter, conducting to energy reduction in AC drive. The classical control (consisting of rotor field oriented control with PI controllers and the optimal one have been implemented by designing an adequate ControlDesk interface. The three-phase induction machine (IM is controlled at constant flux. Therefore, the linear dynamic mathematical model of the IM has been obtained. The optimal control law provides transient regimes with minimal energy consumption. The obtained solution by integration of the MRDE is orientated towards the numerical implementation-by using a zero order hold. The development system is very useful for researchers, doctoral students or experts training in electrical drive. The experimental results are shown.

Energy optimization in mobile sensor networks

Science.gov (United States)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while

Optimal Electrical Energy Slewing for Reaction Wheel Spacecraft

Science.gov (United States)

Marsh, Harleigh Christian

The results contained in this dissertation contribute to a deeper level of understanding to the energy required to slew a spacecraft using reaction wheels. This work addresses the fundamental manner in which spacecrafts are slewed (eigenaxis maneuvering), and demonstrates that this conventional maneuver can be dramatically improved upon in regards to reduction of energy, dissipative losses, as well as peak power. Energy is a fundamental resource that effects every asset, system, and subsystem upon a spacecraft, from the attitude control system which orients the spacecraft, to the communication subsystem to link with ground stations, to the payloads which collect scientific data. For a reaction wheel spacecraft, the attitude control system is a particularly heavy load on the power and energy resources on a spacecraft. The central focus of this dissertation is reducing the burden which the attitude control system places upon the spacecraft in regards to electrical energy, which is shown in this dissertation to be a challenging problem to computationally solve and analyze. Reducing power and energy demands can have a multitude of benefits, spanning from the initial design phase, to in-flight operations, to potentially extending the mission life of the spacecraft. This goal is approached from a practical standpoint apropos to an industry-flight setting. Metrics to measure electrical energy and power are developed which are in-line with the cost associated to operating reaction wheel based attitude control systems. These metrics are incorporated into multiple families of practical high-dimensional constrained nonlinear optimal control problems to reduce the electrical energy, as well as the instantaneous power burdens imposed by the attitude control system upon the spacecraft. Minimizing electrical energy is shown to be a problem in L1 optimal control which is nonsmooth in regards to state variables as well as the control. To overcome the challenge of nonsmoothness, a

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

Directory of Open Access Journals (Sweden)

Shuai Su

2016-02-01

Full Text Available Increasing attention is being paid to the energy efficiency in metro systems to reduce the operational cost and to advocate the sustainability of railway systems. Classical research has studied the energy-efficient operational strategy and the energy-efficient system design separately to reduce the traction energy consumption. This paper aims to combine the operational strategies and the system design by analyzing how the infrastructure and vehicle parameters of metro systems influence the operational traction energy consumption. Firstly, a solution approach to the optimal train control model is introduced, which is used to design the Optimal Train Control Simulator(OTCS. Then, based on the OTCS, the performance of some important energy-efficient system design strategies is investigated to reduce the trains’ traction energy consumption, including reduction of the train mass, improvement of the kinematic resistance, the design of the energy-saving gradient, increasing the maximum traction and braking forces, introducing regenerative braking and timetable optimization. As for these energy-efficient strategies, the performances are finally evaluated using the OTCS with the practical operational data of the Beijing Yizhuang metro line. The proposed approach gives an example to quantitatively analyze the energy reduction of different strategies in the system design procedure, which may help the decision makers to have an overview of the energy-efficient performances and then to make decisions by balancing the costs and the benefits.

Optimal Control Of Nonlinear Wave Energy Point Converters

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Zhou, Qiang; Kramer, Morten

2013-01-01

idea behind the control strategy is to enforce the stationary velocity response of the absorber into phase with the wave excitation force at any time. The controller is optimal under monochromatic wave excitation. It is demonstrated that the devised causal controller, in plane irregular sea states...

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

Methods for Distributed Optimal Energy Management

DEFF Research Database (Denmark)

Brehm, Robert

The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast to convent......The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast...... to conventional centralised optimal energy flow management systems, here-in, focus is set on how optimal energy management can be achieved in a decentralised distributed architecture such as a multi-agent system. Distributed optimisation methods are introduced, targeting optimisation of energy flow in virtual......-consumption of renewable energy resources in low voltage grids. It can be shown that this method prevents mutual discharging of batteries and prevents peak loads, a supervisory control instance can dictate the level of autarchy from the utility grid. Further it is shown that the problem of optimal energy flow management...

Optimal fuzzy logic-based PID controller for load-frequency control including superconducting magnetic energy storage units

International Nuclear Information System (INIS)

Pothiya, Saravuth; Ngamroo, Issarachai

2008-01-01

This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters

Hybrid vehicle energy management: singular optimal control

NARCIS (Netherlands)

Delprat, S.; Hofman, T.; Paganelli, S.

2017-01-01

Hybrid vehicle energymanagement is often studied in simulation as an optimal control problem. Under strict convexity assumptions, a solution can be developed using Pontryagin’s minimum principle. In practice, however, many engineers do not formally check these assumptions resulting in the possible

Optimization control of LNG regasification plant using Model Predictive Control

Science.gov (United States)

Wahid, A.; Adicandra, F. F.

2018-03-01

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

An Optimization Scheme for Water Pump Control in Smart Fish Farm with Efficient Energy Consumption

Directory of Open Access Journals (Sweden)

Israr Ullah

2018-06-01

Full Text Available Healthy fish production requires intensive care and ensuring stable and healthy production environment inside the farm tank is a challenging task. An Internet of Things (IoT based automated system is highly desirable that can continuously monitor the fish tanks with optimal resources utilization. Significant cost reduction can be achieved if farm equipment and water pumps are operated only when required using optimization schemes. In this paper, we present a general system design for smart fish farms. We have developed an optimization scheme for water pump control to maintain desired water level in fish tank with efficient energy consumption through appropriate selection of pumping flow rate and tank filling level. Proposed optimization scheme attempts to achieve a trade-off between pumping duration and flow rate through selection of optimized water level. Kalman filter algorithm is applied to remove error in sensor readings. We observed through simulation results that optimization scheme achieve significant reduction in energy consumption as compared to the two alternate schemes, i.e., pumping with maximum and minimum flow rates. Proposed system can help in collecting the data about the farm for long-term analysis and better decision making in future for efficient resource utilization and overall profit maximization.

Modeling and energy efficiency optimization of belt conveyors

International Nuclear Information System (INIS)

Zhang, Shirong; Xia, Xiaohua

2011-01-01

Highlights: → We take optimization approach to improve operation efficiency of belt conveyors. → An analytical energy model, originating from ISO 5048, is proposed. → Then an off-line and an on-line parameter estimation schemes are investigated. → In a case study, six optimization problems are formulated with solutions in simulation. - Abstract: The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment and operation levels. Specifically, variable speed control, an equipment level intervention, is recommended to improve operation efficiency of belt conveyors. However, the current implementations mostly focus on lower level control loops without operational considerations at the system level. This paper intends to take a model based optimization approach to improve the efficiency of belt conveyors at the operational level. An analytical energy model, originating from ISO 5048, is firstly proposed, which lumps all the parameters into four coefficients. Subsequently, both an off-line and an on-line parameter estimation schemes are applied to identify the new energy model, respectively. Simulation results are presented for the estimates of the four coefficients. Finally, optimization is done to achieve the best operation efficiency of belt conveyors under various constraints. Six optimization problems of a typical belt conveyor system are formulated, respectively, with solutions in simulation for a case study.

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

Science.gov (United States)

Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.

2016-08-01

Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.

Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage

International Nuclear Information System (INIS)

Safari, S.; Ardehali, M.M.; Sirizi, M.J.

2013-01-01

Highlights: ► Optimized fuzzy logic controller for a hybrid green power system is developed. ► PSO algorithm is used to optimize membership functions of controller. ► Optimized fuzzy logic controller results in lower O and M costs and LPSP. ► Optimization results in less variation of battery state of charge. - Abstract: The objective of this study is to develop an optimized fuzzy logic controller (FLC) for operating an autonomous hybrid green power system (HGPS) based on the particle swarm optimization (PSO) algorithm. An electrolyzer produces hydrogen from surplus energy generated by the wind turbine and photovoltaic array of HGPS for later use by a fuel cell. The PSO algorithm is used to optimize membership functions of the FLC. The FLC inputs are (a) net power flow and (b) batteries state of charge (SOC) and FLC output determines the time for hydrogen production or consumption. Actual data for weekly residential load, wind speed, ambient temperature, and solar irradiation are used for performance simulation and analysis of the HGPS examined. The weekly operation and maintenance (O and M) costs and the loss of power supply probability (LPSP) are considered in the optimization procedure. It is determined that FLC optimization results in (a) reduced fluctuations in batteries SOC which translates into longer life for batteries and the average SOC is increased by 6.18% and (b) less working hours for fuel cell, when the load is met by wind and PV. It is found that the optimized FLC results in lower O and M costs and LPSP by 57% and 33%, respectively, as compared to its un-optimized counterpart. In addition, a reduction of 18% in investment cost is achievable by optimal sizing and reducing the capacity of HGPS equipment.

Optimal energy management of HEVs with hybrid storage system

International Nuclear Information System (INIS)

Vinot, E.; Trigui, R.

2013-01-01

Highlights: • A battery and ultra-capacitor system for parallel hybrid vehicle is considered. • Optimal management using Pontryagin’s minimum principle is developed. • Battery stress limitation is taken into account by means of RMS current. • Rule based management approaching the optimal control is proposed. • Comparison between rule based and optimal management are proposed using Pareto front. - Abstract: Energy storage systems are a key point in the design and development of electric and hybrid vehicles. In order to reduce the battery size and its current stress, a hybrid storage system, where a battery is coupled with an electrical double-layer capacitor (EDLC) is considered in this paper. The energy management of such a configuration is not obvious and the optimal operation concerning the energy consumption and battery RMS current has to be identified. Most of the past work on the optimal energy management of HEVs only considered one additional power source. In this paper, the control of a hybrid vehicle with a hybrid storage system (HSS), where two additional power sources are used, is presented. Applying the Pontryagin’s minimum principle, an optimal energy management strategy is found and compared to a rule-based parameterized control strategy. Simulation results are shown and discussed. Applied on a small compact car, optimal and ruled-based methods show that gains of fuel consumption and/or a battery RMS current higher than 15% may be obtained. The paper also proves that a well tuned rule-based algorithm presents rather good performances when compared to the optimal strategy and remains relevant for different driving cycles. This rule-based algorithm may easily be implemented in a vehicle prototype or in an HIL test bench

Modeling and optimization of HVAC energy consumption

Energy Technology Data Exchange (ETDEWEB)

Kusiak, Andrew; Li, Mingyang; Tang, Fan [Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242 - 1527 (United States)

2010-10-15

A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan, and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the setpoint of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (author)

Direct Optimal Control of Duffing Dynamics

Science.gov (United States)

Oz, Hayrani; Ramsey, John K.

2002-01-01

The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.

Operations Optimization of Hybrid Energy Systems under Variable Markets

Energy Technology Data Exchange (ETDEWEB)

Chen, Jun; Garcia, Humberto E.

2016-07-01

Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper investigates the operations flexibility of HES, and develops a methodology for operations optimization to maximize its economic value based on predicted renewable generation and market information. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value, and is illustrated by numerical results.

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

Optimization of boundary controls of string vibrations

Energy Technology Data Exchange (ETDEWEB)

Il' in, V A; Moiseev, E I [Department of Computing Mathematics and Cybernetics, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)

2005-12-31

For a large time interval T boundary controls of string vibrations are optimized in the following seven boundary-control problems: displacement control at one end (with the other end fixed or free); displacement control at both ends; elastic force control at one end (with the other end fixed or free); elastic force control at both ends; combined control (displacement control at one end and elastic force control at the other). Optimal boundary controls in each of these seven problems are sought as functions minimizing the corresponding boundary-energy integral under the constraints following from the initial and terminal conditions for the string at t=0 and t=T, respectively. For all seven problems, the optimal boundary controls are written out in closed analytic form.

A model of optimal voluntary muscular control.

Science.gov (United States)

FitzHugh, R

1977-07-19

In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.

Joint Optimized CPU and Networking Control Scheme for Improved Energy Efficiency in Video Streaming on Mobile Devices

Directory of Open Access Journals (Sweden)

Sung-Woong Jo

2017-01-01

Full Text Available Video streaming service is one of the most popular applications for mobile users. However, mobile video streaming services consume a lot of energy, resulting in a reduced battery life. This is a critical problem that results in a degraded user’s quality of experience (QoE. Therefore, in this paper, a joint optimization scheme that controls both the central processing unit (CPU and wireless networking of the video streaming process for improved energy efficiency on mobile devices is proposed. For this purpose, the energy consumption of the network interface and CPU is analyzed, and based on the energy consumption profile a joint optimization problem is formulated to maximize the energy efficiency of the mobile device. The proposed algorithm adaptively adjusts the number of chunks to be downloaded and decoded in each packet. Simulation results show that the proposed algorithm can effectively improve the energy efficiency when compared with the existing algorithms.

Potential energy savings using dynamically optimizing control in refrigeration systems under daily variations in ambient temperature

DEFF Research Database (Denmark)

Larsen, Lars Finn Sloth; Thybo, Claus; Wisniewski, Rafal

2007-01-01

The objective of this study is to investigate the energy saving potential for refrigeration systems by refrigeration more at the colder night time than at the warmer day time. The potential is evaluated using an optimal control policy and illustrated on a simulation example. The results show...

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

Optimized Fuzzy-Cuckoo Controller for Active Power Control of Battery Energy Storage System, Photovoltaic, Fuel Cell and Wind Turbine in an Isolated Micro-Grid

Directory of Open Access Journals (Sweden)

Mohsen Einan

2017-08-01

Full Text Available This paper presents a new control strategy for isolated micro-grids including wind turbines (WT, fuel cells (FC, photo-voltaic (PV and battery energy storage systems (BESS. FC have been used in parallel with BESSs in order to increase their lifetime and efficiency. The changes in some parameters such as wind speed, sunlight, and consumption, lead to improper performance of droop. To overcome this challenge, a new intelligent method using a combination of fuzzy controller and cuckoo optimization algorithm (COA techniques for active power controllers in isolated networks is proposed. In this paper, COA is compared with genetic algorithm (GA and particles swarm optimization algorithm (PSO. In order to show efficiency of the proposed controller, this optimal controller has been compared with droop, optimized droop, and conventional fuzzy methods, the dynamic analysis of the island is implemented to assess the behavior of isolated generations accurately and simulation results are reported.

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

Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

OpenAIRE

Fusco, Francesco; Ringwood, John

2010-01-01

Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if ...

Optimal control of a CSTR process

Directory of Open Access Journals (Sweden)

A. Soukkou

2008-12-01

Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.

Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing

Directory of Open Access Journals (Sweden)

Muhammad Babar Rasheed

2016-07-01

Full Text Available In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

Optimal Model-Based Control in HVAC Systems

DEFF Research Database (Denmark)

Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

2008-01-01

is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....

Robust active combustion control for the optimization of environmental performance and energy efficiency

Science.gov (United States)

Demayo, Trevor Nat

Criteria pollutant regulations, climate change concerns, and energy conservation efforts are placing strict constraints in the design and operation of advanced, stationary combustion systems. To ensure minimal pollutant emissions and maximal efficiency at every instant of operation while preventing reaction blowout, combustion systems need to react and adapt in real-time to external changes. This study describes the development, demonstration, and evaluation of a multivariable feedback control system, designed to maximize the performance of natural gas-fired combustion systems. A feedback sensor array was developed to monitor reaction stability and measure combustion performance as a function of NOx, CO, and O, emissions. Acoustic and UV chemiluminescent emissions were investigated for use as stability indicators. Modulated signals of CH* and CO2* chemiluminescence were found to correlate well with the onset of lean blowout. A variety of emissions sensors were tested and evaluated, including conventional CEMS', micro-fuel cells, a zirconia NOx transducer, and a rapid response predictive NOx sensor based on UV flame chemiluminescence. A dual time-scale controller was designed to actively optimize operating conditions by maximizing a multivariable performance function J using a linear direction set search algorithm. The controller evaluated J under slow, quasi steady-state conditions, while dynamically monitoring the reaction zone at high speed for pre-blowout instabilities or boundary condition violations. To establish the input control parameters, two burner systems were selected: a 30 kW air-swirl, generic research burner, and a 120 kW scaled, fuel-staged, industrial boiler burner. The parameters, chosen to most affect burner performance, consisted of air swirl intensity and excess air for the generic burner, and fuel-staging and excess air for the boiler burner. A set of optimization parameters was also established to ensure efficient and deterministic

Potential Energy Savings in Refrigeration Systems Using Optimal Setpoints

DEFF Research Database (Denmark)

Larsen, Lars Finn Slot; Thybo, Claus

2004-01-01

Energy efficiency of refrigeration systems has gradually been improved with help of control schemes utilizing the more flexible components. This paper proposes an approach in line with this trend, where a suboptimal condenser pressure is found in order to minimize the energy consumption. The obje......Energy efficiency of refrigeration systems has gradually been improved with help of control schemes utilizing the more flexible components. This paper proposes an approach in line with this trend, where a suboptimal condenser pressure is found in order to minimize the energy consumption....... The objective is to give an idea of how this optimization scheme works as well as to show what amount of energy it is possible to save. A steady state model of a simple refrigeration system will be used as a basis for the optimization....

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

Optimal control of hydroelectric facilities

Science.gov (United States)

Zhao, Guangzhi

This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the

Hierarchical fuzzy control of low-energy building systems

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhen; Dexter, Arthur [Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ (United Kingdom)

2010-04-15

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profile can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)

Optimal Energy Consumption Analysis of Natural Gas Pipeline

Science.gov (United States)

Liu, Enbin; Li, Changjun; Yang, Yi

2014-01-01

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent. PMID:24955410

Immunity-based optimal estimation approach for a new real time group elevator dynamic control application for energy and time saving.

Science.gov (United States)

Baygin, Mehmet; Karakose, Mehmet

2013-01-01

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

Directory of Open Access Journals (Sweden)

Mehmet Baygin

2013-01-01

Full Text Available Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

Science.gov (United States)

Aldrich, Jack B.; Okon, Avi B.

2012-01-01

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used

Optimal Control Design for a Solar Greenhouse

NARCIS (Netherlands)

Ooteghem, van R.J.C.

2010-01-01

Abstract: An optimal climate control has been designed for a solar greenhouse to achieve optimal crop production with sustainable instead of fossil energy. The solar greenhouse extends a conventional greenhouse with an improved roof cover, ventilation with heat recovery, a heat pump, a heat

Energy performance and optimal control of air-conditioned buildings with envelopes enhanced by phase change materials

International Nuclear Information System (INIS)

Zhu Na; Wang Shengwei; Ma Zhenjun; Sun Yongjun

2011-01-01

Highlights: → Impact of PCM on the energy consumption and peak load demand as well as electricity cost of air-conditioned buildings. → Impact of load shifting control on energy consumption, peak load and electricity cost of air-conditioned PCM buildings. → Impact of demand limiting control on energy consumption, peak load and electricity cost of air-conditioned PCM buildings. → Energy/cost effects of different control strategies and use of PCM in energy-plus-demand-based pricing policy. → Energy/cost effects of different control strategies and use of PCM in time-based pricing policy. - Abstract: Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing). Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.

Energy consumption optimization of a continuous ice cream process

International Nuclear Information System (INIS)

González-Ramírez, J.E.; Leducq, D.; Arellano, M.; Alvarez, G.

2013-01-01

Highlights: • This work investigates potential energy savings of an ice cream freezer. • From a full load compressor to a variable speed compressor one in freezer. • 30% less of energy consumption. • It is possible to save between 11 and 14 MWh per year by optimizing freezers. - Abstract: This work investigates potential energy saves in an ice cream freezer by using a variable speed compressor and optimization’s methodology for operating conditions during the process. Two configurations to control the refrigeration capacity were analyzed, the first one, modifies the pressure through the pilot control valve (conventional refrigeration system) and the second one with a variable speed compressor, both with a float expansion valve. Variable speed compressor configuration has showed the highest coefficient of performance and around of 30% less of energy consumption than the conventional one. The optimization of operating conditions in order to minimize the energy consumption is also presented. It was calculated only in France, for all ice cream and sorbet production, it is possible to save energy between 11 and 14 MWh per year by optimizing the operation of the refrigeration system through a variable speed compressor configuration

Stand-alone power systems for the future: Optimal design, operation and control of solar-hydrogen energy systems

Energy Technology Data Exchange (ETDEWEB)

Ulleberg, Oeystein

1998-12-31

This thesis gives a systematic review of the fundamentals of energy systems, the governing physical and chemical laws related to energy, inherent characteristics of energy system, and the availability of the earth`s energy. It shows clearly why solar-hydrogen systems are one of the most viable options for the future. The main subject discussed is the modelling of SAPS (Stand-Alone Power Systems), with focus on photovoltaic-hydrogen energy systems. Simulation models for a transient simulation program are developed for PV-H{sub 2} components, including models for photovoltaics, water electrolysis, hydrogen storage, fuel cells, and secondary batteries. A PV-H{sub 2} demonstration plant in Juelich, Germany, is studied as a reference plant and the models validated against data from this plant. Most of the models developed were found to be sufficiently accurate to perform short-term system simulations, while all were more than accurate enough to perform long-term simulations. Finally, the verified simulation models are used to find the optimal operation and control strategies of an existing PV-H{sub 2} system. The main conclusion is that the simulation methods can be successfully used to find optimal operation and control strategies for a system with fixed design, and similar methods could be used to find alternative system designs. 148 refs., 78 figs., 31 tabs.

Stand-alone power systems for the future: Optimal design, operation and control of solar-hydrogen energy systems

Energy Technology Data Exchange (ETDEWEB)

Ulleberg, Oeystein

1999-12-31

This thesis gives a systematic review of the fundamentals of energy systems, the governing physical and chemical laws related to energy, inherent characteristics of energy system, and the availability of the earth`s energy. It shows clearly why solar-hydrogen systems are one of the most viable options for the future. The main subject discussed is the modelling of SAPS (Stand-Alone Power Systems), with focus on photovoltaic-hydrogen energy systems. Simulation models for a transient simulation program are developed for PV-H{sub 2} components, including models for photovoltaics, water electrolysis, hydrogen storage, fuel cells, and secondary batteries. A PV-H{sub 2} demonstration plant in Juelich, Germany, is studied as a reference plant and the models validated against data from this plant. Most of the models developed were found to be sufficiently accurate to perform short-term system simulations, while all were more than accurate enough to perform long-term simulations. Finally, the verified simulation models are used to find the optimal operation and control strategies of an existing PV-H{sub 2} system. The main conclusion is that the simulation methods can be successfully used to find optimal operation and control strategies for a system with fixed design, and similar methods could be used to find alternative system designs. 148 refs., 78 figs., 31 tabs.

Optimization and Optimal Control

CERN Document Server

Chinchuluun, Altannar; Enkhbat, Rentsen; Tseveendorj, Ider

2010-01-01

During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics. Key features: Provides a collection of selected contributions giving a state-of-the-art accou

Domestic appliances energy optimization with model predictive control

International Nuclear Information System (INIS)

Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.

2017-01-01

Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new

Decentralized Control Strategy for Optimal Energy Management in Grid-Connected and Islanded DC Microgrids

Directory of Open Access Journals (Sweden)

E. Alizadeh

2017-12-01

Full Text Available This paper proposes a decentralized control technique to minimize the total operation cost of a DC microgrid in both grid-connected and islanded modes. In this study, a cost-based droop control scheme based on the hourly bids of all participant distributed generators (DGs and the hourly energy price of the utility is presented. An economic power sharing technique among various types of DG units is adopted to appropriately minimize the daily total operation cost of DC microgrid without a microgrid central controller. The DC microgrid may include non-dispatchable DG units (such as photovoltaic systems and dispatchable generation units. Unlike other energy management techniques, the proposed method suffers neither from forecasting errors for both load demand and renewable energy power prediction modules, nor from complicated optimization techniques. In the proposed method, all DGs and the utility are classified in a sorting rule based on their hourly bids and open market price, and then the droop parameters are determined. The simulation results are presented to verify the effectiveness of the proposed method using MATLAB/SIMULINK software. The results show that the proposed strategy is able to be implemented in various operation conditions of DC microgrid with resistance to uncertainties.

Optimal control of a qubit in an optical cavity

International Nuclear Information System (INIS)

Deffner, Sebastian

2014-01-01

We study quantum information processing by means of optimal control theory. To this end, we analyze the damped Jaynes–Cummings model, and derive optimal control protocols that minimize the heating or energy dispersion rates, and controls that drive the system at the quantum speed limit. Special emphasis is put on analyzing the subtleties of optimal control theory for our system. In particular, it is shown how two fundamentally different approaches to the quantum speed limit can be reconciled by carefully formulating the problem. (paper)

Cycle energy control of magnetorheological dampers on cables

International Nuclear Information System (INIS)

Weber, F; Feltrin, G; Motavalli, M; Distl, H

2009-01-01

The dissipated cycle energy of magnetorheological (MR) dampers operated at constant current results from controllable hysteretic damping and from almost current independent, small viscous damping. Thus, the emulation of Coulomb friction and linear viscous damping necessitates current modulation during one vibration cycle and therefore current drivers. To avoid this drawback, a cycle energy control (CEC) approach is presented which controls the hysteretic MR damper part such that the total MR damper energy equals the energy of optimal linear viscous damping by constant current during one cycle. The excited higher modes due to the hysteretic damping part are partially damped by the MR damper viscous part. Simulations show that CEC copes better with damper force dynamics and constraints than emulated linear viscous damping due to the slow control force dynamics of CEC which are given by cable amplitude dynamics. It is demonstrated that CEC of MR dampers with viscosity of approximately 4.65% of the optimal modal viscosity performs better than optimal linear viscous damping. The reason is that this damper viscosity represents an optimal compromise between maximum energy spillover to higher modes due to the controllable hysteretic part which produces more cable damping and maximum viscous damping of these higher modes. Damping tests on a cable with an MR damper validate the CEC approach

Automatic generation control of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization algorithm

Directory of Open Access Journals (Sweden)

Rabindra Kumar Sahu

2016-03-01

Full Text Available This paper presents the design and analysis of Proportional-Integral-Double Derivative (PIDD controller for Automatic Generation Control (AGC of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization (TLBO algorithm. At first, a two-area reheat thermal power system with appropriate Generation Rate Constraint (GRC is considered. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PIDD controller. The superiority of the proposed TLBO based PIDD controller has been demonstrated by comparing the results with recently published optimization technique such as hybrid Firefly Algorithm and Pattern Search (hFA-PS, Firefly Algorithm (FA, Bacteria Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and conventional Ziegler Nichols (ZN for the same interconnected power system. Also, the proposed approach has been extended to two-area power system with diverse sources of generation like thermal, hydro, wind and diesel units. The system model includes boiler dynamics, GRC and Governor Dead Band (GDB non-linearity. It is observed from simulation results that the performance of the proposed approach provides better dynamic responses by comparing the results with recently published in the literature. Further, the study is extended to a three unequal-area thermal power system with different controllers in each area and the results are compared with published FA optimized PID controller for the same system under study. Finally, sensitivity analysis is performed by varying the system parameters and operating load conditions in the range of ±25% from their nominal values to test the robustness.

Optimal control of hydroelectric facility incorporating pump storage

International Nuclear Information System (INIS)

Zhao, Guangzhi; Davison, Matt

2009-01-01

We consider a simple model of a pump-assisted hydroelectric facility operating in a market with time-varying but deterministic power prices and constant water inflows. The engineering details of the facility are described by a model containing several parameters. We present an algorithm for optimizing first the energy and then the profit produced by these plants. This algorithm allows us to describe the relationships between control trajectory and time, and between inflow and price. Remarkably, we see that under some reasonable choices of facility parameters and for power prices that are not extremely variable, the optimal profit operation of these facilities is not too different from their optimal energy operation, and the control is less affected by the price as the inflow rate increases. (author)

Energy mesh optimization for multi-level calculation schemes

International Nuclear Information System (INIS)

Mosca, P.; Taofiki, A.; Bellier, P.; Prevost, A.

2011-01-01

The industrial calculations of third generation nuclear reactors are based on sophisticated strategies of homogenization and collapsing at different spatial and energetic levels. An important issue to ensure the quality of these calculation models is the choice of the collapsing energy mesh. In this work, we show a new approach to generate optimized energy meshes starting from the SHEM 281-group library. The optimization model is applied on 1D cylindrical cells and consists of finding an energy mesh which minimizes the errors between two successive collision probability calculations. The former is realized over the fine SHEM mesh with Livolant-Jeanpierre self-shielded cross sections and the latter is performed with collapsed cross sections over the energy mesh being optimized. The optimization is done by the particle swarm algorithm implemented in the code AEMC and multigroup flux solutions are obtained from standard APOLLO2 solvers. By this new approach, a set of new optimized meshes which encompass from 10 to 50 groups has been defined for PWR and BWR calculations. This set will allow users to adapt the energy detail of the solution to the complexity of the calculation (assembly, multi-assembly, two-dimensional whole core). Some preliminary verifications, in which the accuracy of the new meshes is measured compared to a direct 281-group calculation, show that the 30-group optimized mesh offers a good compromise between simulation time and accuracy for a standard 17 x 17 UO 2 assembly with and without control rods. (author)

Economic Optimal Operation of Community Energy Storage Systems in Competitive Energy Markets

OpenAIRE

Arghandeh, Reza; Woyak, Jeremy; Onen, Ahmet; Jung, Jaesung; Broadwater, Robert P.

2014-01-01

Distributed, controllable energy storage devices offer several benefits to electric power system operation. Three such benefits include reducing peak load, providing standby power, and enhancing power quality. These benefits, however, are only realized during peak load or during an outage, events that are infrequent. This paper presents a means of realizing additional benefits by taking advantage of the fluctuating costs of energy in competitive energy markets. An algorithm for optimal charge...

Computing energy-optimal trajectories for an autonomous underwater vehicle using direct shooting

Directory of Open Access Journals (Sweden)

Inge Spangelo

1992-07-01

Full Text Available Energy-optimal trajectories for an autonomous underwater vehicle can be computed using a numerical solution of the optimal control problem. The vehicle is modeled with the six dimensional nonlinear and coupled equations of motion, controlled with DC-motors in all degrees of freedom. The actuators are modeled and controlled with velocity loops. The dissipated energy is expressed in terms of the control variables as a nonquadratic function. Direct shooting methods, including control vector parameterization (CVP arc used in this study. Numerical calculations are performed and good results are achieved.

Hybrid vehicle optimal control : Linear interpolation and singular control

NARCIS (Netherlands)

Delprat, S.; Hofman, T.

2015-01-01

Hybrid vehicle energy management can be formulated as an optimal control problem. Considering that the fuel consumption is often computed using linear interpolation over lookup table data, a rigorous analysis of the necessary conditions provided by the Pontryagin Minimum Principle is conducted. For

A Novel Optimal Control Method for Impulsive-Correction Projectile Based on Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ruisheng Sun

2016-01-01

Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.

Implementation of optimal trajectory control of series resonant converter

Science.gov (United States)

Oruganti, Ramesh; Yang, James J.; Lee, Fred C.

1987-01-01

Due to the presence of a high-frequency LC tank circuit, the dynamics of a resonant converter are unpredictable. There is often a large surge of tank energy during transients. Using state-plane analysis technique, an optimal trajectory control utilizing the desired solution trajectory as the control law was previously proposed for the series resonant converters. The method predicts the fastest response possible with minimum energy surge in the resonant tank. The principle of the control and its experimental implementation are described here. The dynamics of the converter are shown to be close to time-optimal.

Simulation and optimal control of wind-farm boundary layers

Science.gov (United States)

Meyers, Johan; Goit, Jay

2014-05-01

In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a

METHOD FOR OPTIMIZING THE ENERGY OF PUMPS

NARCIS (Netherlands)

Skovmose Kallesøe, Carsten; De Persis, Claudio

2013-01-01

The device for energy-optimization on operation of several centrifugal pumps controlled in rotational speed, in a hydraulic installation, begins firstly with determining which pumps as pilot pumps are assigned directly to a consumer and which pumps are hydraulically connected in series upstream of

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Directory of Open Access Journals (Sweden)

Hafiz Majid Hussain

2018-01-01

Full Text Available The traditional power grid is inadequate to overcome modern day challenges. As the modern era demands the traditional power grid to be more reliable, resilient, and cost-effective, the concept of smart grid evolves and various methods have been developed to overcome these demands which make the smart grid superior over the traditional power grid. One of the essential components of the smart grid, home energy management system (HEMS enhances the energy efficiency of electricity infrastructure in a residential area. In this aspect, we propose an efficient home energy management controller (EHEMC based on genetic harmony search algorithm (GHSA to reduce electricity expense, peak to average ratio (PAR, and maximize user comfort. We consider EHEMC for a single home and multiple homes with real-time electricity pricing (RTEP and critical peak pricing (CPP tariffs. In particular, for multiple homes, we classify modes of operation for the appliances according to their energy consumption with varying operation time slots. The constrained optimization problem is solved using heuristic algorithms: wind-driven optimization (WDO, harmony search algorithm (HSA, genetic algorithm (GA, and proposed algorithm GHSA. The proposed algorithm GHSA shows higher search efficiency and dynamic capability to attain optimal solutions as compared to existing algorithms. Simulation results also show that the proposed algorithm GHSA outperforms the existing algorithms in terms of reduction in electricity cost, PAR, and maximize user comfort.

Energy Efficiency of Distributed Environmental Control Systems

Energy Technology Data Exchange (ETDEWEB)

Khalifa, H. Ezzat; Isik, Can; Dannenhoffer, John F. III

2011-02-23

In this report, we present an analytical evaluation of the potential of occupant-regulated distributed environmental control systems (DECS) to enhance individual occupant thermal comfort in an office building with no increase, and possibly even a decrease in annual energy consumption. To this end we developed and applied several analytical models that allowed us to optimize comfort and energy consumption in partitioned office buildings equipped with either conventional central HVAC systems or occupant-regulated DECS. Our approach involved the following interrelated components: 1. Development of a simplified lumped-parameter thermal circuit model to compute the annual energy consumption. This was necessitated by the need to perform tens of thousands of optimization calculations involving different US climatic regions, and different occupant thermal preferences of a population of ~50 office occupants. Yearly transient simulations using TRNSYS, a time-dependent building energy modeling program, were run to determine the robustness of the simplified approach against time-dependent simulations. The simplified model predicts yearly energy consumption within approximately 0.6% of an equivalent transient simulation. Simulations of building energy usage were run for a wide variety of climatic regions and control scenarios, including traditional “one-size-fits-all” (OSFA) control; providing a uniform temperature to the entire building, and occupant-selected “have-it-your-way” (HIYW) control with a thermostat at each workstation. The thermal model shows that, un-optimized, DECS would lead to an increase in building energy consumption between 3-16% compared to the conventional approach depending on the climate regional and personal preferences of building occupants. Variations in building shape had little impact in the relative energy usage. 2. Development of a gradient-based optimization method to minimize energy consumption of DECS while keeping each occupant�

Energy-economical optimization of industrial sites; Energiewirtschaftliche Optimierung von Industriestandorten

Energy Technology Data Exchange (ETDEWEB)

Berthold, A.; Saliba, S.; Franke, R. [ABB AG, Mannheim (Germany)

2015-07-01

The holistic optimization of an industrial estate networks all electrical components of a location and combines energy trading, energy management and production processes. This allows to minimize the energy consumption from the supply network and to relieve the power grid and to maximize the profitability of the industrial self-generation. By analyzing the potential is detected and the cost of optimization solution is estimated. The generation-side optimization is supported through demand-side optimization (demand response). Through a real-time optimization the of Use of fuels is managed, controlled and optimized. [German] Die ganzheitliche Optimierung einer industriellen Liegenschaft vernetzt alle elektrischen Komponenten eines Standorts und verbindet Energiehandel, Energiemanagement und Produktionsprozesse. Dadurch kann der Energiebezug aus dem Versorgungsnetz minimiert und das Stromnetz entlastet werden, sowie die Profitabilitaet der industriellen Eigenerzeugung maximiert werden. Durch eine Analyse wird das Potential ermittelt und die Kosten der Optimierungsloesung abgeschaetzt. Die erzeugungsseitige Optimierung wird durch die nachfrageseitige Optimierung (Demand Response) gestuetzt. Durch eine Echtzeitoptimierung wird der Einsatz der Energietraeger verwaltet, gesteuert und optimiert.

Optimal Energy Management for a Smart Grid using Resource-Aware Utility Maximization

Science.gov (United States)

Abegaz, Brook W.; Mahajan, Satish M.; Negeri, Ebisa O.

2016-06-01

Heterogeneous energy prosumers are aggregated to form a smart grid based energy community managed by a central controller which could maximize their collective energy resource utilization. Using the central controller and distributed energy management systems, various mechanisms that harness the power profile of the energy community are developed for optimal, multi-objective energy management. The proposed mechanisms include resource-aware, multi-variable energy utility maximization objectives, namely: (1) maximizing the net green energy utilization, (2) maximizing the prosumers' level of comfortable, high quality power usage, and (3) maximizing the economic dispatch of energy storage units that minimize the net energy cost of the energy community. Moreover, an optimal energy management solution that combines the three objectives has been implemented by developing novel techniques of optimally flexible (un)certainty projection and appliance based pricing decomposition in an IBM ILOG CPLEX studio. A real-world, per-minute data from an energy community consisting of forty prosumers in Amsterdam, Netherlands is used. Results show that each of the proposed mechanisms yields significant increases in the aggregate energy resource utilization and welfare of prosumers as compared to traditional peak-power reduction methods. Furthermore, the multi-objective, resource-aware utility maximization approach leads to an optimal energy equilibrium and provides a sustainable energy management solution as verified by the Lagrangian method. The proposed resource-aware mechanisms could directly benefit emerging energy communities in the world to attain their energy resource utilization targets.

Energy savings by optimization of drying processes through use of models and effective control; Energibesparelser ved optimering af toerreprocesser gennem anvendelse af modeller og effektiv regulering

Energy Technology Data Exchange (ETDEWEB)

Didriksen, H.; Sandvig Nielsen, J.; Weel Hansen, M.

2001-06-01

The aim of the project is to present a procedure to optimize existing drying processes. The optimization deals with energy consumption, capacity utilization and product quality. Other factors can also be included in the optimization, e.g. minimization of volume of discharged air. The optimization of existing drying processes will use calculation tool based on a mathematical simulation model for the process to calculate the most optimum operation situation on the basis of given conditions. In the project mathematical models have been developed precisely with this aim. The calculation tools have been developed with a user interface so that the tools can be used by technical staff in industrial companies and by consultants. The project also illustrates control of drying processes. Based on the developed models, the effect of using different types of control strategies by means of model simulations is illustrated. Three types of drying processes are treated: drum dryers, disc dryers and drying chambers. The work with the development of the simulation models has been very central in the project, as these have to be the basis for the optimization of the processes. The work is based on a large amount of information from academical literature and knowledge and experience about modelling thermal processes at dk-TEKNIK. The models constitute the core in the simulation programmes. The models describe the most important physical effects in connection with mass and energy transfer and transport under the drying for the three treated drying technologies. (EHS)

Evaluation of Building Energy Saving Through the Development of Venetian Blinds' Optimal Control Algorithm According to the Orientation and Window-to-Wall Ratio

Science.gov (United States)

Kwon, Hyuk Ju; Yeon, Sang Hun; Lee, Keum Ho; Lee, Kwang Ho

2018-02-01

As various studies focusing on building energy saving have been continuously conducted, studies utilizing renewable energy sources, instead of fossil fuel, are needed. In particular, studies regarding solar energy are being carried out in the field of building science; in order to utilize such solar energy effectively, solar radiation being brought into the indoors should be acquired and blocked properly. Blinds are a typical solar radiation control device that is capable of controlling indoor thermal and light environments. However, slat-type blinds are manually controlled, giving a negative effect on building energy saving. In this regard, studies regarding the automatic control of slat-type blinds have been carried out for the last couple of decades. Therefore, this study aims to provide preliminary data for optimal control research through the controlling of slat angle in slat-type blinds by comprehensively considering various input variables. The window area ratio and orientation were selected as input variables. It was found that an optimal control algorithm was different among each window-to-wall ratio and window orientation. In addition, through comparing and analyzing the building energy saving performance for each condition by applying the developed algorithms to simulations, up to 20.7 % energy saving was shown in the cooling period and up to 12.3 % energy saving was shown in the heating period. In addition, building energy saving effect was greater as the window area ratio increased given the same orientation, and the effects of window-to-wall ratio in the cooling period were higher than those of window-to-wall ratio in the heating period.

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

Science.gov (United States)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

An integrated optimization approach for a hybrid energy system in electric vehicles

International Nuclear Information System (INIS)

Hung, Yi-Hsuan; Wu, Chien-Hsun

2012-01-01

Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

Deterministic methods for multi-control fuel loading optimization

Science.gov (United States)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

Science.gov (United States)

Moser, Elke; Grass, Dieter; Tragler, Gernot

Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.

An Energy-Aware Trajectory Optimization Layer for sUAS

Science.gov (United States)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li

2013-06-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2013-01-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

Different Optimal Control Strategies for Exploitation of Demand Response in the Smart Grid

DEFF Research Database (Denmark)

Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver

2012-01-01

To achieve a Danish energy supply based on 100% renewable energy from combinations of wind, biomass, wave and solar power in 2050 and to cover 50% of the Danish electricity consumption by wind power in 2025, it requires coordinated management of large numbers of distributed and demand response...... resources, intermittent renewable energy resources in the Smart Grid. This paper presents different optimal control (Genetic Algorithm-based and Model Predictive Control-based) algorithms that schedule controlled loads in the industrial and residential sectors, based on dynamic price and weather forecast......, considering users’ comfort settings to meet an optimization objective, such as maximum profit or minimum energy consumption. It is demonstrated in this work that the GA-based and MPC-based optimal control strategies are able to achieve load shifting for grid reliability and energy savings, including demand...

Bio-Inspired Optimization of Sustainable Energy Systems: A Review

Directory of Open Access Journals (Sweden)

Yu-Jun Zheng

2013-01-01

Full Text Available Sustainable energy development always involves complex optimization problems of design, planning, and control, which are often computationally difficult for conventional optimization methods. Fortunately, the continuous advances in artificial intelligence have resulted in an increasing number of heuristic optimization methods for effectively handling those complicated problems. Particularly, algorithms that are inspired by the principles of natural biological evolution and/or collective behavior of social colonies have shown a promising performance and are becoming more and more popular nowadays. In this paper we summarize the recent advances in bio-inspired optimization methods, including artificial neural networks, evolutionary algorithms, swarm intelligence, and their hybridizations, which are applied to the field of sustainable energy development. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.

Energy Performance and Optimal Control of Air-conditioned Buildings Integrated with Phase Change Materials

Science.gov (United States)

Zhu, Na

This thesis presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of buildings using PCMs both with and without air-conditioning is reviewed. Since the particular interest in using PCMs for free cooling and peak load shifting, specific research efforts on both subjects are reviewed separately. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. This thesis also presents the studies on the thermodynamic characteristics of buildings enhanced by PCM and on the investigation of the impacts of PCM on the building cooling load and peak cooling demand at different climates and seasons as well as the optimal operation and control strategies to reduce the energy consumption and energy cost by reducing the air-conditioning energy consumption and peak load. An office building floor with typical variable air volume (VAV) air-conditioning system is used and simulated as the reference building in the comparison study. The envelopes of the studied building are further enhanced by integrating the PCM layers. The building system is tested in two selected cities of typical climates in China including Hong Kong and Beijing. The cold charge and discharge processes, the operation and control strategies of night ventilation and the air temperature set-point reset strategy for minimizing the energy consumption and electricity cost are studied. This thesis presents the simulation test platform, the test results on the cold storage and discharge processes, the air-conditioning energy consumption and demand

Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation

International Nuclear Information System (INIS)

Chen, Xiao; Wang, Qian; Srebric, Jelena

2016-01-01

Highlights: • This study evaluates an occupant-feedback driven Model Predictive Controller (MPC). • The MPC adjusts indoor temperature based on a dynamic thermal sensation (DTS) model. • A chamber model for predicting chamber air temperature is developed and validated. • Experiments show that MPC using DTS performs better than using Predicted Mean Vote. - Abstract: In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants’ votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.

Stabilization of microgrid with intermittent renewable energy sources by SMES with optimal coil size

International Nuclear Information System (INIS)

Saejia, M.; Ngamroo, I.

2011-01-01

A controller design of a superconducting magnetic energy storage unit is proposed. The structure of a power controller is the practical proportional-integral (PI). The PI parameters and coil size are tuned by a particle swarm optimization. The proposed method is able to effectively alleviate power fluctuations. It is well known that the superconducting coil is the vital part of a superconducting magnetic energy storage (SMES) unit. This paper deals with the power controller design of a SMES unit with an optimal coil size for stabilization of an isolated microgrid. The study microgrid consists of renewable energy sources with intermittent power outputs i.e., wind and photovoltaic. Since power generations from such renewable sources are unpredictable and variable, these result in power fluctuations in a microgrid. To stabilize power fluctuations, a SMES unit with a fast control of active and reactive power can be applied. The structure of a power controller is the practical proportional-integral (PI). Based on the minimization of the variance of power fluctuations from renewable sources as well as the initial stored energy of SMES, the optimal PI parameters and coil size are automatically and simultaneously tuned by a particle swarm optimization. Simulation studies show that the proposed SMES controller with an optimal coil size is able to effectively alleviate power fluctuations under various power patterns from intermittent renewable sources.

Stabilization of microgrid with intermittent renewable energy sources by SMES with optimal coil size

Energy Technology Data Exchange (ETDEWEB)

Saejia, M., E-mail: samongkol@gmail.com [School of Electrical Engineering, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Bangkok 10520 (Thailand); Ngamroo, I. [School of Electrical Engineering, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Bangkok 10520 (Thailand)

2011-11-15

A controller design of a superconducting magnetic energy storage unit is proposed. The structure of a power controller is the practical proportional-integral (PI). The PI parameters and coil size are tuned by a particle swarm optimization. The proposed method is able to effectively alleviate power fluctuations. It is well known that the superconducting coil is the vital part of a superconducting magnetic energy storage (SMES) unit. This paper deals with the power controller design of a SMES unit with an optimal coil size for stabilization of an isolated microgrid. The study microgrid consists of renewable energy sources with intermittent power outputs i.e., wind and photovoltaic. Since power generations from such renewable sources are unpredictable and variable, these result in power fluctuations in a microgrid. To stabilize power fluctuations, a SMES unit with a fast control of active and reactive power can be applied. The structure of a power controller is the practical proportional-integral (PI). Based on the minimization of the variance of power fluctuations from renewable sources as well as the initial stored energy of SMES, the optimal PI parameters and coil size are automatically and simultaneously tuned by a particle swarm optimization. Simulation studies show that the proposed SMES controller with an optimal coil size is able to effectively alleviate power fluctuations under various power patterns from intermittent renewable sources.

Control and Optimization Methods for Electric Smart Grids

CERN Document Server

Ilić, Marija

2012-01-01

Control and Optimization Methods for Electric Smart Grids brings together leading experts in power, control and communication systems,and consolidates some of the most promising recent research in smart grid modeling,control and optimization in hopes of laying the foundation for future advances in this critical field of study. The contents comprise eighteen essays addressing wide varieties of control-theoretic problems for tomorrow’s power grid. Topics covered include: Control architectures for power system networks with large-scale penetration of renewable energy and plug-in vehicles Optimal demand response New modeling methods for electricity markets Control strategies for data centers Cyber-security Wide-area monitoring and control using synchronized phasor measurements. The authors present theoretical results supported by illustrative examples and practical case studies, making the material comprehensible to a wide audience. The results reflect the exponential transformation that today’s grid is going...

Design and Validation of Real-Time Optimal Control with ECMS to Minimize Energy Consumption for Parallel Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Aiyun Gao

2017-01-01

Full Text Available A real-time optimal control of parallel hybrid electric vehicles (PHEVs with the equivalent consumption minimization strategy (ECMS is presented in this paper, whose purpose is to achieve the total equivalent fuel consumption minimization and to maintain the battery state of charge (SOC within its operation range at all times simultaneously. Vehicle and assembly models of PHEVs are established, which provide the foundation for the following calculations. The ECMS is described in detail, in which an instantaneous cost function including the fuel energy and the electrical energy is proposed, whose emphasis is the computation of the equivalent factor. The real-time optimal control strategy is designed through regarding the minimum of the total equivalent fuel consumption as the control objective and the torque split factor as the control variable. The validation of the control strategy proposed is demonstrated both in the MATLAB/Simulink/Advisor environment and under actual transportation conditions by comparing the fuel economy, the charge sustainability, and parts performance with other three control strategies under different driving cycles including standard, actual, and real-time road conditions. Through numerical simulations and real vehicle tests, the accuracy of the approach used for the evaluation of the equivalent factor is confirmed, and the potential of the proposed control strategy in terms of fuel economy and keeping the deviations of SOC at a low level is illustrated.

Optimized Latching Control of Floating Point Absorber Wave Energy Converter

Science.gov (United States)

Gadodia, Chaitanya; Shandilya, Shubham; Bansal, Hari Om

2018-03-01

There is an increasing demand for energy in today’s world. Currently main energy resources are fossil fuels, which will eventually drain out, also the emissions produced from them contribute to global warming. For a sustainable future, these fossil fuels should be replaced with renewable and green energy sources. Sea waves are a gigantic and undiscovered vitality asset. The potential for extricating energy from waves is extensive. To trap this energy, wave energy converters (WEC) are needed. There is a need for increasing the energy output and decreasing the cost requirement of these existing WECs. This paper presents a method which uses prediction as a part of the control scheme to increase the energy efficiency of the floating-point absorber WECs. Kalman Filter is used for estimation, coupled with latching control in regular as well as irregular sea waves. Modelling and Simulation results for the same are also included.

Power Control Optimization of an Underwater Piezoelectric Energy Harvester

Directory of Open Access Journals (Sweden)

Iñigo Aramendia

2018-03-01

Full Text Available Over the past few years, it has been established that vibration energy harvesters with intentionally designed components can be used for frequency bandwidth enhancement under excitation for sufficiently high vibration amplitudes. Pipelines are often necessary means of transporting important resources such as water, gas, and oil. A self-powered wireless sensor network could be a sustainable alternative for in-pipe monitoring applications. A new control algorithm has been developed and implemented into an underwater energy harvester. Firstly, a computational study of a piezoelectric energy harvester for underwater applications has been studied for using the kinetic energy of water flow at four different Reynolds numbers Re = 3000, 6000, 9000, and 12,000. The device consists of a piezoelectric beam assembled to an oscillating cylinder inside the water of pipes from 2 to 5 inches in diameter. Therefore, unsteady simulations have been performed to study the dynamic forces under different water speeds. Secondly, a new control law strategy based on the computational results has been developed to extract as much energy as possible from the energy harvester. The results show that the harvester can efficiently extract the power from the kinetic energy of the fluid. The maximum power output is 996.25 µW and corresponds to the case with Re = 12,000.

Chaos synchronization and chaotization of complex chaotic systems in series form by optimal control

International Nuclear Information System (INIS)

Ge Zhengming; Yang, C.-H.

2009-01-01

By the method of quadratic optimum control, a quadratic optimal regulator is used for synchronizing two complex chaotic systems in series form. By this method the least error with less control energy is achieved, and the optimization on both energy and error is realized synthetically. The simulation results of two Quantum-CNN chaos systems in series form prove the effectiveness of this method. Finally, chaotization of the system is given by optimal control.

Supervisory Control for Real Time Reactive Power Flow Optimization in Islanded Microgrids

DEFF Research Database (Denmark)

Milczarek, Adam; Vasquez, Juan Carlos; Malinowski, Mariusz

2013-01-01

-line measurements. Similarly to any process system, MG hierarchical control is divided into three levels. However, an additional control algorithm is required to manage power transmission between sources and loads, maximizing efficiency and minimizing transmission losses. This real-time optimization problem......A microgrid (MG) is a local energy system consisting of a number of energy sources, energy storage units and loads that operate connected to the main electrical grid or autonomously. MGs include wind, solar or other renewable energy sources. MGs provide flexibility, reduce the main electricity grid...... dependence and contribute to change the large centralized production paradigm to local and distributed generation. However, such energy systems require complex management, advanced control and optimization. Interest on MGs hierarchical control has increased due to the availability of cheap on...

A dynamic optimization on economic energy efficiency in development: A numerical case of China

International Nuclear Information System (INIS)

Wang, Dong

2014-01-01

This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved. - Highlights: • A new definition on economic energy efficiency is proposed mathematically. • A dynamic optimization modelling links economic energy efficiency with other macroeconomic variables in long run. • Economic energy efficiency is determined by capital stock level and energy consumption. • Energy saving is a key solution for improving economic energy efficiency

System state estimation and optimal energy control framework for multicell lithium-ion battery system

International Nuclear Information System (INIS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai; Kang, Yu

2017-01-01

Highlights: • Employed a dual-scale EKF based estimator for in-pack cells’ SOC values. • Proposed a two-stage hybrid state-feedback and output-feedback equalization algorithm. • A switchable balance current mode is designed in the equalization topology. • Verified the performance of proposed method under two conditions. - Abstract: Cell variations caused by the inevitable inconsistency during manufacture and use of battery cells have significant impacts on battery capacity, security and durability for battery energy storage systems. Thus, the battery equalization systems are essentially required to reduce variations of in-pack cells and increase battery pack capability. In order to protect all in-pack cells from damaging, estimate battery state and reduce variations, a system state estimation and energy optimal control framework for multicell lithium-ion battery system is proposed. The state-of-charge (SOC) values of all in-pack cells are firstly estimated using a dual-scale extended Kalman filtering (EKF) to improve estimation accuracy and reduce computation simultaneously. These estimated SOC values provide specific details of battery system, which cannot only be used to protect cells from over-charging/over-discharging, but also be employed to design state-feedback controller for battery equalization system. A two-stage hybrid state-feedback and output-feedback equalization algorithm is proposed. The state-feedback controller is firstly employed for coarse-grained adjustment to reduce equalization time cost with large current. However, due to the inevitable SOC estimation errors, the output-feedback controller is then used for fine-grained adjustment with trickle current. Experimental results show that the proposed framework can provide an effectively estimation and energy control for multicell battery systems. Finally, the implementation of the proposed method is further discussed for the real applications.

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

Directory of Open Access Journals (Sweden)

Guangyuan Wu

2018-01-01

Full Text Available In Body Area Networks (BANs, how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1 balancing sensors’ energy harvesting and energy consumption while stabilizing the BANs system; and (2 maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.

Desiccant wheel thermal performance modeling for indoor humidity optimal control

International Nuclear Information System (INIS)

Wang, Nan; Zhang, Jiangfeng; Xia, Xiaohua

2013-01-01

Highlights: • An optimal humidity control model is formulated to control the indoor humidity. • MPC strategy is used to implement the optimal operation solution. • Practical applications of the MPC strategy is illustrated by the case study. - Abstract: Thermal comfort is an important concern in the energy efficiency improvement of commercial buildings. Thermal comfort research focuses mostly on temperature control, but humidity control is an important aspect to maintain indoor comfort too. In this paper, an optimal humidity control model (OHCM) is presented. Model predictive control (MPC) strategy is applied to implement the optimal operation of the desiccant wheel during working hours of a commercial building. The OHCM is revised to apply the MPC strategy. A case is studied to illustrate the practical applications of the MPC strategy

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

International Nuclear Information System (INIS)

Gao, Jiajia; Huang, Gongsheng; Xu, Xinhua

2016-01-01

Highlights: • An optimization strategy for a small-scale air-conditioning system is developed. • The optimization strategy aims at optimizing the overall system energy consumption. • The strategy may guarantee the robust control of the space air temperature. • The performance of the optimization strategy was tested on a simulation platform. - Abstract: This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.

Oil Reservoir Production Optimization using Optimal Control

DEFF Research Database (Denmark)

Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan

2011-01-01

Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%.......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...

Multi-agent based distributed control architecture for microgrid energy management and optimization

International Nuclear Information System (INIS)

Basir Khan, M. Reyasudin; Jidin, Razali; Pasupuleti, Jagadeesh

2016-01-01

Highlights: • A new multi-agent based distributed control architecture for energy management. • Multi-agent coordination based on non-cooperative game theory. • A microgrid model comprised of renewable energy generation systems. • Performance comparison of distributed with conventional centralized control. - Abstract: Most energy management systems are based on a centralized controller that is difficult to satisfy criteria such as fault tolerance and adaptability. Therefore, a new multi-agent based distributed energy management system architecture is proposed in this paper. The distributed generation system is composed of several distributed energy resources and a group of loads. A multi-agent system based decentralized control architecture was developed in order to provide control for the complex energy management of the distributed generation system. Then, non-cooperative game theory was used for the multi-agent coordination in the system. The distributed generation system was assessed by simulation under renewable resource fluctuations, seasonal load demand and grid disturbances. The simulation results show that the implementation of the new energy management system proved to provide more robust and high performance controls than conventional centralized energy management systems.

Thermodynamic framework for discrete optimal control in multiphase flow systems

Science.gov (United States)

Sieniutycz, Stanislaw

1999-08-01

Bellman's method of dynamic programming is used to synthesize diverse optimization approaches to active (work producing) and inactive (entropy generating) multiphase flow systems. Thermal machines, optimally controlled unit operations, nonlinear heat conduction, spontaneous relaxation processes, and self-propagating wave fronts are all shown to satisfy a discrete Hamilton-Jacobi-Bellman equation and a corresponding discrete optimization algorithm of Pontryagin's type, with the maximum principle for a Hamiltonian. The extremal structures are always canonical. A common unifying criterion is set for all considered systems, which is the criterion of a minimum generated entropy. It is shown that constraints can modify the entropy functionals in a different way for each group of the processes considered; thus the resulting structures of these functionals may differ significantly. Practical conclusions are formulated regarding the energy savings and energy policy in optimally controlled systems.

Optimal control of quantum systems: a projection approach

International Nuclear Information System (INIS)

Cheng, C.-J.; Hwang, C.-C.; Liao, T.-L.; Chou, G.-L.

2005-01-01

This paper considers the optimal control of quantum systems. The controlled quantum systems are described by the probability-density-matrix-based Liouville-von Neumann equation. Using projection operators, the states of the quantum system are decomposed into two sub-spaces, namely the 'main state' space and the 'remaining state' space. Since the control energy is limited, a solution for optimizing the external control force is proposed in which the main state is brought to the desired main state at a certain target time, while the population of the remaining state is simultaneously suppressed in order to diminish its effects on the final population of the main state. The optimization problem is formulated by maximizing a general cost functional of states and control force. An efficient algorithm is developed to solve the optimization problem. Finally, using the hydrogen fluoride (HF) molecular population transfer problem as an illustrative example, the effectiveness of the proposed scheme for a quantum system initially in a mixed state or in a pure state is investigated through numerical simulations

Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

Directory of Open Access Journals (Sweden)

Jay P. Goit

2016-01-01

Full Text Available We investigate the use of optimal coordinated control techniques in large eddy simulations of wind farm boundary layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators, and their energy extraction is dynamically regulated in time, so as to optimally influence the flow field. We extend earlier work on wind farm optimal control in the fully-developed regime (Goit and Meyers 2015, J. Fluid Mech. 768, 5–50 to a ‘finite’ wind farm case, in which entrance effects play an important role. For the optimal control, a receding horizon framework is employed in which turbine thrust coefficients are optimized in time and per turbine. Optimization is performed with a conjugate gradient method, where gradients of the cost functional are obtained using adjoint large eddy simulations. Overall, the energy extraction is increased 7% by the optimal control. This increase in energy extraction is related to faster wake recovery throughout the farm. For the first row of turbines, the optimal control increases turbulence levels and Reynolds stresses in the wake, leading to better wake mixing and an inflow velocity for the second row that is significantly higher than in the uncontrolled case. For downstream rows, the optimal control mainly enhances the sideways mean transport of momentum. This is different from earlier observations by Goit and Meyers (2015 in the fully-developed regime, where mainly vertical transport was enhanced.

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

Energy Technology Data Exchange (ETDEWEB)

Liu, Guodong [ORNL; Li, Zhi [ORNL; Starke, Michael R. [ORNL; Ollis, Ben [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2017-07-01

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.

Simplified model-based optimal control of VAV air-conditioning system

Energy Technology Data Exchange (ETDEWEB)

Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal, PQ (Canada). Dept. of Construction Engineering

2005-07-01

The improvement of Variable Air Volume (VAV) system performance is one of several attempts being made to minimize the high energy use associated with the operation of heating, ventilation and air conditioning (HVAC) systems. A Simplified Optimization Process (SOP) comprised of controller set point strategies and a simplified VAV model was presented in this paper. The aim of the SOP was to determine supply set points. The advantage of the SOP over previous methods was that it did not require a detailed VAV model and optimization program. In addition, the monitored data for representative local-loop control can be checked on-line, after which controller set points can be updated in order to ensure proper operation by opting for real situations with minimum energy use. The SOP was validated using existing monitoring data and a model of an existing VAV system. Energy use simulations were compared to that of the existing VAV system. At each simulation step, 3 controller set point values were proposed and studied using the VAV model in order to select a value for each point which corresponded to the best performance of the VAV system. Simplified VAV component models were presented. Strategies for controller set points were described, including zone air temperature, duct static pressure set points; chilled water supply set points and supply air temperature set points. Simplified optimization process calculations were presented. Results indicated that the SOP provided significant energy savings when applied to specific AHU systems. In a comparison with a Detailed Optimization Process (DOP), the SOP was capable of determining set points close to those obtained by the DOP. However, it was noted that the controller set points determined by the SOP need a certain amount of time to reach optimal values when outdoor conditions or thermal loads are significantly changed. It was suggested that this disadvantage could be overcome by the use of a dynamic incremental value, which

Optimal utilization of energy resources

Energy Technology Data Exchange (ETDEWEB)

Hudson, E. A.

1977-10-15

General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.

Optimal utilization of energy resources

Energy Technology Data Exchange (ETDEWEB)

Hudson, E.A.

1977-10-15

General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.

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...

Large-scale building energy efficiency retrofit: Concept, model and control

International Nuclear Information System (INIS)

Wu, Zhou; Wang, Bo; Xia, Xiaohua

2016-01-01

BEER (Building energy efficiency retrofit) projects are initiated in many nations and regions over the world. Existing studies of BEER focus on modeling and planning based on one building and one year period of retrofitting, which cannot be applied to certain large BEER projects with multiple buildings and multi-year retrofit. In this paper, the large-scale BEER problem is defined in a general TBT (time-building-technology) framework, which fits essential requirements of real-world projects. The large-scale BEER is newly studied in the control approach rather than the optimization approach commonly used before. Optimal control is proposed to design optimal retrofitting strategy in terms of maximal energy savings and maximal NPV (net present value). The designed strategy is dynamically changing on dimensions of time, building and technology. The TBT framework and the optimal control approach are verified in a large BEER project, and results indicate that promising performance of energy and cost savings can be achieved in the general TBT framework. - Highlights: • Energy efficiency retrofit of many buildings is studied. • A TBT (time-building-technology) framework is proposed. • The control system of the large-scale BEER is modeled. • The optimal retrofitting strategy is obtained.

Stochastic control of inertial sea wave energy converter.

Science.gov (United States)

Raffero, Mattia; Martini, Michele; Passione, Biagio; Mattiazzo, Giuliana; Giorcelli, Ermanno; Bracco, Giovanni

2015-01-01

The ISWEC (inertial sea wave energy converter) is presented, its control problems are stated, and an optimal control strategy is introduced. As the aim of the device is energy conversion, the mean absorbed power by ISWEC is calculated for a plane 2D irregular sea state. The response of the WEC (wave energy converter) is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. The resulting response is obtained as the output of the coupled mechanic-hydrodynamic model of the device. A stochastic suboptimal controller, derived from optimal control theory, is defined and applied to ISWEC. Results of this approach have been compared with the ones obtained with a linear spring-damper controller, highlighting the capability to obtain a higher value of mean extracted power despite higher power peaks.

Control of energy flow in residential buildings; Energieflussregelung in Wohngebaeuden

Energy Technology Data Exchange (ETDEWEB)

Weiss, Martin

2011-07-01

Energy systems in residential buildings are changing from monovalent, combustion based systems to multivalent systems containing technologies such as solar collectors, pellet boilers, heat pumps, CHP and multiple storages. Multivalent heat and electricity generation and additional storages raise the number of possible control signals in the system. This creates additional degrees of freedom regarding the choice of the energy converter and the instant of time for energy conversion. New functionality of controllers such as prioritisation of energy producers, optimization of electric self consumption and control of storages and energy feed-in are required. Within the scope of this thesis, new approaches for demand-driven optimal control of energy flows in multivalent building energy systems are developed and evaluated. The approaches are evaluated by means of system energy costs and operating emissions. For parametrisation of the controllers an easily understandable operating concept is developed. The energy flow controllers are implemented as a multi agent system (MAS) and a nonlinear model predictive controller (MPC). Proper functionality and stability are demonstrated in simulations of two example energy systems. In both example systems the MPC controller achieves less energy costs and operating emissions due to system wide global optimization and the more detailed system model within the controller. The multi agent approach turns out to perform better for systems with a huge number of components, e.g. in home automation and energy management systems. Due to the good performance of the reference control strategies, a significant reduction of energy costs and operating emissions is only possible with limitations. Systems for heat generation show only an especially low potential for optimization because of marginal variation ins heat production costs. The adaptation of the operation mode to user priorities, changing utilization characteristics and dynamic energy

Power flow analysis for islanded microgrid in hierarchical structure of control system using optimal control theory

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.

Optimal control design for a solar greenhouse

NARCIS (Netherlands)

Ooteghem, van R.J.C.

2007-01-01

The research of this thesis was part of a larger project aiming at the design of a greenhouse and an associated climate control that achieves optimal crop production with sustainable instead of fossil energy. This so called solar greenhouse design extends a conventional greenhouse with an improved

Helicopter Control Energy Reduction Using Moving Horizontal Tail

Science.gov (United States)

Oktay, Tugrul; Sal, Firat

2015-01-01

Helicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done. PMID:26180841

Helicopter Control Energy Reduction Using Moving Horizontal Tail

Directory of Open Access Journals (Sweden)

Tugrul Oktay

2015-01-01

Full Text Available Helicopter moving horizontal tail (i.e., MHT strategy is applied in order to save helicopter flight control system (i.e., FCS energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA. In order to observe improvement in behaviors of classical controls closed loop analyses are done.

Simulation-based optimization of sustainable national energy systems

International Nuclear Information System (INIS)

Batas Bjelić, Ilija; Rajaković, Nikola

2015-01-01

The goals of the EU2030 energy policy should be achieved cost-effectively by employing the optimal mix of supply and demand side technical measures, including energy efficiency, renewable energy and structural measures. In this paper, the achievement of these goals is modeled by introducing an innovative method of soft-linking of EnergyPLAN with the generic optimization program (GenOpt). This soft-link enables simulation-based optimization, guided with the chosen optimization algorithm, rather than manual adjustments of the decision vectors. In order to obtain EnergyPLAN simulations within the optimization loop of GenOpt, the decision vectors should be chosen and explained in GenOpt for scenarios created in EnergyPLAN. The result of the optimization loop is an optimal national energy master plan (as a case study, energy policy in Serbia was taken), followed with sensitivity analysis of the exogenous assumptions and with focus on the contribution of the smart electricity grid to the achievement of EU2030 goals. It is shown that the increase in the policy-induced total costs of less than 3% is not significant. This general method could be further improved and used worldwide in the optimal planning of sustainable national energy systems. - Highlights: • Innovative method of soft-linking of EnergyPLAN with GenOpt has been introduced. • Optimal national energy master plan has been developed (the case study for Serbia). • Sensitivity analysis on the exogenous world energy and emission price development outlook. • Focus on the contribution of smart energy systems to the EU2030 goals. • Innovative soft-linking methodology could be further improved and used worldwide.

Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array

Science.gov (United States)

Wu, Xiaohua; Hu, Xiaosong; Moura, Scott; Yin, Xiaofeng; Pickert, Volker

2016-11-01

Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements, and accommodating the variability of solar power. First, the random-variable models are developed, including Markov Chain model of PEV mobility, as well as predictive models of home power demand and PV power supply. Second, a stochastic optimal control problem is mathematically formulated for managing the power flow among energy sources in the smart home. Finally, based on time-varying electricity price, we systematically examine the performance of the proposed control strategy. As a result, the electric cost is 493.6% less for a Tesla Model S with optimal stochastic dynamic programming (SDP) control relative to the no optimal control case, and it is by 175.89% for a Nissan Leaf.

Optimal energy management of a hybrid electric powertrain system using improved particle swarm optimization

International Nuclear Information System (INIS)

Chen, Syuan-Yi; Hung, Yi-Hsuan; Wu, Chien-Hsun; Huang, Siang-Ting

2015-01-01

Highlights: • Online sub-optimal energy management using IPSO. • A second-order HEV model with 5 major segments was built. • IPSO with equivalent-fuel fitness function using 5 particles. • Engine, rule-based control, PSO, IPSO and ECMS are compared. • Max. 31+% fuel economy and 56+% energy consumption improved. - Abstract: This study developed an online suboptimal energy management system by using improved particle swarm optimization (IPSO) for engine/motor hybrid electric vehicles. The vehicle was modeled on the basis of second-order dynamics, and featured five major segments: a battery, a spark ignition engine, a lithium battery, transmission and vehicle dynamics, and a driver model. To manage the power distribution of dual power sources, the IPSO was equipped with three inputs (rotational speed, battery state-of-charge, and demanded torque) and one output (power split ratio). Five steps were developed for IPSO: (1) initialization; (2) determination of the fitness function; (3) selection and memorization; (4) modification of position and velocity; and (5) a stopping rule. Equivalent fuel consumption by the engine and motor was used as the fitness function with five particles, and the IPSO-based vehicle control unit was completed and integrated with the vehicle simulator. To quantify the energy improvement of IPSO, a four-mode rule-based control (system ready, motor only, engine only, and hybrid modes) was designed according to the engine efficiency and rotational speed. A three-loop Equivalent Consumption Minimization Strategy (ECMS) was coded as the best case. The simulation results revealed that IPSO searches the optimal solution more efficiently than conventional PSO does. In two standard driving cycles, ECE and FTP, the improvements in the equivalent fuel consumption and energy consumption compared to baseline were (24.25%, 45.27%) and (31.85%, 56.41%), respectively, for the IPSO. The CO_2 emission for all five cases (pure engine, rule-based, PSO

Stochastic Control of Inertial Sea Wave Energy Converter

Science.gov (United States)

Mattiazzo, Giuliana; Giorcelli, Ermanno

2015-01-01

The ISWEC (inertial sea wave energy converter) is presented, its control problems are stated, and an optimal control strategy is introduced. As the aim of the device is energy conversion, the mean absorbed power by ISWEC is calculated for a plane 2D irregular sea state. The response of the WEC (wave energy converter) is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. The resulting response is obtained as the output of the coupled mechanic-hydrodynamic model of the device. A stochastic suboptimal controller, derived from optimal control theory, is defined and applied to ISWEC. Results of this approach have been compared with the ones obtained with a linear spring-damper controller, highlighting the capability to obtain a higher value of mean extracted power despite higher power peaks. PMID:25874267

Stochastic Control of Inertial Sea Wave Energy Converter

Directory of Open Access Journals (Sweden)

Mattia Raffero

2015-01-01

Full Text Available The ISWEC (inertial sea wave energy converter is presented, its control problems are stated, and an optimal control strategy is introduced. As the aim of the device is energy conversion, the mean absorbed power by ISWEC is calculated for a plane 2D irregular sea state. The response of the WEC (wave energy converter is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. The resulting response is obtained as the output of the coupled mechanic-hydrodynamic model of the device. A stochastic suboptimal controller, derived from optimal control theory, is defined and applied to ISWEC. Results of this approach have been compared with the ones obtained with a linear spring-damper controller, highlighting the capability to obtain a higher value of mean extracted power despite higher power peaks.

Active Power Optimal Control of Wind Turbines with Doubly Fed Inductive Generators Based on Model Predictive Control

Directory of Open Access Journals (Sweden)

Guo Jiuwang

2015-01-01

Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

Directory of Open Access Journals (Sweden)

Yongli Wang

2018-06-01

Full Text Available Integrated energy systems (IESs are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA. The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data.

Optimal Control of Engine Warmup in Hybrid Vehicles

Directory of Open Access Journals (Sweden)

van Reeven Vital

2016-01-01

Full Text Available An Internal Combustion Engine (ICE under cold conditions experiences increased friction losses due to a high viscosity of the lubricant. With the additional control freedom present in hybrid electric vehicles, the losses during warmup can be minimized and fuel can be saved. In this paper, firstly, a control-oriented model of the ICE, describing the warmup behavior, is developed and validated on measured vehicle data. Secondly, the two-state, non-autonomous fuel optimization, for a parallel hybrid electric vehicle with stop-start functionality, is solved using optimal control theory. The principal behavior of the Lagrange multipliers is explicitly derived, including the discontinuities (jumps that are caused by the constraints on the lubricant temperature and the energy in the battery system. The minimization of the Hamiltonian for this two-state problem is also explicitly solved, resulting in a computationally efficient algorithm. The optimal controller shows the fuel benefit, as a function of the initial temperature, for a long-haul truck simulated on the FTP-75.

Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization

OpenAIRE

Khodabakhshian, Mohammad; Feng, Lei; Börjesson, Stefan; Lindgärde, Olof; Wikander, Jan

2017-01-01

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full dr...

Optimal control for chemical engineers

CERN Document Server

Upreti, Simant Ranjan

2013-01-01

Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle.The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, de

Optimization of finances into regional energy

Directory of Open Access Journals (Sweden)

Alexey Yuryevich Domnikov

2014-06-01

Full Text Available The development of modern Russian energy collides with the need for major investments in the modernization and renewal of generation and transmission capacity. In terms of attracting sufficient financial resources and find ways to increase, energy sector profitability and investment attractiveness of particular importance is the problem of investment financing optimizing aimed at minimizing the cost of financing while maintaining financial stability of the power companies and the goals and objectives of Russian energy system long-term development. The article discusses the problem of investment projects financing in power generation from the point of view of the need to achieve optimal investment budget. Presents the author’s approach to the investment financing optimization of power generation company that will achieve the minimum cost of resources involved, taking into account the impact of the funding structure for the power generating company financial sustainability. The developed model is applied to the problem of investment budget optimizing, for example, regional power generating company. The results can improve the efficiency of investment in energy, sustainable and competitive development of regional energy systems.

An Optimal and Distributed Demand Response Strategy for Energy Internet Management

Directory of Open Access Journals (Sweden)

Qian Liu

2018-01-01

Full Text Available This study proposes a new model of demand response management for a future smart grid that consists of smart microgrids. The microgrids have energy storage units, responsive loads, controllable distributed generation units, and renewable energy resources. They can buy energy from the utility company when the power generation in themselves cannot satisfy the load demand, and sell extra power generation to the utility company. The goal is to optimize the operation schedule of microgrids to minimize the microgrids’ payments and the utility company’s operation cost. A parallel distributed optimization algorithm based on games theory is developed to solve the optimization problem, in which microgrids only need to send their aggregated purchasing/selling energy to the utility company, thus avoid infringing its privacy. Microgrids can update their operation schedule simultaneously. A case study is implemented, and the simulation results show that the proposed method is effective and efficient.

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

Directory of Open Access Journals (Sweden)

Yuefei Wang

2016-10-01

Full Text Available As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

Galerkin approximations of nonlinear optimal control problems in Hilbert spaces

Directory of Open Access Journals (Sweden)

Mickael D. Chekroun

2017-07-01

Full Text Available Nonlinear optimal control problems in Hilbert spaces are considered for which we derive approximation theorems for Galerkin approximations. Approximation theorems are available in the literature. The originality of our approach relies on the identification of a set of natural assumptions that allows us to deal with a broad class of nonlinear evolution equations and cost functionals for which we derive convergence of the value functions associated with the optimal control problem of the Galerkin approximations. This convergence result holds for a broad class of nonlinear control strategies as well. In particular, we show that the framework applies to the optimal control of semilinear heat equations posed on a general compact manifold without boundary. The framework is then shown to apply to geoengineering and mitigation of greenhouse gas emissions formulated here in terms of optimal control of energy balance climate models posed on the sphere $\\mathbb{S}^2$.

Exploring the Environment/Energy Pareto Optimal Front of an Office Room Using Computational Fluid Dynamics-Based Interactive Optimization Method

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available This paper is concerned with the development of a high-resolution and control-friendly optimization framework in enclosed environments that helps improve thermal comfort, indoor air quality (IAQ, and energy costs of heating, ventilation and air conditioning (HVAC system simultaneously. A computational fluid dynamics (CFD-based optimization method which couples algorithms implemented in Matlab with CFD simulation is proposed. The key part of this method is a data interactive mechanism which efficiently passes parameters between CFD simulations and optimization functions. A two-person office room is modeled for the numerical optimization. The multi-objective evolutionary algorithm—non-dominated-and-crowding Sorting Genetic Algorithm II (NSGA-II—is realized to explore the environment/energy Pareto front of the enclosed space. Performance analysis will demonstrate the effectiveness of the presented optimization method.

ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

Directory of Open Access Journals (Sweden)

T. SHANKAR

2014-04-01

Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

An optimized surface plasmon photovoltaic structure using energy transfer between discrete nano-particles.

Science.gov (United States)

Lin, Albert; Fu, Sze-Ming; Chung, Yen-Kai; Lai, Shih-Yun; Tseng, Chi-Wei

2013-01-14

Surface plasmon enhancement has been proposed as a way to achieve higher absorption for thin-film photovoltaics, where surface plasmon polariton(SPP) and localized surface plasmon (LSP) are shown to provide dense near field and far field light scattering. Here it is shown that controlled far-field light scattering can be achieved using successive coupling between surface plasmonic (SP) nano-particles. Through genetic algorithm (GA) optimization, energy transfer between discrete nano-particles (ETDNP) is identified, which enhances solar cell efficiency. The optimized energy transfer structure acts like lumped-element transmission line and can properly alter the direction of photon flow. Increased in-plane component of wavevector is thus achieved and photon path length is extended. In addition, Wood-Rayleigh anomaly, at which transmission minimum occurs, is avoided through GA optimization. Optimized energy transfer structure provides 46.95% improvement over baseline planar cell. It achieves larger angular scattering capability compared to conventional surface plasmon polariton back reflector structure and index-guided structure due to SP energy transfer through mode coupling. Via SP mediated energy transfer, an alternative way to control the light flow inside thin-film is proposed, which can be more efficient than conventional index-guided mode using total internal reflection (TIR).

Optimal Allocation of Renewable Energy Sources for Energy Loss Minimization

Directory of Open Access Journals (Sweden)

Vaiju Kalkhambkar

2017-03-01

Full Text Available Optimal allocation of renewable distributed generation (RDG, i.e., solar and the wind in a distribution system becomes challenging due to intermittent generation and uncertainty of loads. This paper proposes an optimal allocation methodology for single and hybrid RDGs for energy loss minimization. The deterministic generation-load model integrated with optimal power flow provides optimal solutions for single and hybrid RDG. Considering the complexity of the proposed nonlinear, constrained optimization problem, it is solved by a robust and high performance meta-heuristic, Symbiotic Organisms Search (SOS algorithm. Results obtained from SOS algorithm offer optimal solutions than Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Firefly Algorithm (FFA. Economic analysis is carried out to quantify the economic benefits of energy loss minimization over the life span of RDGs.

Optimization of thermal insulation to achieve energy savings in low energy house (refurbishment)

International Nuclear Information System (INIS)

Bojić, Milorad; Miletić, Marko; Bojić, Ljubiša

2014-01-01

Highlights: • For buildings that require heating, a thickness of their thermal insulation is optimized. • The objective was to improve energy efficiency of the building. • The optimization is performed by using EnergyPlus and Hooke–Jeeves method. • The embodied energy of thermal insulation and the entire life cycle of the house are taken into account. - Abstract: Due to the current environmental situation, saving energy and reducing CO 2 emission have become the leading drive in modern research. For buildings that require heating, one of the solutions is to optimize a thickness of their thermal insulation and thus improve energy efficiency and reduce energy needs. In this paper, for a small residential house in Serbia, an optimization in the thickness of its thermal insulation layer is investigated by using EnergyPlus software and Hooke–Jeeves direct search method. The embodied energy of thermal insulation is taken into account. The optimization is done for the entire life cycle of thermal insulation. The results show the optimal thickness of thermal insulation that yields the minimum primary energy consumption

Visual prosthesis wireless energy transfer system optimal modeling.

Science.gov (United States)

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Energy-Performance as a driver for optimal production planning

International Nuclear Information System (INIS)

Salahi, Niloofar; Jafari, Mohsen A.

2016-01-01

Highlights: • A 2-dimensional Energy-Performance measure is proposed for energy aware production. • This is a novel approach integrates energy efficiency with production requirements. • This approach simultaneously incorporates machine and process related specifications. • The problem is solved as stochastic MILP with constraints addressing risk averseness. • The optimization is illustrated for 2 cases of single and serial machining operation. • Impact of various electricity pricing schemes on proposed production plan is analyzed. - Abstract: In this paper, we present energy-aware production planning using a two-dimensional “Energy-Performance” measure. With this measure, the production plan explicitly takes into account machine-level requirements, process control strategies, product types and demand patterns. The “Energy-Performance” measure is developed based on an existing concept, namely, “Specific Energy” at machine level. It is further expanded to an “Energy-Performance” profile for a production line. A production planning problem is formulated as a stochastic MILP with risk-averse constraints to account for manufacturer’s risk averseness. The objective is to attain an optimal production plan that minimizes the total loss distribution subject to system throughput targets, probabilistic risk constraints and constraints imposed by the underlying “Energy-Performance” pattern. Electricity price and demand per unit time are assumed to be stochastic. Conditional Value at Risk (CVaR) of loss distributions is used as the manufacturer’s risk measure. Both single-machine and production lines are studied for different profiles and electricity pricing schemes. It is shown that the shape of “Energy-Performance” profile can change optimal plans.

Original Framework for Optimizing Hybrid Energy Supply

Directory of Open Access Journals (Sweden)

Amevi Acakpovi

2016-01-01

Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

Optimal Adaptive Droop Control for Effective Load Sharing in AC Microgrids

DEFF Research Database (Denmark)

Anvari-Moghaddam, Amjad; Shafiee, Qobad; Quintero, Juan Carlos Vasquez

2016-01-01

During the past few years, microgrids (MGs) have been becoming more attractive as effective means to integrate different distributed energy resources (DERs). To coordinate active and reactive power sharing among DERs, conventional droop control method is widely used as a decentralized control...... control strategy is developed in two levels. The upper control level is a mixed-objective optimization algorithm that provides optimal set-points for power generations considering system’s constraints and goals, while the lower control level is responsible for tracking the reference signals coming from...

Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle

Directory of Open Access Journals (Sweden)

Linhui Li

2014-01-01

Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.

An inverter/controller subsystem optimized for photovoltaic applications

Science.gov (United States)

Pickrell, R. L.; Merrill, W. C.; Osullivan, G.

1978-01-01

Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. This paper discusses the optimization of the inverter/controller design as part of an overall Photovoltaic Power System (PPS) designed for maximum energy extraction from the solar array. The special design requirements for the inverter/controller include: (1) a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and (2) an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy. It must be capable of operating connected to the utility line at a level set by an external controller (PSC).

Optimal throughput for cognitive radio with energy harvesting in fading wireless channel.

Science.gov (United States)

Vu-Van, Hiep; Koo, Insoo

2014-01-01

Energy resource management is a crucial problem of a device with a finite capacity battery. In this paper, cognitive radio is considered to be a device with an energy harvester that can harvest energy from a non-RF energy resource while performing other actions of cognitive radio. Harvested energy will be stored in a finite capacity battery. At the start of the time slot of cognitive radio, the radio needs to determine if it should remain silent or carry out spectrum sensing based on the idle probability of the primary user and the remaining energy in order to maximize the throughput of the cognitive radio system. In addition, optimal sensing energy and adaptive transmission power control are also investigated in this paper to effectively utilize the limited energy of cognitive radio. Finding an optimal approach is formulated as a partially observable Markov decision process. The simulation results show that the proposed optimal decision scheme outperforms the myopic scheme in which current throughput is only considered when making a decision.

Optimal Switching Table-Based Sliding Mode Control of an Energy Recovery Li-Ion Power Accumulator Battery Pack Testing System

Directory of Open Access Journals (Sweden)

Kil To Chong

2013-10-01

Full Text Available The main objective of the present work is to apply a sliding mode controller (SMC to medium voltage and high power output energy recovery Li-ion power accumulator battery pack testing systems (ERLPABTSs, which are composed of a three-level neutral-point-clamped (NPC three-phase voltage source inverter (VSI and a two-level buck-boost converter without an isolating transformer. An inner current decoupled control scheme for the aforementioned system is proposed and two sliding mode planes for active and reactive current control are designed based on the control scheme. An optimized switching table for current convergence is used according to the error sign of the equivalent input voltage and feedback voltage. The proposed ERLPABTS could be used to integrate discharging energy into the power grid when performing high accuracy current testing. The active and reactive power references for the grid-connected inverter are determined based on the discharging energy from the DC-DC converter. Simulations and experiments on a laboratory hardware platform using a 175 kW insulated gate bipolar transistor (IGBT-based ERLPABTS have been implemented and verified, and the performance is found satisfactory and superior to conventional ERLPABPTS.

Intelligent multi-objective optimization for building energy and comfort management

Directory of Open Access Journals (Sweden)

Pervez Hameed Shaikh

2018-04-01

Full Text Available The rapid economic and population growth in developing countries, effective and efficient energy usage has turned out to be crucial due to the rising concern of depleting fossil fuels, of which, one-third of primary energy is consumed in buildings and expected to rise by 53% up to 2030. This roaring sector posing a challenge, due to 90% of people spend most of their time in buildings, requires enhanced well-being of indoor environment and living standards. Therefore, building operations require more energy because most of the energy is consumed to make the indoor environment comfortable. Consequently, there is the need of improved energy efficiency to decrease energy consumption in buildings. In relation to this, the primary challenge of building control systems is the energy consumption and comfort level are generally conflicting to each other. Therefore, an important problem of sustainable smart buildings is to effectively manage the energy consumption and comfort and attain the trade-off between the two. Thus, smart buildings are becoming a trend of future construction that facilitates intelligent control in buildings for the fulfillment of occupant’s comfort level. In this study, an intelligent multi-objective system has been developed with evolutionary multi-objective genetic algorithm (MOGA optimization method. The corresponding case study simulation results for the effective management of users’ comfort and energy efficiency have been carried out. The case study results show the management of energy supply for each comfort parameter and maintain high comfort index achieving balance between the energy consumption and comfort level. Keywords: Energy, Buildings, Comfort, Management, Optimization, Trade-off

Energy accounting and optimization for mobile systems

Science.gov (United States)

Dong, Mian

Energy accounting determines how much a software process contributes to the total system energy consumption. It is the foundation for evaluating software and has been widely used by operating system based energy management. While various energy accounting policies have been tried, there is no known way to evaluate them directly simply because it is hard to track every hardware use by software in a heterogeneous multi-core system like modern smartphones and tablets. In this thesis, we provide the ground truth for energy accounting based on multi-player game theory and offer the first evaluation of existing energy accounting policies, revealing their important flaws. The proposed ground truth is based on Shapley value, a single value solution to multi-player games of which four axiomatic properties are natural and self-evident to energy accounting. To obtain the Shapley value-based ground truth, one only needs to know if a process is active during the time under question and the system energy consumption during the same time. We further provide a utility optimization formulation of energy management and show, surprisingly, that energy accounting does not matter for existing energy management solutions that control the energy use of a process by giving it an energy budget, or budget based energy management (BEM). We show an optimal energy management (OEM) framework can always outperform BEM. While OEM does not require any form of energy accounting, it is related to Shapley value in that both require the system energy consumption for all possible combination of processes under question. We provide a novel system solution that meet this requirement by acquiring system energy consumption in situ for an OS scheduler period, i.e.,10 ms. We report a prototype implementation of both Shapley value-based energy accounting and OEM based scheduling. Using this prototype and smartphone workload, we experimentally demonstrate how erroneous existing energy accounting policies can

The Optimization dispatching of Micro Grid Considering Load Control

Science.gov (United States)

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.

Optimal Control of Solar Heating System

KAUST Repository

Huang, Bin-Juine

2017-02-21

Forced-circulation solar heating system has been widely used in process and domestic heating applications. Additional pumping power is required to circulate the water through the collectors to absorb the solar energy. The present study intends to develop a maximum-power point tracking control (MPPT) to obtain the minimum pumping power consumption at an optimal heat collection. The net heat energy gain Qnet (= Qs − Wp/ηe) was found to be the cost function for MPPT. The step-up-step-down controller was used in the feedback design of MPPT. The field test results show that the pumping power is 89 W at Qs = 13.7 kW and IT = 892 W/m2. A very high electrical COP of the solar heating system (Qs/Wp = 153.8) is obtained.

Analysis of Optimal Operation of an Energy Integrated Distillation Plant

DEFF Research Database (Denmark)

Li, Hong Wen; Hansen, C.A.; Gani, Rafiqul

2003-01-01

The efficiency of manufacturing systems can be significantly increased through diligent application of control based on mathematical models thereby enabling more tight integration of decision making with systems operation. In the present paper analysis of optimal operation of an energy integrated...

Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following

Directory of Open Access Journals (Sweden)

Kaijiang Yu

2014-01-01

Full Text Available This paper presents a real-time optimal control approach for the energy management problem of hybrid electric vehicles (HEVs and plug-in hybrid electric vehicles (PHEVs with slope information during car following. The new features of this study are as follows. First, the proposed method can optimize the engine operating points and the driving profile simultaneously. Second, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host vehicle. Third, using the HEV/PHEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Fourth, all of the vehicle operating modes engine charge, electric vehicle, motor assist and electric continuously variable transmission, and regenerative braking, can be realized using the proposed real-time optimal control approach. Computer simulation results are shown among the nonlinear real-time optimal control approach and the ADVISOR rule-based approach. The conclusion is that the nonlinear real-time optimal control approach is effective for the energy management problem of the HEV/PHEV system during car following.

Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

KAUST Repository

Rached, Nadhir B.

2017-02-07

Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.

An historical survey of computational methods in optimal control.

Science.gov (United States)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

Stochastic control applied to the ISWEC Wave Energy System

International Nuclear Information System (INIS)

Bracco, Giovanni; Casassa, Maria; Giorcelli, Ermanno; Mattiazzo, Giuliana; Passione, Biagio; Raffero, Mattia; Vissio, Giacomo; Martini, Michele

2015-01-01

ISWEC (Inertial Sea Wave Energy Converter) is a floating marine device able to harvest sea waves energy by the interaction between the pitching motion of a floater and a spinning flywheel which can drive an electric PTO. In the ISWEC the hull dynamics is governed and controlled by the gyroscopic torque. The optimal control logic results in tuning the floater dynamics to the incoming waves in order to maximize the power transfer from the waves to the floater. In this paper the control problems of the ISWEC are stated and a control scheme based on the sub-optimal stochastic control logic is presented. The control scheme here presented has been tested using real wave records acquired at the deployment location in Pantelleria Island, which is one of the most energetic sites of the Mediterranean Sea.

Optimal charging control of electric vehicles in smart grids

CERN Document Server

Tang, Wanrong

2017-01-01

This book introduces the optimal online charging control of electric vehicles (EVs) and battery energy storage systems (BESSs) in smart grids. The ultimate goal is to minimize the total energy cost as well as reduce the fluctuation of the total power flow caused by the integration of the EVs and renewable energy generators. Using both theoretic analysis and data-driven numerical results, the authors reveal the effectiveness and efficiency of the proposed control techniques. A major benefit of these control techniques is their practicality, since they do not rely on any non-causal knowledge of future information. Researchers, operators of power grids, and EV users will find this to be an exceptional resource. It is also suitable for advanced-level students of computer science interested in networks, electric vehicles, and energy systems.

Optimal power flow for technically feasible Energy Management systems in Islanded Microgrids

DEFF Research Database (Denmark)

Sanseverino, Eleonora Riva; T. T. Quynh, T.; Di Silvestre, Maria Luisa

2016-01-01

This paper presents a combined optimal energy and power flow management for islanded microgrids. The highest control level in this case will provide a feasible and optimized operating point around the economic optimum. In order to account for both unbalanced and balanced loads, the optimal power...... flow is carried out using a Glow-worm Swarm Optimizer. The control level is organized into two different sub-levels, the highest of which accounts for minimum cost operation and the lowest one solving the optimal power flow and devising the set points of inverter interfaced generation units...... and rotating machines with a minimum power loss. A test has been carried out for 6 bus islanded microgrids to show the efficiency and feasibility of the proposed technique....

Power Control and Optimization of Photovoltaic and Wind Energy Conversion Systems

Science.gov (United States)

Ghaffari, Azad

Power map and Maximum Power Point (MPP) of Photovoltaic (PV) and Wind Energy Conversion Systems (WECS) highly depend on system dynamics and environmental parameters, e.g., solar irradiance, temperature, and wind speed. Power optimization algorithms for PV systems and WECS are collectively known as Maximum Power Point Tracking (MPPT) algorithm. Gradient-based Extremum Seeking (ES), as a non-model-based MPPT algorithm, governs the system to its peak point on the steepest descent curve regardless of changes of the system dynamics and variations of the environmental parameters. Since the power map shape defines the gradient vector, then a close estimate of the power map shape is needed to create user assignable transients in the MPPT algorithm. The Hessian gives a precise estimate of the power map in a neighborhood around the MPP. The estimate of the inverse of the Hessian in combination with the estimate of the gradient vector are the key parts to implement the Newton-based ES algorithm. Hence, we generate an estimate of the Hessian using our proposed perturbation matrix. Also, we introduce a dynamic estimator to calculate the inverse of the Hessian which is an essential part of our algorithm. We present various simulations and experiments on the micro-converter PV systems to verify the validity of our proposed algorithm. The ES scheme can also be used in combination with other control algorithms to achieve desired closed-loop performance. The WECS dynamics is slow which causes even slower response time for the MPPT based on the ES. Hence, we present a control scheme, extended from Field-Oriented Control (FOC), in combination with feedback linearization to reduce the convergence time of the closed-loop system. Furthermore, the nonlinear control prevents magnetic saturation of the stator of the Induction Generator (IG). The proposed control algorithm in combination with the ES guarantees the closed-loop system robustness with respect to high level parameter uncertainty

Optimal control

CERN Document Server

Aschepkov, Leonid T; Kim, Taekyun; Agarwal, Ravi P

2016-01-01

This book is based on lectures from a one-year course at the Far Eastern Federal University (Vladivostok, Russia) as well as on workshops on optimal control offered to students at various mathematical departments at the university level. The main themes of the theory of linear and nonlinear systems are considered, including the basic problem of establishing the necessary and sufficient conditions of optimal processes. In the first part of the course, the theory of linear control systems is constructed on the basis of the separation theorem and the concept of a reachability set. The authors prove the closure of a reachability set in the class of piecewise continuous controls, and the problems of controllability, observability, identification, performance and terminal control are also considered. The second part of the course is devoted to nonlinear control systems. Using the method of variations and the Lagrange multipliers rule of nonlinear problems, the authors prove the Pontryagin maximum principle for prob...

Optimization and Control of Cyber-Physical Vehicle Systems

Directory of Open Access Journals (Sweden)

Justin M. Bradley

2015-09-01

Full Text Available A cyber-physical system (CPS is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

Optimization and Control of Cyber-Physical Vehicle Systems.

Science.gov (United States)

Bradley, Justin M; Atkins, Ella M

2015-09-11

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

Energy and operation management of a microgrid using particle swarm optimization

Science.gov (United States)

Radosavljević, Jordan; Jevtić, Miroljub; Klimenta, Dardan

2016-05-01

This article presents an efficient algorithm based on particle swarm optimization (PSO) for energy and operation management (EOM) of a microgrid including different distributed generation units and energy storage devices. The proposed approach employs PSO to minimize the total energy and operating cost of the microgrid via optimal adjustment of the control variables of the EOM, while satisfying various operating constraints. Owing to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties and market prices, a probabilistic approach in the EOM is introduced. The proposed method is examined and tested on a typical grid-connected microgrid including fuel cell, gas-fired microturbine, wind turbine, photovoltaic and energy storage devices. The obtained results prove the efficiency of the proposed approach to solve the EOM of the microgrids.

Techno-Economic Optimization of a Sustainable Energy System for a 100% Renewables Smart House

DEFF Research Database (Denmark)

Craciun, Vasile Simion; Blarke, Morten; Trifa, Viorel

2012-01-01

technical and economic challenges. One such challenge is the discontinuity, or intermittency, of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization strategies. This paper presents a model and optimization...... for a sustainable energy system for a 100% renewables based Smart House (SH). We have devised and analysed an innovative high-efficiency approach to residential energy supply. The analysis involves detailed technical specifications and considerations for providing optimal supply of electricity, heating, cooling......The continuous increasing negative effects of fossil fuel consumption on society and the environment, opens a major interest into environmentally friendly alternatives to sustain the increasing demand for energy services. Despite the obvious advantages of renewable energy, it presents important...

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

Science.gov (United States)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Energy, economy, and environment analysis and optimization on manufacturing plant energy supply system

International Nuclear Information System (INIS)

Feng, Lujia; Mears, Laine; Beaufort, Cleveland; Schulte, Joerg

2016-01-01

Highlights: • Single objective and multicriteria optimization approaches are proposed. • Objectives of energy, economy, and environment are proved conflicting. • 3-input-5-output energy supply system of an automotive plant is studied. - Abstract: Increasing attention has recently been drawn to energy consumption in manufacturing plants. Facing the challenges from reducing emissions coupled with rising raw material prices and energy costs, manufacturers are trying to balance the energy usage strategy among the total energy consumption, economy, and environment, which can be self-conflicting at times. In this paper, energy systems in manufacturing environments are reviewed, and the current status of onsite energy system and renewable energy usage are discussed. Single objective and multicriteria optimization approaches are effectively formulated for making the best use of energy delivered to the production processes. Energy supply operation suggestions based on the optimization results are obtained. Finally, an example from an automotive assembly manufacturer is described to demonstrate the energy usage in the current manufacturing plants and how the optimization approaches can be applied to satisfy the energy management objectives. According to the optimization results, in an energy oriented operation, it takes 35% more in monetary cost; while in an economy oriented operation, it takes 17% more in megawatt hour energy supply and tends to rely more on the inexpensive renewable energy.

Study on the optimal control of the ground thermal storage system in the greenhouse. Part 4; Onshitsu ni okeru taiyo energy dochu chikunetsu system ni okeru saiteki seigyo ni kansuru kenkyu

Energy Technology Data Exchange (ETDEWEB)

Zheng, M [Sanko Air Conditioning Co. Ltd., Osaka (Japan); Nakahara, N [Kanagawa University, Yokohama (Japan)

1996-10-27

Three types of weight in both energy saving and optimum room temperature environment were changed to obtain the optimal control solution of the ground thermal storage system in a greenhouse. The relation diagram between the optimal solution of a performance function, and the state constraints and control function constraints was created in consideration of the energy term in a control function value area and the room temperature environment. As a result, the whole image of the performance function could be grasped in consideration of the energy term with inequality constraints and the room temperature environmental term in this study. The rate of a weighting factor in the performance function significantly influences the optimal solution. The influence on the optimal solution also changes when the optimal room temperature schedule differs. The influence that three types of rising algorithm exert on the convergence and converging speed was investigated. Superiority or inferiority occurs according to the space properties of a performance function. A zigzag method is most disadvantageous. The constraints can be converged to the optimal solution using an SUMT outer point method irrespective of the initial value. 6 refs., 6 figs., 4 tabs.

Optimal Control of Mechanical Systems

Directory of Open Access Journals (Sweden)

Vadim Azhmyakov

2007-01-01

Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.

Introduction to optimal control theory

International Nuclear Information System (INIS)

Agrachev, A.A.

2002-01-01

These are lecture notes of the introductory course in Optimal Control theory treated from the geometric point of view. Optimal Control Problem is reduced to the study of controls (and corresponding trajectories) leading to the boundary of attainable sets. We discuss Pontryagin Maximum Principle, basic existence results, and apply these tools to concrete simple optimal control problems. Special sections are devoted to the general theory of linear time-optimal problems and linear-quadratic problems. (author)

Optimal control of transitions between nonequilibrium steady states.

Directory of Open Access Journals (Sweden)

Patrick R Zulkowski

Full Text Available Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines.

Determining an energy-optimal thermal management strategy for electric driven vehicles

Energy Technology Data Exchange (ETDEWEB)

Suchaneck, Andre; Probst, Tobias; Puente Leon, Fernando [Karlsruher Institut fuer Technology (KIT), Karlsruhe (Germany). Inst. of Industrial Information Technology (IIIT)

2012-11-01

In electric, hybrid electric and fuel cell vehicles, thermal management may have a significant impact on vehicle range. Therefore, optimal thermal management strategies are required. In this paper a method for determining an energy-optimal control strategy for thermal power generation in electric driven vehicles is presented considering all controlled devices (pumps, valves, fans, and the like) as well as influences like ambient temperature, vehicle speed, motor and battery and cooling cycle temperatures. The method is designed to be generic to increase the thermal management development process speed and to achieve the maximal energy reduction for any electric driven vehicle (e.g., by waste heat utilization). Based on simulations of a prototype electric vehicle with an advanced cooling cycle structure, the potential of the method is shown. (orig.)

Real Time Optimal Control of Supercapacitor Operation for Frequency Response

Energy Technology Data Exchange (ETDEWEB)

Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish; Hovsapian, Rob

2016-07-01

Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance to the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.

Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub

International Nuclear Information System (INIS)

Ma, Tengfei; Wu, Junyong; Hao, Liangliang

2017-01-01

Highlights: • Design a novel architecture for energy hub integrating power hub, cooling hub and heating hub. • The micro energy grid based on energy hub is introduced and its advantages are discussed. • Propose a generic modeling method for the energy flow of micro energy grid. • Propose an optimal operation model for micro energy grid with considering demand response. • The roles of renewable energy, energy storage devices and demand response are discussed separately. - Abstract: The energy security and environmental problems impel people to explore a more efficient, environment friendly and economical energy utilization pattern. In this paper, the coordinated operation and optimal dispatch strategies for multiple energy system are studied at the whole Micro Energy Grid level. To augment the operation flexibility of energy hub, the innovation sub-energy hub structure including power hub, heating hub and cooling hub is put forward. Basing on it, a generic energy hub architecture integrating renewable energy, combined cooling heating and power, and energy storage devices is developed. Moreover, a generic modeling method for the energy flow of micro energy grid is proposed. To minimize the daily operation cost, a day-ahead dynamic optimal operation model is formulated as a mixed integer linear programming optimization problem with considering the demand response. Case studies are undertaken on a community Micro Energy Grid in four different scenarios on a typical summer day and the roles of renewable energy, energy storage devices and demand response are discussed separately. Numerical simulation results indicate that the proposed energy flow modeling and optimal operation method are universal and effective over the entire energy dispatching horizon.

Application of Minimum-time Optimal Control System in Buck-Boost Bi-linear Converters

Directory of Open Access Journals (Sweden)

S. M. M. Shariatmadar

2017-08-01

Full Text Available In this study, the theory of minimum-time optimal control system in buck-boost bi-linear converters is described, so that output voltage regulation is carried out within minimum time. For this purpose, the Pontryagin's Minimum Principle is applied to find optimal switching level applying minimum-time optimal control rules. The results revealed that by utilizing an optimal switching level instead of classical switching patterns, output voltage regulation will be carried out within minimum time. However, transient energy index of increased overvoltage significantly reduces in order to attain minimum time optimal control in reduced output load. The laboratory results were used in order to verify numerical simulations.

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

Science.gov (United States)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the

Optimization of operation of energy supply systems with co-generation and absorption refrigeration

Directory of Open Access Journals (Sweden)

Stojiljković Mirko M.

2012-01-01

Full Text Available Co-generation systems, together with absorption refrigeration and thermal storage, can result in substantial benefits from the economic, energy and environmental point of view. Optimization of operation of such systems is important as a component of the entire optimization process in pre-construction phases, but also for short-term energy production planning and system control. This paper proposes an approach for operational optimization of energy supply systems with small or medium scale co-generation, additional boilers and heat pumps, absorption and compression refrigeration, thermal energy storage and interconnection to the electric utility grid. In this case, the objective is to minimize annual costs related to the plant operation. The optimization problem is defined as mixed integer nonlinear and solved combining modern stochastic techniques: genetic algorithms and simulated annealing with linear programming using the object oriented “ESO-MS” software solution for simulation and optimization of energy supply systems, developed as a part of this research. This approach is applied to optimize a hypothetical plant that might be used to supply a real residential settlement in Niš, Serbia. Results are compared to the ones obtained after transforming the problem to mixed 0-1 linear and applying the branch and bound method.

I.T., Optimized energy systems and new customer services. The deregulated electricity market and the Ronneby case

Energy Technology Data Exchange (ETDEWEB)

Bergstroem, U

1999-03-01

This thesis concerns the utilization of information technology to obtain optimized energy systems and the increasing dependence on IT applications within the power industry in general, and especially within electricity. Based on energy system optimizations, industrial simulations, interviews and literature surveys, the thesis concludes that information technology is a condition for optimized energy systems. Through large-scale load control, enabled by IT, the energy system cost for supplying a local energy system can be reduced considerably. Diurnal energy system optimizations further illustrate the increased utilization of load control, accentuated, when customers are exposed to the variations of the spot market price. Thereby, the increased need for load management on a deregulated market, where real time pricing is applied, is mirrored. However, given the boundary conditions of the deregulated electricity market, optimization of energy systems is no condition for competitiveness within electricity sales. This study also points out that, apart from industrial customers, other market actors, like electricity sales companies and local distributors, have few incentives to introduce load control. Distributors mainly lose money on power reducing measures, except for when there are distribution limitations. Neither do electricity sales companies make short-term earnings from large-scale load control. The combination with small economic savings for residential customers make the financing of large-scale load control problematic. Regarding electricity sales companies, increased IT utilization is observed to enable marketing and service offerings on the Internet, and IT-based value-added services (VAS). For pure communication services, the sales companies utilize IT to offer telephone services (analogue technique) and Internet access, the latter is sometimes performed on the electricity grid. Extended IT-systems for customer administration, customer service, and market

Model Predictive Control of Buoy Type Wave Energy Converter

DEFF Research Database (Denmark)

Soltani, Mohsen N.; Sichani, Mahdi T.; Mirzaei, Mahmood

2014-01-01

by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

Optimal Control and Optimization of Stochastic Supply Chain Systems

CERN Document Server

Song, Dong-Ping

2013-01-01

Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies.                 In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...

Analysis and Optimization of Building Energy Consumption

Science.gov (United States)

Chuah, Jun Wei

Energy is one of the most important resources required by modern human society. In 2010, energy expenditures represented 10% of global gross domestic product (GDP). By 2035, global energy consumption is expected to increase by more than 50% from current levels. The increased pace of global energy consumption leads to significant environmental and socioeconomic issues: (i) carbon emissions, from the burning of fossil fuels for energy, contribute to global warming, and (ii) increased energy expenditures lead to reduced standard of living. Efficient use of energy, through energy conservation measures, is an important step toward mitigating these effects. Residential and commercial buildings represent a prime target for energy conservation, comprising 21% of global energy consumption and 40% of the total energy consumption in the United States. This thesis describes techniques for the analysis and optimization of building energy consumption. The thesis focuses on building retrofits and building energy simulation as key areas in building energy optimization and analysis. The thesis first discusses and evaluates building-level renewable energy generation as a solution toward building energy optimization. The thesis next describes a novel heating system, called localized heating. Under localized heating, building occupants are heated individually by directed radiant heaters, resulting in a considerably reduced heated space and significant heating energy savings. To support localized heating, a minimally-intrusive indoor occupant positioning system is described. The thesis then discusses occupant-level sensing (OLS) as the next frontier in building energy optimization. OLS captures the exact environmental conditions faced by each building occupant, using sensors that are carried by all building occupants. The information provided by OLS enables fine-grained optimization for unprecedented levels of energy efficiency and occupant comfort. The thesis also describes a retrofit

Control parameter optimization for AP1000 reactor using Particle Swarm Optimization

International Nuclear Information System (INIS)

Wang, Pengfei; Wan, Jiashuang; Luo, Run; Zhao, Fuyu; Wei, Xinyu

2016-01-01

Highlights: • The PSO algorithm is applied for control parameter optimization of AP1000 reactor. • Key parameters of the MSHIM control system are optimized. • Optimization results are evaluated though simulations and quantitative analysis. - Abstract: The advanced mechanical shim (MSHIM) core control strategy is implemented in the AP1000 reactor for core reactivity and axial power distribution control simultaneously. The MSHIM core control system can provide superior reactor control capabilities via automatic rod control only. This enables the AP1000 to perform power change operations automatically without the soluble boron concentration adjustments. In this paper, the Particle Swarm Optimization (PSO) algorithm has been applied for the parameter optimization of the MSHIM control system to acquire better reactor control performance for AP1000. System requirements such as power control performance, control bank movement and AO control constraints are reflected in the objective function. Dynamic simulations are performed based on an AP1000 reactor simulation platform in each iteration of the optimization process to calculate the fitness values of particles in the swarm. The simulation platform is developed in Matlab/Simulink environment with implementation of a nodal core model and the MSHIM control strategy. Based on the simulation platform, the typical 10% step load decrease transient from 100% to 90% full power is simulated and the objective function used for control parameter tuning is directly incorporated in the simulation results. With successful implementation of the PSO algorithm in the control parameter optimization of AP1000 reactor, four key parameters of the MSHIM control system are optimized. It has been demonstrated by the calculation results that the optimized MSHIM control system parameters can improve the reactor power control capability and reduce the control rod movement without compromising AO control. Therefore, the PSO based optimization

An effective and optimal quality control approach for green energy manufacturing using design of experiments framework and evolutionary algorithm

Science.gov (United States)

Saavedra, Juan Alejandro

Quality Control (QC) and Quality Assurance (QA) strategies vary significantly across industries in the manufacturing sector depending on the product being built. Such strategies range from simple statistical analysis and process controls, decision-making process of reworking, repairing, or scraping defective product. This study proposes an optimal QC methodology in order to include rework stations during the manufacturing process by identifying the amount and location of these workstations. The factors that are considered to optimize these stations are cost, cycle time, reworkability and rework benefit. The goal is to minimize the cost and cycle time of the process, but increase the reworkability and rework benefit. The specific objectives of this study are: (1) to propose a cost estimation model that includes energy consumption, and (2) to propose an optimal QC methodology to identify quantity and location of rework workstations. The cost estimation model includes energy consumption as part of the product direct cost. The cost estimation model developed allows the user to calculate product direct cost as the quality sigma level of the process changes. This provides a benefit because a complete cost estimation calculation does not need to be performed every time the processes yield changes. This cost estimation model is then used for the QC strategy optimization process. In order to propose a methodology that provides an optimal QC strategy, the possible factors that affect QC were evaluated. A screening Design of Experiments (DOE) was performed on seven initial factors and identified 3 significant factors. It reflected that one response variable was not required for the optimization process. A full factorial DOE was estimated in order to verify the significant factors obtained previously. The QC strategy optimization is performed through a Genetic Algorithm (GA) which allows the evaluation of several solutions in order to obtain feasible optimal solutions. The GA

Optimization of Key Parameters of Energy Management Strategy for Hybrid Electric Vehicle Using DIRECT Algorithm

Directory of Open Access Journals (Sweden)

Jingxian Hao

2016-11-01

Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.

Global Energy-Optimal Redundancy Resolution of Hydraulic Manipulators: Experimental Results for a Forestry Manipulator

Directory of Open Access Journals (Sweden)

Jarmo Nurmi

2017-05-01

Full Text Available This paper addresses the energy-inefficiency problem of four-degrees-of-freedom (4-DOF hydraulic manipulators through redundancy resolution in robotic closed-loop controlled applications. Because conventional methods typically are local and have poor performance for resolving redundancy with respect to minimum hydraulic energy consumption, global energy-optimal redundancy resolution is proposed at the valve-controlled actuator and hydraulic power system interaction level. The energy consumption of the widely popular valve-controlled load-sensing (LS and constant-pressure (CP systems is effectively minimised through cost functions formulated in a discrete-time dynamic programming (DP approach with minimum state representation. A prescribed end-effector path and important actuator constraints at the position, velocity and acceleration levels are also satisfied in the solution. Extensive field experiments performed on a forestry hydraulic manipulator demonstrate the performance of the proposed solution. Approximately 15–30% greater hydraulic energy consumption was observed with the conventional methods in the LS and CP systems. These results encourage energy-optimal redundancy resolution in future robotic applications of hydraulic manipulators.

Optimization of Overtopping Wave Energy Converters by Geometry Control

DEFF Research Database (Denmark)

Victor, L.; Troch, P.; Kofoed, Jens Peter

2011-01-01

In this paper, the results of a study on the effects of geometry control on the performance of overtopping wave energy converters with a simple geometry built in coastal structures (simple OWECs) are presented. Empirical formulae, derived based on experimental tests on simple OWECs with varying...

Optimal Control to Increase Energy Production of Wind Farm Considering Wake Effect and Lifetime Estimation

DEFF Research Database (Denmark)

Tian, Jie; Zhou, Dao; Su, Chi

2017-01-01

as an example. Due to the small range of the effective wake area, it is found that the energy production is almost the same. Finally, the pitch angle curve and active power curve are optimized according to the Maximum Energy Production (MEP) of a wind farm. Upon considering and contrasting the MPPT method...... to maximize the energy production of wind farms by considering the wake effect and the lifetime of wind turbine. It starts with the analysis of the pitch angle curve and active power curve seen from the Maximum Power Point Tracking (MPPT) of individual wind turbines. Taking the wake effect into account......, the pitch angle curve and active power curve are optimized with the aim of Maximum Power Generation (MPG) of the wind farm. Afterwards, considering the lifetime of wind turbines, a comparison is offered between the MPPT method and the MPG method for energy production using a simplified two-turbine wind farm...

Integrated energy optimization with smart home energy management systems

NARCIS (Netherlands)

Asare-Bediako, B.; Ribeiro, P.F.; Kling, W.L.

2012-01-01

Optimization of energy use is a vital concept in providing solutions to many of the energy challenges in our world today. Large chemical, mechanical, pneumatic, hydraulic, and electrical systems require energy efficiency as one of the important aspects of operating systems. At the micro-scale, the

Integrated solar energy system optimization

Science.gov (United States)

Young, S. K.

1982-11-01

The computer program SYSOPT, intended as a tool for optimizing the subsystem sizing, performance, and economics of integrated wind and solar energy systems, is presented. The modular structure of the methodology additionally allows simulations when the solar subsystems are combined with conventional technologies, e.g., a utility grid. Hourly energy/mass flow balances are computed for interconnection points, yielding optimized sizing and time-dependent operation of various subsystems. The program requires meteorological data, such as insolation, diurnal and seasonal variations, and wind speed at the hub height of a wind turbine, all of which can be taken from simulations like the TRNSYS program. Examples are provided for optimization of a solar-powered (wind turbine and parabolic trough-Rankine generator) desalinization plant, and a design analysis for a solar powered greenhouse.

Energy optimization of bread baking process undergoing quality constraints

International Nuclear Information System (INIS)

Papasidero, Davide; Pierucci, Sauro; Manenti, Flavio

2016-01-01

International home energy rating regulations are forcing to use efficient cooking equipment and processes towards energy saving and sustainability. For this reason gas ovens are replaced by the electric ones, to get the highest energy rating. Due to this fact, the study of the technologies related to the energy efficiency in cooking is increasingly developing. Indeed, big industries are working to the energy optimization of their processes since decades, while there is still a lot of room in energy optimization of single household appliances. The achievement of a higher efficiency can have a big impact on the society only if the use of modern equipment gets widespread. The combination of several energy sources (e.g. forced convection, irradiation, microwave, etc.) and their optimization is an emerging target for oven manufacturers towards optimal oven design. In this work, an energy consumption analysis and optimization is applied to the case of bread baking. Each source of energy gets the due importance and the process conditions are compared. A basic quality standard is guaranteed by taking into account some quality markers, which are relevant based on a consumer viewpoint. - Highlights: • Energy optimization is based on a validated finite-element model for bread baking. • Quality parameters for the product acceptability are introduced as constraints. • Dynamic optimization leads to 20% energy saving compared to non-optimized case. • The approach is applicable to many products, quality parameters, thermal processes. • Other heating processes can be easily integrated in the presented model.

Optimized design of low energy buildings

DEFF Research Database (Denmark)

Rudbeck, Claus Christian; Esbensen, Peter Kjær; Svendsen, Sv Aa Højgaard

1999-01-01

concern which can be seen during the construction of new buildings. People want energy-friendly solutions, but they should be economical optimized. An exonomical optimized building design with respect to energy consumption is the design with the lowest total cost (investment plus operational cost over its...... to evaluate different separate solutions when they interact in the building.When trying to optimize several parameters there is a need for a method, which will show the correct price-performance of each part of a building under design. The problem with not having such a method will first be showed...

Nonlinear optimal control theory

CERN Document Server

Berkovitz, Leonard David

2012-01-01

Nonlinear Optimal Control Theory presents a deep, wide-ranging introduction to the mathematical theory of the optimal control of processes governed by ordinary differential equations and certain types of differential equations with memory. Many examples illustrate the mathematical issues that need to be addressed when using optimal control techniques in diverse areas. Drawing on classroom-tested material from Purdue University and North Carolina State University, the book gives a unified account of bounded state problems governed by ordinary, integrodifferential, and delay systems. It also dis

The Design of Optimal PID Control Method for Quadcopter Movement Control

Directory of Open Access Journals (Sweden)

Hanum Arrosida

2018-02-01

Full Text Available Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.

Energy optimized automatic public transportation system with a microprocessor in the vehicle

Energy Technology Data Exchange (ETDEWEB)

Tchinda, A.

1980-09-11

The matter with energy optimizing running is, that the train reaches the final state (target station) from the initial state (original station) in time with consideration of the given safety demands and other limitations and the consumed energy has its minimal value. This principle was extended for a driverless train operation in a sense that the optimization problem was formulated new and solved with regards to extensive secondary conditions as: velocity-dependent train and braking power and motion resistance force, path-dependent maximum velocity of the route and hazardous points. The algorithms for optimal vehicle control were developed by means of E. Bellmann's dynamic programming with regards to the secondary conditions mentioned above.

Comparison of three control strategies for optimization of spray dryer operation

DEFF Research Database (Denmark)

Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2017-01-01

controllers for operation of a four-stage spray dryer. The three controllers are a proportional-integral (PI) controller that is used in industrial practice for spray dryer operation, a linear model predictive controller with real-time optimization (MPC with RTO, MPC-RTO), and an economically optimizing...... nonlinear model predictive controller (E-NMPC). The MPC with RTO is based on the same linear state space model in the MPC and the RTO layer. The E-NMPC consists of a single optimization layer that uses a nonlinear system of ordinary differential equations for its predictions. The PI control strategy has...... the production rate, while minimizing the energy consumption, keeping the residual moisture content of the powder below a maximum limit, and avoiding that the powder sticks to the chamber walls. We use an industrially recorded disturbance scenario in order to produce realistic simulations and conclusions...

Optimization in the energy sector

International Nuclear Information System (INIS)

2015-01-01

The implementation of the energy transition and the developments in the national and international Energy markets constantly require sound analysis and new answers. The symposium ''optimization in the energy sector'' gives an overview of methods and models that can be practically used for decision support. Storage and electromobility as demand flexibility are important factors for the long-term design of the German and European energy system. But methodological aspects such as the consideration of uncertainties at the conference an important place is given. A key issue is also the short and medium term further development of the electricity market design. Not only broadly but also in detail e.g. the standard benefit and intraday markets there is considerable potential for optimization, which will be discussed in the context of technical presentations. And in view of challenging market environment is also new approaches to portfolio management a great importance for the practice. Therefore we are convinced that the Conference and its results for energy companies, public services and new entrants in the energy industry as well are of interest as for consultants, authorities, associations and energy economic research institutes. [de

Optimization in the design and control of robotic manipulators: A survey

International Nuclear Information System (INIS)

Rao, S.S.; Bhatti, P.K.

1989-01-01

Robotics is a relatively new and evolving technology being applied to manufacturing automation and is fast replacing the special-purpose machines or hard automation as it is often called. Demands for higher productivity, better and uniform quality products, and better working environments are primary reasons for its development. An industrial robot is a multifunctional and computer-controlled mechanical manipulator exhibiting a complex and highly nonlinear behavior. Even though most current robots have anthropomorphic configurations, they have far inferior manipulating abilities compared to humans. A great deal of research effort is presently being directed toward improving their overall performance by using optimal mechanical structures and control strategies. The optimal design of robot manipulators can include kinematic performance characteristics such as workspace, accuracy, repeatability, and redundancy. The static load capacity as well as dynamic criteria such as generalized inertia ellipsoid, dynamic manipulability, and vibratory response have also been considered in the design stages. The optimal control problems typically involve trajectory planning, time-optimal control, energy-optimal control, and mixed-optimal control. The constraints in a robot manipulator design problem usually involve link stresses, actuator torques, elastic deformation of links, and collision avoidance. This paper presents a review of the literature on the issues of optimum design and control of robotic manipulators and also the various optimization techniques currently available for application to robotics

Fuel optimization for low-thrust Earth-Moon transfer via indirect optimal control

Science.gov (United States)

Pérez-Palau, Daniel; Epenoy, Richard

2018-02-01

The problem of designing low-energy transfers between the Earth and the Moon has attracted recently a major interest from the scientific community. In this paper, an indirect optimal control approach is used to determine minimum-fuel low-thrust transfers between a low Earth orbit and a Lunar orbit in the Sun-Earth-Moon Bicircular Restricted Four-Body Problem. First, the optimal control problem is formulated and its necessary optimality conditions are derived from Pontryagin's Maximum Principle. Then, two different solution methods are proposed to overcome the numerical difficulties arising from the huge sensitivity of the problem's state and costate equations. The first one consists in the use of continuation techniques. The second one is based on a massive exploration of the set of unknown variables appearing in the optimality conditions. The dimension of the search space is reduced by considering adapted variables leading to a reduction of the computational time. The trajectories found are classified in several families according to their shape, transfer duration and fuel expenditure. Finally, an analysis based on the dynamical structure provided by the invariant manifolds of the two underlying Circular Restricted Three-Body Problems, Earth-Moon and Sun-Earth is presented leading to a physical interpretation of the different families of trajectories.

Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries

Directory of Open Access Journals (Sweden)

Yan Li

2016-01-01

Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.

Energy Hub’s Structural and Operational Optimization for Minimal Energy Usage Costs in Energy Systems

Directory of Open Access Journals (Sweden)

Thanh Tung Ha

2018-03-01

Full Text Available The structural and optimal operation of an Energy Hub (EH has a tremendous influence on the hub’s performance and reliability. This paper envisions an innovative methodology that prominently increases the synergy between structural and operational optimization and targets system cost affordability. The generalized energy system structure is presented theoretically with all selective hub sub-modules, including electric heater (EHe and solar sources block sub-modules. To minimize energy usage cost, an energy hub is proposed that consists of 12 kinds of elements (i.e., energy resources, conversion, and storage functions and is modeled mathematically in a General Algebraic Modeling System (GAMS, which indicates the optimal hub structure’s corresponding elements with binary variables (0, 1. Simulation results contrast with 144 various scenarios established in all 144 categories of hub structures, in which for each scenario the corresponding optimal operation cost is previously calculated. These case studies demonstrate the effectiveness of the suggested model and methodology. Finally, avenues for future research are also prospected.

Hydrogen Production from Optimal Wind-PV Energies Systems

Energy Technology Data Exchange (ETDEWEB)

Tafticht, T.; Agbossou, K. [Institut de recherche sur l hydrogene, Universite du Quebec - Trois-Rivieres, C.P. 500, Trois-Rivieres, (Ciheam), G9A 5H7, (Canada)

2006-07-01

Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energies (RE). A stand-alone RE system based on hydrogen production has been developed at the Hydrogen Research Institute and successfully tested for automatic operation with designed control devices. The system is composed of a wind turbine, a photovoltaic (PV) array, an electrolyser, batteries for buffer energy storage, hydrogen and oxygen storage tanks, a fuel cell, AC and DC loads, power conditioning devices and different sensors. The long-term excess energy with respect to load demand has been sent to the electrolyser for hydrogen production and then the fuel cell has utilised this stored hydrogen to produce electricity when there were insufficient wind and solar energies with respect to load requirements. The RE system components have substantially different voltage-current characteristics and they are integrated on the DC bus through power conditioning devices for optimal operation by using the developed Maximum Power Point Tracking (MPPT) control method. The experimental results show that the power gain obtained by this method clearly increases the hydrogen production and storage rate from wind-PV systems. (authors)

Hydrogen Production from Optimal Wind-PV Energies Systems

International Nuclear Information System (INIS)

T Tafticht; K Agbossou

2006-01-01

Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energies (RE). A stand-alone RE system based on hydrogen production has been developed at the Hydrogen Research Institute and successfully tested for automatic operation with designed control devices. The system is composed of a wind turbine, a photovoltaic (PV) array, an electrolyzer, batteries for buffer energy storage, hydrogen and oxygen storage tanks, a fuel cell, AC and DC loads, power conditioning devices and different sensors. The long-term excess energy with respect to load demand has been sent to the electrolyser for hydrogen production and then the fuel cell has utilised this stored hydrogen to produce electricity when there were insufficient wind and solar energies with respect to load requirements. The RE system components have substantially different voltage-current characteristics and they are integrated on the DC bus through power conditioning devices for optimal operation by using the developed Maximum Power Point Tracking (MPPT) control method. The experimental results show that the power gain obtained by this method clearly increases the hydrogen production and storage rate from wind-PV systems. (authors)

Hydrogen Production from Optimal Wind-PV Energies Systems

International Nuclear Information System (INIS)

Tafticht, T.; Agbossou, K.

2006-01-01

Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energies (RE). A stand-alone RE system based on hydrogen production has been developed at the Hydrogen Research Institute and successfully tested for automatic operation with designed control devices. The system is composed of a wind turbine, a photovoltaic (PV) array, an electrolyser, batteries for buffer energy storage, hydrogen and oxygen storage tanks, a fuel cell, AC and DC loads, power conditioning devices and different sensors. The long-term excess energy with respect to load demand has been sent to the electrolyser for hydrogen production and then the fuel cell has utilised this stored hydrogen to produce electricity when there were insufficient wind and solar energies with respect to load requirements. The RE system components have substantially different voltage-current characteristics and they are integrated on the DC bus through power conditioning devices for optimal operation by using the developed Maximum Power Point Tracking (MPPT) control method. The experimental results show that the power gain obtained by this method clearly increases the hydrogen production and storage rate from wind-PV systems. (authors)

Hydrogen Production from Optimal Wind-PV Energies Systems

Energy Technology Data Exchange (ETDEWEB)

T Tafticht; K Agbossou [Institut de recherche sur l hydrogene, Universite du Quebec - Trois-Rivieres, C.P. 500, Trois-Rivieres, (Ciheam), G9A 5H7, (Canada)

2006-07-01

Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energies (RE). A stand-alone RE system based on hydrogen production has been developed at the Hydrogen Research Institute and successfully tested for automatic operation with designed control devices. The system is composed of a wind turbine, a photovoltaic (PV) array, an electrolyzer, batteries for buffer energy storage, hydrogen and oxygen storage tanks, a fuel cell, AC and DC loads, power conditioning devices and different sensors. The long-term excess energy with respect to load demand has been sent to the electrolyser for hydrogen production and then the fuel cell has utilised this stored hydrogen to produce electricity when there were insufficient wind and solar energies with respect to load requirements. The RE system components have substantially different voltage-current characteristics and they are integrated on the DC bus through power conditioning devices for optimal operation by using the developed Maximum Power Point Tracking (MPPT) control method. The experimental results show that the power gain obtained by this method clearly increases the hydrogen production and storage rate from wind-PV systems. (authors)

Performance comparison of renewable incentive schemes using optimal control

International Nuclear Information System (INIS)

Oak, Neeraj; Lawson, Daniel; Champneys, Alan

2014-01-01

Many governments worldwide have instituted incentive schemes for renewable electricity producers in order to meet carbon emissions targets. These schemes aim to boost investment and hence growth in renewable energy industries. This paper examines four such schemes: premium feed-in tariffs, fixed feed-in tariffs, feed-in tariffs with contract for difference and the renewable obligations scheme. A generalised mathematical model of industry growth is presented and fitted with data from the UK onshore wind industry. The model responds to subsidy from each of the four incentive schemes. A utility or ‘fitness’ function that maximises installed capacity at some fixed time in the future while minimising total cost of subsidy is postulated. Using this function, the optimal strategy for provision and timing of subsidy for each scheme is calculated. Finally, a comparison of the performance of each scheme, given that they use their optimal control strategy, is presented. This model indicates that the premium feed-in tariff and renewable obligation scheme produce the joint best results. - Highlights: • Stochastic differential equation model of renewable energy industry growth and prices, using UK onshore wind data 1992–2010. • Cost of production reduces as cumulative installed capacity of wind energy increases, consistent with the theory of learning. • Studies the effect of subsidy using feed-in tariff schemes, and the ‘renewable obligations’ scheme. • We determine the optimal timing and quantity of subsidy required to maximise industry growth and minimise costs. • The premium feed-in tariff scheme and the renewable obligations scheme produce the best results under optimal control

Complex fluid network optimization and control integrative design based on nonlinear dynamic model

International Nuclear Information System (INIS)

Sui, Jinxue; Yang, Li; Hu, Yunan

2016-01-01

In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

Application of optimization techniques on lumped HVAC models for energy conservation

Energy Technology Data Exchange (ETDEWEB)

Wemhoff, A.P. [Department of Mechanical Engineering, Villanova University, Villanova, PA 19085 (United States)

2010-12-15

Heating, ventilating, and air conditioning (HVAC) systems comprise nearly one third of annual household energy consumption in the United States. HVAC energy use can be reduced by applying controls. This study applies a novel control method on a system with arbitrary steady-state and transient load distributions. The new method uses multi-dimensional interpolation between optimized control configurations for various steady-state load distributions. Demonstration of the new method on a two-room HVAC system predicts power savings for an arbitrary steady load that is nearly equivalent to that using a Variable-Air-Volume (VAV) with chiller modulation. However, the new method provides better energy savings for arbitrary transient loads: 19% energy savings over an uncontrolled system compared to energy savings of 6% for a VAV with chiller modulation. The average transient temperature deviation from setpoint using the new method is slightly better than that using VAV with chiller modulation. (author)

Energy control in industry ''case of SAP Olympic''. ''Pre- energy diagnosis of SAP Olympic: optimization of consumption of electricity and compressed air''

International Nuclear Information System (INIS)

Zemba, Ouamsibiri Ernest

2007-01-01

This document is a report of a training course to graduate university degree in electronic engineering. It tackles the important question of the competitiveness of Burkina Faso societies in the UEMOA zone. The cost of energy is very high for these societies. This situation affects the distribution of their products. In this case the societies have to optimize their energy consumption. A company as SAP Olympic is supplied energy by a primary tension of 15 KV and a contractual demand of 750 kWh. This society works on 24 hours a day, from Monday to Saturday. Its energy consumption raised and was accentuated by the lack of measuring devices, controls, adjustments and monitoring. That is also caused the one's age of the equipment and installations: all that involves over consumptions and thus penalties of going beyond the contractual demand. It would thus be necessary to have an electric diagram, to have numerical analyzers of electricity consumption and to subscribe has a higher power in order to carry out savings of time of maintenance, availability of production, equipment and staff safety and in order to avoid the penalties of going beyond [fr

Luminosity Optimization for a Higher-Energy LHC

CERN Document Server

Dominguez, O

2011-01-01

A Higher-Energy Large Hadron Collider (HE-LHC) is an option to further push the energy frontier of particle physics beyond the present LHC. A beam energy of 16.5 TeV would require 20 T dipole magnets in the existing LHC tunnel, which should be compared with 7 TeV and 8.33 T for the nominal LHC. Since the synchrotron radiation power increases with the fourth power of the energy, radiation damping becomes significant for the HE-LHC. It calls for transverse and longitudinal emittance control vis-a-vis beam-beam interaction and Landau damping. The heat load from synchrotron radiation, gas scattering, and electron cloud also increases with respect to the LHC. In this paper we discuss the proposed HE-LHC beam parameters; the time evolution of luminosity, beam-beam tune shifts, and emittances during an HE-LHC store; the expected heat load; and luminosity optimization schemes for both round and flat beams.

Optimizing energy management of fuel cell-direct storage-hybrid systems; Optimierendes Energiemanagement von Brennstoffzelle-Direktspeicher-Hybridsystemen

Energy Technology Data Exchange (ETDEWEB)

Bocklisch, Thilo

2010-03-29

The dissertation presents a new optimizing energy management concept for fuel cell-direct storage-hybrid systems. Initially, the characteristics of specific energy time series are investigated on the basis of real measurement data. A new concept for the multi-scale analysis, modelling and prediction of fluctuating photovoltaic supply and electric load demand profiles is developed. The second part of the dissertation starts with a discussion of the benefits of and the basic coupling and control principles for fuel cell-direct storage-hybrid systems. The typical characteristics of a PEM-fuel cell, a metal hydride hydrogen storage, a lithium-ion battery and a supercap unit are presented. A new modular DC/DC-converter is described. Results from experimental and theoretical investigations of the individual components and the overall hybrid system are discussed. New practicable models for the voltage-current-curve, the state of charge behaviour and the conversion losses are presented. The third part of the dissertation explains the new energy management concept. The optimization of power flows is achieved by a control-oriented approach, employing a) the primary control of bus voltage and fuel cell current, b) the secondary control to limit fuel cell current gradient and operating range and to perform direct storage charge control, and c) the system control to optimally adjust secondary control parameters aiming for a reduction of dynamic fuel cell stress and hydrogen consumption. Results from simulations and experimental investigations demonstrate the benefits and high capabilities of the new optimizing energy management concept. Examples of stationary and portable applications conclude the dissertation. (orig.)

An optimal renewable energy mix for Indonesia

Science.gov (United States)

Leduc, Sylvain; Patrizio, Piera; Yowargana, Ping; Kraxner, Florian

2016-04-01

Indonesia has experienced a constant increase of the use of petroleum and coal in the power sector, while the share of renewable sources has remained stable at 6% of the total energy production during the last decade. As its domestic energy demand undeniably continues to grow, Indonesia is committed to increase the production of renewable energy. Mainly to decrease its dependency on fossil fuel-based resources, and to decrease the anthropogenic emissions, the government of Indonesia has established a 23 percent target for renewable energy by 2025, along with a 100 percent electrification target by 2020 (the current rate is 80.4 percent). In that respect, Indonesia has abundant resources to meet these targets, but there is - inter alia - a lack of proper integrated planning, regulatory support, investment, distribution in remote areas of the Archipelago, and missing data to back the planning. To support the government of Indonesia in its sustainable energy system planning, a geographic explicit energy modeling approach is applied. This approach is based on the energy systems optimization model BeWhere, which identifies the optimal location of energy conversion sites based on the minimization of the costs of the supply chain. The model will incorporate the existing fossil fuel-based infrastructures, and evaluate the optimal costs, potentials and locations for the development of renewable energy technologies (i.e., wind, solar, hydro, biomass and geothermal based technologies), as well as the development of biomass co-firing in existing coal plants. With the help of the model, an optimally adapted renewable energy mix - vis-à-vis the competing fossil fuel based resources and applicable policies in order to promote the development of those renewable energy technologies - will be identified. The development of the optimal renewable energy technologies is carried out with special focus on nature protection and cultural heritage areas, where feedstock (e.g., biomass

Developing traction control strategy for a plug-in hybrid electric vehicle using innovative optimization based approaches

Energy Technology Data Exchange (ETDEWEB)

Zhou, L.; Gu, J.; Dong, Z. [Victoria Univ., BC (Canada). Dept. of Mechanical Engineering

2010-07-01

This paper described a traction control system designed for hybrid vehicles with multiple power plants and drive axles. Model-based design tools were used to develop the traction control system and plug-in hybrid vehicle models. Optimization studies were conducted in a finite number of operating states in order to maximize the electrical and mechanical energy conversion efficiency of an extended range electric vehicle. Four global optimization algorithms were then evaluated in relation to their CPU times. The studied algorithms included a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, a hybrid adaptive metamodel optimization (HAM) and space elimination and unimodal region reduction (SEUMRE) algorithm. A comparative evaluation of the algorithms demonstrated that the PSO algorithm obtained optimal results, while the HAM algorithm used significantly less computational time. Results of the optimization studies were then implemented in a controller model. Results of the study showed that the energy efficiency of the vehicle improved using the developed controller model. 4 refs., 2 tabs., 8 figs.

Tackling optimization challenges in industrial load control and full-duplex radios

Science.gov (United States)

Gholian, Armen

In price-based demand response programs in smart grid, utilities set the price in accordance with the grid operating conditions and consumers respond to price signals by conducting optimal load control to minimize their energy expenditure while satisfying their energy needs. Industrial sector consumes a large portion of world electricity and addressing optimal load control of energy-intensive industrial complexes, such as steel industry and oil-refinery, is of practical importance. Formulating a general industrial complex and addressing issues in optimal industrial load control in smart grid is the focus of the second part of this dissertation. Several industrial load details are considered in the proposed formulation, including those that do not appear in residential or commercial load control problems. Operation under different smart pricing scenarios, namely, day-ahead pricing, time-of-use pricing, peak pricing, inclining block rates, and critical peak pricing are considered. The use of behind-the-meter renewable generation and energy storage is also considered. The formulated optimization problem is originally nonlinear and nonconvex and thus hard to solve. However, it is then reformulated into a tractable linear mixed-integer program. The performance of the design is assessed through various simulations for an oil refinery and a steel mini-mill. In the third part of this dissertation, a novel all-analog RF interference canceler is proposed. Radio self-interference cancellation (SIC) is the fundamental enabler for full-duplex radios. While SIC methods based on baseband digital signal processing and/or beamforming are inadequate, an all-analog method is useful to drastically reduce the self-interference as the first stage of SIC. It is shown that a uniform architecture with uniformly distributed RF attenuators has a performance highly dependent on the carrier frequency. It is also shown that a new architecture with the attenuators distributed in a clustered

Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

OpenAIRE

Beinarts, I; Ļevčenkovs, A; Kuņicina, N

2007-01-01

In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

Multi-objective optimization of the control strategy of electric vehicle electro-hydraulic composite braking system with genetic algorithm

Directory of Open Access Journals (Sweden)

Zhang Fengjiao

2015-03-01

Full Text Available Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a multi-objective genetic algorithm is applied to optimize the key parameters in the control strategy of electric vehicle electro-hydraulic composite braking system. Various limitations are considered in the optimization process, and the optimization results are verified by a software simulation platform of electric vehicle regenerative braking system in typical brake conditions. The results show that optimization objectives achieved a good astringency, and the optimized control strategy can increase the brake energy recovery effectively under the condition of ensuring the braking stability.

Energy based optimization of viscous–friction dampers on cables

International Nuclear Information System (INIS)

Weber, F; Boston, C

2010-01-01

This investigation optimizes numerically a viscous–friction damper connected to a cable close to one cable anchor for fastest reduction of the total mechanical cable energy during a free vibration decay test. The optimization parameters are the viscous coefficient of the viscous part and the ratio between the friction force and displacement amplitude of the friction part of the transverse damper. Results demonstrate that an almost pure friction damper with negligibly small viscous damping generates fastest cable energy reduction over the entire decay. The ratio between the friction force and displacement amplitude of the optimal friction damper differs from that derived from the energy equivalent optimal viscous damper. The reason for this is that the nonlinearity of the friction damper causes energy spillover from the excited to higher modes of the order of 10%, i.e. cables with attached friction dampers vibrate at several frequencies. This explains why the energy equivalent approach does not yield the optimal friction damper. Analysis of the simulation data demonstrates that the optimally tuned friction damper dissipates the same energy per cycle as if each modal component of the cable were damped by its corresponding optimal linear viscous damper

Coordinated Optimal Operation Method of the Regional Energy Internet

Directory of Open Access Journals (Sweden)

Rishang Long

2017-05-01

Full Text Available The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized.

Optimal planning of integrated multi-energy systems

DEFF Research Database (Denmark)

van Beuzekom, I.; Gibescu, M.; Pinson, Pierre

2017-01-01

In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration...... and sustainability goals for 2030 and 2045. Optimal green- and brownfield designs for a district's future integrated energy system are compared using a one-step, as well as a two-step planning approach. As expected, the greenfield designs are more cost efficient, as their results are not constrained by the existing...

Optimal centralized and decentralized velocity feedback control on a beam

International Nuclear Information System (INIS)

Engels, W P; Elliott, S J

2008-01-01

This paper considers the optimization of a velocity feedback controller with a collocated force actuator, to minimize the kinetic energy of a simply supported beam. If the beam is excited at a single location, the optimum feedback gain varies with the position of the control system. It is shown that this variation depends partly on the location of the control force relative to the exciting force. If a distributed excitation is assumed, that is random in both time and space, a unique optimum value of the feedback gain can be found for a given control location. The effect of the control location on performance and the optimal feedback gain can then be examined and is found to be limited provided the control locations are not close to the ends of the beam. The optimization can also be performed for a multichannel velocity feedback system. Both a centralized and a decentralized controller are considered. It is shown that the difference in performance between a centralized and a decentralized controller is small, unless the control locations are closely spaced. In this case the centralized controller effectively feeds back a moment proportional to angular velocity as well as a force proportional to a velocity. It is also shown that the optimal feedback gain can be approximated on the basis of a limited model and that similar results can be achieved

Research on Optimized Torque-Distribution Control Method for Front/Rear Axle Electric Wheel Loader

Directory of Open Access Journals (Sweden)

Zhiyu Yang

2017-01-01

Full Text Available Optimized torque-distribution control method (OTCM is a critical technology for front/rear axle electric wheel loader (FREWL to improve the operation performance and energy efficiency. In the paper, a longitudinal dynamics model of FREWL is created. Based on the model, the objective functions are that the weighted sum of variance and mean of tire workload is minimal and the total motor efficiency is maximal. Four nonlinear constraint optimization algorithms, quasi-newton Lagrangian multiplier method, sequential quadratic programming, adaptive genetic algorithms, and particle swarm optimization with random weighting and natural selection, which have fast convergent rate and quick calculating speed, are used as solving solutions for objective function. The simulation results show that compared to no-control FREWL, controlled FREWL utilizes the adhesion ability better and slips less. It is obvious that controlled FREWL gains better operation performance and higher energy efficiency. The energy efficiency of FREWL in equipment transferring condition is increased by 13–29%. In addition, this paper discussed the applicability of OTCM and analyzed the reason for different simulation results of four algorithms.

FPA Tuned Fuzzy Logic Controlled Synchronous Buck Converter for a Wave/SC Energy System

Directory of Open Access Journals (Sweden)

SAHIN, E.

2017-02-01

Full Text Available This paper presents a flower pollination algorithm (FPA tuned fuzzy logic controlled (FLC synchronous buck converter (SBC for an integrated wave/ supercapacitor (SC hybrid energy system. In order to compensate the irregular wave effects on electrical side of the wave energy converter (WEC, a SC unit charged by solar panels is connected in parallel to the WEC system and a SBC is controlled to provide more reliable and stable voltage to the DC load. In order to test the performance of the designed FLC, a classical proportional-integral-derivative (PID controller is also employed. Both of the controllers are optimized by FPA which is a pretty new optimization algorithm and a well-known optimization algorithm of which particle swarm optimization (PSO to minimize the integral of time weighted absolute error (ITAE performance index. Also, the other error-based objective functions are considered. The entire energy system and controllers are developed in Matlab/Simulink and realized experimentally. Real time applications are done through DS1104 Controller Board. The simulation and experimental results show that FPA tuned fuzzy logic controller provides lower value performance indices than conventional PID controller by reducing output voltage sags and swells of the wave/SC energy system.

Stochastic Control of Energy Efficient Buildings: A Semidefinite Programming Approach

Energy Technology Data Exchange (ETDEWEB)

Ma, Xiao [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M [ORNL; Nutaro, James J [ORNL; Kuruganti, Teja [ORNL

2015-01-01

The key goal in energy efficient buildings is to reduce energy consumption of Heating, Ventilation, and Air- Conditioning (HVAC) systems while maintaining a comfortable temperature and humidity in the building. This paper proposes a novel stochastic control approach for achieving joint performance and power control of HVAC. We employ a constrained Stochastic Linear Quadratic Control (cSLQC) by minimizing a quadratic cost function with a disturbance assumed to be Gaussian. The problem is formulated to minimize the expected cost subject to a linear constraint and a probabilistic constraint. By using cSLQC, the problem is reduced to a semidefinite optimization problem, where the optimal control can be computed efficiently by Semidefinite programming (SDP). Simulation results are provided to demonstrate the effectiveness and power efficiency by utilizing the proposed control approach.

Multidimensional optimal droop control for wind resources in DC microgrids

Science.gov (United States)

Bunker, Kaitlyn J.

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Chaoying Xia

2017-07-01

Full Text Available This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs. The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA. The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.

Near optimal decentralized H_inf control

DEFF Research Database (Denmark)

Stoustrup, J.; Niemann, Hans Henrik

It is shown that foir a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinity dimentional optimal controller. Using the insight of the line of proof of these results, a heuri......It is shown that foir a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinity dimentional optimal controller. Using the insight of the line of proof of these results...

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

Energy Technology Data Exchange (ETDEWEB)

Gregor P. Henze; Moncef Krarti

2005-09-30

Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very

Power, control and optimization

CERN Document Server

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...

A Method for Determining Optimal Residential Energy Efficiency Packages

Energy Technology Data Exchange (ETDEWEB)

Polly, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gestwick, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bianchi, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Horowitz, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Christensen, C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Judkoff, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2011-04-01

This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location.

Aerostructural optimization of a morphing wing for airborne wind energy applications

Science.gov (United States)

Fasel, U.; Keidel, D.; Molinari, G.; Ermanni, P.

2017-09-01

Airborne wind energy (AWE) vehicles maximize energy production by constantly operating at extreme wing loading, permitted by high flight speeds. Additionally, the wide range of wind speeds and the presence of flow inhomogeneities and gusts create a complex and demanding flight environment for AWE systems. Adaptation to different flow conditions is normally achieved by conventional wing control surfaces and, in case of ground generator-based systems, by varying the reel-out speed. These control degrees of freedom enable to remain within the operational envelope, but cause significant penalties in terms of energy output. A significantly greater adaptability is offered by shape-morphing wings, which have the potential to achieve optimal performance at different flight conditions by tailoring their airfoil shape and lift distribution at different levels along the wingspan. Hence, the application of compliant structures for AWE wings is very promising. Furthermore, active gust load alleviation can be achieved through morphing, which leads to a lower weight and an expanded flight envelope, thus increasing the power production of the AWE system. This work presents a procedure to concurrently optimize the aerodynamic shape, compliant structure, and composite layup of a morphing wing for AWE applications. The morphing concept is based on distributed compliance ribs, actuated by electromechanical linear actuators, guiding the deformation of the flexible—yet load-carrying—composite skin. The goal of the aerostructural optimization is formulated as a high-level requirement, namely to maximize the average annual power production per wing area of an AWE system by tailoring the shape of the wing, and to extend the flight envelope of the wing by actively alleviating gust loads. The results of the concurrent multidisciplinary optimization show a 50.7% increase of extracted power with respect to a sequentially optimized design, highlighting the benefits of morphing and the

A Galerkin-Parameterization Method for the Optimal Control of Smart Microbeams

Directory of Open Access Journals (Sweden)

Marwan Abukhaled

2009-01-01

Full Text Available A proposed computational method is applied to damp out the excess vibrations in smart microbeams, where the control action is implemented using piezoceramic actuators. From a mathematical point of view, we wish to determine the optimal boundary actuators that minimize a given energy-based performance measure. The minimization of the performance measure over the actuators is subjected to the full motion of the structural vibrations of the micro-beams. A direct state-control parametrization approach is proposed where the shifted Legendre polynomials are employed to solve the optimization problem. Legendre operational matrix and the properties of Kronecker product are utilized to find the approximated optimal trajectory and optimal control law of the lumped parameter systems with respect to the quadratic cost function by solving linear algebraic equations. Numerical examples are provided to demonstrate the applicability and efficiency of the proposed approach.

A multidimensional pseudospectral method for optimal control of quantum ensembles

International Nuclear Information System (INIS)

Ruths, Justin; Li, Jr-Shin

2011-01-01

In our previous work, we have shown that the pseudospectral method is an effective and flexible computation scheme for deriving pulses for optimal control of quantum systems. In practice, however, quantum systems often exhibit variation in the parameters that characterize the system dynamics. This leads us to consider the control of an ensemble (or continuum) of quantum systems indexed by the system parameters that show variation. We cast the design of pulses as an optimal ensemble control problem and demonstrate a multidimensional pseudospectral method with several challenging examples of both closed and open quantum systems from nuclear magnetic resonance spectroscopy in liquid. We give particular attention to the ability to derive experimentally viable pulses of minimum energy or duration.

Real Time Energy Management Control Strategies for Hybrid Powertrains

Science.gov (United States)

Zaher, Mohamed Hegazi Mohamed

In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

Control of Vibratory Energy Harvesters in the Presence of Nonlinearities and Power-Flow Constraints

Science.gov (United States)

Cassidy, Ian L.

Over the past decade, a significant amount of research activity has been devoted to developing electromechanical systems that can convert ambient mechanical vibrations into usable electric power. Such systems, referred to as vibratory energy harvesters, have a number of useful of applications, ranging in scale from self-powered wireless sensors for structural health monitoring in bridges and buildings to energy harvesting from ocean waves. One of the most challenging aspects of this technology concerns the efficient extraction and transmission of power from transducer to storage. Maximizing the rate of power extraction from vibratory energy harvesters is further complicated by the stochastic nature of the disturbance. The primary purpose of this dissertation is to develop feedback control algorithms which optimize the average power generated from stochastically-excited vibratory energy harvesters. This dissertation will illustrate the performance of various controllers using two vibratory energy harvesting systems: an electromagnetic transducer embedded within a flexible structure, and a piezoelectric bimorph cantilever beam. Compared with piezoelectric systems, large-scale electromagnetic systems have received much less attention in the literature despite their ability to generate power at the watt--kilowatt scale. Motivated by this observation, the first part of this dissertation focuses on developing an experimentally validated predictive model of an actively controlled electromagnetic transducer. Following this experimental analysis, linear-quadratic-Gaussian control theory is used to compute unconstrained state feedback controllers for two ideal vibratory energy harvesting systems. This theory is then augmented to account for competing objectives, nonlinearities in the harvester dynamics, and non-quadratic transmission loss models in the electronics. In many vibratory energy harvesting applications, employing a bi-directional power electronic drive to actively

Systems and methods for energy cost optimization in a building system

Energy Technology Data Exchange (ETDEWEB)

Turney, Robert D.; Wenzel, Michael J.

2016-09-06

Methods and systems to minimize energy cost in response to time-varying energy prices are presented for a variety of different pricing scenarios. A cascaded model predictive control system is disclosed comprising an inner controller and an outer controller. The inner controller controls power use using a derivative of a temperature setpoint and the outer controller controls temperature via a power setpoint or power deferral. An optimization procedure is used to minimize a cost function within a time horizon subject to temperature constraints, equality constraints, and demand charge constraints. Equality constraints are formulated using system model information and system state information whereas demand charge constraints are formulated using system state information and pricing information. A masking procedure is used to invalidate demand charge constraints for inactive pricing periods including peak, partial-peak, off-peak, critical-peak, and real-time.

Method for Determining Optimal Residential Energy Efficiency Retrofit Packages

Energy Technology Data Exchange (ETDEWEB)

Polly, B.; Gestwick, M.; Bianchi, M.; Anderson, R.; Horowitz, S.; Christensen, C.; Judkoff, R.

2011-04-01

Businesses, government agencies, consumers, policy makers, and utilities currently have limited access to occupant-, building-, and location-specific recommendations for optimal energy retrofit packages, as defined by estimated costs and energy savings. This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location. Energy savings and incremental costs are calculated relative to a minimum upgrade reference scenario, which accounts for efficiency upgrades that would occur in the absence of a retrofit because of equipment wear-out and replacement with current minimum standards.

Intelligent energy management of optimally located renewable energy systems incorporating PHEV

International Nuclear Information System (INIS)

El-Zonkoly, Amany

2014-01-01

Highlights: • The algorithm optimally selects the number, locations and sizes of DGs. • Wind units, PV units, diesel units and PHEV parking lots are considered as DGs. • The algorithm determines the corresponding energy scheduling of resources. • The problem is formulated as an optimization problem solved using ABC. • The objective is to minimize the overall energy cost of the system. - Abstract: The recent interest in plug-in-hybrid electric vehicles (PHEV) results in the increase in the utilization of vehicles batteries for grid support. In addition, the integration of renewable energy systems (RES) into electricity grid is a promising technique for addressing the environmental concerns. This paper presents a multi-objective algorithm to optimally allocate a number of renewable energy systems including parking lots for PHEV in a distribution system. The proposed algorithm determines the number, locations and sizes of the RES and parking lots. In addition, a rule based expert system is used to find the corresponding energy scheduling of the system resources. The objective of the proposed algorithm is to minimize the overall energy cost of the system. The problem is formulated as an optimization problem which is solved using artificial bee colony (ABC) algorithm taking into consideration the power system and PHEV operational constraints. The proposed algorithm is applied to a 45-bus distribution network of Alexandria, Egypt. The test results indicate an improvement in the operational conditions of the system

Rovibrational controlled-NOT gates using optimized stimulated Raman adiabatic passage techniques and optimal control theory

International Nuclear Information System (INIS)

Sugny, D.; Bomble, L.; Ribeyre, T.; Dulieu, O.; Desouter-Lecomte, M.

2009-01-01

Implementation of quantum controlled-NOT (CNOT) gates in realistic molecular systems is studied using stimulated Raman adiabatic passage (STIRAP) techniques optimized in the time domain by genetic algorithms or coupled with optimal control theory. In the first case, with an adiabatic solution (a series of STIRAP processes) as starting point, we optimize in the time domain different parameters of the pulses to obtain a high fidelity in two realistic cases under consideration. A two-qubit CNOT gate constructed from different assignments in rovibrational states is considered in diatomic (NaCs) or polyatomic (SCCl 2 ) molecules. The difficulty of encoding logical states in pure rotational states with STIRAP processes is illustrated. In such circumstances, the gate can be implemented by optimal control theory and the STIRAP sequence can then be used as an interesting trial field. We discuss the relative merits of the two methods for rovibrational computing (structure of the control field, duration of the control, and efficiency of the optimization).

Optimization of sources for focusing wave energy in targeted formations

International Nuclear Information System (INIS)

Jeong, C; Kallivokas, L F; Huh, C; Lake, L W

2010-01-01

We discuss a numerical approach for identifying the surface excitation that is necessary to maximize the response of a targeted subsurface formation. The motivation stems from observations in the aftermath of earthquakes, and from limited field experiments, whereby increased oil production rates were recorded and were solely attributable to the induced reservoir shaking. The observations suggest that focusing wave energy to the reservoir could serve as an effective low-cost enhanced oil recovery method. In this paper, we report on a general method that allows the determination of the source excitation, when provided with a desired maximization outcome at the targeted formation. We discuss, for example, how to construct the excitation that will maximize the kinetic energy in the target zone, while keeping silent the neighbouring zones. To this end, we cast the problem as an inverse-source problem, and use a partial-differential-equation-constrained optimization approach to arrive at an optimized source signal. We seek to satisfy stationarity of an augmented functional, which formally leads to a triplet of state, adjoint and control problems. We use finite elements to resolve the state and adjoint problems, and an iterative scheme to satisfy the control problem to converge to the sought source signal. We report on one-dimensional numerical experiments in the time domain involving a layered medium of semi-infinite extent. The numerical results show that the targeted formation's kinetic energy resulting from an optimized wave source could be several times greater than the one resulting from a blind source choice, and could overcome the mobility threshold of entrapped reservoir oil

The Application of Euler-Lagrange Method of Optimization for Electromechanical Motion Control

Directory of Open Access Journals (Sweden)

Cristian VASILACHE

2000-12-01

Full Text Available Industrial and non-industrial processes such as production plans, robots, pumps, compressors, home applications, transportation of people and goods etc., require some kinds of motion control. The main functions of electromechanical drives are to adjust these processes by controlling the torque, speed or position. The objective of this paper is to perform the control of motion while minimizing power losses, that is ∫Ri2dt, in process conversion of electrical energy to mechanical energy. The optimal control laws for our problem is find using the Euler - Lagrange principle. We consider three types of controlled drives: torque, speed and position. Each of them has different control laws. By implementation of these controls with Borland C++ and Matlab environment, substantial energy savings are obtained.

Assessment of grid-friendly collective optimization framework for distributed energy resources

Energy Technology Data Exchange (ETDEWEB)

Pensini, Alessandro; Robinson, Matthew; Heine, Nicholas; Stadler, Michael; Mammoli, Andrea

2015-11-04

Distributed energy resources have the potential to provide services to facilities and buildings at lower cost and environmental impact in comparison to traditional electric-gridonly services. The reduced cost could result from a combination of higher system efficiency and exploitation of electricity tariff structures. Traditionally, electricity tariffs are designed to encourage the use of ‘off peak’ power and discourage the use of ‘onpeak’ power, although recent developments in renewable energy resources and distributed generation systems (such as their increasing levels of penetration and their increased controllability) are resulting in pressures to adopt tariffs of increasing complexity. Independently of the tariff structure, more or less sophisticated methods exist that allow distributed energy resources to take advantage of such tariffs, ranging from simple pre-planned schedules to Software-as-a-Service schedule optimization tools. However, as the penetration of distributed energy resources increases, there is an increasing chance of a ‘tragedy of the commons’ mechanism taking place, where taking advantage of tariffs for local benefit can ultimately result in degradation of service and higher energy costs for all. In this work, we use a scheduling optimization tool, in combination with a power distribution system simulator, to investigate techniques that could mitigate the deleterious effect of ‘selfish’ optimization, so that the high-penetration use of distributed energy resources to reduce operating costs remains advantageous while the quality of service and overall energy cost to the community is not affected.

Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center

International Nuclear Information System (INIS)

Cho, Jinkyun; Kim, Yundeok

2016-01-01

Highlights: • Energy-optimized data center’s cooling solutions were derived for four different climate zones. • We studied practical technologies of green data center that greatly improved energy efficiency. • We identified the relationship between mutually dependent factors in datacenter cooling systems. • We evaluated the effect of the dedicated cooling system applications. • Power Usage Effectiveness (PUE) was computed with energy simulation for data centers. - Abstract: Data centers are approximately 50 times more energy-intensive than general buildings. The rapidly increasing energy demand for data center operation has motivated efforts to better understand data center electricity use and to identify strategies that reduce the environmental impact. This research is presented analytical approach to the energy efficiency optimization of high density data center, in a synergy with relevant performance analysis of corresponding case study. This paper builds on data center energy modeling efforts by characterizing climate and cooling system differences among data centers and then evaluating their consequences for building energy use. Representative climate conditions for four regions are applied to data center energy models for several different prototypical cooling types. This includes cooling system, supplemental cooling solutions, design conditions and controlling the environment of ICT equipment were generally used for each climate zone, how these affect energy efficiency, and how the prioritization of system selection is derived. Based on the climate classification and the required operating environmental conditions for data centers suggested by the ASHRAE TC 9.9, a dedicated data center energy evaluation tool was taken to examine the potential energy savings of the cooling technology. Incorporating economizer use into the cooling systems would increase the variation in energy efficiency among geographic regions, indicating that as data centers

Model predictive control-based efficient energy recovery control strategy for regenerative braking system of hybrid electric bus

International Nuclear Information System (INIS)

Li, Liang; Zhang, Yuanbo; Yang, Chao; Yan, Bingjie; Marina Martinez, C.

2016-01-01

Highlights: • A 7-degree-of-freedom model of hybrid electric vehicle with regenerative braking system is built. • A modified nonlinear model predictive control strategy is developed. • The particle swarm optimization algorithm is employed to solve the optimization problem. • The proposed control strategy is verified by simulation and hardware-in-loop tests. • Test results verify the effectiveness of the proposed control strategy. - Abstract: As one of the main working modes, the energy recovered with regenerative braking system provides an effective approach so as to greatly improve fuel economy of hybrid electric bus. However, it is still a challenging issue to ensure braking stability while maximizing braking energy recovery. To solve this problem, an efficient energy recovery control strategy is proposed based on the modified nonlinear model predictive control method. Firstly, combined with the characteristics of the compound braking process of single-shaft parallel hybrid electric bus, a 7 degrees of freedom model of the vehicle longitudinal dynamics is built. Secondly, considering nonlinear characteristic of the vehicle model and the efficiency of regenerative braking system, the particle swarm optimization algorithm within the modified nonlinear model predictive control is adopted to optimize the torque distribution between regenerative braking system and pneumatic braking system at the wheels. So as to reduce the computational time of modified nonlinear model predictive control, a nearest point method is employed during the braking process. Finally, the simulation and hardware-in-loop test are carried out on road conditions with different tire–road adhesion coefficients, and the proposed control strategy is verified by comparing it with the conventional control method employed in the baseline vehicle controller. The simulation and hardware-in-loop test results show that the proposed strategy can ensure vehicle safety during emergency braking

Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control

DEFF Research Database (Denmark)

Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller

2017-01-01

For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated...... and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm....

Engineering to Control Noise, Loading, and Optimal Operating Points

International Nuclear Information System (INIS)

Mitchell R. Swartz

2000-01-01

Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems

An optimal open/closed-loop control method with application to a pre-stressed thin duralumin plate

Science.gov (United States)

Nadimpalli, Sruthi Raju

The excessive vibrations of a pre-stressed duralumin plate, suppressed by a combination of open-loop and closed-loop controls, also known as open/closed-loop control, is studied in this thesis. The two primary steps involved in this process are: Step (I) with an assumption that the closed-loop control law is proportional, obtain the optimal open-loop control by direct minimization of the performance measure consisting of energy at terminal time and a penalty on open-loop control force via calculus of variations. If the performance measure also involves a penalty on closed-loop control effort then a Fourier based method is utilized. Step (II) the energy at terminal time is minimized numerically to obtain optimal values of feedback gains. The optimal closed-loop control gains obtained are used to describe the displacement and the velocity of open-loop, closed-loop and open/closed-loop controlled duralumin plate.

Energy optimization methodology of multi-chiller plant in commercial buildings

International Nuclear Information System (INIS)

Thangavelu, Sundar Raj; Myat, Aung; Khambadkone, Ashwin

2017-01-01

This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions. - Highlights: • Energy optimization methodology improves the performance of multi-chiller plant. • Overall energy model of chiller plant accounts all equipment and the interactions. • Operation decisions are derived at regular interval based on time-varying factors. • Three case studies confirmed 20 to 40% of energy savings than conventional method.

Constrained Optimization and Optimal Control for Partial Differential Equations

CERN Document Server

Leugering, Günter; Griewank, Andreas

2012-01-01

This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont

Long-term optimal energy mix planning towards high energy security and low GHG emission

International Nuclear Information System (INIS)

Thangavelu, Sundar Raj; Khambadkone, Ashwin M.; Karimi, Iftekhar A.

2015-01-01

Highlights: • We develop long-term energy planning considering the future uncertain inputs. • We analyze the effect of uncertain inputs on the energy cost and energy security. • Conventional energy mix prone to cause high energy cost and energy security issues. • Stochastic and optimal energy mix show benefits over conventional energy planning. • Nuclear option consideration reduces the energy cost and carbon emissions. - Abstract: Conventional energy planning focused on energy cost, GHG emission and renewable contribution based on future energy demand, fuel price, etc. Uncertainty in the projected variables such as energy demand, volatile fuel price and evolution of renewable technologies will influence the cost of energy when projected over a period of 15–30 years. Inaccurate projected variables could affect energy security and lead to the risk of high energy cost, high emission and low energy security. The energy security is an ability of generation capacity to meet the future energy demand. In order to minimize the risks, a generic methodology is presented to determine an optimal energy mix for a period of around 15 years. The proposed optimal energy mix is a right combination of energy sources that minimize the risk caused due to future uncertainties related to the energy sources. The proposed methodology uses stochastic optimization to address future uncertainties over a planning horizon and minimize the variations in the desired performance criteria such as energy security and costs. The developed methodology is validated using a case study for a South East Asian region with diverse fuel sources consists of wind, solar, geothermal, coal, biomass and natural gas, etc. The derived optimal energy mix decision outperformed the conventional energy planning by remaining stable and feasible against 79% of future energy demand scenarios at the expense of 0–10% increase in the energy cost. Including the nuclear option in the energy mix resulted 26

Optimising Reactive Control in non-ideal Efficiency Wave Energy Converters

DEFF Research Database (Denmark)

Strager, Thomas; Lopez, Pablo Fernandez; Giorgio, Giuseppe

2014-01-01

When analytically optimising the control strategy in wave energy converters which use a point absorber, the efficiency aspect is generally neglected. The results presented in this paper provide an analytical expression for the mean harvested electrical power in non-ideal efficiency situations....... These have been derived under the assumptions of monochromatic incoming waves and linear system behaviour. This allows to establish the power factor of a system with non-ideal efficiency. The locus of the optimal reactive control parameters is then studied and an alternative method of representation...... is developed to model the optimal control parameters. Ultimately we present a simple method of choosing optimal control parameters for any combination of efficiency and wave frequency....

Management of solar energy in microgrids using IoT-based dependable control

OpenAIRE

Phung, Manh Duong; De La Villefromoy, Michel; Ha, Quang

2017-01-01

Solar energy generation requires efficient monitoring and management in moving towards technologies for net-zero energy buildings. This paper presents a dependable control system based on the Internet of Things (IoT) to control and manage the energy flow of renewable energy collected by solar panels within a microgrid. Data for optimal control include not only measurements from local sensors but also meteorological information retrieved in real-time from online sources. For system fault toler...

FUZZY-LOGIC-BASED CONTROLLERS FOR EFFICIENCY OPTIMIZATION OF INVERTER-FED INDUCTION MOTOR DRIVES

Science.gov (United States)

This paper describes a fuzzy-logic-based energy optimizing controller to improve the efficiency of induction motor/drives operating at various load (torque) and speed conditions. Improvement of induction motor efficiency is important not only from the considerations of energy sav...

Optimal Energy Management of Multi-Microgrids with Sequentially Coordinated Operations

Directory of Open Access Journals (Sweden)

Nah-Oak Song

2015-08-01

Full Text Available We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically modeled to find the optimal operation conditions and illustrated with physical interpretation of how to achieve optimal energy management in the cooperative multi-microgrid community. This global electric energy optimization of the cooperative community is realized by the ancillary internal trading between the microgrids in the cooperative community which reduces the extra cost from unnecessary external trading by adjusting the electric energy production amounts of combined heat and power (CHP generators and amounts of both internal and external electric energy trading of the cooperative community. A simulation study is also conducted to validate the proposed mathematical energy management models.

A reduced energy supply strategy in active vibration control

Science.gov (United States)

Ichchou, M. N.; Loukil, T.; Bareille, O.; Chamberland, G.; Qiu, J.

2011-12-01

In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings.

A reduced energy supply strategy in active vibration control

International Nuclear Information System (INIS)

Ichchou, M N; Loukil, T; Bareille, O; Chamberland, G; Qiu, J

2011-01-01

In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings

Nonlinear Burn Control and Operating Point Optimization in ITER

Science.gov (United States)

Boyer, Mark; Schuster, Eugenio

2013-10-01

Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).

A Wind Farm Controller for Load and Power Optimization in a Farm

DEFF Research Database (Denmark)

Soleimanzadeh, Maryam; Brand, Arno; Wisniewski, Rafal

2011-01-01

This paper describes the design procedure of an optimal wind farm controller. The controller optimizes the structural load and power production simultaneously, on the basis of an analytical wind farm model. The farm model delivers maps of wind, loads and energy in the wind farm. Moreover, the model...... computes the wind speed at the turbines, turbine bending moments and aerodynamic power and torque. The optimal control problem is formulated based on the model for two different wind directions. The controller determines the reference signals for each individual wind turbine controller in two scenarios...... based on low and high wind speed. In low wind speed, the reference signals for rotor speed are adjusted, taking the trade-off between power maximization and load minimization into account. In high wind speed, the power and pitch angle reference signals are determined while structural loads are minimized....

Optimal Velocity Control for a Battery Electric Vehicle Driven by Permanent Magnet Synchronous Motors

Directory of Open Access Journals (Sweden)

Dongbin Lu

2014-01-01

Full Text Available The permanent magnet synchronous motor (PMSM has high efficiency and high torque density. Field oriented control (FOC is usually used in the motor to achieve maximum efficiency control. In the electric vehicle (EV application, the PMSM efficiency model, combined with the EV and road load system model, is used to study the optimal energy-saving control strategy, which is significant for the economic operation of EVs. With the help of GPS, IMU, and other information technologies, the road conditions can be measured in advance. Based on this information, the optimal velocity of the EV driven by PMSM can be obtained through the analytical algorithm according to the efficiency model of PMSM and the vehicle dynamic model in simple road conditions. In complex road conditions, considering the dynamic characteristics, the economic operating velocity trajectory of the EV can be obtained through the dynamic programming (DP algorithm. Simulation and experimental results show that the minimum energy consumption and global energy optimization can be achieved when the EV operates in the economic operation area.

Fuzzy logic control and optimization system

Science.gov (United States)

Lou, Xinsheng [West Hartford, CT

2012-04-17

A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Super-capacitors fuel-cell hybrid electric vehicle optimization and control strategy development

International Nuclear Information System (INIS)

Paladini, Vanessa; Donateo, Teresa; De Risi, Arturo; Laforgia, Domenico

2007-01-01

In the last decades, due to emissions reduction policies, research focused on alternative powertrains among which hybrid electric vehicles (HEVs) powered by fuel cells are becoming an attractive solution. One of the main issues of these vehicles is the energy management in order to improve the overall fuel economy. The present investigation aims at identifying the best hybrid vehicle configuration and control strategy to reduce fuel consumption. The study focuses on a car powered by a fuel cell and equipped with two secondary energy storage devices: batteries and super-capacitors. To model the powertrain behavior an on purpose simulation program called ECoS has been developed in Matlab/Simulink environment. The fuel cell model is based on the Amphlett theory. The battery and the super-capacitor models account for charge/discharge efficiency. The analyzed powertrain is also equipped with an energy regeneration system to recover braking energy. The numerical optimization of vehicle configuration and control strategy of the hybrid electric vehicle has been carried out with a multi objective genetic algorithm. The goal of the optimization is the reduction of hydrogen consumption while sustaining the battery state of charge. By applying the algorithm to different driving cycles, several optimized configurations have been identified and discussed

REopt: A Platform for Energy System Integration and Optimization: Preprint

Energy Technology Data Exchange (ETDEWEB)

Simpkins, T.; Cutler, D.; Anderson, K.; Olis, D.; Elgqvist, E.; Callahan, M.; Walker, A.

2014-08-01

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

Science.gov (United States)

Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T

2018-04-03

While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.

Modeling of optimal energy flows for systems with close integration of sea water desalination and renewable energy sources: Case study for Jordan

International Nuclear Information System (INIS)

Perković, Luka; Novosel, Tomislav; Pukšec, Tomislav; Ćosić, Boris; Mustafa, Manal; Krajačić, Goran; Duić, Neven

2016-01-01

Highlights: • A new methodology for optimal management of energy systems is proposed. • Critical excess of electricity production is reduced by optimizing the energy flows. • At the same time, the curtailment from the RES can be decreased. - Abstract: This paper presents a new approach for modeling energy flows in complex energy systems with parallel supply of fresh water and electricity. Such systems consist of renewable energy sources (RES), desalination plant, conventional power plants and the residual brine storage which is used as energy storage. The presented method is treating energy vectors in the system as control variables to provide the optimal solution in terms of the lowest critical excess of electricity production (CEEP) and highest possible share of RES in the supply mix. The optimal solution for supplying the demands for fresh water and electricity is always found within the framework of model constraints which are derived from the physical limitations of the system. The presented method enables the optimization of energy flows for a larger period of time. This increases the role of energy storage when higher integration of RES in the supply mix. The method is tested on a hypothetical case of Jordan for different levels of installed wind and PV capacities, as well as different sizes of the brine storage. Results show that increasing the optimization horizon from one hour to 24 h can reduce the CEEP by 80% and allow the increase of RES in the supply mix by more than 5% without violating the CEEP threshold limit of 5%. The activity of the energy (brine) storage is crucial for achieving this goal.

Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review

Directory of Open Access Journals (Sweden)

Maria Ferrara

2018-06-01

Full Text Available Since the introduction of the recast of the EPBD European Directive 2010/31/EU, many studies on the cost-effective feasibility of nearly zero-energy buildings (NZEBs were carried out either by academic research bodies and by national bodies. In particular, the introduction of the cost-optimal methodology has given a strong impulse to research in this field. This paper presents a comprehensive and significant review on scientific works based on the application of cost-optimal analysis applications in Europe since the EPBD recast entered into force, pointing out the differences in the analyzed studies and comparing their outcomes before the new recast of EPBD enters into force in 2018. The analysis is conducted with special regard to the methods used for the energy performance assessment, the global cost calculation, and for the selection of the energy efficiency measures leading to design optimization. A critical discussion about the assumptions on which the studies are based and the resulting gaps between the resulting cost-optimal performance and the zero energy target is provided together with a summary of the resulting cost-optimal set of technologies to be used for cost-optimal NZEB design in different contexts. It is shown that the cost-optimal approach results as an effective method for delineating the future of NZEB design throughout Europe while emerging criticalities and open research issues are presented.

Multi-objective optimal dispatch of distributed energy resources

Science.gov (United States)

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.

Control strategy optimization of HVAC plants

Energy Technology Data Exchange (ETDEWEB)

Facci, Andrea Luigi; Zanfardino, Antonella [Department of Engineering, University of Napoli “Parthenope” (Italy); Martini, Fabrizio [Green Energy Plus srl (Italy); Pirozzi, Salvatore [SIAT Installazioni spa (Italy); Ubertini, Stefano [School of Engineering (DEIM) University of Tuscia (Italy)

2015-03-10

In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.

Control strategy optimization of HVAC plants

International Nuclear Information System (INIS)

Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano

2015-01-01

In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting

An energy systems engineering approach to the optimal design of energy systems in commercial buildings

Energy Technology Data Exchange (ETDEWEB)

Liu, Pei; Pistikopoulos, Efstratios N. [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Li, Zheng [Department of Thermal Engineering, Tsinghua University, Beijing 100084 (China)

2010-08-15

Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach. (author)

An energy systems engineering approach to the optimal design of energy systems in commercial buildings

International Nuclear Information System (INIS)

Liu Pei; Pistikopoulos, Efstratios N.; Li Zheng

2010-01-01

Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach.

An energy systems engineering approach to the optimal design of energy systems in commercial buildings

Energy Technology Data Exchange (ETDEWEB)

Liu Pei [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Pistikopoulos, Efstratios N., E-mail: e.pistikopoulos@imperial.ac.u [Centre for Process Systems Engineering (CPSE), Department of Chemical Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Li Zheng [Department of Thermal Engineering, Tsinghua University, Beijing 100084 (China)

2010-08-15

Energy consumption in commercial buildings accounts for a significant proportion of worldwide energy consumption. Any increase in the energy efficiency of the energy systems for commercial buildings would lead to significant energy savings and emissions reductions. In this work, we introduce an energy systems engineering framework towards the optimal design of such energy systems with improved energy efficiency and environmental performance. The framework features a superstructure representation of the various energy technology alternatives, a mixed-integer optimization formulation of the energy systems design problem, and a multi-objective design optimization solution strategy, where economic and environmental criteria are simultaneously considered and properly traded off. A case study of a supermarket energy systems design is presented to illustrate the key steps and potential of the proposed energy systems engineering approach.

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems: Preprint

Energy Technology Data Exchange (ETDEWEB)

Yang, Rui; Zhang, Yingchen

2016-08-01

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder and results illustrate the superior control performance of the proposed approach.

Scheduling home-appliances to optimize energy consumption

DEFF Research Database (Denmark)

Rossello Busquet, Ana

In order to optimize the energy consumption, energy demand peaks should be avoided, and energy consumption should be smoothly distributed over time. This can be achieved by setting a maximum energy consumption per user’s household. In other words, the overall consumption of the user’s appliances...

Optimal Control of Diesel Engines with Waste Heat Recovery System

NARCIS (Netherlands)

Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.

2014-01-01

This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO2-NOx trade-off by minimizing the operational costs associated with fuel and AdBlue

Optimal control of diesel engines with waste heat recovery systems

NARCIS (Netherlands)

Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.; Waschl, H.; Kolmanovsky, I.; Steinbuch, M.; Del Re, L.

2014-01-01

This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO 2 - NO x trade-off by minimizing the operational costs associated with fuel and AdBlue

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.

Control of Refrigeration Systems for Trade-off between Energy Consumption and Food Quality Loss

DEFF Research Database (Denmark)

Cai, Junping

In supermarkets, control strategies determine both the energy consumption of refrigeration systems and the quality loss of refrigerated foodstuffs. The question is, what can be done to optimize the balance between quality loss and energy consumption? This thesis tries to answer this question...... by applying two main optimization strategies to traditional refrigeration systems. The first strategy is a new defrost-on-demand scheme, which based on an objective function between quality loss and energy consumption, continuously seeks an optimal time interval for defrosting in dynamic situation. The second...... strategy is through utilization of the thermal mass of the refrigerated foodstuffs, the day-night temperature variation and the capacity control of the compressor, to realize a trade-off between system energy consumption and food quality loss....

Optimizing Storage and Renewable Energy Systems with REopt

Energy Technology Data Exchange (ETDEWEB)

Elgqvist, Emma M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, Katherine H. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Cutler, Dylan S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); DiOrio, Nicholas A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Laws, Nicholas D. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olis, Daniel R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Walker, H. A. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2017-12-27

Under the right conditions, behind the meter (BTM) storage combined with renewable energy (RE) technologies can provide both cost savings and resiliency. Storage economics depend not only on technology costs and avoided utility rates, but also on how the technology is operated. REopt, a model developed at NREL, can be used to determine the optimal size and dispatch strategy for BTM or off-grid applications. This poster gives an overview of three applications of REopt: Optimizing BTM Storage and RE to Extend Probability of Surviving Outage, Optimizing Off-Grid Energy System Operation, and Optimizing Residential BTM Solar 'Plus'.

Optimization of HTS superconducting magnetic energy storage magnet volume

Science.gov (United States)

Korpela, Aki; Lehtonen, Jorma; Mikkonen, Risto

2003-08-01

Nonlinear optimization problems in the field of electromagnetics have been successfully solved by means of sequential quadratic programming (SQP) and the finite element method (FEM). For example, the combination of SQP and FEM has been proven to be an efficient tool in the optimization of low temperature superconductors (LTS) superconducting magnetic energy storage (SMES) magnets. The procedure can also be applied for the optimization of HTS magnets. However, due to a strongly anisotropic material and a slanted electric field, current density characteristic high temperature superconductors HTS optimization is quite different from that of the LTS. In this paper the volumes of solenoidal conduction-cooled Bi-2223/Ag SMES magnets have been optimized at the operation temperature of 20 K. In addition to the electromagnetic constraints the stress caused by the tape bending has also been taken into account. Several optimization runs with different initial geometries were performed in order to find the best possible solution for a certain energy requirement. The optimization constraints describe the steady-state operation, thus the presented coil geometries are designed for slow ramping rates. Different energy requirements were investigated in order to find the energy dependence of the design parameters of optimized solenoidal HTS coils. According to the results, these dependences can be described with polynomial expressions.