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Sample records for based day-ahead self-scheduling

  1. Hybrid Particle Swarm Optimization based Day-Ahead Self-Scheduling for Thermal Generator in Competitive Electricity Market

    DEFF Research Database (Denmark)

    Pindoriya, Naran M.; Singh, S.N.; Østergaard, Jacob

    2009-01-01

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting bi-objective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead self-scheduling for thermal power producer in competitive electricity market. The objective functions considered to model the self-scheduling problem are 1) to maximize the profit from selling energy...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a day-ahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the day...

  2. Day-Ahead Self-Scheduling of Thermal Generator in Competitive Electricity Market Using Hybrid PSO

    DEFF Research Database (Denmark)

    Pindoriya, N.M.; Singh, Sri Niwas; Østergaard, Jacob

    2009-01-01

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting biobjective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead selfscheduling for thermal power producer in competitive electricity market. The objective functions considered to model the selfscheduling problem are: 1) to maximize the profit from selling energy...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a dayahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the dayahead...

  3. Hydrothermal self-scheduling problem in a day-ahead electricity market

    International Nuclear Information System (INIS)

    Bisanovic, Smajo; Dlakic, Muris; Hajro, Mensur

    2008-01-01

    This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis. (author)

  4. Security-constrained self-scheduling of generation companies in day-ahead electricity markets considering financial risk

    International Nuclear Information System (INIS)

    Amjady, Nima; Vahidinasab, Vahid

    2013-01-01

    Highlights: ► A security-constrained self-scheduling is presented. ► The proposed framework takes into account the uncertainty of the predicted market prices. ► We model the risk and profit tradeoff of a GENCO based on an efficient multi-objective model. ► Unit commitment and inter-temporal constraints of generators are considered in an MIP model. ► Simulation results are presented on the IEEE 30-bus and IEEE 118-bus test systems. - Abstract: In this paper, a new security-constrained self-scheduling framework incorporating the transmission flow limits in both steady state conditions and post-contingent states is presented to produce efficient bidding strategy for generation companies (GENCOs) in day-ahead electricity markets. Moreover, the proposed framework takes into account the uncertainty of the predicted market prices and models the risk and profit tradeoff of a GENCO based on an efficient multi-objective model. Furthermore, unit commitment and inter-temporal constraints of generators are considered in the suggested model converting it to a mixed-integer programming (MIP) optimization problem. Sensitivity of the proposed framework with respect to both the level of the market prices and adopted risk level is also evaluated in the paper. Simulation results are presented on the IEEE 30-bus and IEEE 118-bus test systems illustrating the performance of the proposed self-scheduling model.

  5. Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate

    International Nuclear Information System (INIS)

    Esmaeily, Ali; Ahmadi, Abdollah; Raeisi, Fatima; Ahmadi, Mohammad Reza; Esmaeel Nezhad, Ali; Janghorbani, Mohammadreza

    2017-01-01

    A new optimization framework based on MILP model is introduced in the paper for the problem of stochastic self-scheduling of hydrothermal units known as HTSS Problem implemented in a joint energy and reserve electricity market with day-ahead mechanism. The proposed MILP framework includes some practical constraints such as the cost due to valve-loading effect, the limit due to DRR and also multi-POZs, which have been less investigated in electricity market models. For the sake of more accuracy, for hydro generating units’ model, multi performance curves are also used. The problem proposed in this paper is formulated using a model on the basis of a stochastic optimization technique while the objective function is maximizing the expected profit utilizing MILP technique. The suggested stochastic self-scheduling model employs the price forecast error in order to take into account the uncertainty due to price. Besides, LMCS is combined with roulette wheel mechanism so that the scenarios corresponding to the non-spinning reserve price and spinning reserve price as well as the energy price at each hour of the scheduling are generated. Finally, the IEEE 118-bus power system is used to indicate the performance and the efficiency of the suggested technique. - Highlights: • Characterizing the uncertainties of price and FOR of units. • Replacing the fixed ramping rate constraints with the dynamic ones. • Proposing linearized model for the valve-point effects of thermal units. • Taking into consideration the multi-POZs relating to the thermal units. • Taking into consideration the multi-performance curves of hydroelectric units.

  6. Real-time versus day-ahead market power in a hydro-based electricity market

    OpenAIRE

    Tangerås, Thomas P.; Mauritzen, Johannes

    2014-01-01

    We analyse in a theoretical framework the link between real-time and day-ahead market performance in a hydro-based and imperfectly competitive wholesale electricity market. Theoretical predictions of the model are tested on data from the Nordic power exchange, Nord Pool Spot (NPS).We reject the hypothesis that prices at NPS were at their competitive levels throughout the period under examination. The empirical approach uses equilibrium prices and quantities and does not rely on bid data nor o...

  7. Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market

    Directory of Open Access Journals (Sweden)

    Sh. Yousefi

    2011-09-01

    Full Text Available In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer’s effective demand according to the prices. Here, Q-learning (QL approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

  8. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    DEFF Research Database (Denmark)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

    2015-01-01

    how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how...... to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also...... taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand....

  9. New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming

    International Nuclear Information System (INIS)

    Attaviriyanupap, Pathom; Kita, Hiroyuki; Tanaka, Eiichi; Hasegawa, Jun

    2005-01-01

    In this paper, a new bidding strategy for a day-ahead market is formulated. The proposed algorithm is developed from the viewpoint of a generation company wishing to maximize a profit as a participant in the deregulated power and reserve markets. Separate power and reserve markets are considered, both are operated by clearing price auction system. The optimal bidding parameters for both markets are determined by solving an optimization problem that takes unit commitment constraints such as generating limits and unit minimum up/down time constraints into account. This is a non-convex and non-differentiable which is difficult to solve by traditional optimization techniques. In this paper, evolutionary programming is used to solve the problem. The algorithm is applied to both single-sided and double-sided auctions, numerical simulations are carried out to demonstrate the performance of the proposed scheme compared with those obtained from a sequential quadratic programming. (author)

  10. Day-ahead resource scheduling of a renewable energy based virtual power plant

    International Nuclear Information System (INIS)

    Zamani, Ali Ghahgharaee; Zakariazadeh, Alireza; Jadid, Shahram

    2016-01-01

    Highlights: • Simultaneous energy and reserve scheduling of a VPP. • Aggregate uncertainties of electricity prices, renewable generation and load demand. • Develop a stochastic scheduling model using the point estimate method. - Abstract: The evolution of energy markets is accelerating in the direction of a greater reliance upon distributed energy resources (DERs). To manage this increasing two-way complexity, virtual power plants (VPPs) are being deployed today all over the world. In this paper, a probabilistic model for optimal day ahead scheduling of electrical and thermal energy resources in a VPP is proposed where participation of energy storage systems and demand response programs (DRPs) are also taken into account. In the proposed model, energy and reserve is simultaneously scheduled considering the uncertainties of market prices, electrical demand and intermittent renewable power generation. The Point Estimate Method (PEM) is applied in order to model the uncertainties of VPP’s scheduling problem. Moreover, the optimal reserve scheduling of VPP is presented which efficiently decreases VPP’s risk facing the unexpected fluctuations of uncertain parameters at the power delivery time. The results demonstrated that implementation of demand response programs (DRPs) would decrease total operation costs of VPP as well as its dependency on the upstream network.

  11. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    International Nuclear Information System (INIS)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita

    2015-01-01

    Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks

  12. Day-ahead electricity prices forecasting by a modified CGSA technique and hybrid WT in LSSVM based scheme

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.

    2013-01-01

    Highlights: • Presenting a hybrid CGSA-LSSVM scheme for price forecasting. • Considering uncertainties for filtering in input data and feature selection to improve efficiency. • Using DWT input featured LSSVM approach to classify next-week prices. • Used three real markets to illustrate performance of the proposed price forecasting model. - Abstract: At the present time, day-ahead electricity market is closely associated with other commodity markets such as fuel market and emission market. Under such an environment, day-ahead electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new combination of a Feature Selection (FS) technique based mutual information (MI) technique and Wavelet Transform (WT) in this study. Moreover, in this paper a new modified version of Gravitational Search Algorithm (GSA) optimization based chaos theory, namely Chaotic Gravitational Search Algorithm (CGSA) is developed to find the optimal parameters of Least Square Support Vector Machine (LSSVM) to predict electricity prices. The performance and price forecast accuracy of the proposed technique is assessed by means of real data from Iran’s, Ontario’s and Spain’s price markets. The simulation results from numerical tables and figures in different cases show that the proposed technique increases electricity price market forecasting accuracy than the other classical and heretical methods in the scientific researches

  13. A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

    DEFF Research Database (Denmark)

    Jiang, Yuewen; Chen, Meisen; You, Shi

    2017-01-01

    In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase...... in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view...... of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle...

  14. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2014-01-01

    Full Text Available As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

  15. Optimal Resources Planning of Residential Complex Energy System in a Day-ahead Market Based on Invasive Weed Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    P. Αhmadi

    2017-10-01

    Full Text Available This paper deals with optimal resources planning in a residential complex energy system, including FC (fuel cell, PV (Photovoltaic panels and the battery. A day-ahead energy management system (EMS based on invasive weed optimization (IWO algorithm is defined for managing different resources to determine an optimal operation schedule for the energy resources at each time interval to minimize the operation cost of a smart residential complex energy system. Moreover, in this paper the impacts of the sell to grid and purchase from grid are also considered. All practical constraints of the each energy resources and utility policies are taken into account. Moreover, sensitivity analysis are conducted on electricity prices and sell to grid factor (SGF, in order to improve understanding the impact of key parameters on residential CHP systems economy. It is shown that proposed system can meet all electrical and thermal demands with economic point of view. Also enhancement of electricity price leads to substantial growth in utilization of proposed CHP system.

  16. Day Ahead Real Time Pricing and Critical Peak Pricing Based Power Scheduling for Smart Homes with Different Duty Cycles

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2018-06-01

    Full Text Available In this paper, we propose a demand side management (DSM scheme in the residential area for electricity cost and peak to average ratio (PAR alleviation with maximum users’ satisfaction. For this purpose, we implement state-of-the-art algorithms: enhanced differential evolution (EDE and teacher learning-based optimization (TLBO. Furthermore, we propose a hybrid technique (HT having the best features of both aforementioned algorithms. We consider a system model for single smart home as well as for a community (multiple homes and each home consists of multiple appliances with different priorities. The priority is assigned (to each appliance by electricity consumers and then the proposed scheme finds an optimal solution according to the assigned priorities. Day-ahead real time pricing (DA-RTP and critical peak pricing (CPP are used for electricity cost calculation. To validate our proposed scheme, simulations are carried out and results show that our proposed scheme efficiently achieves the aforementioned objectives. However, when we perform a comparison with existing schemes, HT outperforms other state-of-the-art schemes (TLBO and EDE in terms of electricity cost and PAR reduction while minimizing the average waiting time.

  17. Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2017-12-01

    Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

  18. A Modified Feature Selection and Artificial Neural Network-Based Day-Ahead Load Forecasting Model for a Smart Grid

    Directory of Open Access Journals (Sweden)

    Ashfaq Ahmad

    2015-12-01

    Full Text Available In the operation of a smart grid (SG, day-ahead load forecasting (DLF is an important task. The SG can enhance the management of its conventional and renewable resources with a more accurate DLF model. However, DLF model development is highly challenging due to the non-linear characteristics of load time series in SGs. In the literature, DLF models do exist; however, these models trade off between execution time and forecast accuracy. The newly-proposed DLF model will be able to accurately predict the load of the next day with a fair enough execution time. Our proposed model consists of three modules; the data preparation module, feature selection and the forecast module. The first module makes the historical load curve compatible with the feature selection module. The second module removes redundant and irrelevant features from the input data. The third module, which consists of an artificial neural network (ANN, predicts future load on the basis of selected features. Moreover, the forecast module uses a sigmoid function for activation and a multi-variate auto-regressive model for weight updating during the training process. Simulations are conducted in MATLAB to validate the performance of our newly-proposed DLF model in terms of accuracy and execution time. Results show that our proposed modified feature selection and modified ANN (m(FS + ANN-based model for SGs is able to capture the non-linearity(ies in the history load curve with 97 . 11 % accuracy. Moreover, this accuracy is achieved at the cost of a fair enough execution time, i.e., we have decreased the average execution time of the existing FS + ANN-based model by 38 . 50 % .

  19. A Modified Feature Selection and Artificial Neural Network-Based Day-Ahead Load Forecasting Model for a Smart Grid

    OpenAIRE

    Ahmad, Ashfaq; Javaid, Nadeem; Alrajeh, Nabil; Khan, Zahoor; Qasim, Umar; Khan, Abid

    2015-01-01

    In the operation of a smart grid (SG), day-ahead load forecasting (DLF) is an important task. The SG can enhance the management of its conventional and renewable resources with a more accurate DLF model. However, DLF model development is highly challenging due to the non-linear characteristics of load time series in SGs. In the literature, DLF models do exist; however, these models trade off between execution time and forecast accuracy. The newly-proposed DLF model will be able to accurately ...

  20. A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

    Directory of Open Access Journals (Sweden)

    Yuewen Jiang

    2017-04-01

    Full Text Available In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO. Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.

  1. Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey

    Directory of Open Access Journals (Sweden)

    Mustafa Akpinar

    2017-06-01

    Full Text Available The increase of energy consumption in the world is reflected in the consumption of natural gas. However, this increment requires additional investment. This effect leads imbalances in terms of demand forecasting, such as applying penalties in the case of error rates occurring beyond the acceptable limits. As the forecasting errors increase, penalties increase exponentially. Therefore, the optimal use of natural gas as a scarce resource is important. There are various demand forecast ranges for natural gas and the most difficult range among these demands is the day-ahead forecasting, since it is hard to implement and makes predictions with low error rates. The objective of this study is stabilizing gas tractions on day-ahead demand forecasting using low-consuming subscriber data for minimizing error using univariate artificial bee colony-based artificial neural networks (ANN-ABC. For this purpose, households and low-consuming commercial users’ four-year consumption data between the years of 2011–2014 are gathered in daily periods. Previous consumption values are used to forecast day-ahead consumption values with sliding window technique and other independent variables are not taken into account. Dataset is divided into two parts. First, three-year daily consumption values are used with a seven day window for training the networks, while the last year is used for the day-ahead demand forecasting. Results show that ANN-ABC is a strong, stable, and effective method with a low error rate of 14.9 mean absolute percentage error (MAPE for training utilizing MAPE with a univariate sliding window technique.

  2. A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

    Science.gov (United States)

    Zack, J. W.

    2015-12-01

    Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

  3. Finding diversity for building one-day ahead Hydrological Ensemble Prediction System based on artificial neural network stacks

    Science.gov (United States)

    Brochero, Darwin; Anctil, Francois; Gagné, Christian; López, Karol

    2013-04-01

    In this study, we addressed the application of Artificial Neural Networks (ANN) in the context of Hydrological Ensemble Prediction Systems (HEPS). Such systems have become popular in the past years as a tool to include the forecast uncertainty in the decision making process. HEPS considers fundamentally the uncertainty cascade model [4] for uncertainty representation. Analogously, the machine learning community has proposed models of multiple classifier systems that take into account the variability in datasets, input space, model structures, and parametric configuration [3]. This approach is based primarily on the well-known "no free lunch theorem" [1]. Consequently, we propose a framework based on two separate but complementary topics: data stratification and input variable selection (IVS). Thus, we promote an ANN prediction stack in which each predictor is trained based on input spaces defined by the IVS application on different stratified sub-samples. All this, added to the inherent variability of classical ANN optimization, leads us to our ultimate goal: diversity in the prediction, defined as the complementarity of the individual predictors. The stratification application on the 12 basins used in this study, which originate from the second and third workshop of the MOPEX project [2], shows that the informativeness of the data is far more important than the quantity used for ANN training. Additionally, the input space variability leads to ANN stacks that outperform an ANN stack model trained with 100% of the available information but with a random selection of dataset used in the early stopping method (scenario R100P). The results show that from a deterministic view, the main advantage focuses on the efficient selection of the training information, which is an equally important concept for the calibration of conceptual hydrological models. On the other hand, the diversity achieved is reflected in a substantial improvement in the scores that define the

  4. A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

    International Nuclear Information System (INIS)

    Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

    2015-01-01

    Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

  5. Powernext Day-AheadTM statistics - June 30, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the June 30, 2006 update of Powernext Day-Ahead TM statistics: daily traded volumes and base-load prices from November 2001 to June 2006, monthly overview from June 2005 to June 2006 (volumes and prices), weekly overview from March to June 2006 (volumes and prices), daily and hourly overview and market resilience for June 2006, power consumption in May and June 2006 (average consumption, average forecasted consumption and average price on Powernext Day-Ahead TM ), power consumption on the French hub from July 2005 to May 2006 and Powernext Day-Ahead TM prices, transfer capacities in June 2006 (auction results for France-Germany, France-Belgium, France-UK, France-Spain and France-Italy, and daily capacity allocation for France-Switzerland), temperature variations in France from January 2005 to June 2006 and base-load Powernext Day-Ahead TM prices, and balancing mechanism for April, May and June 2006 (half-hourly imbalance settlement prices). (J.S.)

  6. A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price

    Directory of Open Access Journals (Sweden)

    Zhilong Wang

    2014-01-01

    Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.

  7. Robust Optimization-Based Generation Self-Scheduling under Uncertain Price

    Directory of Open Access Journals (Sweden)

    Xiao Luo

    2011-01-01

    Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.

  8. One-day-ahead streamflow forecasting via super-ensembles of several neural network architectures based on the Multi-Level Diversity Model

    Science.gov (United States)

    Brochero, Darwin; Hajji, Islem; Pina, Jasson; Plana, Queralt; Sylvain, Jean-Daniel; Vergeynst, Jenna; Anctil, Francois

    2015-04-01

    Theories about generalization error with ensembles are mainly based on the diversity concept, which promotes resorting to many members of different properties to support mutually agreeable decisions. Kuncheva (2004) proposed the Multi Level Diversity Model (MLDM) to promote diversity in model ensembles, combining different data subsets, input subsets, models, parameters, and including a combiner level in order to optimize the final ensemble. This work tests the hypothesis about the minimisation of the generalization error with ensembles of Neural Network (NN) structures. We used the MLDM to evaluate two different scenarios: (i) ensembles from a same NN architecture, and (ii) a super-ensemble built by a combination of sub-ensembles of many NN architectures. The time series used correspond to the 12 basins of the MOdel Parameter Estimation eXperiment (MOPEX) project that were used by Duan et al. (2006) and Vos (2013) as benchmark. Six architectures are evaluated: FeedForward NN (FFNN) trained with the Levenberg Marquardt algorithm (Hagan et al., 1996), FFNN trained with SCE (Duan et al., 1993), Recurrent NN trained with a complex method (Weins et al., 2008), Dynamic NARX NN (Leontaritis and Billings, 1985), Echo State Network (ESN), and leak integrator neuron (L-ESN) (Lukosevicius and Jaeger, 2009). Each architecture performs separately an Input Variable Selection (IVS) according to a forward stepwise selection (Anctil et al., 2009) using mean square error as objective function. Post-processing by Predictor Stepwise Selection (PSS) of the super-ensemble has been done following the method proposed by Brochero et al. (2011). IVS results showed that the lagged stream flow, lagged precipitation, and Standardized Precipitation Index (SPI) (McKee et al., 1993) were the most relevant variables. They were respectively selected as one of the firsts three selected variables in 66, 45, and 28 of the 72 scenarios. A relationship between aridity index (Arora, 2002) and NN

  9. Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

    Directory of Open Access Journals (Sweden)

    Dehua Zheng

    2017-12-01

    Full Text Available The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs and distribution system operators (DSOs in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs and DSOs in enhancing the control and management of the power network. In this paper, a novel two-stage hybrid approach based on the combination of the Hilbert-Huang transform (HHT, genetic algorithm (GA and artificial neural network (ANN is proposed for day-ahead wind power forecasting. The approach is composed of two stages. The first stage utilizes numerical weather prediction (NWP meteorological information to predict wind speed at the exact site of the wind farm. The second stage maps actual wind speed vs. power characteristics recorded by SCADA. Then, the wind speed forecast in the first stage for the future day is fed to the second stage to predict the future day’s wind power. Comparative selection of input-data parameter sets for the forecasting model and impact analysis of input-data dependency on forecasting accuracy have also been studied. The proposed approach achieves significant forecasting accuracy improvement compared with three other artificial intelligence-based forecasting approaches and a benchmark model using the smart persistence method.

  10. Hourly Electricity Prices in Day-Ahead Markets

    NARCIS (Netherlands)

    R. Huisman (Ronald); C. Huurman; R.J. Mahieu (Ronald)

    2007-01-01

    textabstractThis paper focuses on the characteristics of hourly electricity prices in day-ahead markets. In these markets, quotes for day-ahead delivery of electricity are submitted simultaneously for all hours in the next day. The same information set is used for quoting all hours of the day. The

  11. Optimal day-ahead operational planning of microgrids

    International Nuclear Information System (INIS)

    Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad; Siano, Pierluigi

    2016-01-01

    Highlights: • A new multi-objective model for optimal day-ahead operational planning of microgrids is proposed. • A new concept called seamlessness is introduced to control the sustainability of microgrid. • A new method is developed to manage the load and renewable energy resources estimation errors. • A new solution based on a combination of numerical and evolutionary approaches is proposed. - Abstract: Providing a cost-efficient, eco-friendly and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of microgrid technology have provided huge potentials while distributing electricity more effectively, economically and securely. Accordingly, this paper presents a new multi-objective generation management model for optimal day-ahead operational planning of medium voltage microgrids. The proposed model optimizes both pollutant emission and operating cost of a microgrid by using multi-objective optimization. Besides, a seamlessness-selective algorithm is integrated into the model, which can be adopted to achieve the desired self-sufficiency level for microgrids along a specified planning horizon. Furthermore, the model is characterized by a reserve-assessment strategy developed to handle the load and renewable energy resources estimation errors. The introduced model is solved using a combination of numerical and evolutionary methods of species-based quantum particle swarm optimization to find the optimal scheduling scheme and minos-based optimal power flow to optimize the operating cost and emission. In addition, the suggested solution approach also incorporates an efficient mechanism for considering energy storage systems and coding the candidate solutions in the evolutionary algorithm. The proposed model is implemented on a test microgrid and is investigated through simulations to study the different aspects of the problem. The results show significant improvements and benefits which are obtained by

  12. What day-ahead reserves are needed in electric grids with high levels of wind power?

    International Nuclear Information System (INIS)

    Mauch, Brandon; Apt, Jay; Jaramillo, Paulina; Carvalho, Pedro M S

    2013-01-01

    Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity. (letter)

  13. Day-Ahead Anticipation of Complex Network Vulnerability

    Science.gov (United States)

    Stefanov, S. Z.; Wang, Paul P.

    2017-11-01

    In this paper, a day-ahead anticipation of complex network vulnerability for an intentional threat of an attack or a shock is carried out. An ecological observer is introduced for that reason, which is a watch in the intentional multiverse, tiled by cells; dynamics of the intentional threat for a day-ahead is characterized by a space-time cell; spreading of the intentional threat is derived from its energy; duration of the intentional threat is found by the self-assembling of a space-time cell; the lower bound of probability is assessed to anticipate for a day-ahead the intentional threat; it is indicated that this vulnerability anticipation for a day-ahead is right when the intentional threat leads to dimension doubling of the complex network.

  14. Powernext Day-AheadTM products and market organization

    International Nuclear Information System (INIS)

    2004-06-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents the principle of the trading of hourly contracts on Powernext Day-Ahead TM , the accessibility of the market, the SAPRI trading platform operated by Nord Pool, the Scandinavian power exchange, the validation of the auction results, the collaboration with LCH.Clearnet SA to secure and facilitate the transactions, and the delivery guarantee implemented by RTE (the French energy transport network). (J.S.)

  15. Powernext Day-AheadTM statistics April 30, 2005

    International Nuclear Information System (INIS)

    2005-04-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the April 30, 2005 update of Powernext Day-Ahead TM statistics: traded volumes and average prices from November 2001 to April 2005, monthly overview from April 2004 to April 2005 (volumes, prices and price spreads), weekly overview from January to April 2005, daily and hourly overview and market resilience for April 2005, power consumption in March and April 2005 (average consumption, average forecasted consumption and average price on Powernext Day-Ahead TM ), power consumption on the French hub from January to April 2005 and Powernext Day-Ahead TM prices, transfer capacities in April 2005 (daily capacity allocations for France-Germany, France-Switzerland and France-Spain, daily and monthly capacity allocations for France-Belgium, auction on the France-UK Interconnector, daily and yearly capacity allocation for France-Italy), temperature variations in France from November 2004 to April 2005 and average prices on Powernext Day-Ahead TM , and balancing mechanism for March-April 2005 (half-hourly imbalance settlement prices). (J.S.)

  16. Feedback, competition and stochasticity in a day ahead electricity market

    International Nuclear Information System (INIS)

    Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik

    2010-01-01

    Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society.

  17. Feedback, competition and stochasticity in a day ahead electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik [DTU Informatics, Technical University of Denmark, Richard Petersens Plads 305, DK-2800 Kgs. Lyngby (Denmark)

    2010-03-15

    Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society. (author)

  18. Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements

    International Nuclear Information System (INIS)

    Liu, Fan; Bie, Zhaohong; Liu, Shiyu; Ding, Tao

    2017-01-01

    Highlights: • Analyzing zonal reserve requirements for wind integrated power system. • Modeling day-ahead optimal dispatch solved by chance constrained programming theory. • Determining optimal zonal reserve demand with minimum confidence interval. • Analyzing numerical results on test and large-scale real-life power systems. - Abstract: Large-scale integration of renewable power presents a great challenge for day-ahead dispatch to manage renewable resources while provide available reserve for system security. Considering zonal reserve is an effective way to ensure reserve deliverability when network congested, a random day-ahead dispatch optimization of wind integrated power system for a least operational cost is modeled including zonal reserve requirements and N − 1 security constraints. The random model is transformed into a deterministic one based on the theory of chance constrained programming and a determination method of optimal zonal reserve demand is proposed using the minimum confidence interval. After solving the deterministic model, the stochastic simulation is conducted to verify the validity of solution. Numerical tests and results on the IEEE 39 bus system and a large-scale real-life power system demonstrate the optimal day-ahead dispatch scheme is available and the proposed method is effective for improving reserve deliverability and reducing load shedding after large-capacity power outage.

  19. MASCEM: EPEX SPOT Day-Ahead market integration and simulation

    DEFF Research Database (Denmark)

    Santos, Gabriel; Fernandes, Ricardo; Pinto, Tiago

    2015-01-01

    . It is crucial to MASCEM to have the ability to simulate as many market models and player types as possible, thus enhancing the ability to recreate the electricity markets reality in its maximum possible extent. This paper presents the EPEX Spot Day-Ahead market integration in MASCEM. EPEX Spot SE's mission...

  20. Day-ahead economic optimisation of energy storage

    NARCIS (Netherlands)

    Lampropoulos, I.; Garoufalis, P.; Bosch, van den P.P.J.; Groot, de R.J.W.; Kling, W.L.

    2014-01-01

    This article addresses the day-ahead economic optimisation of energy storage systems within the setting of electricity spot markets. The case study is about a lithium-ion battery system integrated in a low voltage distribution grid with residential customers and photovoltaic generation in the

  1. Can a wind farm with CAES survive in the day-ahead market?

    International Nuclear Information System (INIS)

    Mauch, Brandon; Carvalho, Pedro M.S.; Apt, Jay

    2012-01-01

    We investigate the economic viability of coupling a wind farm with compressed air energy storage (CAES) to participate in the day-ahead electricity market at a time when renewable portfolio standards are not binding and wind competes freely in the marketplace. In our model, the CAES is used to reduce the risk of committing uncertain quantities of wind energy and to shift dispatch of wind generation to high price periods. Other sources of revenue (capacity markets, ancillary services, price arbitrage) are not included in the analysis. We present a model to calculate profit maximizing day-ahead dispatch schedules based on wind forecasts. Annual profits are determined with dispatch schedules and actual wind generation values. We find that annual income for the modeled wind–CAES system would not cover annualized capital costs using market prices from the years 2006 to 2009. We also estimate market prices with a carbon price of $20 and $50 per tonne CO 2 and find that revenue would still not cover the capital costs. The implied cost per tonne of avoided CO 2 to make a wind–CAES profitable from trading on the day-ahead market is roughly $100, with large variability due to electric power prices. - Highlights: ► We modeled a wind farm participating in the day-ahead electricity market. ► We calculated optimal day-ahead market offers based on wind forecasts. ► Revenue is then calculated using measured wind power. ► We find that revenue is insufficient to cover capital costs at current market prices.

  2. How Does Pricing of Day-ahead Electricity Market Affect Put Option Pricing?

    Directory of Open Access Journals (Sweden)

    H. Raouf Sheybani

    2016-09-01

    Full Text Available In this paper, impacts of day-ahead market pricing on behavior of producers and consumers in option and day-ahead markets and on option pricing are studied. To this end, two comprehensive equilibrium models for joint put option and day-ahead markets under pay-as-bid and uniform pricing in day-ahead market are presented, respectively. Interaction between put option and day-ahead markets, uncertainty in fuel price, day-ahead market pricing, and elasticity of consumers to strike price, premium price, and day-ahead price are taken into account in these models. By applying the presented models to a test system impact of day-ahead market pricing on equilibrium of joint put option and day-ahead markets are studied.

  3. Optimal operation and forecasting policy for pump storage plants in day-ahead markets

    International Nuclear Information System (INIS)

    Muche, Thomas

    2014-01-01

    Highlights: • We investigate unit commitment deploying stochastic and deterministic approaches. • We consider day-ahead markets, its forecast and weekly price based unit commitment. • Stochastic and deterministic unit commitment are identical for the first planning day. • Unit commitment and bidding policy can be based on the deterministic approach. • Robust forecasting models should be estimated based on the whole planning horizon. - Abstract: Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation

  4. Comparative analysis of features of Polish and Lithuanian Day-ahead electricity market prices

    International Nuclear Information System (INIS)

    Bobinaite, Viktorija; Juozapaviciene, Aldona; Staniewski, Marcin; Szczepankowski, Piotr

    2013-01-01

    The goal of this article is to better understand the processes of electricity market price formation in Poland and Lithuania through an analysis of the features (volatility and spikes) of Lithuanian and Polish day-ahead electricity market prices and to assess how acquired electricity price features could affect the achievement of the main goals of the national energy policy. The following indicators have been calculated to determine electricity market price volatility: the oscillation coefficient, the coefficient of variation, an adjusted coefficient of variation, the standard deviation indicator, the daily velocity indicator (based on the overall average price) and the daily velocity indicator (based on the daily average price). Critical values for electricity market price have been calculated to evaluate price spikes. This analysis reveals that electricity market-price volatility is moderate in Poland and high in Lithuania. Electricity price spikes have been an observable phenomenon both in Lithuanian and in Polish day-ahead electricity markets, but they are more common in Lithuania, encompassing 3.15% of the time period analysed in Poland and 4.68% of the time period analysed in Lithuania. Volatile, spiking and increasing electricity prices in day-ahead electricity markets in Lithuania and Poland create preconditions and substantiate the relevance of implementation of the national energy policies and measures. - Highlights: • Moderate and seasonal volatility. • spiking market price and. • stable average price

  5. Forecasting Nord Pool day-ahead prices with an autoregressive model

    International Nuclear Information System (INIS)

    Kristiansen, Tarjei

    2012-01-01

    This paper presents a model to forecast Nord Pool hourly day-ahead prices. The model is based on but reduced in terms of estimation parameters (from 24 sets to 1) and modified to include Nordic demand and Danish wind power as exogenous variables. We model prices across all hours in the analysis period rather than across each single hour of 24 hours. By applying three model variants on Nord Pool data, we achieve a weekly mean absolute percentage error (WMAE) of around 6–7% and an hourly mean absolute percentage error (MAPE) ranging from 8% to 11%. Out of sample results yields a WMAE and an hourly MAPE of around 5%. The models enable analysts and traders to forecast hourly day-ahead prices accurately. Moreover, the models are relatively straightforward and user-friendly to implement. They can be set up in any trading organization. - Highlights: ► Forecasting Nord Pool day-ahead prices with an autoregressive model. ► The model is based on but with the set of parameters reduced from 24 to 1. ► The model includes Nordic demand and Danish wind power as exogenous variables. ► Hourly mean absolute percentage error ranges from 8% to 11%. ► Out of sample results yields a WMAE and an hourly MAPE of around 5%.

  6. Value of flexible resources, virtual bidding, and self-scheduling in two-settlement electricity markets with wind generation - Part II: ISO Models and Application

    DEFF Research Database (Denmark)

    Kazempour, Jalal; Hobbs, Benjamin F.

    2017-01-01

    In Part II of this paper, we present formulations for three two-settlement market models: baseline cost-minimization (Stoch-Opt); and two sequential market models in which an independent system operator (ISO) runs real-time (RT) balancing markets after making day-ahead (DA) generating unit...... commitment decisions based upon deterministic wind forecasts, while virtual bidders arbitrage the two markets (Seq and SeqSS). The latter two models differ in terms of whether some slow-start generators can self-schedule in the DA market while anticipating probabilities of RT prices. Models in Seq and Seq......-SS build on components of the two-settlement equilibrium model (Stoch-MP) defined in Part I of this paper [1]. We then provide numerical results for all four models. A simple single-node case illustrates the economic impacts of flexibility, virtual bidding, and self-schedules, and is followed by a larger...

  7. Simulation of regional day-ahead PV power forecast scenarios

    DEFF Research Database (Denmark)

    Nuno, Edgar; Koivisto, Matti Juhani; Cutululis, Nicolaos Antonio

    2017-01-01

    Uncertainty associated with Photovoltaic (PV) generation can have a significant impact on real-time planning and operation of power systems. This obstacle is commonly handled using multiple forecast realizations, obtained using for example forecast ensembles and/or probabilistic forecasts, often...... at the expense of a high computational burden. Alternatively, some power system applications may require realistic forecasts rather than actual estimates; able to capture the uncertainty of weatherdriven generation. To this end, we propose a novel methodology to generate day-ahead forecast scenarios of regional...... PV production matching the spatio-temporal characteristics while preserving the statistical properties of actual records....

  8. Coordination of bidding strategies in day-ahead energy and spinning reserve markets

    International Nuclear Information System (INIS)

    Fushuan Wen; David, A.K.

    2002-01-01

    In this paper, the problem of building optimally coordinated bidding strategies for competitive suppliers in day-ahead energy and spinning reserve markets is addressed. It is assumed that each supplier bids 24 linear energy supply functions and 24 linear spinning reserve supply functions, one for each hour, into the energy and spinning reserve markets, respectively, and each market is cleared separately and simultaneously for all the 24 delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy and spinning reserve supply functions to maximise total benefits, subject to expectations about how rival suppliers will bid in both markets. Two different bidding schemes have been suggested for each hour, and based on them an overall coordinated bidding strategy in the day-ahead energy and spinning reserve market is then developed. Stochastic optimisation models are first developed to describe these two different bidding schemes and a genetic algorithm (GA) is then used to build the optimally coordinated bidding strategies for each scheme and to develop an overall bidding strategy for the day-ahead energy and spinning reserve markets. A numerical example is utilised to illustrate the essential features of the method. (Author)

  9. Risk premiums in the German day-ahead Electricity Market

    International Nuclear Information System (INIS)

    Viehmann, Johannes

    2011-01-01

    This paper conducts an empirical analysis of risk premiums in the German day-ahead Electricity Wholesale Market. We compare hourly price data of the European Energy Exchange (EEX) auction and of the continuous over-the-counter (OTC) market which takes place prior to the EEX auction. Data provided by the Energy Exchange Austria (EXAA) has been used as a snapshot of the OTC market two hours prior to the EEX auction. Ex post analysis found market participants are willing to pay both significant positive and negative premiums for hourly contracts. The largest positive premiums were paid for high demand evening peak hours on weekdays during winter months. By contrast, night hours on weekends featuring lowest demand levels display negative premiums. Additionally, ex ante analysis found a strong positive correlation between the expected tightness of the system and positive premiums. For this purpose, a tightness factor has been introduced that includes expectations of fundamental factors such as power plant availability, wind power production and demand. Hence, findings by can be supported that power traders in liberalised markets behave like risk-averse rational economic agents. - Research highlights: →Analysis of hourly risk premiums in the German day-ahead Electricity Wholesale Market. →Market participants are willing to pay both significant positive and negative premiums for hourly contracts. →A strong correlation exists between the expected tightness of the power system and premiums.

  10. Powernext Day-AheadTM. Powernext futuresTM. Activity report - 2004

    International Nuclear Information System (INIS)

    2004-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document is the 2004 activity report of Powernext SA, it presents the key figures of the power market and of Powernext in 2004: - Increasing volumes: Powernext Day-Ahead TM 's traded volumes increased by 89%, from 7.48 to 14.18 TWh. Powernext Futures TM kicks off to a promising debut with 12.86 TWh traded in less than 7 months. - Less volatile prices: During 2004, the base price averaged 28.13 euro/MWh, and the peak prices averaged 33.71 euro/MWh. Compared to 2003, these prices decreased by an average of 3.7% on base-load and 10.9% on peak-load. In comparison to the two previous years, the daily volatility has noticeably settled down with 27% on base-load and 37% on peak-load. - Increasing liquidity: 10 new members joined Powernext Day-Ahead TM in 2004. The activity level of the members remains very high as 89% of them trade on an actual daily basis during 2004. The market resiliency stays strong. In December, an additional market 50 MW order on each hour resulted in a balance price variation of only 0.16 euro/MWh, or 0.53% of this balance price. For a 100 MW order, the resiliency is 0.32 euro/MWh, or 1.07% of the balance price. Thus, in 2004, Powernext Day-Ahead TM consolidates its role as a short term reference price. Moreover, in 2004, Powernext launched a futures market, Powernext Futures TM . This new market segment proposes contracts tradable up to 2 years ahead of delivery

  11. Stochastic multiobjective self-scheduling of a power producer in joint energy and reserves markets

    International Nuclear Information System (INIS)

    Vahidinasab, V.; Jadid, S.

    2010-01-01

    This paper presents a stochastic multiobjective model for self-scheduling of a power producer which participates in the day-ahead joint energy and reserves markets. The objective of a power producer is to compromise the conflicting objectives of payoff maximization and gaseous emissions minimization when committing its generation of thermal units. The proposed schedule will be used by the power producers to decide on emission quota arbitrage opportunities and for strategic bidding to the energy and reserves market. The paper analyzes a scenario-based multiobjective model in which random distributions, such as price forecasting inaccuracies as well as forced outage of generating units are modeled as scenarios tree using a combined fuzzy c-mean/Monte-Carlo simulation (FCM/MCS) method. With the above procedure the stochastic multiobjective self-scheduling problem is converted into corresponding deterministic problems. Then a multiobjective mathematical programming (MMP) approach based on ε-constraint method is implemented for each deterministic scenario. Piecewise linearized fuel and emission cost functions are applied for computational efficiency and the model is formulated as a mixed-integer programming (MIP) problem. Numerical simulations for a power producer with 21 thermal units are discussed to demonstrate the performance of the proposed approach in increasing expected payoffs by adjusting the emission quota arbitrage opportunities. (author)

  12. Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

    International Nuclear Information System (INIS)

    Kazempour, S. Jalal; Moghaddam, Mohsen Parsa

    2011-01-01

    This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz's seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed. (author)

  13. Predictive densities for day-ahead electricity prices using time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices. These scenarios are most likely to be generated based on marginal predictive densities for such prices, then enhanced with a temporal...... dependence structure. A semi-parametric methodology for generating such densities is presented: it includes: (i) a time-adaptive quantile regression model for the 5%–95% quantiles; and (ii) a description of the distribution tails with exponential distributions. The forecasting skill of the proposed model...

  14. Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050

    Directory of Open Access Journals (Sweden)

    Zhaoxi Liu

    2014-03-01

    Full Text Available This paper presents the day-ahead energy planning of passenger cars with 100% electric vehicle (EV penetration in the Nordic region by 2050. EVs will play an important role in the future energy systems which can both reduce the greenhouse gas (GHG emissions from the transport sector and provide the demand side flexibility required by smart grids. On the other hand, the EVs will increase the electricity consumption. In order to quantify the electricity consumption increase due to the 100% EV penetration in the Nordic region to facilitate the power system planning studies, the day-ahead energy planning of EVs has been investigated with different EV charging scenarios. Five EV charging scenarios have been considered in the energy planning analysis which are: uncontrolled charging all day, uncontrolled charging at home, timed charging, spot price based charging all day and spot price based charging at home. The demand profiles of the five charging analysis show that timed charging is the least favorable charging option and the spot priced based EV charging might induce high peak demands. The EV charging demand will have a considerable share of the energy consumption in the future Nordic power system.

  15. Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets

    Directory of Open Access Journals (Sweden)

    Xiaolin Ayón

    2017-04-01

    Full Text Available This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES generation. The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets.

  16. Optimal Day-ahead Charging Scheduling of Electric Vehicles through an Aggregative Game Model

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Huang, Shaojun

    2017-01-01

    The electric vehicle (EV) market has been growing rapidly around the world. With large scale deployment of EVs in power systems, both the grid and EV owners will benefit if the flexible demand of EV charging is properly managed through the electricity market. When EV charging demand is considerable...... in a grid, it will impact spot prices in the electricity market and consequently influence the charging scheduling itself. The interaction between the spot prices and the EV demand needs to be considered in the EV charging scheduling, otherwise it will lead to a higher charging cost. A day-ahead EV charging...... scheduling based on an aggregative game model is proposed in this paper. The impacts of the EV demand on the electricity prices are formulated with the game model in the scheduling considering possible actions of other EVs. The existence and uniqueness of the pure strategy Nash equilibrium are proved...

  17. Modeling the transient security constraints of natural gas network in day-ahead power system scheduling

    DEFF Research Database (Denmark)

    Yang, Jingwei; Zhang, Ning; Kang, Chongqing

    2017-01-01

    The rapid deployment of gas-fired generating units makes the power system more vulnerable to failures in the natural gas system. To reduce the risk of gas system failure and to guarantee the security of power system operation, it is necessary to take the security constraints of natural gas...... accurately, they are hard to be embedded into the power system scheduling model, which consists of algebraic equations and inequations. This paper addresses this dilemma by proposing an algebraic transient model of natural gas network which is similar to the branch-node model of power network. Based...... pipelines into account in the day-ahead power generation scheduling model. However, the minute- and hour-level dynamic characteristics of gas systems prevents an accurate decision-making simply with the steady-state gas flow model. Although the partial differential equations depict the dynamics of gas flow...

  18. Incorporating price-responsive customers in day-ahead scheduling of smart distribution networks

    International Nuclear Information System (INIS)

    Mazidi, Mohammadreza; Monsef, Hassan; Siano, Pierluigi

    2016-01-01

    Highlights: • Proposing a model for incorporating price-responsive customers in day-ahead scheduling of smart distribution networks; this model provides a win–win situation. • Introducing a risk management model based on a bi-level information-gap decision theory and recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. • Utilizing mixed-integer linear programing formulation that is efficiently solved by commercial optimization software. - Abstract: Demand response and real-time pricing of electricity are key factors in a smart grid as they can increase economic efficiency and technical performances of power grids. This paper focuses on incorporating price-responsive customers in day-ahead scheduling of smart distribution networks under a dynamic pricing environment. A novel method is proposed and formulated as a tractable mixed integer linear programming optimization problem whose objective is to find hourly sale prices offered to customers, transactions (purchase/sale) with the wholesale market, commitment of distribution generation units, dispatch of battery energy storage systems and planning of interruptible loads in a way that the profit of the distribution network operator is maximized while customers’ benefit is guaranteed. To hedge distribution network operator against financial risk arising from uncertainty of wholesale market prices, a risk management model based on a bi-level information-gap decision theory is proposed. The proposed bi-level problem is solved by recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. Performance of the proposed model is verified by applying it to a modified version of the IEEE 33-bus distribution test network. Numerical results demonstrate the effectiveness and efficiency of the proposed method.

  19. Price forecasting of day-ahead electricity markets using a hybrid forecast method

    International Nuclear Information System (INIS)

    Shafie-khah, M.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

    2011-01-01

    Research highlights: → A hybrid method is proposed to forecast the day-ahead prices in electricity market. → The method combines Wavelet-ARIMA and RBFN network models. → PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. → One of the merits of the proposed method is lower need to the input data. → The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

  20. Price forecasting of day-ahead electricity markets using a hybrid forecast method

    Energy Technology Data Exchange (ETDEWEB)

    Shafie-khah, M., E-mail: miadreza@gmail.co [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Moghaddam, M. Parsa, E-mail: parsa@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Sheikh-El-Eslami, M.K., E-mail: aleslam@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of)

    2011-05-15

    Research highlights: {yields} A hybrid method is proposed to forecast the day-ahead prices in electricity market. {yields} The method combines Wavelet-ARIMA and RBFN network models. {yields} PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. {yields} One of the merits of the proposed method is lower need to the input data. {yields} The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

  1. A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

    International Nuclear Information System (INIS)

    Varkani, Ali Karimi; Daraeepour, Ali; Monsef, Hassan

    2011-01-01

    Highlights: → A strategy for integrated operation of wind and pumped-storage plants is proposed. → Participation of both plants in energy and ancillary service markets is modeled. → The uncertainty of wind production is modeled by a novel probabilistic function. → The proposed strategy is tested on a real case in the Spanish electricity market. -- Abstract: Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.

  2. Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets

    OpenAIRE

    Ziel, Florian; Steinert, Rick; Husmann, Sven

    2015-01-01

    In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe. We focus on markets, which settle their prices after the EXAA, which enables traders to include the EXAA price into their calculations. For each market we employ econometric models to incorporate the EXAA price and compare them with their counterparts without the price of the Austrian exchange. By employing a forecasting study...

  3. Everything you need to know to operate on Day-Ahead{sup TM}; Tout ce que vous devez savoir pour intervenir sur Powernext Day-Ahead{sup TM}

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-05-15

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead{sup TM} since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures{sup TM} since 18 June 2004. This document is the user's guide of Powernext Day-Ahead{sup TM}. It presents: 1 - the power exchange in France (market model, Powernext's regulatory environment, general market operations, 2 - Powernext Day-Ahead{sup TM} members (membership, agreement, start-up notification, tariffs, standing obligations, membership termination), 3 - Powernext Day-Ahead{sup TM} products (specifications, management), 4 - trading (connections, system flow chart, ElWeb client installation and daily connections, portfolio-management, single bidding, type of order, submitting, importing, saving, sending, modifying or canceling an order form, transmission problems, block bidding block bid characteristics, sending, saving, transmitting, modifying and canceling a block bid, price calculations, blind auction procedure, example, taking into account block bids, rounding off rules, consulting and saving the results, sample documents, auction validation), 5 - clearing (LCH.Clearnet SA, legal framework, clearing agreement, PP-DPES agreement, market security, initial margin, daily adjustments, additional margin calls, trade-related financial flows, net financial position, value-added tax, settlement statements, general idea, characteristics and transmission method of settlement statements sample Documents, cash calls, settlement, default, sample cash call documents, financial Reports), 6 - delivery (balance responsible entity, file characteristics and transmission, imbalance settlement

  4. Application of a Gradient Descent Continuous Actor-Critic Algorithm for Double-Side Day-Ahead Electricity Market Modeling

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2016-09-01

    Full Text Available An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs and demanders (represented by DisCOs compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP and each rival’s bidding strategy as common knowledge (in dynamic game market models, and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models, which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n. The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare

  5. Day-ahead tariffs for the alleviation of distribution grid congestion from electric vehicles

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Wu, Qiuwei; Østergaard, Jacob

    2012-01-01

    An economically efficient day-ahead tariff (DT) is proposed with the purpose of preventing the distribution grid congestion resulting from electric vehicle (EV) charging scheduled on a dayahead basis. The DT concept developed herein is derived from the locational marginal price (LMP), in particular...... the congestion cost component of the LMP. A step-wise congestion management structure has been developed whereby the distribution system operator (DSO) predicts congestion for the coming day and publishes DTs prior to the clearing of the day-ahead market. EV fleet operators (FOs) optimize their EV charging...... schedules with respect to the predicted day-ahead prices and the published DTs, thereby avoiding congestion while still minimizing the charging cost. A Danish 400V distribution network is used to carry out case studies to illustrate the effectiveness of the developed concept for the prevention...

  6. Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market

    International Nuclear Information System (INIS)

    Gomes, I.L.R.; Pousinho, H.M.I.; Melício, R.; Mendes, V.M.F.

    2017-01-01

    This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed. - • Joint wind and PV systems with energy storage. • Electricity markets. • Stochastic optimization. • Day-ahead market.

  7. Day-ahead wind speed forecasting using f-ARIMA models

    International Nuclear Information System (INIS)

    Kavasseri, Rajesh G.; Seetharaman, Krithika

    2009-01-01

    With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed/power forecasts. Accurate wind speed forecasts are necessary to schedule dispatchable generation and tariffs in the day-ahead electricity market. This paper examines the use of fractional-ARIMA or f-ARIMA models to model, and forecast wind speeds on the day-ahead (24 h) and two-day-ahead (48 h) horizons. The models are applied to wind speed records obtained from four potential wind generation sites in North Dakota. The forecasted wind speeds are used in conjunction with the power curve of an operational (NEG MICON, 750 kW) turbine to obtain corresponding forecasts of wind power production. The forecast errors in wind speed/power are analyzed and compared with the persistence model. Results indicate that significant improvements in forecasting accuracy are obtained with the proposed models compared to the persistence method. (author)

  8. Value of Flexible Resources, Virtual Bidding, and Self-Scheduling in Two-Settlement Electricity Markets With Wind Generation – Part I: Principles and Competitive Model

    DEFF Research Database (Denmark)

    Kazempour, Jalal; Hobbs, Benjamin F.

    2017-01-01

    Part one of this two-part paper presents new models for evaluating flexible resources in two-settlement electricity markets (day-ahead and real-time) with uncertain net loads (demand minus wind). Physical resources include wind together with fast- and slow-start demand response and thermal...... of certain equivalencies of the four models. We show how virtual bidding enhances market performance, since, together with self-scheduling by slow-start generators, it can help deterministic day-ahead market to choose the most efficient unit commitment....

  9. How uncertain are day-ahead wind forecasts?

    Energy Technology Data Exchange (ETDEWEB)

    Grimit, E. [3TIER Environmental Forecast Group, Seattle, WA (United States)

    2006-07-01

    Recent advances in the combination of weather forecast ensembles with Bayesian statistical techniques have helped to address uncertainties in wind forecasting. Weather forecast ensembles are a collection of numerical weather predictions. The combination of several equally-skilled forecasts typically results in a consensus forecast with greater accuracy. The distribution of forecasts also provides an estimate of forecast inaccuracy. However, weather forecast ensembles tend to be under-dispersive, and not all forecast uncertainties can be taken into account. In order to address these issues, a multi-variate linear regression approach was used to correct the forecast bias for each ensemble member separately. Bayesian model averaging was used to provide a predictive probability density function to allow for multi-modal probability distributions. A test location in eastern Canada was used to demonstrate the approach. Results of the test showed that the method improved wind forecasts and generated reliable prediction intervals. Prediction intervals were much shorter than comparable intervals based on a single forecast or on historical observations alone. It was concluded that the approach will provide economic benefits to both wind energy developers and investors. refs., tabs., figs.

  10. Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Nielsen, Arne Hejde

    2014-01-01

    This paper presents the day-ahead energy planning of passenger cars with 100% electric vehicle (EV) penetration in the Nordic region by 2050. EVs will play an important role in the future energy systems which can both reduce the greenhouse gas (GHG) emission from the transport sector and provide...... demand side flexibility required by the smart grids. On the other hand, the EVs will increase the electricity consumption. In order to quantify the electricity consumption increase due to the 100% EV penetration in the Nordic region to facilitate the power system planning studies, the day-ahead energy...

  11. Optimal scheduling for electric heat booster under day-ahead electricity and heat pricing

    DEFF Research Database (Denmark)

    Cai, Hanmin; You, Shi; Bindner, Henrik W.

    2017-01-01

    Multi-energy system (MES) operation calls for active management of flexible resources across energy sectors to improve efficiency and meet challenging environmental targets. Electric heat booster, a solution for Domestic Hot Water (DHW) preparation under Low-Temperature-District-Heating (LTDH......) context, is identified as one of aforementioned flexible resources for electricity and heat sectors. This paper extends the concept of optimal load scheduling under day-ahead pricing from electricity sector only to both electricity and heat sectors. A case study constructing day-ahead energy prices...

  12. Day-ahead distributed energy resource scheduling using differential search algorithm

    DEFF Research Database (Denmark)

    Soares, J.; Lobo, C.; Silva, M.

    2015-01-01

    The number of dispersed energy resources is growing every day, such as the use of more distributed generators. This paper deals with energy resource scheduling model in future smart grids. The methodology can be used by virtual power players (VPPs) considering day-ahead time horizon. This method...... considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. This paper presents an application of differential search algorithm (DSA) for solving the day-ahead scheduling...

  13. Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Activity assessment first-half 2006

    International Nuclear Information System (INIS)

    2006-01-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO 2 exchange markets. This activity report presents the highlights of the market and of Powernext in the first half of 2006: market conditions, prices and traded volumes on Powernext (Powernext Day-Ahead TM in the case of day-ahead contracts, Powernext Futures TM in the case of medium-term contracts, and Powernext Carbon in the case of CO 2 ), new active members, and liquidity on the power market. (J.S.)

  14. Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market

    Directory of Open Access Journals (Sweden)

    Xiaolin Liu

    2012-11-01

    Full Text Available Wind Power Producers (WPPs seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS, the chance-constrained programming-based strategy (CPS and the multi-objective bidding strategy (ECPS. Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets.

  15. Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

    International Nuclear Information System (INIS)

    Zhang, Ning

    2009-01-01

    This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry. (author)

  16. Risk-constrained dynamic self-scheduling of a pumped-storage plant in the energy and ancillary service markets

    International Nuclear Information System (INIS)

    Kazempour, S. Jalal; Moghaddam, M. Parsa; Haghifam, M.R.; Yousefi, G.R.

    2009-01-01

    This work addresses a new framework for self-scheduling of an individual price-taker pumped-storage plant in a day-ahead (DA) market. The goal is achieving the best trade-off between the expected profit and the risks when the plant participates in DA energy, spinning reserve and regulation markets. In this paper, a set of uncertainties including price forecasting errors and also the uncertainty of power delivery requests in the ancillary service markets are contemplated. Considering these uncertainties, a new approach is proposed which is called dynamic self-scheduling (DSS). This risk-constrained dynamic self-scheduling problem is therefore formulated and solved as a mixed integer programming (MIP) problem. Numerical results for a case study are discussed. (author)

  17. The effect of contingency analysis on the nodal prices in the day-ahead market

    International Nuclear Information System (INIS)

    Murphy, Frederic H.; Mudrageda, Murthy; Soyster, Allen L.; Saric, Andrija T.; Stankovic, Aleksandar M.

    2010-01-01

    We look at the effect of modeling branch-outage contingencies on locational marginal prices. To model contingencies in the day-ahead auction, we formulate a two-stage stochastic program. Rather than follow the current practice of including a list of possible contingencies that must be satisfied, we incorporate a larger set of contingencies in the model and allow contingencies to result in load reductions/outages at a cost. The model can be used and interpreted in two ways. One is to look at the tradeoff between reliability and outage costs. Another is to consider the load losses resulting from a contingency to be consumer offers of load reductions in response to line outages as part of the day-ahead auction. In analyzing the model structure, we find that the prices in the model closer in definition to those currently used in the day-ahead auction do not maximize expected surplus because the day-ahead auction produces prices that assume shortages will never occur. This raises issues with the design of auctions with important stochastic elements in the market. We present results for a 68-node grid with 86 branches (lines and transformers) to illustrate how prices and expected values change as the costs of outages are varied.

  18. The impact of renewable energies on EEX day-ahead electricity prices

    International Nuclear Information System (INIS)

    Paraschiv, Florentina; Erni, David; Pietsch, Ralf

    2014-01-01

    In this paper, we analyze the impact of renewable energies, wind and photovoltaic, on the formation of day-ahead electricity prices at EEX. We give an overview of the policy decisions concerning the promotion of renewable energy sources in Germany and discuss their consequences on day-ahead prices. An analysis of electricity spot prices reveals that the introduction of renewable energies enhances extreme price changes. In the frame of a dynamic fundamental model, we show that there has been a continuous electricity price adaption process to market fundamentals. Furthermore, the fundamental drivers of prices differ among hours with different load profiles. Our results imply that renewable energies decrease market spot prices and have implications on the traditional fuel mix for electricity production. However, the prices for the final consumers increased overall because they must pay in addition the feed-in tariffs for the promotion of renewable energy. - Highlights: • We analyze the impact of renewable energies on the day-ahead electricity prices at EEX. • We discuss the impact of renewables on day-ahead prices. • We show a continuous electricity price adaption process to market fundamentals. • Renewable energies decrease market spot prices and shift the merit order curve. • The prices for the final consumers however increased because of feed-in tariffs

  19. Demand Response from Day-Ahead Hourly Pricing for Large Customers

    International Nuclear Information System (INIS)

    Hopper, Nicole; Goldman, Charles; Neenan, Bernie

    2006-01-01

    Day-ahead default-service RTP for large customers not only improves the linkage between wholesale and retail markets, but also promotes the development of retail competition. The default service sets a standard for competitive alternatives and its structure shapes the types of retail market products that develop. (author)

  20. Day-ahead resource scheduling including demand response for electric vehicles

    DEFF Research Database (Denmark)

    Soares, Joao; Morais, Hugo; Sousa, Tiago

    2014-01-01

    Summary form only given. The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering...

  1. Everything you need to know to operate on Day-AheadTM

    International Nuclear Information System (INIS)

    2005-05-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document is the user's guide of Powernext Day-Ahead TM . It presents: 1 - the power exchange in France (market model, Powernext's regulatory environment, general market operations, 2 - Powernext Day-Ahead TM members (membership, agreement, start-up notification, tariffs, standing obligations, membership termination), 3 - Powernext Day-Ahead TM products (specifications, management), 4 - trading (connections, system flow chart, ElWeb client installation and daily connections, portfolio-management, single bidding, type of order, submitting, importing, saving, sending, modifying or canceling an order form, transmission problems, block bidding block bid characteristics, sending, saving, transmitting, modifying and canceling a block bid, price calculations, blind auction procedure, example, taking into account block bids, rounding off rules, consulting and saving the results, sample documents, auction validation), 5 - clearing (LCH.Clearnet SA, legal framework, clearing agreement, PP-DPES agreement, market security, initial margin, daily adjustments, additional margin calls, trade-related financial flows, net financial position, value-added tax, settlement statements, general idea, characteristics and transmission method of settlement statements sample Documents, cash calls, settlement, default, sample cash call documents, financial Reports), 6 - delivery (balance responsible entity, file characteristics and transmission, imbalance settlement, interconnection access), contacts and

  2. Self-scheduling with Microsoft Excel.

    Science.gov (United States)

    Irvin, S A; Brown, H N

    1999-01-01

    Excessive time was being spent by the emergency department (ED) staff, head nurse, and unit secretary on a complex 6-week manual self-scheduling system. This issue, plus inevitable errors and staff dissatisfaction, resulted in a manager-lead initiative to automate elements of the scheduling process using Microsoft Excel. The implementation of this initiative included: common coding of all 8-hour and 12-hour shifts, with each 4-hour period represented by a cell; the creation of a 6-week master schedule using the "count-if" function of Excel based on current staffing guidelines; staff time-off requests then entered by the department secretary; the head nurse, with staff input, then fine-tuned the schedule to provide even unit coverage. Outcomes of these changes included an increase in staff satisfaction, time saved by the head nurse, and staff work time saved because there was less arguing about the schedule. Ultimately, the automated self-scheduling method was expanded to the entire 700-bed hospital.

  3. Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. 2006 activity assessment

    International Nuclear Information System (INIS)

    2006-01-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO 2 exchange markets. This activity report presents the highlights of the market and of Powernext in 2006: market conditions (prices on the electricity market, prices on the CO 2 emission allowances market, weather conditions, institutional aspects of the CO 2 market, power generation and consumption, situation at the borders, fuel prices), traded volumes on Powernext (Powernext Day-Ahead TM in the case of day-ahead contracts, Powernext Futures TM in the case of medium-term contracts, and Powernext Carbon in the case of CO 2 ), new active members, and Powernext liquidity on the power market. (J.S.)

  4. A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets

    DEFF Research Database (Denmark)

    Pircalabu, Anca; Benth, Fred Espen

    2017-01-01

    significant evidence of tail dependence in all pairs of interconnected areas we consider. As a first application of the proposed model, we consider the pricing of financial transmission rights, and highlight how the choice of marginal distributions and copula impacts prices. As a second application we......The recent price coupling of many European electricity markets has triggered a fundamental change in the interaction of day-ahead prices, challenging additionally the modeling of the joint behavior of prices in interconnected markets. In this paper we propose a regime-switching AR–GARCH copula...... to model pairs of day-ahead electricity prices in coupled European markets. While capturing key stylized facts empirically substantiated in the literature, this model easily allows us to 1) deviate from the assumption of normal margins and 2) include a more detailed description of the dependence between...

  5. Sequential bidding in day-ahead auctions for spot energy and power systems reserve

    International Nuclear Information System (INIS)

    Swider, Derk J.

    2005-01-01

    In this paper a novel approach for sequential bidding on day-ahead auction markets for spot energy and power systems reserve is presented. For the spot market a relatively simple method is considered as a competitive market is assumed. For the reserve market one bidder is assumed to behave strategically and the behavior of the competitors is summarized in a probability distribution of the market price. This results in a method for sequential bidding, where the bidding prices and capacities on the spot and reserve markets are calculated by maximizing a stochastic non-linear objective function of expected profit. With an exemplary application is shown that the trading sequence leads to increasing bidding capacities and prices in the reverse rank number of the markets. Hence, the consideration of a defined trading sequence greatly influences the mathematical representation of the optimal bidding behavior under price uncertainty in day-ahead auctions for spot energy and power systems reserve. (Author)

  6. Hourly price elasticity pattern of electricity demand in the German day-ahead market

    OpenAIRE

    Knaut, Andreas; Paulus, Simon

    2016-01-01

    System security in electricity markets relies crucially on the interaction between demand and supply over time. However, research on electricity markets has been mainly focusing on the supply side arguing that demand is rather inelastic. Assuming perfectly inelastic demand might lead to delusive statements regarding the price formation in electricity markets. In this article we quantify the short-run price elasticity of electricity demand in the German day-ahead market and show that demand is...

  7. How to sell renewable electricity. Interactions of the intraday and day-ahead market under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Knaut, Andreas; Obermueller, Frank

    2016-04-15

    Uncertainty about renewable production increases the importance of sequential short-term trading in electricity markets. We consider a two-stage market where conventional and renewable producers compete in order to satisfy the demand of consumers. The trading in the first stage takes place under uncertainty about production levels of renewable producers, which can be associated with trading in the day-ahead market. In the second stage, which we consider as the intraday market, uncertainty about the production levels is resolved. Our model is able to capture different levels of flexibility for conventional producers as well as different levels of competition for renewable producers. We find that it is optimal for renewable producers to sell less than the expected production in the day-ahead market. In situations with high renewable production it is even profitable for renewable producers to withhold quantities in the intraday market. However, for an increasing number of renewable producers, the optimal quantity tends towards the expected production level. More competition as well as a more flexible power plant fleet lead to an increase in overall welfare, which can even be further increased by delaying the gate-closure of the day-ahead market or by improving the quality of renewable production forecasts.

  8. A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism

    International Nuclear Information System (INIS)

    Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat

    2016-01-01

    Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.

  9. Energy and Reserve under Distributed Energy Resources Management—Day-Ahead, Hour-Ahead and Real-Time

    Directory of Open Access Journals (Sweden)

    Tiago Soares

    2017-11-01

    Full Text Available The increasing penetration of distributed energy resources based on renewable energy sources in distribution systems leads to a more complex management of power systems. Consequently, ancillary services become even more important to maintain the system security and reliability. This paper proposes and evaluates a generic model for day-ahead, intraday (hour-ahead and real-time scheduling, considering the joint optimization of energy and reserve in the scope of the virtual power player concept. The model aims to minimize the operation costs in the point of view of one aggregator agent taking into account the balance of the distribution system. For each scheduling stage, previous scheduling results and updated forecasts are considered. An illustrative test case of a distribution network with 33 buses, considering a large penetration of distribution energy resources allows demonstrating the benefits of the proposed model.

  10. Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

    DEFF Research Database (Denmark)

    Soares, João; Valle, Zita; Morais, Hugo

    2013-01-01

    This paper presents a decision support Tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy ressource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application...... of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network...... constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance...

  11. Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

    International Nuclear Information System (INIS)

    Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

    2017-01-01

    Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

  12. Customer Strategies for Responding to Day-Ahead Market HourlyElectricity Pricing

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Chuck; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Boisvert, Dick; Cappers, Peter; Pratt, Donna; Butkins, Kim

    2005-08-25

    Real-time pricing (RTP) has been advocated as an economically efficient means to send price signals to customers to promote demand response (DR) (Borenstein 2002, Borenstein 2005, Ruff 2002). However, limited information exists that can be used to judge how effectively RTP actually induces DR, particularly in the context of restructured electricity markets. This report describes the second phase of a study of how large, non-residential customers' adapted to default-service day-ahead hourly pricing. The customers are located in upstate New York and served under Niagara Mohawk, A National Grid Company (NMPC)'s SC-3A rate class. The SC-3A tariff is a type of RTP that provides firm, day-ahead notice of hourly varying prices indexed to New York Independent System Operator (NYISO) day-ahead market prices. The study was funded by the California Energy Commission (CEC)'s PIER program through the Demand Response Research Center (DRRC). NMPC's is the first and longest-running default-service RTP tariff implemented in the context of retail competition. The mix of NMPC's large customers exposed to day-ahead hourly prices is roughly 30% industrial, 25% commercial and 45% institutional. They have faced periods of high prices during the study period (2000-2004), thereby providing an opportunity to assess their response to volatile hourly prices. The nature of the SC-3A default service attracted competitive retailers offering a wide array of pricing and hedging options, and customers could also participate in demand response programs implemented by NYISO. The first phase of this study examined SC-3A customers' satisfaction, hedging choices and price response through in-depth customer market research and a Constant Elasticity of Substitution (CES) demand model (Goldman et al. 2004). This second phase was undertaken to answer questions that remained unresolved and to quantify price response to a higher level of granularity. We accomplished these

  13. Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling

    DEFF Research Database (Denmark)

    Soares, Joao; Vale, Zita; Canizes, Bruno

    2013-01-01

    This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle-To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming...... to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow...

  14. Customer response to day-ahead market hourly pricing: Choices and performance

    International Nuclear Information System (INIS)

    Hopper, Nicole; Goldman, Charles; Bharvirkar, Ranjit; Neenan, Bernie

    2006-01-01

    Real-time pricing (RTP) has been advocated to address extreme price volatility and market power in electricity markets. This study of Niagara Mohawk Power Corporation's largest customers analyzes their choices and performance in response to day-ahead, default-service RTP. Overall price response is modest: 119 customers are estimated to reduce their peak demand by about 10% at high prices. Manufacturing customers are most responsive with a price elasticity of 0.16, followed by government/education customers (0.11), while commercial/retail, healthcare and public works customers are, at present, relatively unresponsive. Within market segments, individual customer response varies significantly. (author)

  15. Congestion management of distribution networks with day-ahead dynamic grid tariffs

    DEFF Research Database (Denmark)

    Huang, Shaojun; Wu, Qiuwei

    vehicles (EV) and heat pumps (HP), will be largely deployed in electrical distribution networks. Congestion management will be important in the future active distribution networks. In the IDE4L project, work package 5 is dedicated to develop different kinds of congestion management methods. Demand response...... (DR) is one of the important methods. In this report, as one task of work package 5, the day-ahead dynamic tariff (DADT) method for congestion management in distribution networks is presented. The dynamic tariff (DT) can motivate the flexible demands (EV and HP) to shift their energy consumption...

  16. Thermal energy storage for electricity-driven space heating in a day-ahead electricity market

    DEFF Research Database (Denmark)

    Pensini, Alessandro

    2012-01-01

    Thermal Energy Storage (TES) in a space heating (SH) application was investigated. The study aimed to determine the economic benefits of introducing TES into an electricity-driven SH system under a day-ahead electricity market. The performance of the TES was assessed by comparing the cost...... of electricity in a system with a TES unit to the case where no storage is in use and the entire heat requirement is fulfilled by purchasing electricity according to the actual load. The study had two goals: 1. Determining how the size – in terms of electricity input (Pmax) and energy capacity (Emax...

  17. Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

    Directory of Open Access Journals (Sweden)

    José R. Andrade

    2017-10-01

    Full Text Available Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 €/MWh for day-ahead market and a maximum value of 2.53 €/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

  18. The impact of wind power on APX day-ahead electricity prices in the Netherlands VVM-Intermittency project

    Energy Technology Data Exchange (ETDEWEB)

    Nieuwenhout, F.D.J. [ECN Policy Studies, Amsterdam (Netherlands); Brand, A.J. [ECN Wind Energy, Petten (Netherlands)

    2013-02-15

    A detailed analysis was conducted to assess to what extent availability of wind energy has influenced day-ahead electricity prices in the Netherlands over the period 2006-2009. With a meteorological model, time series of day-ahead wind forecasts were generated, and these were compared with APX-ENDEX day-ahead market prices. Wind energy contributes to only 4% of electricity generation in the Netherlands, but was found to depress average day-ahead market prices by about 5%. With the help of the bid curves on the APX-ENDEX day-ahead market for 2009, a model was developed to assess the impact of increasing levels of wind generation on power prices in the Netherlands. One of the main findings is that the future impact on prices will be less than in the past. With an increase of installed wind capacity from 2200 MW to 6000 MW, average day-ahead prices are expected to be depressed by an additional 6% in case no additional conventional generation is assumed. Taking into account existing government policy on wind and ongoing investments in new conventional power plants, prices in 2016 will be only 3% lower.

  19. Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

    Science.gov (United States)

    Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

    2015-04-01

    This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

  20. Day-Ahead Scheduling Considering Demand Response as a Frequency Control Resource

    Directory of Open Access Journals (Sweden)

    Yu-Qing Bao

    2017-01-01

    Full Text Available The development of advanced metering technologies makes demand response (DR able to provide fast response services, e.g., primary frequency control. It is recognized that DR can contribute to the primary frequency control like thermal generators. This paper proposes a day-ahead scheduling method that considers DR as a frequency control resource, so that the DR resources can be dispatched properly with other resources. In the proposed method, the objective of frequency control is realized by defining a frequency limit equation under a supposed contingency. The frequency response model is used to model the dynamics of system frequency. The nonlinear frequency limit equation is transformed to a linear arithmetic equation by piecewise linearization, so that the problem can be solved by mixed integer linear programming (MILP. Finally, the proposed method is verified on numerical examples.

  1. Computational Intelligence Techniques Applied to the Day Ahead PV Output Power Forecast: PHANN, SNO and Mixed

    Directory of Open Access Journals (Sweden)

    Emanuele Ogliari

    2018-06-01

    Full Text Available An accurate forecast of the exploitable energy from Renewable Energy Sources is extremely important for the stability issues of the electric grid and the reliability of the bidding markets. This paper presents a comparison among different forecasting methods of the photovoltaic output power introducing a new method that mixes some peculiarities of the others: the Physical Hybrid Artificial Neural Network and the five parameters model estimated by the Social Network Optimization. In particular, the day-ahead forecasts evaluated against real data measured for two years in an existing photovoltaic plant located in Milan, Italy, are compared by means both new and the most common error indicators. Results reported in this work show the best forecasting capability of the new “mixed method” which scored the best forecast skill and Enveloped Mean Absolute Error on a yearly basis (47% and 24.67%, respectively.

  2. A day-ahead market for electricity in Alberta : is there a case to be made?

    International Nuclear Information System (INIS)

    Fronimos, P.

    2006-01-01

    Following the success of the introduction of competition in several heavily regulated industries in the 1980s and 1990s, traditional utilities were broken up and markets were introduced for their respective services. Some of these markets evolved into complex structures with multiple sub-markets for installed capacity, energy, transmission and for all types of reserves. Electricity submarkets now operate in a similar manner in different timeframes comprising two settlement systems: the Day Ahead (DA) market, operating a day ahead of the actual generation and consumption of electricity and one that operates in real time, the Real-Time (RT) or Balancing market. This paper explored the case for a binding DA market for electricity in Alberta, by looking at the challenges facing the marketplace and examining how using a DA market would affect them. This paper hypothesized that a correctly designed and implemented, financially binding DA market would enhance the fidelity of the price signal in Alberta by providing an information rich environment for participants and the system operator. The paper defined and discussed both types of settlement systems. It then discussed the DA market in Alberta in terms of risk management, reliability, price fidelity and demand response. It was noted that some of the benefits of using a DA market could also be achieved by improvements to the existing market. Alberta faces several challenges, such as merit order instability and price volatility which are likely due to market design and operations rather than the inherent inability of a power exchange to address them. 31 refs., 1 tab., 3 figs

  3. Robust optimisation for self-scheduling and bidding strategies of hybrid CSP-fossil power plants

    DEFF Research Database (Denmark)

    Pousinho, H.M.I.; Contreras, J.; Pinson, P.

    2015-01-01

    between the molten-salt thermal energy storage (TES) and a fossil-fuel backup to overcome solar irradiation insufficiency, but with emission allowances constrained in the backup system to mitigate carbon footprint. A robust optimisation-based approach is proposed to provide the day-ahead self...

  4. Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Activity assessment first-half 2006; Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Bilan d'activite premier semestre 2006

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO{sub 2} exchange markets. This activity report presents the highlights of the market and of Powernext in the first half of 2006: market conditions, prices and traded volumes on Powernext (Powernext Day-Ahead{sup TM} in the case of day-ahead contracts, Powernext Futures{sup TM} in the case of medium-term contracts, and Powernext Carbon in the case of CO{sub 2}), new active members, and liquidity on the power market. (J.S.)

  5. Influence of feasibility constrains on the bidding strategy selection in a day-ahead electricity market session

    International Nuclear Information System (INIS)

    Borghetti, Alberto; Massucco, Stefano; Silvestro, Federico

    2009-01-01

    Large part of liberalized electricity markets, including the Italian one, features an auction mechanism, called day-ahead energy market, which matches producers' and buyers' simple bids, consisting of energy quantity and price pairs. The match is achieved by a merit-order economic dispatch procedure independently applied for each of the hours of the following day. Power plants operation should, however, take into account several technical constraints, such as maximum and minimum production bounds, ramp constraints and minimum up and downs times, as well as no-load and startup costs. The presence of these constraints forces to adjust the scheduling provided by the market in order to obtain a feasible scheduling. The paper presents an analysis of the possibility and the limits of taking into account the power plants technical constraints in the bidding strategy selection procedure of generating companies (Gencos). The analysis is carried out by using a computer procedure based both on a simple static game-theory approach and on a cost-minimization unit-commitment algorithm. For illustrative purposes, we present the results obtained for a system with three Gencos, each owning several power plants, trying to model the bidding behaviour of every generator in the system. This approach, although complex from the computational point of view, allows an analysis of both price and quantity bidding strategies and appears to be applicable to markets having different rules and features. (author)

  6. Energy and Reserve under Distributed Energy Resources Management-Day-Ahead, Hour-Ahead and Real-Time

    DEFF Research Database (Denmark)

    Soares, Tiago; Silva, Marco; Sousa, Tiago

    2017-01-01

    and evaluates a generic model for day-ahead, intraday (hour-ahead) and real-time scheduling, considering the joint optimization of energy and reserve in the scope of the virtual power player concept. The model aims to minimize the operation costs in the point of view of one aggregator agent taking into account...

  7. Customer response to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, C.; Hopper, N.; Sezgen, O.; Moezzi, M.; Bharvirkar, R.; Neenan, B.; Boisvert, R.; Cappers, P.; Pratt, D.

    2004-07-01

    There is growing interest in policies, programs and tariffs that encourage customer loads to provide demand response (DR) to help discipline wholesale electricity markets. Proposals at the retail level range from eliminating fixed rate tariffs as the default service for some or all customer groups to reinstituting utility-sponsored load management programs with market-based inducements to curtail. Alternative rate designs include time-of-use (TOU), day-ahead real-time pricing (RTP), critical peak pricing, and even pricing usage at real-time market balancing prices. Some Independent System Operators (ISOs) have implemented their own DR programs whereby load curtailment capabilities are treated as a system resource and are paid an equivalent value. The resulting load reductions from these tariffs and programs provide a variety of benefits, including limiting the ability of suppliers to increase spot and long-term market-clearing prices above competitive levels (Neenan et al., 2002; Boren stein, 2002; Ruff, 2002). Unfortunately, there is little information in the public domain to characterize and quantify how customers actually respond to these alternative dynamic pricing schemes. A few empirical studies of large customer RTP response have shown modest results for most customers, with a few very price-responsive customers providing most of the aggregate response (Herriges et al., 1993; Schwarz et al., 2002). However, these studies examined response to voluntary, two-part RTP programs implemented by utilities in states without retail competition.1 Furthermore, the researchers had limited information on customer characteristics so they were unable to identify the drivers to price response. In the absence of a compelling characterization of why customers join RTP programs and how they respond to prices, many initiatives to modernize retail electricity rates seem to be stymied.

  8. Not All Large Customers are Made Alike: Disaggregating Response to Default-Service Day-Ahead Market Pricing

    International Nuclear Information System (INIS)

    Hopper, Nicole; Goldman, Charles; Neenan, Bernie

    2006-01-01

    For decades, policymakers and program designers have gone on the assumption that large customers, particularly industrial facilities, are the best candidates for realtime pricing (RTP). This assumption is based partly on practical considerations (large customers can provide potentially large load reductions) but also on the premise that businesses focused on production cost minimization are most likely to participate and respond to opportunities for bill savings. Yet few studies have examined the actual price response of large industrial and commercial customers in a disaggregated fashion, nor have factors such as the impacts of demand response (DR) enabling technologies, simultaneous emergency DR program participation and price response barriers been fully elucidated. This second-phase case study of Niagara Mohawk Power Corporation (NMPC)'s large customer RTP tariff addresses these information needs. The results demonstrate the extreme diversity of large customers' response to hourly varying prices. While two-thirds exhibit some price response, about 20 percent of customers provide 75-80 percent of the aggregate load reductions. Manufacturing customers are most price-responsive as a group, followed by government/education customers, while other sectors are largely unresponsive. However, individual customer response varies widely. Currently, enabling technologies do not appear to enhance hourly price response; customers report using them for other purposes. The New York Independent System Operator (NYISO)'s emergency DR programs enhance price response, in part by signaling to customers that day-ahead prices are high. In sum, large customers do currently provide moderate price response, but there is significant room for improvement through targeted programs that help customers develop and implement automated load-response strategies

  9. Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. 2006 activity assessment; Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Bilan d'activite 2006

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO{sub 2} exchange markets. This activity report presents the highlights of the market and of Powernext in 2006: market conditions (prices on the electricity market, prices on the CO{sub 2} emission allowances market, weather conditions, institutional aspects of the CO{sub 2} market, power generation and consumption, situation at the borders, fuel prices), traded volumes on Powernext (Powernext Day-Ahead{sup TM} in the case of day-ahead contracts, Powernext Futures{sup TM} in the case of medium-term contracts, and Powernext Carbon in the case of CO{sub 2}), new active members, and Powernext liquidity on the power market. (J.S.)

  10. Revisiting short-term price and volatility dynamics in day-ahead electricity markets with rising wind power

    International Nuclear Information System (INIS)

    Li, Yuanjing

    2015-01-01

    This paper revisits the short-term price and volatility dynamics in day-ahead electricity markets in consideration of an increasing share of wind power, using an example of the Nord Pool day-ahead market and the Danish wind generation. To do so, a GARCH process is applied, and market coupling and the counterbalance effect of hydropower in the Scandinavian countries are additionally accounted for. As results, we found that wind generation weakly dampens spot prices with an elasticity of 0.008 and also reduces price volatility with an elasticity of 0.02 in the Nordic day-ahead market. The results shed lights on the importance of market coupling and interactions between wind power and hydropower in the Nordic system through cross-border exchanges, which play an essential role in price stabilization. Additionally, an EGARCH specification confirms an asymmetric influence of the price innovations, whereby negative shocks produce larger volatility in the Nordic spot market. While considering heavy tails in error distributions can improve model fits significantly, the EGARCH model outperforms the GARCH model on forecast evaluations. (author)

  11. Pricing Energy and Ancillary Services in a Day-Ahead Market for a Price-Taker Hydro Generating Company Using a Risk-Constrained Approach

    Directory of Open Access Journals (Sweden)

    Perica Ilak

    2014-04-01

    Full Text Available This paper analyzes a price-taker hydro generating company which participates simultaneously in day-ahead energy and ancillary services markets. An approach for deriving marginal cost curves for energy and ancillary services is proposed, taking into consideration price uncertainty and opportunity cost of water, which can later be used to determine hourly bid curves. The proposed approach combines an hourly conditional value-at-risk, probability of occurrence of automatic generation control states and an opportunity cost of water to determine energy and ancillary services marginal cost curves. The proposed approach is in a linear constraint form and is easy to implement in optimization problems. A stochastic model of the hydro-economic river basin is presented, based on the actual Vinodol hydropower system in Croatia, with a complex three-dimensional relationship between the power produced, the discharged water, and the head of associated reservoir.

  12. Assessment of the Impact of Stochastic Day-Ahead SCUC on Economic and Reliability Metrics at Multiple Timescales: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Wu, H.; Ela, E.; Krad, I.; Florita, A.; Zhang, J.; Hodge, B. M.; Ibanez, E.; Gao, W.

    2015-03-01

    This paper incorporates the stochastic day-ahead security-constrained unit commitment (DASCUC) within a multi-timescale, multi-scheduling application with commitment, dispatch, and automatic generation control. The stochastic DASCUC is solved using a progressive hedging algorithm with constrained ordinal optimization to accelerate the individual scenario solution. Sensitivity studies are performed in the RTS-96 system, and the results show how this new scheduling application would impact costs and reliability with a closer representation of timescales of system operations in practice.

  13. Guidelines for successful self-scheduling on nursing units.

    Science.gov (United States)

    Russell, Elizabeth; Hawkins, Jenna; Arnold, Kara A

    2012-09-01

    Self-scheduling programs are an increasingly popular strategy utilized by employers to address the individual and organizational challenges resulting from employee work-life imbalance among the nursing workforce. Certain key components will ensure buy-in and support from staff when self-scheduling programs are developed.

  14. Optimal bidding in Turkey day ahead electricity market for wind energy and pumped storage hydro power plant

    Directory of Open Access Journals (Sweden)

    Ceyhun Yıldız

    2016-10-01

    Full Text Available In electrical grid; when the demand power increases energy prices increase, when the demand decreases energy prices decrease. For this reason; to increase the total daily income, it is required to shift generations to the hours that high demand power values occurred. Wind Power Plants (WPP have unstable and uncontrollable generation characteristic. For this reason, energy storage systems are needed to shift the generations of WPPs in time scale. In this study, four wind power plants (WPP which are tied to the Turkish interconnected grid and a pumped hydro storage power plant (PSPP that meets the energy storage requirement of these power plants are investigated in Turkey day ahead energy market. An optimization algorithm is developed using linear programming technique to maximize the day ahead market bids of these plants which are going to generate power together. When incomes and generations of the plants that are operated with optimization strategy is analyzed, it is seen that annual income increased by 2.737% compared with WPPs ‘s alone operation and generations are substantially shifted to the high demand power occurred hours.

  15. Probability-Weighted LMP and RCP for Day-Ahead Energy Markets using Stochastic Security-Constrained Unit Commitment: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Ela, E.; O' Malley, M.

    2012-06-01

    Variable renewable generation resources are increasing their penetration on electric power grids. These resources have weather-driven fuel sources that vary on different time scales and are difficult to predict in advance. These characteristics create challenges for system operators managing the load balance on different timescales. Research is looking into new operational techniques and strategies that show great promise on facilitating greater integration of variable resources. Stochastic Security-Constrained Unit Commitment models are one strategy that has been discussed in literature and shows great benefit. However, it is rarely used outside the research community due to its computational limits and difficulties integrating with electricity markets. This paper discusses how it can be integrated into day-ahead energy markets and especially on what pricing schemes should be used to ensure an efficient and fair market.

  16. On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?

    Directory of Open Access Journals (Sweden)

    Ana-Maria Fuertes

    2016-09-01

    Full Text Available This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et al. that constructs the forecast at the market close instead and, accordingly, it models separately the daytime and overnight return processes and their covariance. For a small cap portfolio, the bivariate VaR approach affords superior predictive ability than the ex post overnight VaR approach whereas for a large cap portfolio the results are reversed. The contrast indicates that price discovery at the market open is less efficient for small capitalization, thinly traded stocks.

  17. Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

    International Nuclear Information System (INIS)

    Jiang, Bo; Farid, Amro M.; Youcef-Toumi, Kamal

    2015-01-01

    Highlights: • We compare two demand side management in a day-ahead electricity wholesale market. • We develop and reconcile social welfare & industrial DSM mathematical models. • We show the industrial netload has an additional forecast quantity of baseline. • We analytically and numerically show the model equivalence with accurate baseline. • We numerically demonstrate the baseline errors lead to higher and costlier dispatch. - Abstract: The intermittent nature of renewable energy has been discussed in the context of the operational challenges that it brings to electrical grid reliability. Demand side management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has often been recognized as an efficient way to mitigate the variable effects of renewable energy as well as to increase system efficiency and reduce system costs. However, the academic & industrial literature have taken divergent approaches to DSM implementation. While the popular approach among academia adopts a social welfare maximization formulation, the industrial practice compensates customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DSM. This paper rigorously compares these two different approaches in a day-ahead wholesale market context analytically and in a test case using the same system configuration and mathematical formalism. The comparison of the two models showed that a proper reconciliation of the two models might make them mitigate the stochastic netload in fundamentally the same way, but only under very specific conditions which are rarely met in practice. While the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. DSM participants are likely to manipulate the baseline in order to receive greater financial

  18. Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

    Directory of Open Access Journals (Sweden)

    Yi Xiao

    2013-02-01

    Full Text Available Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN and wavelet neural network (WNN are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO. Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.

  19. Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies

    NARCIS (Netherlands)

    Paterakis, N.G.; Erdinç, O.; Bakirtzis, A.G.; Catalao, J.P.S.

    2015-01-01

    In this paper, a detailed home energy management system structure is developed to determine the optimal dayahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets

  20. Day-Ahead Congestion Management in Distribution Systems through Household Demand Response and Distribution Congestion Prices

    DEFF Research Database (Denmark)

    Liu, Weijia; Wu, Qiuwei; Wen, Fushuan

    2014-01-01

    into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the loca- tional marginal pricing (LMP) model...... is proposed. Finally, a practical Danish 60kV/10.5kV distribution system is employed as the test case to verify the proposed method for mitigating congestion....

  1. Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models

    International Nuclear Information System (INIS)

    Tan, Zhongfu; Zhang, Jinliang; Xu, Jun; Wang, Jianhui

    2010-01-01

    This paper proposes a novel price forecasting method based on wavelet transform combined with ARIMA and GARCH models. By wavelet transform, the historical price series is decomposed and reconstructed into one approximation series and some detail series. Then each subseries can be separately predicted by a suitable time series model. The final forecast is obtained by composing the forecasted results of each subseries. This proposed method is examined on Spanish and PJM electricity markets and compared with some other forecasting methods. (author)

  2. Simultaneous day-ahead forecasting of electricity price and load in smart grids

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.; Moradzadeh, M.; Nooshyar, M.

    2015-01-01

    Highlights: • This paper presents a novel MIMO-based support vector machine for forecasting. • Considered uncertainties for better simulation for filtering in input data. • Used LSSVM technique for learning. • Proposed a new modification for standard artificial bee colony algorithm to optimize LSSVM engine. - Abstract: In smart grids, customers are promoted to change their energy consumption patterns by electricity prices. In fact, in this environment, the electricity price and load consumption are highly corrected such that the market participants will have complex model in their decisions to maximize their profit. Although the available forecasting mythologies perform well in electricity market by way of little or no load and price interdependencies, but cannot capture load and price dynamics if they exist. To overcome this shortage, a Multi-Input Multi-Output (MIMO) model is presented which can consider the correlation between electricity price and load. The proposed model consists of three components known as a Wavelet Packet Transform (WPT) to make valuable subsets, Generalized Mutual Information (GMI) to select best input candidate and Least Squares Support Vector Machine (LSSVM) based on MIMO model, called LSSVM-MIMO, to make simultaneous load and price forecasts. Moreover, the LSSVM-MIMO parameters are optimized by a novel Quasi-Oppositional Artificial Bee Colony (QOABC) algorithm. Some forecasting indices based on error factor are considered to evaluate the forecasting accuracy. Simulations carried out on New York Independent System Operator, New South Wales (NSW) and PJM electricity markets data, and showing that the proposed hybrid algorithm has good potential for simultaneous forecasting of electricity price and load

  3. Day ahead forecast of wind power through optimal application of multivariate analyzing methods

    Energy Technology Data Exchange (ETDEWEB)

    Arnoldt, Alexander; Bretschneider, Peter [Fraunhofer Institute for Optronics, System Technology, and Image Exploitation - Application Centre System Technology (IOSB-AST), Ilmenau (Germany). Energy Systems Group

    2011-07-01

    This paper presents two algorithms in identifying input models for artificial neural networks. The algorithms are based on an entropy analysis and an eigenvalue analysis of the correlation matrix. The resulting input models are used for investigating a feed forward and a recurrent artificial neural network structure to simulate a 24 hour forecast of wind power production. The limitation of the forecast error distribution is investigated through successful implementation of hybridization of single forecast models. Errors of the best forecast model stay between a normalized root mean square error from 3.5% to 6.1%. (orig.)

  4. Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

    Directory of Open Access Journals (Sweden)

    Chong Chen

    2018-04-01

    Full Text Available In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP, and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL, are still imperfect, which make it difficult for the active distribution network (ADN to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

  5. Day-ahead load forecast using random forest and expert input selection

    International Nuclear Information System (INIS)

    Lahouar, A.; Ben Hadj Slama, J.

    2015-01-01

    Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

  6. Optimal operational strategies for a day-ahead electricity market in the presence of market power using multi-objective evolutionary algorithms

    Science.gov (United States)

    Rodrigo, Deepal

    2007-12-01

    This dissertation introduces a novel approach for optimally operating a day-ahead electricity market not only by economically dispatching the generation resources but also by minimizing the influences of market manipulation attempts by the individual generator-owning companies while ensuring that the power system constraints are not violated. Since economic operation of the market conflicts with the individual profit maximization tactics such as market manipulation by generator-owning companies, a methodology that is capable of simultaneously optimizing these two competing objectives has to be selected. Although numerous previous studies have been undertaken on the economic operation of day-ahead markets and other independent studies have been conducted on the mitigation of market power, the operation of a day-ahead electricity market considering these two conflicting objectives simultaneously has not been undertaken previously. These facts provided the incentive and the novelty for this study. A literature survey revealed that many of the traditional solution algorithms convert multi-objective functions into either a single-objective function using weighting schemas or undertake optimization of one function at a time. Hence, these approaches do not truly optimize the multi-objectives concurrently. Due to these inherent deficiencies of the traditional algorithms, the use of alternative non-traditional solution algorithms for such problems has become popular and widely used. Of these, multi-objective evolutionary algorithms (MOEA) have received wide acceptance due to their solution quality and robustness. In the present research, three distinct algorithms were considered: a non-dominated sorting genetic algorithm II (NSGA II), a multi-objective tabu search algorithm (MOTS) and a hybrid of multi-objective tabu search and genetic algorithm (MOTS/GA). The accuracy and quality of the results from these algorithms for applications similar to the problem investigated here

  7. Day-Ahead Coordination of Vehicle-to-Grid Operation and Wind Power in Security Constraints Unit Commitment (SCUC

    Directory of Open Access Journals (Sweden)

    Mohammad Javad Abdollahi

    2015-08-01

    Full Text Available In this paper security constraints unit commitment (SCUC in the presence of wind power resources and electrical vehicles to grid is presented. SCUC operation prepare an optimal time table for generation unit commitment in order to maximize security, minimize operation cost and satisfy the constraints of networks and units in a period of time, as one of the most important research interest in power systems. Today, the relationship between power network and energy storage systems is interested for many researchers and network operators. Using Electrical Vehicles (PEVs and wind power for energy production is one of the newest proposed methods for replacing fossil fuels.One of the effective strategies for analyzing of the effects of Vehicle 2 Grid (V2G and wind power in optimal operation of generation is running of SCUC for power systems that are equipped with V2G and wind power resources. In this paper, game theory method is employed for deterministic solution of day-ahead unit commitment with considering security constraints in the simultaneous presence of V2G and wind power units. This problem for two scenarios of grid-controlled mode and consumer-controlled mode in three different days with light, medium and heavy load profiles is analyzed. Simulation results show the effectiveness of the presence of V2G and wind power for decreasing of generation cost and improving operation indices of power systems.

  8. On the importance of the long-term seasonal component in day-ahead electricity price forecasting

    International Nuclear Information System (INIS)

    Nowotarski, Jakub; Weron, Rafał

    2016-01-01

    In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring – contrary to a common belief – an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves. - Highlights: • A new class of Seasonal Component AutoRegressive (SCAR) models is introduced. • Electricity prices are decomposed into a trend-seasonal and a stochastic component. • Both components are modeled independently, their forecasts are combined. • Significant accuracy gains can be achieved compared to commonly used approaches.

  9. Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2009-01-01

    With the introduction of restructuring into the electric power industry, the price of electricity has become the focus of all activities in the power market. Electricity price forecast is key information for electricity market managers and participants. However, electricity price is a complex signal due to its non-linear, non-stationary, and time variant behavior. In spite of performed research in this area, more accurate and robust price forecast methods are still required. In this paper, a new forecast strategy is proposed for day-ahead price forecasting of electricity markets. Our forecast strategy is composed of a new two stage feature selection technique and cascaded neural networks. The proposed feature selection technique comprises modified Relief algorithm for the first stage and correlation analysis for the second stage. The modified Relief algorithm selects candidate inputs with maximum relevancy with the target variable. Then among the selected candidates, the correlation analysis eliminates redundant inputs. Selected features by the two stage feature selection technique are used for the forecast engine, which is composed of 24 consecutive forecasters. Each of these 24 forecasters is a neural network allocated to predict the price of 1 h of the next day. The whole proposed forecast strategy is examined on the Spanish and Australia's National Electricity Markets Management Company (NEMMCO) and compared with some of the most recent price forecast methods.

  10. Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets

    International Nuclear Information System (INIS)

    Woo, C.K.; Moore, J.; Schneiderman, B.; Ho, T.; Olson, A.; Alagappan, L.; Chawla, K.; Toyama, N.; Zarnikau, J.

    2016-01-01

    We answer two policy questions: (1) what are the estimated merit-order effects of renewable energy in the California Independent System Operator’s (CAISO’s) day-ahead market (DAM) and real-time market (RTM)? and (2) what causes the hourly DAM and RTM prices to systematically diverge? The first question is timely and relevant because if the merit-order effect estimates are small, California’s renewable energy development is of limited help in cutting electricity consumers’ bills but also has a lesser adverse impact on the state’s investment incentive for natural-gas-fired generation. The second question is related to the efficient market hypothesis under which the hourly RTM and DAM prices tend to converge. Using a sample of about 21,000 hourly observations of CAISO market prices and their fundamental drivers during 12/12/2012–04/30/2015, we document statistically significant estimates (p-value≤0.01) for the DAM and RTM merit-order effects. This finding lends support to California’s adopted procurement process to provide sufficient investment incentives for natural-gas-fired generation. We document that the RTM-DAM price divergence partly depends on the CASIO’s day-ahead forecast errors for system loads and renewable energy. This finding suggests that improving the performance of the CAISO’s day-ahead forecasts can enhance trading efficiency in California’s DAM and RTM electricity markets. - Highlights: •Estimate the day-ahead and real-time merit-order effects of renewable energy in California. •Document statistically significant merit-order effects of solar and wind energy. •Document the difference between the day-ahead and real-time prices. •Attribute the price differences to forecast errors for load, solar and wind energy. •Discuss the evidence’s implications for California’s energy policy.

  11. Inexact stochastic risk-aversion optimal day-ahead dispatch model for electricity system management with wind power under uncertainty

    International Nuclear Information System (INIS)

    Ji, Ling; Huang, Guo-He; Huang, Lu-Cheng; Xie, Yu-Lei; Niu, Dong-Xiao

    2016-01-01

    High penetration of wind power generation and deregulated electricity market brings a great challenge to the electricity system operators. It is crucial to make optimal strategy among various generation units and spinning reserve for supporting the system safety operation. By integrating interval two-stage programming and stochastic robust programming, this paper proposes a novel robust model for day-ahead dispatch and risk-aversion management under uncertainties. In the proposed model, the uncertainties are expressed as interval values with different scenario probability. The proposed method requires low computation, and still retains the complete information. A case study is to validate the effectiveness of this approach. Facing the uncertainties of future demand and electricity price, the system operators need to make optimal dispatch strategy for thermal power units and wind turbine, and arrange proper spinning reserve and flexible demand response program to mitigate wind power forecasting error. The optimal strategies provide the system operators with better trade-off between the maximum benefits and the minimum system risk. In additional, two different market rules are compared. The results show that extra financial penalty for the wind power dispatch deviation is another efficient way to enhance the risk consciousness of decision makers and lead to more conservative strategy. - Highlights: • An inexact two-stage stochastic robust programming model for electricity system with wind power penetration. • Uncertainties expressed as discrete intervals and probability distributions. • Demand response program was introduced to adjust the deviation in real-time market. • Financial penalty for imbalance risk from wind power generation was evaluated.

  12. Two-stage stochastic day-ahead optimal resource scheduling in a distribution network with intensive use of distributed energy resources

    DEFF Research Database (Denmark)

    Sousa, Tiago; Ghazvini, Mohammad Ali Fotouhi; Morais, Hugo

    2015-01-01

    The integration of renewable sources and electric vehicles will introduce new uncertainties to the optimal resource scheduling, namely at the distribution level. These uncertainties are mainly originated by the power generated by renewables sources and by the electric vehicles charge requirements....... This paper proposes a two-state stochastic programming approach to solve the day-ahead optimal resource scheduling problem. The case study considers a 33-bus distribution network with 66 distributed generation units and 1000 electric vehicles....

  13. A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty

    DEFF Research Database (Denmark)

    Zhang, Ning; Kang, Chongqing; Xia, Qing

    2015-01-01

    The integration of wind power requires the power system to be sufficiently flexible to accommodate its forecast errors. In the market clearing process, the scheduling of flexibility relies on the manner in which the wind power uncertainty is addressed in the unit commitment (UC) model. This paper...... and are considered in both the objective functions and the constraints. The RUC model is shown to be convex and is transformed into a mixed integer linear programming (MILP) problem using relaxation and piecewise linearization. The proposed RUC model is tested using a three-bus system and an IEEE RTS79 system...... that the risk modeling facilitates a strategic market clearing procedure with a reasonable computational expense....

  14. On the effectiveness of the anti-gaming policy between the day-ahead and real-time electricity markets in The Netherlands

    Energy Technology Data Exchange (ETDEWEB)

    Boogert, A. [Essent Energy Trading (Netherlands); Dupont, D. [University of Twente (Netherlands). School of Business, Public Administration and Technology

    2005-09-01

    In the paper, we study the linkage between two related markets for electricity in The Netherlands: the day-ahead market and the real-time market. The Dutch regulator wants to prevent trading across these two markets and has set up a dual pricing system for this purpose. In this paper, we test the effectiveness of this policy by studying the ex post profitability of trading strategies spanning the two markets over various time segments. Our results show that profits generated by these strategies are rarely positive on average and always characterized by very large potential losses, which dwarf the mean profit when the latter is positive. (author)

  15. On the effectiveness of the anti-gaming policy between the day-ahead and real-time electricity markets in The Netherlands

    International Nuclear Information System (INIS)

    Boogert, A.; Dupont, D.

    2005-01-01

    In the paper, we study the linkage between two related markets for electricity in The Netherlands: the day-ahead market and the real-time market. The Dutch regulator wants to prevent trading across these two markets and has set up a dual pricing system for this purpose. In this paper, we test the effectiveness of this policy by studying the ex post profitability of trading strategies spanning the two markets over various time segments. Our results show that profits generated by these strategies are rarely positive on average and always characterized by very large potential losses, which dwarf the mean profit when the latter is positive. (author)

  16. Deriving Optimal End of Day Storage for Pumped-Storage Power Plants in the Joint Energy and Reserve Day-Ahead Scheduling

    Directory of Open Access Journals (Sweden)

    Manuel Chazarra

    2017-06-01

    Full Text Available This paper presents a new methodology to maximise the income and derive the optimal end of day storage of closed-loop and daily-cycle pumped-storage hydropower plants. The plants participate in the day-ahead energy market as a price-taker and in the secondary regulation reserve market as a price-maker, in the context of the Iberian electricity system. The real-time use of the committed reserves is considered in the model formulation. The operation of the plants with the proposed methodology is compared to the ones that use an end of day storage of an empty reservoir or half of the storage capacity. Results show that the proposed methodology increases the maximum theoretical income in all the plants analysed both if they only participate in the day-ahead energy market and if they also participate in the secondary regulation service. It is also shown that the increase in the maximum theoretical income strongly depends on the size of the plant. In addition, it is proven that the end of day storages change notably in the new reserve-driven strategies of pumped-storage hydropower plants and that the proposed methodology is even more recommended if the secondary regulation service is considered.

  17. Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

    International Nuclear Information System (INIS)

    Laia, R.; Pousinho, H.M.I.; Melíco, R.; Mendes, V.M.F.

    2015-01-01

    Highlights: • The management of thermal power plants is considered for different emission allowance levels. • The uncertainty on electricity price is considered by a set of scenarios. • A stochastic MILP approach allows devising the bidding strategies and hedging against price uncertainty and emission allowances. - Abstract: This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies

  18. Optimal day-ahead wind-thermal unit commitment considering statistical and predicted features of wind speeds

    International Nuclear Information System (INIS)

    Sun, Yanan; Dong, Jizhe; Ding, Lijuan

    2017-01-01

    Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.

  19. Investigation by CRE into record high electricity prices on Powernext Day-ahead Auction in October and November 2007. Analysis report

    International Nuclear Information System (INIS)

    2008-01-01

    In October and November 2007, electricity prices hit record highs on the Powernext Day-Ahead Auction trading platform. While, during the first nine months of the year, prices for delivery between 6 pm and 8 pm averaged euros 36 /MWh, rising to a maximum of euros 118 /MWh, they spiked at: - euros 1,236 /MWh for delivery on Monday, 29 October 2007 between 6 pm and 7 pm; - euros 2,500 /MWh for delivery on Monday, 12 November 2007 between 8 pm and 9 pm; - euros 1,762 /MWh for delivery on Thursday, 15 November 2007 between 6 pm and 7 pm. Day ahead prices of electricity have a major effect on the procurement costs of suppliers, and consequently on the formation of selling prices to end consumers. Article 28 of French Act No.2000-108 of 10 February 2000 stipulates that CRE 'shall monitor, for electricity and natural gas, all transactions made between suppliers, brokers and producers, all transactions made on the organised markets and cross-border trading. It shall ensure that bids made by suppliers, brokers and producers are consistent with their financial and technical requirements'. Article 33 of the same Act specifies that, 'In performing the tasks entrusted to it, the French Energy Regulatory Commission (CRE) may gather any information it requires from the Ministers for the Economy and for Energy, from public electricity transmission and distribution system operators, from operators of infrastructures for the natural gas transmission and distribution networks and operators of liquefied natural gas facilities, as well as from any other company involved in the electricity and natural gas market. It may also call upon any person whose evidence it deems necessary for the purposes of its investigations'. In this context, and in application of its duty to monitor the electricity wholesale markets, CRE has undertaken an investigation to analyse the mechanisms underlying the formation of such high prices. To this end, CRE gathered information relative to decisions taken by

  20. Does self-scheduling increase nurses' job satisfaction? An integrative literature review.

    Science.gov (United States)

    Koning, Clare

    2014-09-25

    Flexible work schedules give nurses the freedom and control to manage the demands of work and home, allow organisations to meet their staffing needs and can improve job satisfaction. This article reports the results of an integrative review of published peer-reviewed research and personal narratives that examined nurses' perceptions of the relationship between job satisfaction and a self-scheduling system. Results suggest that self-scheduling is one of a number of factors that influence job satisfaction, but that implementing and sustaining such a system can be challenging. The review also found that self-scheduling programmes underpin more flexible work schedules and can benefit nurses and their organisations.

  1. Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

    KAUST Repository

    Lima, Ricardo

    2015-01-01

    This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

  2. Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

    KAUST Repository

    Lima, Ricardo

    2015-01-07

    This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

  3. Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza; Anvari-Moghaddam, Amjad

    2017-01-01

    In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response...

  4. An energy credit based incentive mechanism for the direct load control of residential HVAC systems incorporation in day-ahead planning

    NARCIS (Netherlands)

    Erdinc, O.; Tascikaraoglu, A.; Paterakis, N.G.; Catalao, J.P.S.

    2017-01-01

    The increasing operational complexity of power systems considering the higher renewable energy penetration and changing load characteristics, together with the recent developments in the ICT field have led to more research and implementation efforts related to the activation of the demand side. In

  5. Experimental validation of a real time energy management system for microgrids in islanded mode using a local day-ahead electricity market and MINLP

    International Nuclear Information System (INIS)

    Marzband, Mousa; Sumper, Andreas; Domínguez-García, José Luis; Gumara-Ferret, Ramon

    2013-01-01

    Highlights: • An algorithm is developed to enhance Microgrid performance. • Local energy market cost model is proposed to obtain the cheapest price. • Several real technical and market scenarios are considered in the study. • Simulation and experimental results demonstrate a significant reduction in cost. - Abstract: Energy management systems (EMS) are vital supervisory control tools used to optimally operate and schedule Microgrids (MG). In this paper, an EMS algorithm based on mixed-integer nonlinear programming (MINLP) is presented for MG in islanding mode considering different scenarios. A local energy market (LEM) is also proposed with in this EMS to obtain the cheapest price, maximizing the utilization of distributed energy resources. The proposed energy management is based on LEM and allows scheduling the MG generation with minimum information shared sent by generation units. Load demand management is carried out by demand response concept to improve reliability and efficiency as well as to reduce the total cost of energy (COE). Simulations are performed with real data to test the performance and accuracy of the proposed algorithm. The proposed algorithm is experimentally tested to evaluate processing speed as well as to validate the results obtained from the simulation setup on a real MG Testbed. The results of the EMS–MINLP based on LEM are compared with a conventional EMS based on LEM. Simulation and experimental results show the effectiveness of the proposed algorithm which provides a reduction of 15% in COE, in comparison with conventional EMS

  6. Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

    OpenAIRE

    Dehua Zheng; Min Shi; Yifeng Wang; Abinet Tesfaye Eseye; Jianhua Zhang

    2017-01-01

    The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs) and distribution system operators (DSOs) in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs ...

  7. Day-Ahead Probabilistic Model for Scheduling the Operation of a Wind Pumped-Storage Hybrid Power Station: Overcoming Forecasting Errors to Ensure Reliability of Supply to the Grid

    Directory of Open Access Journals (Sweden)

    Jakub Jurasz

    2018-06-01

    Full Text Available Variable renewable energy sources (VRES, such as solarphotovoltaic (PV and wind turbines (WT, are starting to play a significant role in several energy systems around the globe. To overcome the problem of their non-dispatchable and stochastic nature, several approaches have been proposed so far. This paper describes a novel mathematical model for scheduling the operation of a wind-powered pumped-storage hydroelectricity (PSH hybrid for 25 to 48 h ahead. The model is based on mathematical programming and wind speed forecasts for the next 1 to 24 h, along with predicted upper reservoir occupancy for the 24th hour ahead. The results indicate that by coupling a 2-MW conventional wind turbine with a PSH of energy storing capacity equal to 54 MWh it is possible to significantly reduce the intraday energy generation coefficient of variation from 31% for pure wind turbine to 1.15% for a wind-powered PSH The scheduling errors calculated based on mean absolute percentage error (MAPE are significantly smaller for such a coupling than those seen for wind generation forecasts, at 2.39% and 27%, respectively. This is even stronger emphasized by the fact that, those for wind generation were calculated for forecasts made for the next 1 to 24 h, while those for scheduled generation were calculated for forecasts made for the next 25 to 48 h. The results clearly show that the proposed scheduling approach ensures the high reliability of the WT–PSH energy source.

  8. Powernext Day-Ahead. Powernext Futures. Activity report - 2004

    International Nuclear Information System (INIS)

    2004-01-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange market. This activity report presents the highlights of the market and of Powernext in 2004: market conditions (more reasonable and less volatile prices, steadier market conditions (climate conditions, power consumption, correlation between French and German prices), increasing liquidity, start-up of Powernext Futures TM for medium-term contracts and introduction of futures price curve, promising volumes to start, and liquidity of the futures market. (J.S)

  9. Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices

    OpenAIRE

    Raviv, Eran; Bouwman, Kees E.; van Dijk, Dick

    2013-01-01

    This discussion paper led to a publication in 'Energy Economics' , 2015, 50, 227-239. The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This paper demonstrates that the disaggregated hourly prices contain useful predictive information for the daily average ...

  10. Forecasting Day-Ahead Electricity Prices : Utilizing Hourly Prices

    NARCIS (Netherlands)

    E. Raviv (Eran); K.E. Bouwman (Kees); D.J.C. van Dijk (Dick)

    2013-01-01

    textabstractThe daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual

  11. Powernext Day-Ahead. Powernext Futures. Activity report - 2004; Powernext Day-Ahead. Powernext Futures. Bilan statistique 2004

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange market. This activity report presents the highlights of the market and of Powernext in 2004: market conditions (more reasonable and less volatile prices, steadier market conditions (climate conditions, power consumption, correlation between French and German prices), increasing liquidity, start-up of Powernext Futures{sup TM} for medium-term contracts and introduction of futures price curve, promising volumes to start, and liquidity of the futures market. (J.S)

  12. Two-Stage Optimal Scheduling of Electric Vehicle Charging based on Transactive Control

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Ma, Kang

    2018-01-01

    In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time EV charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day......-ahead energy cost and expected real-time operation cost. In the real-time charging management, the cost of employing the charging flexibility from the EV owners is explicitly modelled. The aggregator uses a transactive market to manage the real-time charging demand to provide the regulating power. A model...... predictive control (MPC) based method is proposed for the aggregator to clear the transactive market. The realtime charging decisions of the EVs are determined by the clearing of the proposed transactive market according to the realtime requests and preferences of the EV owners. As such, the aggregators...

  13. 75 FR 42380 - Orders Finding That the SP-15 Financial Day-Ahead LMP Peak Contract and SP-15 Financial Day-Ahead...

    Science.gov (United States)

    2010-07-21

    ... Exchange Act (``CEA'' or the ``Act''), perform a significant price discovery function pursuant to section 2...Exchange, Inc., Perform a Significant Price Discovery Function AGENCY: Commodity Futures Trading Commission... that the SPM and OFP contracts perform a significant price discovery function. Authority for this...

  14. Optimal energy exchange of an industrial cogeneration in a day-ahead electricity market

    International Nuclear Information System (INIS)

    Yusta, J.M.; De Oliveira-De Jesus, P.M.; Khodr, H.M.

    2008-01-01

    This paper addresses an optimal strategy for the daily energy exchange of a 22-MW combined-cycle cogeneration plant of an industrial factory operating in a liberalized electricity market. The optimization problem is formulated as a Mixed-Integer Linear Programming Problem (MILP) that maximizes the profit from energy exchange of the cogeneration, and is subject to the technical constraints and the industrial demand profile. The integer variables are associated with export or import of electricity whereas the real variables relate to the power output of gas and steam turbines, and to the electricity purchased from or sold to the market. The proposal is applied to a real cogeneration plant in Spain where the detailed cost function of the process is obtained. The problem is solved using a large-scale commercial package and the results are discussed and compared with different predefined scheduling strategies. (author)

  15. Day-ahead residential load forecasting with artificial neural network using smart meter data

    NARCIS (Netherlands)

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

    2013-01-01

    Load forecasting is an important operational procedure for the electric industry particularly in a liberalized, deregulated environment. It enables the prediction of utilization of assets, provides input for load/supply balancing and supports optimal energy utilization. Current residential load

  16. Day-ahead deregulated electricity market price forecasting using neural network input featured by DCT

    International Nuclear Information System (INIS)

    Anbazhagan, S.; Kumarappan, N.

    2014-01-01

    Highlights: • We presented DCT input featured FFNN model for forecasting in Spain market. • The key factors impacting electricity price forecasting are historical prices. • Past 42 days were trained and the next 7 days were forecasted. • The proposed approach has a simple and better NN structure. • The DCT-FFNN mode is effective and less computation time than the recent models. - Abstract: In a deregulated market, a number of factors determined the outcome of electricity price and displays a perplexed and maverick fluctuation. Both power producers and consumers needs single compact and robust price forecasting tool in order to maximize their profits and utilities. In order to achieve the helter–skelter kind of electricity price, one dimensional discrete cosine transforms (DCT) input featured feed-forward neural network (FFNN) is modeled (DCT-FFNN). The proposed FFNN is a single compact and robust architecture (without hybridizing the various hard and soft computing models). It has been predicted that the DCT-FFNN model is close to the state of the art can be achieved with less computation time. The proposed DCT-FFNN approach is compared with 17 other recent approaches to estimate the market clearing prices of mainland Spain. Finally, the accuracy of the price forecasting is also applied to the electricity market of New York in year 2010 that shows the effectiveness of the proposed DCT-FFNN approach

  17. Day-Ahead Scheduling of a Photovoltaic Plant by the Energy Management of a Storage System

    DEFF Research Database (Denmark)

    Marinelli, Mattia; Sossan, Fabrizio; Isleifsson, Fridrik Rafn

    2013-01-01

    The paper discusses and describes a system for energy management of a 10 kW PV plant coupled with a 15 kW - 190 kWh storage system. The overall idea is, by knowing the meteorological forecast for the next 24h, to dispatch the PV system and to be able to grant the scheduled hourly energy profile...... by a proper management of the storage. Due to forecast inaccuracies, the energy manager controls the storage in order to ensure that the plan for hourly energy production is respected, minimizing the storage itself usage. The experimental study is carried out in SYSLAB, a distributed power system test...

  18. Day-ahead price forecasting in restructured power systems using artificial neural networks

    International Nuclear Information System (INIS)

    Vahidinasab, V.; Jadid, S.; Kazemi, A.

    2008-01-01

    Over the past 15 years most electricity supply companies around the world have been restructured from monopoly utilities to deregulated competitive electricity markets. Market participants in the restructured electricity markets find short-term electricity price forecasting (STPF) crucial in formulating their risk management strategies. They need to know future electricity prices as their profitability depends on them. This research project classifies and compares different techniques of electricity price forecasting in the literature and selects artificial neural networks (ANN) as a suitable method for price forecasting. To perform this task, market knowledge should be used to optimize the selection of input data for an electricity price forecasting tool. Then sensitivity analysis is used in this research to aid in the selection of the optimum inputs of the ANN and fuzzy c-mean (FCM) algorithm is used for daily load pattern clustering. Finally, ANN with a modified Levenberg-Marquardt (LM) learning algorithm are implemented for forecasting prices in Pennsylvania-New Jersey-Maryland (PJM) market. The forecasting results were compared with the previous works and showed that the results are reasonable and accurate. (author)

  19. Optimal Day-Ahead Scheduling of a Hybrid Electric Grid Using Weather Forecasts

    Science.gov (United States)

    2013-12-01

    with 214 turbines [22]. In July 2011, the DoD declared that a complete study of 217 wind farm projects proposed in 35 states and Puerto Rico found...14. SUBJECT TERMS Hybrid electric grid , Microgrid , Hybrid renewable energy system , energy management center, optimization, Day...electric grid. In the case of a hybrid electric grid (HEG), or hybrid renewable energy system (HRES) where the microgrid can be connected to the commercial

  20. A New Quantile Regression Model to forecast one-day-ahead Value-at-Risk

    OpenAIRE

    Steine, Sturla Aavik; Eliassen, Markus Thorsø

    2014-01-01

    This master thesis focuses on the problem of forecasting volatility and Value-at-Risk (VaR) in the nancial markets. There are numerous methods for calculating VaR. However, research in this area has not currently reached one universally accepted method that can produce good VaR estimates across dierent data series, and VaR prediction and quality testing is still a very challenging statistical problem. The thesis has two main purposes, the rst is to propose a simple quantile regression mod...

  1. New approach to bidding strategies of generating companies in day ahead energy market

    International Nuclear Information System (INIS)

    Soleymani, S.; Ranjbar, A.M.; Shirani, A.R.

    2008-01-01

    In the restructured power systems, generating companies (Genco) are responsible for selling their product in the energy market. In this condition, the question is how much and for what price must each Genco generate to maximize its profit. Therefore, this paper intends to propose a rational method to answer this question. In the proposed methodology, the hourly forecasted market clearing price (FMCP) is used as a reference to model the possible and probable price strategies of Gencos. The forecasted price is the basis of the bidding strategies of each Genco, which can be achieved by solving a bi-level optimization problem using GAMS (general algebraic modeling system) language. The first level, called upper sub-problem is used to maximize the individual Genco's payoffs for obtaining the optimal offered quantity of Gencos. The second one, hereafter called the lower sub-problem uses the results of the upper sub-problem and minimizes the consumer's payment with regard to the technical and network constraints, which leads to the awarded generation of the Gencos. Similar to the other game problems, the Nash equilibrium strategies are the optimum bidding strategies of Gencos. A six bus system is employed to illustrate the application of the proposed method and to show its high precision and capabilities. (author)

  2. Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    In a competitive electricity market, forecast of energy prices is a key information for the market participants. However, price signal usually has a complex behavior due to its nonlinearity, nonstationarity, and time variancy. In spite of all performed researches on this area in the recent years, there is still an essential need for more accurate and robust price forecast methods. In this paper, a combination of wavelet transform (WT) and a hybrid forecast method is proposed for this purpose. The hybrid method is composed of cascaded forecasters where each forecaster consists of a neural network (NN) and an evolutionary algorithms (EA). Both time domain and wavelet domain features are considered in a mixed data model for price forecast, in which the candidate input variables are refined by a feature selection technique. The adjustable parameters of the whole method are fine-tuned by a cross-validation technique. The proposed method is examined on PJM electricity market and compared with some of the most recent price forecast methods. (author)

  3. Forecasting short-term power prices in the Ontario Electricity Market (OEM) with a fuzzy logic based inference system

    International Nuclear Information System (INIS)

    Arciniegas, Alvaro I.; Arciniegas Rueda, Ismael E.

    2008-01-01

    The Ontario Electricity Market (OEM), which opened in May 2002, is relatively new and is still under change. In addition, the bidding strategies of the participants are such that the relationships between price and fundamentals are non-linear and dynamic. The lack of market maturity and high complexity hinders the use of traditional statistical methodologies (e.g., regression analysis) for price forecasting. Therefore, a flexible model is needed to achieve good forecasting in OEM. This paper uses a Takagi-Sugeno-Kang (TSK) fuzzy inference system in forecasting the one-day-ahead real-time peak price of the OEM. The forecasting results of TSK are compared with those obtained by traditional statistical and neural network based forecasting. The comparison suggests that TSK has considerable value in forecasting one-day-ahead peak price in OEM. (author)

  4. Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency- based pricing

    International Nuclear Information System (INIS)

    Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad

    2015-01-01

    Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

  5. Exploiting Flexibility in Coupled Electricity and Natural Gas Markets: A Price-Based Approach

    DEFF Research Database (Denmark)

    Ordoudis, Christos; Delikaraoglou, Stefanos; Pinson, Pierre

    2017-01-01

    Natural gas-fired power plants (NGFPPs) are considered a highly flexible component of the energy system and can facilitate the large-scale integration of intermittent renewable generation. Therefore, it is necessary to improve the coordination between electric power and natural gas systems....... Considering a market-based coupling of these systems, we introduce a decision support tool that increases market efficiency in the current setup where day-ahead and balancing markets are cleared sequentially. The proposed approach relies on the optimal adjustment of natural gas price to modify the scheduling...

  6. Day-Ahead Coordination of Vehicle-to-Grid Operation and Wind Power in Security Constraints Unit Commitment (SCUC)

    OpenAIRE

    Mohammad Javad Abdollahi; Majid Moazzami

    2015-01-01

    In this paper security constraints unit commitment (SCUC) in the presence of wind power resources and electrical vehicles to grid is presented. SCUC operation prepare an optimal time table for generation unit commitment in order to maximize security, minimize operation cost and satisfy the constraints of networks and units in a period of time, as one of the most important research interest in power systems. Today, the relationship between power network and energy storage systems is interested...

  7. Offering strategy of a price-maker energy storage system in day-ahead and balancing markets

    DEFF Research Database (Denmark)

    Vespermann, Niklas Peter René Erich; Delikaraoglou, Stefanos; Pinson, Pierre

    2017-01-01

    . The offering strategy of a price-maker ESS operator is formulated as a bilevel model, where the upper-level problem represents the profit maximization of the ESS operator and the lower-level problem simulates the market-clearing outcome. This methodological framework can be used either to assess market...... efficiency distortion or as a trading strategy from the perspective of the ESS operator. Our analysis shows that adopting strategic behavior may improve ESS expected profit but reduces social welfare, especially for high ESS energy-to-power ratios....

  8. Price-Maker Wind Power Producer Participating in a Joint Day-Ahead and Real-Time Market

    DEFF Research Database (Denmark)

    Delikaraoglou, Stefanos; Papakonstantinou, Athanasios; Ordoudis, Christos

    2015-01-01

    The large scale integration of stochastic renewable energy introduces significant challenges for power system operators and disputes the efficiency of the current market design. Recent research embeds the uncertain nature of renewable sources by modelling electricity markets as a two...... Constraints (MPEC) that is reformulated as a single-level Mixed-Integer Linear Program (MILP), which can be readily solved. Our analysis shows that adopting strategic behaviour may improve producer’s expected profit as the share of wind power increases. However, this incentive diminishes in power systems...... where available flexible capacity is high enough to ensure an efficient market operation....

  9. An improved charging/discharging strategy of lithium batteries considering depreciation cost in day-ahead microgrid scheduling

    International Nuclear Information System (INIS)

    Zhang, Zhong; Wang, Jianxue; Wang, Xiuli

    2015-01-01

    Highlights: • A quantitative depreciation cost model is put forward for lithium batteries. • A practical charging/discharging strategy is applied to battery management. • The depth of discharge of the battery storage is scheduled more rationally. • The proposed strategy improves the cost efficiency of lithium batteries in MGs. - Abstract: An energy storage system is critical for the safe and stable operation of a microgrid (MG) and has a promising prospect in future power system. Economical and safe operation of storage system is of great significance to MGs. This paper presents an improved management strategy for lithium battery storage by establishing a battery depreciation cost model and employing a practical charging/discharging strategy. Firstly, experimental data of lithium battery cycle lives, which are functions of the depth of discharge, are investigated and synthesized. A quantitative depreciation cost model is put forward for lithium batteries from the perspective of cycle life. Secondly, a practical charging/discharging strategy is applied to the lithium battery management in MGs. Then, an optimal scheduling model is developed to minimize MG operational cost including battery depreciation cost. Finally, numerical tests are conducted on a typical grid-connected MG. Results show that the depth of discharge of storage is scheduled more rationally, and operational cost is simultaneously saved for MG under the proposed management strategy. This study helps to improve the cost efficiency and alleviate the aging process for lithium batteries.

  10. End-user comfort oriented day-ahead planning for responsive residential HVAC demand aggregation considering weather forecasts

    NARCIS (Netherlands)

    Erdinç, O.; Taşcikaraogυlu, A.; Paterakis, N.G.; Eren, Y.; Catalão, J.P.S.

    2017-01-01

    There is a remarkable potential for implementing demand response (DR) strategies for several purposes, such as peak load reduction, frequency regulation, etc., by using thermostatically controllable appliances. In this paper, an end-user comfort violation minimization oriented DR strategy for

  11. Distinguishing high and low flow domains in urban drainage systems 2 days ahead using numerical weather prediction ensembles

    Science.gov (United States)

    Courdent, Vianney; Grum, Morten; Mikkelsen, Peter Steen

    2018-01-01

    Precipitation constitutes a major contribution to the flow in urban storm- and wastewater systems. Forecasts of the anticipated runoff flows, created from radar extrapolation and/or numerical weather predictions, can potentially be used to optimize operation in both wet and dry weather periods. However, flow forecasts are inevitably uncertain and their use will ultimately require a trade-off between the value of knowing what will happen in the future and the probability and consequence of being wrong. In this study we examine how ensemble forecasts from the HIRLAM-DMI-S05 numerical weather prediction (NWP) model subject to three different ensemble post-processing approaches can be used to forecast flow exceedance in a combined sewer for a wide range of ratios between the probability of detection (POD) and the probability of false detection (POFD). We use a hydrological rainfall-runoff model to transform the forecasted rainfall into forecasted flow series and evaluate three different approaches to establishing the relative operating characteristics (ROC) diagram of the forecast, which is a plot of POD against POFD for each fraction of concordant ensemble members and can be used to select the weight of evidence that matches the desired trade-off between POD and POFD. In the first approach, the rainfall input to the model is calculated for each of 25 ensemble members as a weighted average of rainfall from the NWP cells over the catchment where the weights are proportional to the areal intersection between the catchment and the NWP cells. In the second approach, a total of 2825 flow ensembles are generated using rainfall input from the neighbouring NWP cells up to approximately 6 cells in all directions from the catchment. In the third approach, the first approach is extended spatially by successively increasing the area covered and for each spatial increase and each time step selecting only the cell with the highest intensity resulting in a total of 175 ensemble members. While the first and second approaches have the disadvantage of not covering the full range of the ROC diagram and being computationally heavy, respectively, the third approach leads to both a broad coverage of the ROC diagram range at a relatively low computational cost. A broad coverage of the ROC diagram offers a larger selection of prediction skill to choose from to best match to the prediction purpose. The study distinguishes itself from earlier research in being the first application to urban hydrology, with fast runoff and small catchments that are highly sensitive to local extremes. Furthermore, no earlier reference has been found on the highly efficient third approach using only neighbouring cells with the highest threat to expand the range of the ROC diagram. This study provides an efficient and robust approach to using ensemble rainfall forecasts affected by bias and misplacement errors for predicting flow threshold exceedance in urban drainage systems.

  12. Distinguishing high and low flow domains in urban drainage systems 2 days ahead using numerical weather prediction ensembles

    DEFF Research Database (Denmark)

    Courdent, Vianney Augustin Thomas; Grum, Morten; Mikkelsen, Peter Steen

    2018-01-01

    Precipitation constitutes a major contribution to the flow in urban storm- and wastewater systems. Forecasts of the anticipated runoff flows, created from radar extrapolation and/or numerical weather predictions, can potentially be used to optimize operation in both wet and dry weather periods...... to transform the forecasted rainfall into forecasted flow series and evaluate three different approaches to establishing the relative operating characteristics (ROC) diagram of the forecast, which is a plot of POD against POFD for each fraction of concordant ensemble members and can be used to select...... itself from earlier research in being the first application to urban hydrology, with fast runoff and small catchments that are highly sensitive to local extremes. Furthermore, no earlier reference has been found on the highly efficient third approach using only neighbouring cells with the highest threat...

  13. Availability Based Tariff and its impact On different Industry Players-A Review

    Science.gov (United States)

    Holmukhe, R. M.; Pawar, Yogini; Desai, R. S.; Hasarmani, T. S.

    2010-10-01

    ABT is a performance-based tariff for the supply of electricity by generators owned and controlled by the central government. It is also a new system of scheduling and dispatch, which requires both generators and beneficiaries to commit to day-ahead schedules. It is a system of rewards and penalties seeking to enforce day ahead pre-committed schedules, though variations are permitted if notified One and one half hours in advance. The order emphasizes prompt payment of dues. ABT (Availability Based Tariff) along with the Electricity Act of 2003 is perhaps the most significant and definitive step taken in the Indian power sector so far to bring more efficiency and focus to this vital infrastructure. The ABT mechanism is based on financial principles. ABT scheme is for unscheduled interchange of power. The paper reviews ABT issues, its components, clauses, mechanism, benefits and the impact of grid on different players like generation utilities, grid operator, consumers involved in power generation, transmission and distribution. While the proposed tariff structure has wide implications for each player, this deals exclusively with the technology challenges/opportunities thrown up by ABT.

  14. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    Directory of Open Access Journals (Sweden)

    Fanrong Kong

    2017-09-01

    Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.

  15. Transactive-Market-Based Operation of Distributed Electrical Energy Storage with Grid Constraints

    Directory of Open Access Journals (Sweden)

    M. Nazif Faqiry

    2017-11-01

    Full Text Available In a transactive energy market, distributed energy resources (DERs such as dispatchable distributed generators (DGs, electrical energy storages (EESs, distribution-scale load aggregators (LAs, and renewable energy sources (RESs have to earn their share of supply or demand through a bidding process. In such a market, the distribution system operator (DSO may optimally schedule these resources, first in a forward market, i.e., day-ahead, and in a real-time market later on, while maintaining a reliable and economic distribution grid. In this paper, an efficient day-ahead scheduling of these resources, in the presence of interaction with wholesale market at the locational marginal price (LMP, is studied. Due to inclusion of EES units with integer constraints, a detailed mixed integer linear programming (MILP formulation that incorporates simplified DistFlow equations to account for grid constraints is proposed. Convex quadratic line and transformer apparent power flow constraints have been linearized using an outer approximation. The proposed model schedules DERs based on distribution locational marginal price (DLMP, which is obtained as the Lagrange multiplier of the real power balance constraint at each distribution bus while maintaining physical grid constraints such as line limits, transformer limits, and bus voltage magnitudes. Case studies are performed on a modified IEEE 13-bus system with high DER penetration. Simulation results show the validity and efficiency of the proposed model.

  16. Pay-as-bid based reactive power market

    International Nuclear Information System (INIS)

    Amjady, N.; Rabiee, A.; Shayanfar, H.A.

    2010-01-01

    In energy market clearing, the offers are stacked in increasing order and the offer that intersects demand curve, determines the market clearing price (MCP). In reactive power market, the location of reactive power compensator is so important. A low cost reactive producer may not essentially be favorable if it is far from the consumer. Likewise, a high cost local reactive compensator at a heavily loaded demand center of network could be inevitably an alternative required to produce reactive power to maintain the integrity of power system. Given the background, this paper presents a day-ahead reactive power market based on pay-as-bid (PAB) mechanism. Generators expected payment function (EPF) is used to construct a bidding framework. Then, total payment function (TPF) of generators is used as the objective function of optimal power flow (OPF) problem to clear the PAB based market. The CIGRE-32 bus test system is used to examine the effectiveness of the proposed reactive power market.

  17. Pay-as-bid based reactive power market

    Energy Technology Data Exchange (ETDEWEB)

    Amjady, N. [Department of Electrical Engineering, Semnan University, Semnan (Iran, Islamic Republic of); Rabiee, A., E-mail: Rabiee@iust.ac.i [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2010-02-15

    In energy market clearing, the offers are stacked in increasing order and the offer that intersects demand curve, determines the market clearing price (MCP). In reactive power market, the location of reactive power compensator is so important. A low cost reactive producer may not essentially be favorable if it is far from the consumer. Likewise, a high cost local reactive compensator at a heavily loaded demand center of network could be inevitably an alternative required to produce reactive power to maintain the integrity of power system. Given the background, this paper presents a day-ahead reactive power market based on pay-as-bid (PAB) mechanism. Generators expected payment function (EPF) is used to construct a bidding framework. Then, total payment function (TPF) of generators is used as the objective function of optimal power flow (OPF) problem to clear the PAB based market. The CIGRE-32 bus test system is used to examine the effectiveness of the proposed reactive power market.

  18. Simulation-based Strategies for Smart Demand Response

    Directory of Open Access Journals (Sweden)

    Ines Leobner

    2018-03-01

    Full Text Available Demand Response can be seen as one effective way to harmonize demand and supply in order to achieve high self-coverage of energy consumption by means of renewable energy sources. This paper presents two different simulation-based concepts to integrate demand-response strategies into energy management systems in the customer domain of the Smart Grid. The first approach is a Model Predictive Control of the heating and cooling system of a low-energy office building. The second concept aims at industrial Demand Side Management by integrating energy use optimization into industrial automation systems. Both approaches are targeted at day-ahead planning. Furthermore, insights gained into the implications of the concepts onto the design of the model, simulation and optimization will be discussed. While both approaches share a similar architecture, different modelling and simulation approaches were required by the use cases.

  19. Machine learning based switching model for electricity load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Shu; Lee, Wei-Jen [Energy Systems Research Center, The University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen, Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan)

    2008-06-15

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma. (author)

  20. Machine learning based switching model for electricity load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Fan Shu [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan); Lee, Weijen [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States)], E-mail: wlee@uta.edu

    2008-06-15

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma.

  1. Machine learning based switching model for electricity load forecasting

    International Nuclear Information System (INIS)

    Fan Shu; Chen Luonan; Lee, Weijen

    2008-01-01

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma

  2. Robust optimization-based DC optimal power flow for managing wind generation uncertainty

    Science.gov (United States)

    Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn

    2012-11-01

    Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.

  3. Mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets

    International Nuclear Information System (INIS)

    Canizes, Bruno; Soares, João; Faria, Pedro; Vale, Zita

    2013-01-01

    Highlights: • Ancillary services market management. • Ancillary services requirements forecast based on Artificial Neural Network. • Ancillary services clearing mechanisms without complex bids and with complex bids. - Abstract: Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids

  4. Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

    Science.gov (United States)

    Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

    2017-11-01

    This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

  5. 75 FR 42411 - Orders Finding That the SP-15 Financial Day-Ahead LMP Peak Daily Contract; SP-15 Financial Day...

    Science.gov (United States)

    2010-07-21

    ...''), an exempt commercial market (``ECM'') under sections 2(h)(3)-(5) of the Commodity Exchange Act (``CEA'' or the ``Act''), perform a significant price discovery function pursuant to section 2(h)(7) of the... Perform a Significant Price Discovery Function AGENCY: Commodity Futures Trading Commission. ACTION: Final...

  6. Proceedings of the Canadian Solar Industries Association Solar Forum 2005 : sunny days ahead : a forum on solar energy for government officials

    International Nuclear Information System (INIS)

    2006-01-01

    Solar energy is the fastest growing energy source in the world. Government involvement is critical in the deployment of solar energy. This forum focused on the application of solar energy in government facilities. The forum was divided into 3 sessions: (1) solar technologies and markets; (2) government initiatives that support solar energy; and (3) the use of solar energy on government facilities in Canada. The current state of solar technologies and products in Canada was reviewed. Solar thermal markets were discussed with reference to passive solar energy and photovoltaic applications. On-site solar generation for federal facilities was discussed, and various federal initiatives were reviewed. Issues concerning Ontario's standard offer contract program were discussed. Government users and buyers of solar products spoke of their experiences in using solar energy and the challenges that were faced. The role that solar energy can play in reducing government costs was discussed, as well as the impact of solar energy on the environment. Opportunities and barriers to the use of solar energy in Canada were explored. The conference featured 14 presentations, of which 2 have been catalogued separately for inclusion in this database. refs., tabs., figs

  7. Investigation of arbitrage between the Dutch day-ahead and imbalance markets as a business case for the hydrogen bromine flow battery

    NARCIS (Netherlands)

    Paterakis, N.G.; Gibescu, M.; Kout, W.; Hugo, Y.A.

    2017-01-01

    The role of energy storage as a means to support power systems in the light of increasing penetration of renewable energy sources is already recognized. A large number of scientific studies highlight the potential benefits, while transmission and distribution system operators actively engage in

  8. Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

    International Nuclear Information System (INIS)

    Samimi, Abouzar; Kazemi, Ahad; Siano, Pierluigi

    2015-01-01

    Highlights: • A new market-based approach is proposed to schedule active and reactive powers. • Multi-component reactive power bidding structures for DERs is introduced. • A new economical/environmental operational scheduling method is proposed. • At distribution level, a reactive power market is developed in presence of DERs. - Abstract: Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energy-balance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO_2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The

  9. Autonomous power networks based power system

    International Nuclear Information System (INIS)

    Jokic, A.; Van den Bosch, P.P.J.

    2006-01-01

    This paper presented the concept of autonomous networks to cope with this increased complexity in power systems while enhancing market-based operation. The operation of future power systems will be more challenging and demanding than present systems because of increased uncertainties, less inertia in the system, replacement of centralized coordinating activities by decentralized parties and the reliance on dynamic markets for both power balancing and system reliability. An autonomous network includes the aggregation of networked producers and consumers in a relatively small area with respect to the overall system. The operation of an autonomous network is coordinated and controlled with one central unit acting as an interface between internal producers/consumers and the rest of the power system. In this study, the power balance problem and system reliability through provision of ancillary services was formulated as an optimization problem for the overall autonomous networks based power system. This paper described the simulation of an optimal autonomous network dispatching in day ahead markets, based on predicted spot prices for real power, and two ancillary services. It was concluded that large changes occur in a power systems structure and operation, most of them adding to the uncertainty and complexity of the system. The introduced concept of an autonomous power network-based power system was shown to be a realistic and consistent approach to formulate and operate a market-based dispatch of both power and ancillary services. 9 refs., 4 figs

  10. A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System

    Directory of Open Access Journals (Sweden)

    Yan Bao

    2018-01-01

    Full Text Available Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators.

  11. Residential Consumption Scheduling Based on Dynamic User Profiling

    Science.gov (United States)

    Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

    Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

  12. Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

    Science.gov (United States)

    Prada, Jose Fernando

    Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm

  13. Virtual power plant mid-term dispatch optimization

    International Nuclear Information System (INIS)

    Pandžić, Hrvoje; Kuzle, Igor; Capuder, Tomislav

    2013-01-01

    Highlights: ► Mid-term virtual power plant dispatching. ► Linear modeling. ► Mixed-integer linear programming applied to mid-term dispatch scheduling. ► Operation profit maximization combining bilateral contracts and the day-ahead market. -- Abstract: Wind power plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind power plants and other non-dispatchable power sources are combined with dispatchable power sources forming a virtual power plant. This paper considers a weekly self-scheduling of a virtual power plant composed of intermittent renewable sources, storage system and a conventional power plant. On the one hand, the virtual power plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly virtual power plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind power and solar power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional power plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.

  14. Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System

    Directory of Open Access Journals (Sweden)

    Bo Lin

    2017-10-01

    Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.

  15. Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2017-10-01

    Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

  16. GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting

    Directory of Open Access Journals (Sweden)

    Lintao Yang

    2018-01-01

    Full Text Available With the development of smart power grids, communication network technology and sensor technology, there has been an exponential growth in complex electricity load data. Irregular electricity load fluctuations caused by the weather and holiday factors disrupt the daily operation of the power companies. To deal with these challenges, this paper investigates a day-ahead electricity peak load interval forecasting problem. It transforms the conventional continuous forecasting problem into a novel interval forecasting problem, and then further converts the interval forecasting problem into the classification forecasting problem. In addition, an indicator system influencing the electricity load is established from three dimensions, namely the load series, calendar data, and weather data. A semi-supervised feature selection algorithm is proposed to address an electricity load classification forecasting issue based on the group method of data handling (GMDH technology. The proposed algorithm consists of three main stages: (1 training the basic classifier; (2 selectively marking the most suitable samples from the unclassified label data, and adding them to an initial training set; and (3 training the classification models on the final training set and classifying the test samples. An empirical analysis of electricity load dataset from four Chinese cities is conducted. Results show that the proposed model can address the electricity load classification forecasting problem more efficiently and effectively than the FW-Semi FS (forward semi-supervised feature selection and GMDH-U (GMDH-based semi-supervised feature selection for customer classification models.

  17. Mutual Information-Based Inputs Selection for Electric Load Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Nenad Floranović

    2013-02-01

    Full Text Available Providing accurate load forecast to electric utility corporations is essential in order to reduce their operational costs and increase profits. Hence, training set selection is an important preprocessing step which has to be considered in practice in order to increase the accuracy of load forecasts. The usage of mutual information (MI has been recently proposed in regression tasks, mostly for feature selection and for identifying the real instances from training sets that contains noise and outliers. This paper proposes a methodology for the training set selection in a least squares support vector machines (LS-SVMs load forecasting model. A new application of the concept of MI is presented for the selection of a training set based on MI computation between initial training set instances and testing set instances. Accordingly, several LS-SVMs models have been trained, based on the proposed methodology, for hourly prediction of electric load for one day ahead. The results obtained from a real-world data set indicate that the proposed method increases the accuracy of load forecasting as well as reduces the size of the initial training set needed for model training.

  18. Frequency Based Real-time Pricing for Residential Prosumers

    Science.gov (United States)

    Hambridge, Sarah Mabel

    stability in a free, competitive, market. Frequency based pricing is applied to secondary frequency control in this work, providing support at one to five minute time intervals. In Chapter 2, a frequency based pricing curve is designed as a preliminary study and the response of the prosumer is optimized for economic dispatch. In Chapter 3, a day-ahead schedule and real-time adjustment energy management framework is presented for the prosumer, creating a market structure similar to the existing energy market supervised by Independent System Operators (ISOs). Enabling technology, such as the solid state transformer (SST) is described for prosumer energy transactions, controlling power flow from the prosumer's energy cell to the grid or neighboring prosumer as an energy router. Experimental results are shown to demonstrate this capability. Additionally, the SST is capable of measuring the grid frequency. Lastly, a frequency based real-time hybrid electricity rate is presented in Chapter 4 and Chapter 5. Chapter 4 specializes in a single direction rate while Chapter 5 presents a bi-directional rate. A Time-of-use (TOU) rate is combined with the real-time frequency based price to lower energy bills for a residential prosumer with ESS, in agreement with the proposed day-ahead and real-time energy management framework. The cost to the ESS is also considered in this section. Linear programming and strategic rule based methods are utilized to find the lowest energy bill. As a result, prosumers can use ESS to balance the grid, reducing their bill as much per kWh as PV or DG under a TOU net-metering price scheme, while providing distributed frequency support to the grid authority. The variability of the frequency based rate is similar to variability in the stock market, which gives a sense of how prosumers will interact with variable prices in a system supported by The Energy Internet.

  19. A Game Theoretical Approach Based Bidding Strategy Optimization for Power Producers in Power Markets with Renewable Electricity

    Directory of Open Access Journals (Sweden)

    Yi Tang

    2017-05-01

    Full Text Available In a competitive electricity market with substantial involvement of renewable electricity, maximizing profits by optimizing bidding strategies is crucial to different power producers including conventional power plants and renewable ones. This paper proposes a game-theoretic bidding optimization method based on bi-level programming, where power producers are at the upper level and utility companies are at the lower level. The competition among the multiple power producers is formulated as a non-cooperative game in which bidding curves are their strategies, while uniform clearing pricing is considered for utility companies represented by an independent system operator. Consequently, based on the formulated game model, the bidding strategies for power producers are optimized for the day-ahead market and the intraday market with considering the properties of renewable energy; and the clearing pricing for the utility companies, with respect to the power quantity from different power producers, is optimized simultaneously. Furthermore, a distributed algorithm is provided to search the solution of the generalized Nash equilibrium. Finally, simulation results were performed and discussed to verify the feasibility and effectiveness of the proposed non-cooperative game-based bi-level optimization approach.

  20. Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis

    Science.gov (United States)

    Rzepecka, Zofia; Kalita, Jakub

    2016-04-01

    It is well known that the dry part of the zenith tropospheric delay (ZTD) is much easier to model than the wet part (ZTW). The aim of the research is applying stochastic modeling and prediction of ZTW using time series analysis tools. Application of time series analysis enables closer understanding of ZTW behavior as well as short-term prediction of future ZTW values. The ZTW data used for the studies were obtained from the GGOS service hold by Vienna technical University. The resolution of the data is six hours. ZTW for the years 2010 -2013 were adopted for the study. The International GNSS Service (IGS) permanent stations LAMA and GOPE, located in mid-latitudes, were admitted for the investigations. Initially the seasonal part was separated and modeled using periodic signals and frequency analysis. The prominent annual and semi-annual signals were removed using sines and consines functions. The autocorrelation of the resulting signal is significant for several days (20-30 samples). The residuals of this fitting were further analyzed and modeled with ARIMA processes. For both the stations optimal ARMA processes based on several criterions were obtained. On this basis predicted ZTW values were computed for one day ahead, leaving the white process residuals. Accuracy of the prediction can be estimated at about 3 cm.

  1. Cognitive Self-Scheduled Mechanism for Access Control in Noisy Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Mario Manzano

    2015-01-01

    Full Text Available Within the challenging environment of intelligent transportation systems (ITS, networked control systems such as platooning guidance of autonomous vehicles require innovative mechanisms to provide real-time communications. Although several proposals are currently under discussion, the design of a rapid, efficient, flexible, and reliable medium access control mechanism which meets the specific constraints of such real-time communications applications remains unsolved in this highly dynamic environment. However, cognitive radio (CR combines the capacity to sense the radio spectrum with the flexibility to adapt to transmission parameters in order to maximize system performance and has thus become an effective approach for the design of dynamic spectrum access (DSA mechanisms. This paper presents the enhanced noncooperative cognitive division multiple access (ENCCMA proposal combining time division multiple access (TDMA and frequency division multiple access (FDMA schemes with CR techniques to obtain a mechanism fulfilling the requirements of real-time communications. The analysis presented here considers the IEEE WAVE and 802.11p as reference standards; however, the proposed medium access control (MAC mechanism can be adapted to operate on the physical layer of different standards. The mechanism also offers the advantage of avoiding signaling, thus enhancing system autonomy as well as behavior in adverse scenarios.

  2. Coordinated Volt/Var Control in Distribution Systems with Distributed Generations Based on Joint Active and Reactive Powers Dispatch

    Directory of Open Access Journals (Sweden)

    Abouzar Samimi

    2016-01-01

    Full Text Available One of the most significant control schemes in optimal operation of distribution networks is Volt/Var control (VVC. Owing to the radial structure of distribution systems and distribution lines with a small X/R ratio, the active power scheduling affects the VVC issue. A Distribution System Operator (DSO procures its active and reactive power requirements from Distributed Generations (DGs along with the wholesale electricity market. This paper proposes a new operational scheduling method based on a joint day-ahead active/reactive power market at the distribution level. To this end, based on the capability curve, a generic reactive power cost model for DGs is developed. The joint active/reactive power dispatch model presented in this paper motivates DGs to actively participate not only in the energy markets, but also in the VVC scheme through a competitive market. The proposed method which will be performed in an offline manner aims to optimally determine (i the scheduled active and reactive power values of generation units; (ii reactive power values of switched capacitor banks; and (iii tap positions of transformers for the next day. The joint active/reactive power dispatch model for daily VVC is modeled in GAMS and solved with the DICOPT solver. Finally, the plausibility of the proposed scheduling framework is examined on a typical 22-bus distribution test network over a 24-h period.

  3. Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

    2017-11-01

    A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

  4. Sharing wind power forecasts in electricity markets: A numerical analysis

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Pinson, Pierre; Kazempour, Jalal

    2016-01-01

    In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day......-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding...... flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making...

  5. Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines

    International Nuclear Information System (INIS)

    Li, Yanting; He, Yong; Su, Yan; Shu, Lianjie

    2016-01-01

    Highlights: • Suggests a nonparametric model based on MARS for output power prediction. • Compare the MARS model with a wide variety of prediction models. • Show that the MARS model is able to provide an overall good performance in both the training and testing stages. - Abstract: Both linear and nonlinear models have been proposed for forecasting the power output of photovoltaic systems. Linear models are simple to implement but less flexible. Due to the stochastic nature of the power output of PV systems, nonlinear models tend to provide better forecast than linear models. Motivated by this, this paper suggests a fairly simple nonlinear regression model known as multivariate adaptive regression splines (MARS), as an alternative to forecasting of solar power output. The MARS model is a data-driven modeling approach without any assumption about the relationship between the power output and predictors. It maintains simplicity of the classical multiple linear regression (MLR) model while possessing the capability of handling nonlinearity. It is simpler in format than other nonlinear models such as ANN, k-nearest neighbors (KNN), classification and regression tree (CART), and support vector machine (SVM). The MARS model was applied on the daily output of a grid-connected 2.1 kW PV system to provide the 1-day-ahead mean daily forecast of the power output. The comparisons with a wide variety of forecast models show that the MARS model is able to provide reliable forecast performance.

  6. Optimal trading strategy for GenCo in LMP-based and bilateral ...

    African Journals Online (AJOL)

    GenCo) in multi-market environment including day-ahead spot and long term bilateral contract markets using self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC). The proposed trading ...

  7. Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming

    DEFF Research Database (Denmark)

    Shuai, Hang; Fang, Jiakun; Ai, Xiaomeng

    2018-01-01

    slope updating strategy is employed for the proposed method. With sufficient information extracted from these scenarios and embedded in the PLF function, the proposed ADPED algorithm can not only be used in day-ahead scheduling but also the intra-day optimization process. The algorithm can make full use......-ahead and intra-day operation under uncertainty....

  8. Market based solutions for increased flexibility in electricity consumption

    International Nuclear Information System (INIS)

    Grande, Ove S.; Saele, Hanne

    2005-06-01

    The main focus of this paper is on manual and automatic demand response to prices in the day ahead market. The content is mainly based on the results and experiences from the large scale Norwegian test and research project End User flexibility by efficient use of ICT (2001-2004) involving 10,894 customers with automatic meter reading (AMR) and remote load control (RLC) options. The response to hourly spot price products and intraday time of use (ToU) tariffs were tested. The registered response differs from 0.18-1 kWh/h in average per household customer for the different combination of these price signals. The largest response was achieved for the customers with both the ToU network tariff and hourly spot price. Some of the customers were offered remote controlled automatic disconnection of water heaters in the high price periods during week days. The test shows that the potential of load reduction from water heaters can be estimated to 0.6 kWh/h in the peak hours on average. For Norway this indicates that a total of 600 MWh/h automatic price elasticity could be achieved, provided that half of the 2 million Norwegian households accept RLC of their water heater referred to spot price. The benefit for load shifting is limited for each customer, but of great value for the power system as a whole. Combination of an hourly spot price contract with an intraday ToU network tariff should therefore be considered, in order to provide stable economic incentives for load reduction. One potential drawback for customers with spot price energy contracts is the risk of high electricity prices in periods of lasting scarcity. Combination with financial power contracts as an insurance for the customer is an option that will be examined in a follow up project

  9. A dynamic optimization-based architecture for polygeneration microgrids with tri-generation, renewables, storage systems and electrical vehicles

    International Nuclear Information System (INIS)

    Bracco, Stefano; Delfino, Federico; Pampararo, Fabio; Robba, Michela; Rossi, Mansueto

    2015-01-01

    Highlights: • We describe two national special projects on smart grid. • We developed dynamic decision model based on a MPC architecture. • We developed an optimization model for microgrids, for a specific case study. - Abstract: An overall architecture, or Energy Management System (EMS), based on a dynamic optimization model to minimize operating costs and CO 2 emissions is formalized and applied to the University of Genova Savona Campus test-bed facilities consisting of a Smart Polygeneration Microgrid (SPM) and a Sustainable Energy Building (SEB) connected to such microgrid. The electric grid is a three phase low voltage distribution system, connecting many different technologies: three cogeneration micro gas turbines fed by natural gas, a photovoltaic field, three cogeneration Concentrating Solar Powered (CSP) systems (equipped with Stirling engines), an absorption chiller equipped with a storage tank, two types of electrical storage based on batteries technology (long term Na–Ni and short term Li-Ion ion), two electric vehicles charging stations, other electrical devices (inverters and smart metering systems), etc. The EMS can be used both for microgrids approximated as single bus bar (or one node) and for microgrids in which all buses are taken into account. The optimal operation of the microgrid is based on a central controller that receives forecasts and data from a SCADA system and that can schedule all dispatchable plants in the day ahead or in real time through an approach based on Model Predictive Control (MPC). The architecture is tested and applied to the case study of the Savona Campus

  10. 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.

  11. Solar energy prediction and verification using operational model forecasts and ground-based solar measurements

    International Nuclear Information System (INIS)

    Kosmopoulos, P.G.; Kazadzis, S.; Lagouvardos, K.; Kotroni, V.; Bais, A.

    2015-01-01

    The present study focuses on the predictions and verification of these predictions of solar energy using ground-based solar measurements from the Hellenic Network for Solar Energy and the National Observatory of Athens network, as well as solar radiation operational forecasts provided by the MM5 mesoscale model. The evaluation was carried out independently for the different networks, for two forecast horizons (1 and 2 days ahead), for the seasons of the year, for varying solar elevation, for the indicative energy potential of the area, and for four classes of cloud cover based on the calculated clearness index (k_t): CS (clear sky), SC (scattered clouds), BC (broken clouds) and OC (overcast). The seasonal dependence presented relative rRMSE (Root Mean Square Error) values ranging from 15% (summer) to 60% (winter), while the solar elevation dependence revealed a high effectiveness and reliability near local noon (rRMSE ∼30%). An increment of the errors with cloudiness was also observed. For CS with mean GHI (global horizontal irradiance) ∼ 650 W/m"2 the errors are 8%, for SC 20% and for BC and OC the errors were greater (>40%) but correspond to much lower radiation levels (<120 W/m"2) of consequently lower energy potential impact. The total energy potential for each ground station ranges from 1.5 to 1.9 MWh/m"2, while the mean monthly forecast error was found to be consistently below 10%. - Highlights: • Long term measurements at different atmospheric cases are needed for energy forecasting model evaluations. • The total energy potential at the Greek sites presented ranges from 1.5 to 1.9 MWh/m"2. • Mean monthly energy forecast errors are within 10% for all cases analyzed. • Cloud presence results of an additional forecast error that varies with the cloud cover.

  12. Two-stage robust UC including a novel scenario-based uncertainty model for wind power applications

    International Nuclear Information System (INIS)

    Álvarez-Miranda, Eduardo; Campos-Valdés, Camilo; Rahmann, Claudia

    2015-01-01

    Highlights: • Methodological framework for obtaining Robust Unit Commitment (UC) policies. • Wind-power forecast using a revisited bootstrap predictive inference approach. • Novel scenario-based model for wind-power uncertainty. • Efficient modeling framework for obtaining nearly optimal UC policies in reasonable time. • Effective incorporation of wind-power uncertainty in the UC modeling. - Abstract: The complex processes involved in the determination of the availability of power from renewable energy sources, such as wind power, impose great challenges in the forecasting processes carried out by transmission system operators (TSOs). Nowadays, many of these TSOs use operation planning tools that take into account the uncertainty of the wind-power. However, most of these methods typically require strict assumptions about the probabilistic behavior of the forecast error, and usually ignore the dynamic nature of the forecasting process. In this paper a methodological framework to obtain Robust Unit Commitment (UC) policies is presented; such methodology considers a novel scenario-based uncertainty model for wind power applications. The proposed method is composed by three main phases. The first two phases generate a sound wind-power forecast using a bootstrap predictive inference approach. The third phase corresponds to modeling and solving a one-day ahead Robust UC considering the output of the first phase. The performance of proposed approach is evaluated using as case study a new wind farm to be incorporated into the Northern Interconnected System (NIS) of Chile. A projection of wind-based power installation, as well as different characteristic of the uncertain data, are considered in this study

  13. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm

    International Nuclear Information System (INIS)

    Guo, Zhenhai; Chi, Dezhong; Wu, Jie; Zhang, Wenyu

    2014-01-01

    Highlights: • Impact of meteorological factors on wind speed forecasting is taken into account. • Forecasted wind speed results are corrected by the associated rules. • Forecasting accuracy is improved by the new wind speed forecasting strategy. • Robust of the proposed model is validated by data sampled from different sites. - Abstract: Wind energy has been the fastest growing renewable energy resource in recent years. Because of the intermittent nature of wind, wind power is a fluctuating source of electrical energy. Therefore, to minimize the impact of wind power on the electrical grid, accurate and reliable wind power forecasting is mandatory. In this paper, a new wind speed forecasting approach based on based on the chaotic time series modelling technique and the Apriori algorithm has been developed. The new approach consists of four procedures: (I) Clustering by using the k-means clustering approach; (II) Employing the Apriori algorithm to discover the association rules; (III) Forecasting the wind speed according to the chaotic time series forecasting model; and (IV) Correcting the forecasted wind speed data using the associated rules discovered previously. This procedure has been verified by 31-day-ahead daily average wind speed forecasting case studies, which employed the wind speed and other meteorological data collected from four meteorological stations located in the Hexi Corridor area of China. The results of these case studies reveal that the chaotic forecasting model can efficiently improve the accuracy of the wind speed forecasting, and the Apriori algorithm can effectively discover the association rules between the wind speed and other meteorological factors. In addition, the correction results demonstrate that the association rules discovered by the Apriori algorithm have powerful capacities in handling the forecasted wind speed values correction when the forecasted values do not match the classification discovered by the association rules

  14. Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework

    International Nuclear Information System (INIS)

    Rezaei, Navid; Kalantar, Mohsen

    2015-01-01

    Highlights: • Detailed formulation of the microgrid static and dynamic securities based on droop control and virtual inertia concepts. • Constructing a novel objective function using frequency excursion and rate of change of frequency profiles. • Ensuring the microgrid security subject to the microgrid economic and environmental policies. • Coordinated management of demand response and droop controlled distributed generation resources. • Precise scheduling of day-ahead hierarchical frequency control ancillary services using a scenario based stochastic programming. - Abstract: Low inertia stack, high penetration levels of renewable energy source and great ratio of power deviations in a small power delivery system put microgrid frequency at risk of instability. On the basis of the close coupling between the microgrid frequency and system security requirements, procurement of adequate ancillary services from cost-effective and environmental friendly resources is a great challenge requests an efficient energy management system. Motivated by this need, this paper presents a novel energy management system that is aimed to coordinately manage the demand response and distributed generation resources. The proposed approach is carried out by constructing a hierarchical frequency control structure in which the frequency dependent control functions of the microgrid components are modeled comprehensively. On the basis of the derived modeling, both the static and dynamic frequency securities of an islanded microgrid are provided in primary and secondary control levels. Besides, to cope with the low inertia stack of islanded microgrids, novel virtual inertia concept is devised based on the precise modeling of droop controlled distributed generation resources. The proposed approach is applied to typical test microgrid. Energy and hierarchical reserve resource are scheduled precisely using a scenario-based stochastic programming methodology. Moreover, analyzing the

  15. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

    Directory of Open Access Journals (Sweden)

    Chan-Uk Yeom

    2017-10-01

    Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

  16. Base

    DEFF Research Database (Denmark)

    Hjulmand, Lise-Lotte; Johansson, Christer

    2004-01-01

    BASE - Engelsk basisgrammatik er resultatet af Lise-Lotte Hjulmands grundige bearbejdning og omfattende revidering af Christer Johanssons Engelska basgrammatik. Grammatikken adskiller sig fra det svenske forlæg på en lang række punkter. Den er bl.a. tilpasset til et dansk publikum og det danske...

  17. Flow-based market coupling. A joint ETSO-EuroPEX proposal for cross-border congestion management and integration of electricity markets in Europe. Interim report

    International Nuclear Information System (INIS)

    2004-09-01

    , it does not attempt to put forward a prescriptive 'blueprint' for a particular market model, but rather to signal a general direction. It is assumed that implementation of changes in practice would proceed through a series of regional initiatives, governed where necessary by the EU Regulation on Cross-border Exchanges of Electricity, together with the associated Guidelines. The FMC model describes arrangements for day-ahead trading. This needs to be part of a broader set of arrangements including, on one side, effective opportunities for participants to hedge price risk and, on the other side, complementary adjustment and balancing arrangements. FMC is compatible with price risk being hedged via a variety of forward physical or financial markets. The minimum set of regulatory/contractual arrangements necessary to implement FMC has been identified. Some issues concerning the status of power exchanges in some Member States remain to be resolved, particularly regarding the designated nature of the proposed day-ahead market. The transmission modelling and market co-ordination processes remain to be specified in technical detail. Both should be as transparent as reasonably possible, and the latter is likely to be an iterative process, introducing the possibility of convergence issues. Subject to the response to this interim report from other parties, ETSO and EuroPEX agree that the FMC concept should be developed further. Eventual deliverables should include inputs for consideration under the EU Comitology procedure, and advice for consideration by local implementation projects

  18. Flow-based market coupling. A joint ETSO-EuroPEX proposal for cross-border congestion management and integration of electricity markets in Europe. Interim report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-09-01

    debate and provide feedback. In particular, it does not attempt to put forward a prescriptive 'blueprint' for a particular market model, but rather to signal a general direction. It is assumed that implementation of changes in practice would proceed through a series of regional initiatives, governed where necessary by the EU Regulation on Cross-border Exchanges of Electricity, together with the associated Guidelines. The FMC model describes arrangements for day-ahead trading. This needs to be part of a broader set of arrangements including, on one side, effective opportunities for participants to hedge price risk and, on the other side, complementary adjustment and balancing arrangements. FMC is compatible with price risk being hedged via a variety of forward physical or financial markets. The minimum set of regulatory/contractual arrangements necessary to implement FMC has been identified. Some issues concerning the status of power exchanges in some Member States remain to be resolved, particularly regarding the designated nature of the proposed day-ahead market. The transmission modelling and market co-ordination processes remain to be specified in technical detail. Both should be as transparent as reasonably possible, and the latter is likely to be an iterative process, introducing the possibility of convergence issues. Subject to the response to this interim report from other parties, ETSO and EuroPEX agree that the FMC concept should be developed further. Eventual deliverables should include inputs for consideration under the EU Comitology procedure, and advice for consideration by local implementation projects.

  19. Impact of load management on the energy management strategy of a wind-short hydro hybrid system in frequency based pricing

    International Nuclear Information System (INIS)

    Malakar, T.; Goswami, S.K.; Sinha, A.K.

    2014-01-01

    Highlights: • This paper presents a new profit centric operating strategy of a hybrid power system under market environment. • The profit is ensured by optimal coordination of RES and load management approach. • The problem is formulated as dynamic optimization problem and solved using ABC algorithm. • Comparison shows that the proposed approach results more profit for the hybrid system. - Abstract: In the post restructuring era of electrical power system, each of the generating farm or utility has its own business strategy in terms of generation planning, load management and for other decisions. The basic objective of the utility is to maximize the operational profit for a given period of time. Generation scheduling for a utility with wind farm largely depends on the accuracy of wind power prediction. Therefore, it is important to explore the suitability of load management approach in coordination with the use of energy storage facility to compensate the uncertainty in wind power generation. This paper focuses mainly the operating strategy of a grid connected small hybrid power system to maximize its profit by adopting coordination between load management technique and utilization of storage plant under frequency based pricing. The optimum load scheduling has been implemented to utilities own local load. An hourly-discretized optimization algorithm is proposed and solved using artificial bee colony algorithm. To verify the effectiveness of the proposed method, the optimization problem is solved for varied wind power scenarios with different demand expectations cases in a day ahead Indian electricity market. It is noted that the proposed load management approach results more profit for the hybrid system because of better power management compared to the case when load scheduling has not been incorporated. The solution of the proposed optimization algorithm gives the strategies to be followed by the hybrid system how to operate its pump storage unit and to

  20. A Bilevel Model for Participation of a Storage System in Energy and Reserve Markets

    DEFF Research Database (Denmark)

    Nasrolahpour, Ehsan; Kazempour, Jalal; Zareipour, Hamidreza

    2017-01-01

    We develop a decision-making tool based on a bilevel complementarity model for a merchant price-maker energy storage system to determine the most beneficial trading actions in pool-based markets, including day-ahead (as joint energy and reserve markets) and balancing settlements. The uncertainty...... of net load deviation in real-time is incorporated into the model using a set of scenarios generated from the available forecast in the day-ahead. The objective of this energy storage system is to maximize its expected profit. The day-ahead products of energy storage system include energy as well...... system into clearing process of multiple markets and enables such a facility to possibly affect the outcomes of those markets to its own benefit through strategic price and quantity offers. The validity of the proposed approach is evaluated using a numerical study....

  1. Minimising the expectation value of the procurement cost in electricity markets based on the prediction error of energy consumption

    OpenAIRE

    Yamaguchi, Naoya; Hori, Maiya; Ideguchi, Yoshinari

    2018-01-01

    In this paper, we formulate a method for minimising the expectation value of the procurement cost of electricity in two popular spot markets: {\\it day-ahead} and {\\it intra-day}, under the assumption that expectation value of unit prices and the distributions of prediction errors for the electricity demand traded in two markets are known. The expectation value of the total electricity cost is minimised over two parameters that change the amounts of electricity. Two parameters depend only on t...

  2. Effects of intraday trade on NorNed

    Energy Technology Data Exchange (ETDEWEB)

    2011-06-15

    In this report we study the effects of introducing intraday trade on the NorNed cable between Norway and the Netherlands, effectively increasing the geographical scope of the existing intraday markets in both countries, by analysing the effects on the incentives of existing and potential new market participants. The analysis of the effects on incentives is mainly based on a fundamental analysis of resource prices in the two countries, using the day-ahead supply curves in both countries. It also includes an analysis of the dynamics of trade, interdependencies between the different market time frames (day-ahead, intraday and balancing stage) and price behaviour. In addition we describe the day-ahead, intraday and balancing markets of the two countries and identify factors in the market designs which may affect the incentives for intraday trade. (Author)

  3. Modeling prices of wholesale market of electric energy and power by the example of the UPS of the Ural

    Directory of Open Access Journals (Sweden)

    Mokhov V.G.

    2017-01-01

    Full Text Available The article oversees forecasting model for deviations of the balancing market index and day-ahead market index according to the maximum similarity sample for different levels of approximation in the context of positive and negative time-series value. The model was being tested on the factual data of the Integrated Power system of the Ural, Wholesale market for electricity and power of Russian Federation. Describes the price formation on the day-ahead market and the balancing market index. The necessity to use accurate forecasting methods consumption and prices of electrical energy and power to reduce penalties when the electric power industry entities on the energy exchange. The testing of mathematical models to predict the balancing market index deviations and day-ahead market based on a sample of maximum similarity with certain approximation equations for positive and negative values gave the prediction error of 3.3%.

  4. Uncertainty Management of Dynamic Tariff Method for Congestion Management in Distribution Networks

    DEFF Research Database (Denmark)

    Huang, Shaojun; Wu, Qiuwei; Cheng, Lin

    2016-01-01

    The dynamic tariff (DT) method is designed for the distribution system operator (DSO) to alleviate congestions that might occur in a distribution network with high penetration of distributed energy resources (DERs). Uncertainty management is required for the decentralized DT method because the DT...... is de- termined based on optimal day-ahead energy planning with forecasted parameters such as day-ahead energy prices and en- ergy needs which might be different from the parameters used by aggregators. The uncertainty management is to quantify and mitigate the risk of the congestion when employing...

  5. Multiple time-scale optimization scheduling for islanded microgrids including PV, wind turbine, diesel generator and batteries

    DEFF Research Database (Denmark)

    Xiao, Zhao xia; Nan, Jiakai; Guerrero, Josep M.

    2017-01-01

    A multiple time-scale optimization scheduling including day ahead and short time for an islanded microgrid is presented. In this paper, the microgrid under study includes photovoltaics (PV), wind turbine (WT), diesel generator (DG), batteries, and shiftable loads. The study considers the maximum...... efficiency operation area for the diesel engine and the cost of the battery charge/discharge cycle losses. The day-ahead generation scheduling takes into account the minimum operational cost and the maximum load satisfaction as the objective function. Short-term optimal dispatch is based on minimizing...

  6. Impacts of Base-Case and Post-Contingency Constraint Relaxations on Static and Dynamic Operational Security

    Science.gov (United States)

    Salloum, Ahmed

    Constraint relaxation by definition means that certain security, operational, or financial constraints are allowed to be violated in the energy market model for a predetermined penalty price. System operators utilize this mechanism in an effort to impose a price-cap on shadow prices throughout the market. In addition, constraint relaxations can serve as corrective approximations that help in reducing the occurrence of infeasible or extreme solutions in the day-ahead markets. This work aims to capture the impact constraint relaxations have on system operational security. Moreover, this analysis also provides a better understanding of the correlation between DC market models and AC real-time systems and analyzes how relaxations in market models propagate to real-time systems. This information can be used not only to assess the criticality of constraint relaxations, but also as a basis for determining penalty prices more accurately. Constraint relaxations practice was replicated in this work using a test case and a real-life large-scale system, while capturing both energy market aspects and AC real-time system performance. System performance investigation included static and dynamic security analysis for base-case and post-contingency operating conditions. PJM peak hour loads were dynamically modeled in order to capture delayed voltage recovery and sustained depressed voltage profiles as a result of reactive power deficiency caused by constraint relaxations. Moreover, impacts of constraint relaxations on operational system security were investigated when risk based penalty prices are used. Transmission lines in the PJM system were categorized according to their risk index and each category was as-signed a different penalty price accordingly in order to avoid real-time overloads on high risk lines. This work also extends the investigation of constraint relaxations to post-contingency relaxations, where emergency limits are allowed to be relaxed in energy market models

  7. Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

    International Nuclear Information System (INIS)

    Chou, Jui-Sheng; Ngo, Ngoc-Tri

    2016-01-01

    Highlights: • This study develops a novel time-series sliding window forecast system. • The system integrates metaheuristics, machine learning and time-series models. • Site experiment of smart grid infrastructure is installed to retrieve real-time data. • The proposed system accurately predicts energy consumption in residential buildings. • The forecasting system can help users minimize their electricity usage. - Abstract: Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time-series sliding window metaheuristic optimization-based machine learning system for predicting real-time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm-based least squares support vector regression (MetaFA-LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA-LSSVR model captures nonlinear data components in the second stage. Real-time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k-week sliding window approach is proposed for employing historical data as input for the novel time-series forecasting system. The prediction system yielded high and reliable accuracy rates in 1-day-ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026 kW h. Notably, the system demonstrates an improved accuracy rate in the range of 36.8–113.2% relative to those of the linear forecasting model (i.e., SARIMA) and nonlinear forecasting models (i.e., LSSVR and MetaFA-LSSVR). Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially

  8. A mid-term, market-based power systems planning model

    International Nuclear Information System (INIS)

    Koltsaklis, Nikolaos E.; Dagoumas, Athanasios S.; Georgiadis, Michael C.; Papaioannou, George; Dikaiakos, Christos

    2016-01-01

    Highlights: • A mid-term Energy Planning along with a Unit Commitment model is developed. • The model identifies the optimum interconnection capacity. • Electricity interconnections affect the power mix and the day-ahead spot price. • Renewables’ penetration has impacts on the power reserves and the CO_2 emissions. • Energy policy and fuel pricing can have significant impacts on the power mix. - Abstract: This paper presents a generic Mixed Integer Linear Programming (MILP) model that integrates a Mid-term Energy Planning (MEP) model, which implements generation and transmission system planning at a yearly level, with a Unit Commitment (UC) model, which performs the simulation of the Day-Ahead Electricity Market. The applicability of the proposed model is illustrated in a case study of the Greek interconnected power system. The aim is to evaluate a critical project in the Ten Year Network Development Plan (TYNDP) of the Independent Power Transmission System Operator S.A. (ADMIE), namely the electric interconnection of the Crete Island with the mainland electric system. The proposed modeling framework identifies the implementation (or not) of the interconnection of the Crete Island with the mainland electric system, as well as the optimum interconnection capacity. It also quantifies the effects on the Day-Ahead electricity market and on the energy mix. The paper demonstrates that the model can provide useful insights into the strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level, by providing the optimal energy roadmap and management, as well as clear price signals on critical energy projects under real operating and design constraints.

  9. Sharing wind power forecasts in electricity markets: A numerical analysis

    International Nuclear Information System (INIS)

    Exizidis, Lazaros; Kazempour, S. Jalal; Pinson, Pierre; Greve, Zacharie de; Vallée, François

    2016-01-01

    Highlights: • Information sharing among different agents can be beneficial for electricity markets. • System cost decreases by sharing wind power forecasts between different agents. • Market power of wind producer may increase by sharing forecasts with market operator. • Extensive out-of-sample analysis is employed to draw reliable conclusions. - Abstract: In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

  10. An application of ensemble/multi model approach for wind power production forecasting

    Science.gov (United States)

    Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S.

    2011-02-01

    The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.

  11. Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2016-09-01

    Full Text Available This paper presents novel intraday session models for price forecasts (ISMPF models for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL and the analysis of mean absolute percentage errors (MAPEs obtained with suitable combinations of their input variables in order to find the best ISMPF models. Comparisons of errors from different ISMPF models identified the most important variables for forecasting purposes. Similar analyses were applied to determine the best daily session models for price forecasts (DSMPF models for the day-ahead price forecasting in the daily session of the MIBEL, considering as input variables extensive hourly time series records of recent prices, power demands and power generations in the previous day, forecasts of demand, wind power generation and weather for the day-ahead, and chronological variables. ISMPF models include the input variables of DSMPF models as well as the daily session prices and prices of preceding intraday sessions. The best ISMPF models achieved lower MAPEs for most of the intraday sessions compared to the error of the best DSMPF model; furthermore, such DSMPF error was very close to the lowest limit error for the daily session. The best ISMPF models can be useful for MIBEL agents of the electricity intraday market and the electric energy industry.

  12. Optimised performance of a plug-in electric vehicle aggregator in energy and reserve markets

    International Nuclear Information System (INIS)

    Shafie-khah, M.; Moghaddam, M.P.; Sheikh-El-Eslami, M.K.; Catalão, J.P.S.

    2015-01-01

    Highlights: • A new model is developed to optimise the performance of a PEV aggregator in the power market. • PEVs aggregator can combine the PEVs and manage the charge/discharge of their batteries. • A new approach to calculate the satisfaction/motivation of PEV owners is proposed. • Several uncertainties are taken into account using a two-stage stochastic programing approach. • The proposed model is proficient in significantly improving the short- and long-term behaviour. - Abstract: In this paper, a new model is developed to optimise the performance of a plug-in Electric Vehicle (EV) aggregator in electricity markets, considering both short- and long-term horizons. EV aggregator as a new player of the power market can aggregate the EVs and manage the charge/discharge of their batteries. The aggregator maximises the profit and optimises EV owners’ revenue by applying changes in tariffs to compete with other market players for retaining current customers and acquiring new owners. On this basis, a new approach to calculate the satisfaction/motivation of EV owners and their market participation is proposed in this paper. Moreover, the behaviour of owners to select their supplying company is considered. The aggregator optimises the self-scheduling programme and submits the best bidding/offering strategies to the day-ahead and real-time markets. To achieve this purpose, the day-ahead and real-time energy and reserve markets are modelled as oligopoly markets, in contrast with previous works that utilised perfectly competitive ones. Furthermore, several uncertainties and constraints are taken into account using a two-stage stochastic programing approach, which have not been addressed in previous works. The numerical studies show the effectiveness of the proposed model

  13. Market redesign and regulatory change : how companies doing business in Alberta's power markets will be affected

    International Nuclear Information System (INIS)

    Runge, C.

    2003-01-01

    The Power Pool of Alberta (PPA) began its operations in 1996 based on a model with a single price set based on day ahead offers/bids and real time dispatch. The Electric Utilities Act was amended in 1998 and direct sales were permitted in 1999. The Power Purchase Arrangement Auction was implemented in 2000. Significant events took place in 2001, including: (1) retail competition, (2) PPAs began operations, (3) restrictions on direct sales were removed, (4) forward exchange operation, and (5) ancillary services market. In 2002, the Market Achievement Plan II was implemented and government industry structure was reviewed. There are several considerations regarding market redesign, such as day ahead market, capacity market, congestion management, and Northwest Regional Transmission Organization (RTO West). The role of the International Standard Organization (ISO) was discussed, with reference to the Independent System Operator, Independent Market Operator, and Transmission and Market Planner. Redesign must involve all participants and include informed, phased in changes

  14. Powernext FuturesTM statistics. April 30, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the April 30, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for April 2006, base-load and peak-load contracts overview from November 2005 to April 2006 (monthly volume in MW, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period), and market liquidity in April 2006 (average bid ask spread and availability for base-load and peak-load contracts). (J.S.)

  15. Powernext FuturesTM statistics. Jun 30, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the June 30, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for June 2006, base-load and peak-load contracts overview from January 2006 to June 2006 (monthly volume in MW, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period), and market liquidity in June 2006 (average bid ask spread and availability for base-load and peak-load contracts). (J.S.)

  16. Powernext futures statistics - March 31, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the March 31, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for March 2006, base-load and peak-load contracts overview from October 2005 to March 2006 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity in March 2006 (average bid ask spread and availability). (J.S.)

  17. Powernext futures statistics - August 31, 2005

    International Nuclear Information System (INIS)

    2005-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the August 31, 2005 update of Powernext Futures TM statistics: year, quarter and month contracts for August 2005, base-load and peak-load contracts overview from March 2005 to August 2005 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity in August 2005 (average bid ask spread and availability). (J.S.)

  18. Powernext futures statistics - December 31, 2005

    International Nuclear Information System (INIS)

    2005-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the December 31, 2005 update of Powernext Futures TM statistics: year, quarter and month contracts for December 2005, base-load and peak-load contracts overview from July 2005 to December 2005 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity in December 2005 (average bid ask spread and availability). (J.S.)

  19. Powernext futures statistics - November 30, 2005

    International Nuclear Information System (INIS)

    2005-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the November 30, 2005 update of Powernext Futures TM statistics: year, quarter and month contracts for November 2005, base-load and peak-load contracts overview from June 2005 to November 2005 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity in November 2005 (average bid ask spread and availability). (J.S.)

  20. Powernext futures statistics - January 31, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the January 31, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for January 2006, base-load and peak-load contracts overview from August 2005 to January 2006 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity in January 2006 (average bid ask spread and availability). (J.S.)

  1. An online learning approach to dynamic pricing for demand response

    OpenAIRE

    Jia, Liyan; Tong, Lang; Zhao, Qing

    2014-01-01

    In this paper, the problem of optimal dynamic pricing for retail electricity with an unknown demand model is considered. Under the day-ahead dynamic pricing (a.k.a. real time pricing) mechanism, a retailer obtains electricity in a twosettlement wholesale market and serves its customers in real time. Without knowledge on the aggregated demand function of its customers, the retailer aims to maximize its retail surplus by sequentially adjusting its price based on the behavior of its customers in...

  2. Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands

    OpenAIRE

    Klaassen, EAM; Kobus, C.B.A.; Frunt, J; Slootweg, JG

    2016-01-01

    To efficiently facilitate the energy transition it is essential to evaluate the potential of demand response in practice. Based on the results of a Dutch smart grid pilot, this paper assesses the potential of both manual and semi-automated demand response in residential areas. To stimulate demand response, a dynamic tariff and smart appliances were used. The participating households were informed about the tariff day-ahead through a home energy management system, connected to a display instal...

  3. Solar PV Power Forecasting Using Extreme Learning Machine and Information Fusion

    OpenAIRE

    Le Cadre , Hélène; Aravena , Ignacio; Papavasiliou , Anthony

    2015-01-01

    International audience; We provide a learning algorithm combining distributed Extreme Learning Machine and an information fusion rule based on the ag-gregation of experts advice, to build day ahead probabilistic solar PV power production forecasts. These forecasts use, apart from the current day solar PV power production, local meteorological inputs, the most valuable of which is shown to be precipitation. Experiments are then run in one French region, Provence-Alpes-Côte d'Azur, to evaluate ...

  4. Solar PV power forecasting using extreme machine learning and experts advice fusion

    OpenAIRE

    Le Cadre, Hélène; Aravena Solís, Ignacio Andrés; Papavasiliou, Anthony; European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

    2015-01-01

    We provide a learning algorithm combining distributed Extreme Learning Machine and an information fusion rule based on the aggregation of experts advice, to build day ahead probabilistic solar PV power production forecasts. These forecasts use, apart from the current day solar PV power production, local meteorological inputs, the most valuable of which is shown to be precipitation. Experiments are then run in one French region, Provence-Alpes-Côte d’Azur, to evaluate the algorithm performance...

  5. Effects of Risk Aversion on Market Outcomes: A Stochastic Two-Stage Equilibrium Model

    DEFF Research Database (Denmark)

    Kazempour, Jalal; Pinson, Pierre

    2016-01-01

    This paper evaluates how different risk preferences of electricity producers alter the market-clearing outcomes. Toward this goal, we propose a stochastic equilibrium model for electricity markets with two settlements, i.e., day-ahead and balancing, in which a number of conventional and stochastic...... by its optimality conditions, resulting in a mixed complementarity problem. Numerical results from a case study based on the IEEE one-area reliability test system are derived and discussed....

  6. Wind power forecasting-a review of the state of the art

    DEFF Research Database (Denmark)

    Giebel, Gregor; Kariniotakis, George

    2017-01-01

    This chapter gives an overview over past and present attempts to predict wind power for single turbines, wind, farms or for whole regions, for a few minutes up to a few days ahead. It is based on a survey and report (Giebel et al., 2011) initiated in the frame of the European project ANEMOS, whic...... integration of the forecasts in the work flow of end users....

  7. Practical operation strategies for pumped hydroelectric energy storage (PHES) utilising electricity price arbitrage

    DEFF Research Database (Denmark)

    Connolly, David; Lund, Henrik; Finn, P.

    2011-01-01

    In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360 MW pump, 300 MW turbine, and a 2 GWh storage utilising price arbitrage on 13 electricity spot markets. The results indicate...... that almost all (not, vert, similar97%) of the profits can be obtained by a PHES facility when it is optimised using the 24Optimal strategy developed, which optimises the energy storage based on the day-ahead electricity prices. However, to maximise profits with the 24Optimal strategy, the day......-ahead electricity prices must be the actual prices which the PHES facility is charged or the PHES operator must have very accurate price predictions. Otherwise, the predicted profit could be significantly reduced and even become a loss. Finally, using the 24Optimal strategy, the PHES profit can surpass the annual...

  8. Optimal offering and operating strategies for wind-storage systems with linear decision rules

    DEFF Research Database (Denmark)

    Ding, Huajie; Pinson, Pierre; Hu, Zechun

    2016-01-01

    The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy...... to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF...

  9. Improving offering strategies for wind farms enhanced with storage capability

    DEFF Research Database (Denmark)

    Ding, Huajie; Hu, Zechun; Song, Yonghua

    2015-01-01

    Due to the flexible charging and discharging capability, energy storage system (ESS) is thought of as a promising complement to wind farms (WF) in participating into electricity markets. This paper proposes a reserve-based real-time operation strategy of ESS to make arbitrage and to alleviate...... the wind power deviation from day-ahead contracts. Taking into account the operation strategy as well as two-price balancing market rules, a day-ahead bidding strategy of WF-ESS system is put forward and formulated. A modified gradient descent algorithm is described to solve the formulations. In the case...... studies, the computational efficiency of the algorithm is validated firstly. Moreover, a number of scenarios with/without considering the temporal dependence of wind power forecast error are designed and employed to compare the proposed strategy with other common ones in terms of profit....

  10. Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

    Science.gov (United States)

    Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

    2018-03-01

    The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

  11. The launch of a trading platform: a story of success, a matter of life

    Energy Technology Data Exchange (ETDEWEB)

    Ionescu, Victor; Palade, Lucian

    2007-07-01

    On the background of the electricity market liberalization challenge which Romania responded to without reserve on the edge between centuries by regulatory authority establishing, market opening and unbundling making, a spot market was launched. Taking advantage of generation split, market opening and consumption decline during the years '90, the competition is rising even without privatization, based negotiated contracts and Day Ahead market as spot. Year by year this market matured, asking for relevant changes as switching to multi-market concept. The preparation of related new mechanisms generated long term debates during 2003-2004 but finally the new trading platform was launched in 2005. As a market operator since 2000, based unceasing day ahead operation, OPCOM is making now a review of changes by also providing day ahead market performance coordinates. There are also overviewed the rationales and performance of two new other products offered by OPCOM to support renewable (green certificates market) and bilateral energy contracting through centralized bilateral contracts market. According to the Treaty of the Energy Community in South East Europe and the works of the Forum of Athens, OPCOM gets ready to grow the region of the spot market by using implicit auctions. The paper also provides concepts and principles concerning this initiative.

  12. Multi-time scale energy management of wind farms based on comprehensive evaluation technology

    Science.gov (United States)

    Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

    2017-11-01

    A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

  13. An application of ensemble/multi model approach for wind power production forecast.

    Science.gov (United States)

    Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

    2010-09-01

    The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic

  14. Decentralized Transactive Mechanism in Distribution Network Based on Smart Contract%基于智能合约的配电网去中心化交易机制

    Institute of Scientific and Technical Information of China (English)

    平健; 陈思捷; 张宁; 严正; 姚良忠

    2017-01-01

    With the deregulation of power industry and increasing penetration of distributed energy resources,both opportunities and challenges arise in distribution networks.Traditionally a distribution network is operated in a centralized way similar to a transmission network.However,this may incur problems such as high transaction costs,inefficiency,lack of transparency,and cyber-security risk.This paper presented a decentralized transactive distribution system operation method.Firstly,a transactive and decentralized mechanism was proposed.When a prosumer's actual generation/load deviates from her day-ahead schedule,she can send a real-time transaction request to neighboring prosumers and ask help to eliminate the deviation.A Vickrey-Clarke-Groves (VCG) auction method was introduced to encourage honest bidding of her neighbors.A security check method was proposed to ensure that power flows are within limits.Then,an operation method of a transactive distribution system,based on Ethereum blockchain that ensures transparency and information symmetry,was proposed.We also designed a smart contract of transactive energy.The simulation result based on Ethereum private blockchain shows that the proposed decentralized transactive method can deliver multilateral bidding of prosumers,minimize the total cost of eliminating deviation,and ensure the economic and secure operation of a distribution network.%电力体制改革的推进以及分布式能源渗透率的提高给配网运行带来了机遇与挑战.传统上,配网借鉴输电侧经验,以集中的方式管理运行.然而,这一模式在新形势下存在成本高、效率低、透明度低、信息安全风险高等问题.为此,该文提出了去中心化的配网运行模式和方法.首先,提出无须中心机构参与的配网交易机制与模型:配网中的产消者在其实际出力/负荷偏离发用电计划时,可发起实时交易请求,由周边产消者协助消除这一偏差,维持配网的供求动态平

  15. Correlations and clustering in wholesale electricity markets

    Science.gov (United States)

    Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin

    2018-02-01

    We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. This allows us to reconstruct aspects of the locational structure of the grid.

  16. A New Framework for Reactive Power Market Considering Power System Security

    Directory of Open Access Journals (Sweden)

    A. Rabiee

    2009-09-01

    Full Text Available This paper presents a new framework for the day-ahead reactive power market based on the uniform auction price. Voltage stability and security have been considered in the proposed framework. Total Payment Function (TPF is suggested as the objective function of the Optimal Power Flow (OPF used to clear the reactive power market. Overload, voltage drop and voltage stability margin (VSM are included in the constraints of the OPF. Another advantage of the proposed method is the exclusion of Lost Opportunity Cost (LOC concerns from the reactive power market. The effectiveness of the proposed reactive power market is studied based on the CIGRÉ-32 bus test system.

  17. Correlations and clustering in wholesale electricity markets

    International Nuclear Information System (INIS)

    Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin

    2017-01-01

    We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.

  18. Into the new electricity age with Optimal integration of decentralized energy resources - The FENIX Project

    Energy Technology Data Exchange (ETDEWEB)

    Cech, Heinz; Fuchs, Erich; Heher, Anton; Ilo, Albana; Sezi, Tevfik; Trimmel, Johann; Werner, Thomas; Marti-Rodriguez, Juan

    2010-09-15

    Decentralized Energy Resources (DERs) will play a significant role in future energy scenarios. Today, the 'plug and forget' connection principle for renewable energy resources has the goal to maximize the active power transfer, without using their real capabilities. Other DERs based on fossil fuels are only activated in emergency situations. This paper describes the results of a demonstration project, where DERs installed in a large distribution area are utilized for participating in the day ahead energy market, frequency and voltage support for the transmission system, voltage support at specific distribution locations and feeders, and stability support in emergency situations.

  19. Optimal operation strategy of battery energy storage system to real-time electricity price in Denmark

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2010-01-01

    markets in some ways, is chosen as the studied power system in this paper. Two kinds of BESS, based on polysulfide-bromine (PSB) and vanadium redox (VRB) battery technologies, are studies in the paper. Simulation results show, that the proposed optimal operation strategy is an effective measure to achieve......Since the hourly spot market price is available one day ahead, the price could be transferred to the consumers and they may have some motivations to install an energy storage system in order to save their energy costs. This paper presents an optimal operation strategy for a battery energy storage...

  20. Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

    OpenAIRE

    Huisman, Ronald; Mahieu, Ronald; Schlichter, Felix

    2007-01-01

    textabstractElectricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to allocate optimal positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relati...

  1. Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

    OpenAIRE

    D'Errico, Maria; Bollino, Carlo

    2015-01-01

    The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX), for 2011, in order to construct an aggregate demand function at the h...

  2. Testing of a Predictive Control Strategy for Balancing Renewable Sources in a Microgrid

    DEFF Research Database (Denmark)

    Marinelli, Mattia; Sossan, Fabrizio; Costanzo, Giuseppe Tommaso

    2014-01-01

    This paper presents the design of a control strategy for the energy management of a grid-connected microgrid with local distributed energy resources as: 10-kW photovoltaic plant, 11-kW wind turbine, and 15-kW–190-kWh vanadium-based electric storage system. According to future regulations......, the renewable energy producers will also have to provide a day-ahead hourly production plan. The overall idea is, by knowing the meteorological forecasts for the next 24 h, to dispatch the microgrid in order to be able to grant the scheduled hourly production by means of proper management of the storage system...

  3. A modelling breakthrough for market design analysis to test massive intermittent generation integration in markets results of selected OPTIMATE studies

    DEFF Research Database (Denmark)

    Beaude, Francois; Atayi, A.; Bourmaud, J.-Y.

    2013-01-01

    The OPTIMATE1 platform focuses on electricity system and market designs modelling in order to assess current and innovative designs in Europe. The current paper describes the results of the first validation studies' conducted with the tool. These studies deal with day-ahead market rules, load...... flexibility, cross-border management and intermittent renewable support schemes with a view to better integrating large amounts of renewable energy in Europe. Market and system designs were assessed based on economic efficiency, security of supply2 and environmental impact3 indicators. These results give...

  4. Real-time energy resources scheduling considering short-term and very short-term wind forecast

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

    2012-07-01

    This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

  5. Belpex and trilateral market coupling

    International Nuclear Information System (INIS)

    2006-01-01

    interconnections, Aspects of current explicit day-ahead allocation, Daily Market Process, Road-map by Regulators, CRE-CREG-DTE Road-map: Extension to NorNed and other areas, Further steps, Transmission Rights, Flow-based transmission model, Towards an Open and Multilateral Market Coupling). (J.S.)

  6. Pricing and Application of Electric Storage

    Science.gov (United States)

    Zhao, Jialin

    Electric storage provides a vehicle to store power for future use. It contributes to the grids in multiple aspects. For instance, electric storage is a more effective approach to provide electricity ancillary services than conventional methods. Additionally, electric storage, especially fast-responding units, allows owners to implement high-frequency power transactions in settings such as the 5-min real-time trading market. Such high-frequency power trades were limited in the past. However, as technology advances, the power markets have evolved. For instance, the California Independent System Operator now supports the 5-min real-time trading and the hourly day-ahead ancillary services bidding. Existing valuation models of electric storage were not designed to accommodate these recent market developments. To fill this gap, I focus on the fast-responding grid-level electric storage that provides both the real-time trading and the day-ahead ancillary services bidding. To evaluate such an asset, I propose a Monte Carlo Simulation-based valuation model. The foundation of my model is simulations of power prices. This study develops a new simulation model of electric prices. It is worth noting that, unlike existing models, my proposed simulation model captures the dependency of the real-time markets on the day-ahead markets. Upon such simulations, this study investigates the pricing and the application of electric storage at a 5-min granularity. Essentially, my model is a Dynamic Programming system with both endogenous variables (i.e., the State-of-Charge of electric storage) and exogenous variables (i.e., power prices). My first numerical example is the valuation of a fictitious 4MWh battery. Similarly, my second example evaluates the application of two units of 2MWh batteries. By comparing these two experiments, I investigate the issues related to battery configurations, such as the impacts of splitting storage capability on the valuation of electric storage.

  7. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  8. Essays on the integration of renewables in electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Knaut, Andreas

    2017-07-06

    The thesis sheds light onto the integration of renewable energy generation into electricity markets based on five articles. The first article is concerned with the optimal strategies of renewable producers selling electricity in sequential markets. A model is developed in which renewable generators trade their production in two sequential markets, which can be regarded as the day-ahead and intraday markets. Trading in the first market takes place under uncertainty about the final production level of renewable generation. The results show that it might be optimal for renewable producers to sell less than the expected quantity in the day-ahead market. The second article focuses on the high variability in production from renewable electricity and its effect on prices. A model for the allocation of hourly and quarter-hourly electricity generation is developed, assuming that the participation in the market for quarter-hourly products is restricted. Restricted participation in the market for quarter-hourly products may have caused welfare losses of about EUR 96 million in 2015. In the third article, the hourly price elasticity of demand for electricity in the German day-ahead market is empirically estimated. The results indicate a high level of variation of price elasticity of demand throughout the day ranging from -0.02 to -0.13 depending on the time of the day in the German day-ahead market in 2015. The fourth article is concerned with the tariff design in retail markets for electricity. It focuses on the inefficiency from time-invariant pricing in combination with an increasing share of renewable energies. The last article finally takes a closer look at the balancing power market and the impact of different market designs on efficiency and competition. Based on a developed model, it shows that shorter tender frequencies could lower the costs of balancing power procurement by up to 15 %. While market concentration decreases in many markets with shorter provision

  9. Essays on the integration of renewables in electricity markets

    International Nuclear Information System (INIS)

    Knaut, Andreas

    2017-01-01

    The thesis sheds light onto the integration of renewable energy generation into electricity markets based on five articles. The first article is concerned with the optimal strategies of renewable producers selling electricity in sequential markets. A model is developed in which renewable generators trade their production in two sequential markets, which can be regarded as the day-ahead and intraday markets. Trading in the first market takes place under uncertainty about the final production level of renewable generation. The results show that it might be optimal for renewable producers to sell less than the expected quantity in the day-ahead market. The second article focuses on the high variability in production from renewable electricity and its effect on prices. A model for the allocation of hourly and quarter-hourly electricity generation is developed, assuming that the participation in the market for quarter-hourly products is restricted. Restricted participation in the market for quarter-hourly products may have caused welfare losses of about EUR 96 million in 2015. In the third article, the hourly price elasticity of demand for electricity in the German day-ahead market is empirically estimated. The results indicate a high level of variation of price elasticity of demand throughout the day ranging from -0.02 to -0.13 depending on the time of the day in the German day-ahead market in 2015. The fourth article is concerned with the tariff design in retail markets for electricity. It focuses on the inefficiency from time-invariant pricing in combination with an increasing share of renewable energies. The last article finally takes a closer look at the balancing power market and the impact of different market designs on efficiency and competition. Based on a developed model, it shows that shorter tender frequencies could lower the costs of balancing power procurement by up to 15 %. While market concentration decreases in many markets with shorter provision

  10. Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

    Directory of Open Access Journals (Sweden)

    Hee-Jun Cha

    2015-12-01

    Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

  11. Lotus Base

    DEFF Research Database (Denmark)

    Mun, Terry; Bachmann, Asger; Gupta, Vikas

    2016-01-01

    exploration of Lotus genomic and transcriptomic data. Equally important are user-friendly in-browser tools designed for data visualization and interpretation. Here, we present Lotus Base, which opens to the research community a large, established LORE1 insertion mutant population containing an excess of 120...... such data, allowing users to construct, visualize, and annotate co-expression gene networks. Lotus Base takes advantage of modern advances in browser technology to deliver powerful data interpretation for biologists. Its modular construction and publicly available application programming interface enable...... developers to tap into the wealth of integrated Lotus data. Lotus Base is freely accessible at: https://lotus.au.dk....

  12. Touch BASE

    CERN Multimedia

    Antonella Del Rosso

    2015-01-01

    In a recent Nature article (see here), the BASE collaboration reported the most precise comparison of the charge-to-mass ratio of the proton to its antimatter equivalent, the antiproton. This result is just the beginning and many more challenges lie ahead.   CERN's AD Hall, where the BASE experiment is set-up. The Baryon Antibaryon Symmetry Experiment (BASE) was approved in June 2013 and was ready to take data in August 2014. During these 14 months, the BASE collaboration worked hard to set up its four cryogenic Penning traps, which are the heart of the whole experiment. As their name indicates, these magnetic devices are used to trap antiparticles – antiprotons coming from the Antiproton Decelerator – and particles of matter – negative hydrogen ions produced in the system by interaction with a degrader that slows the antiprotons down, allowing scientists to perform their measurements. “We had very little time to set up the wh...

  13. Daily River Flow Forecasting with Hybrid Support Vector Machine – Particle Swarm Optimization

    Science.gov (United States)

    Zaini, N.; Malek, M. A.; Yusoff, M.; Mardi, N. H.; Norhisham, S.

    2018-04-01

    The application of artificial intelligence techniques for river flow forecasting can further improve the management of water resources and flood prevention. This study concerns the development of support vector machine (SVM) based model and its hybridization with particle swarm optimization (PSO) to forecast short term daily river flow at Upper Bertam Catchment located in Cameron Highland, Malaysia. Ten years duration of historical rainfall, antecedent river flow data and various meteorology parameters data from 2003 to 2012 are used in this study. Four SVM based models are proposed which are SVM1, SVM2, SVM-PSO1 and SVM-PSO2 to forecast 1 to 7 day ahead of river flow. SVM1 and SVM-PSO1 are the models with historical rainfall and antecedent river flow as its input, while SVM2 and SVM-PSO2 are the models with historical rainfall, antecedent river flow data and additional meteorological parameters as input. The performances of the proposed model are measured in term of RMSE and R2 . It is found that, SVM2 outperformed SVM1 and SVM-PSO2 outperformed SVM-PSO1 which meant the additional meteorology parameters used as input to the proposed models significantly affect the model performances. Hybrid models SVM-PSO1 and SVM-PSO2 yield higher performances as compared to SVM1 and SVM2. It is found that hybrid models are more effective in forecasting river flow at 1 to 7 day ahead at the study area.

  14. POWERNEXT futures statistics November 30, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the November 30, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for November 2006, base-load and peak-load contracts overview from May 2005 or May 2006 to November 2006 (monthly volume in MW, open interest by delivery year in MWh, daily settlement price in euros/MWh), base-load and peak-load price spreads and market liquidity in November 2006 (average bid ask spread and availability). (J.S.)

  15. POWERNEXT futures statistics September 30, 2006

    International Nuclear Information System (INIS)

    2006-01-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the September 30, 2006 update of Powernext Futures TM statistics: year, quarter and month contracts for September 2006, base-load and peak-load contracts overview from April 2005 or March 2006 to September 2006 (monthly volume in MW, open interest by delivery year in MWh, daily settlement price in euros/MWh), base-load and peak-load price spreads and market liquidity in September 2006 (average bid ask spread and availability). (J.S.)

  16. Electricity market models and RES integration: The Greek case

    International Nuclear Information System (INIS)

    Simoglou, Christos K.; Biskas, Pandelis N.; Vagropoulos, Stylianos I.; Bakirtzis, Anastasios G.

    2014-01-01

    This paper presents an extensive analysis of the Greek electricity market for the next 7-year period (2014–2020) based on an hour-by-hour simulation considering five different RES technologies, namely wind, PV, small hydro, biomass and CHP with emphasis on PV integration. The impact of RES penetration on the electricity market operation is evaluated under two different models regarding the organization of the Greek wholesale day-ahead electricity market: a mandatory power pool for year 2014 (current market design) and a power exchange for the period 2015–2020 (Target Model). An integrated software tool is used for the simulation of the current and the future day-ahead market clearing algorithm of the Greek wholesale electricity market. Simulation results indicate the impact of the anticipated large-scale RES integration, in conjunction with each market model, on specific indicators of the Greek electricity market in the long-term. - Highlights: • Analysis of the Greek electricity market for the next 7-year period (2014–2020) based on hour-by-hour simulation. • Five different RES technologies are considered with emphasis on PV integration. • A power pool (for 2014) and a power exchange (for 2015–2020) are considered. • Various market indicators are used for the analysis of the impact of the RES integration on the Greek electricity market. • Two alternative tariff schemes for the compensation of the new ground-mounted PV units from 2015 onwards are investigated

  17. Powernext futuresTM statistics 31st, July 2004

    International Nuclear Information System (INIS)

    2004-07-01

    The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the July 31, 2004 update of Powernext Futures TM statistics: year, quarter and month contracts for July 2004, base-load and peak-load contracts overview from June 2004 to July 2004 (daily volume in lots, open interest by delivery year in MWh, daily settlement price of the upcoming delivery period, base-load and peak-load price spreads), and market liquidity from mid-June to end of July 2004 (average bid ask spread and availability). (J.S.)

  18. Measuring competitiveness of the EPEX spot market for electricity

    International Nuclear Information System (INIS)

    Graf, Christoph; Wozabal, David

    2013-01-01

    The issue of market concentration in electricity markets and resulting possible anti-competitive behavior of producers is a much discussed topic in many countries. We investigate the day-ahead market for electricity at the EPEX, the largest central European market for electricity. To analyze whether generating companies use their market power to influence prices, we use a conjectural variations approach as well as a direct approach to construct marginal costs of electricity production. Given the available data, we cannot reject the hypothesis that there was no systematic abuse of market power by the suppliers of electricity on the EPEX day-ahead spot market for the years 2007–2010. These results are essentially robust when restricting the sample to high load hours, which are generally considered to be the most prone to market manipulation. -- Highlights: •We investigate the efficiency of the German spot market for electricity. •We employ a conjectural variations approach and a fundamental market model. •Peak load hours and base load hours are analyzed separately. •We find that the market was competitive from 2007 to 2010 for both base and peak hours. •Policies to promote market transparency in Germany can be regarded as successful

  19. Fragmentation based

    Directory of Open Access Journals (Sweden)

    Shashank Srivastava

    2014-01-01

    Gaining the understanding of mobile agent architecture and the security concerns, in this paper, we proposed a security protocol which addresses security with mitigated computational cost. The protocol is a combination of self decryption, co-operation and obfuscation technique. To circumvent the risk of malicious code execution in attacking environment, we have proposed fragmentation based encryption technique. Our encryption technique suits the general mobile agent size and provides hard and thorny obfuscation increasing attacker’s challenge on the same plane providing better performance with respect to computational cost as compared to existing AES encryption.

  20. Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

    Directory of Open Access Journals (Sweden)

    Ryusuke Konishi

    2018-01-01

    Full Text Available In deregulated electricity markets, minimizing the procurement costs of electricity is a critical problem for procurement agencies (PAs. However, uncertainty is inevitable for PAs and includes multiple factors such as market prices, photovoltaic system (PV output and demand. This study focuses on settlements in multi-period markets (a day-ahead market and a real-time market and the installation of energy storage systems (ESSs. ESSs can be utilized for time arbitrage in the day-ahead market and to reduce the purchasing/selling of electricity in the real-time market. However, the high costs of an ESS mean the size of the system needs to be minimized. In addition, when determining the size of an ESS, it is important to identify the size appropriate for each role. Therefore, we employ the concept of a “slow” and a “fast” ESS to quantify the size of a system’s role, based on the values associated with the various uncertainties. Because the problem includes nonlinearity and non-convexity, we solve it within a realistic computational burden by reformulating the problem using reasonable assumptions. Therefore, this study identifies the optimal sizes of ESSs and procurement, taking into account the uncertainties of prices in multi-period markets, PV output and demand.

  1. Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators

    Directory of Open Access Journals (Sweden)

    Saber Talari

    2017-11-01

    Full Text Available Price forecasting plays a vital role in the day-ahead markets. Once sellers and buyers access an accurate price forecasting, managing the economic risk can be conducted appropriately through offering or bidding suitable prices. In networks with high wind power penetration, the electricity price is influenced by wind energy; therefore, price forecasting can be more complicated. This paper proposes a novel hybrid approach for price forecasting of day-ahead markets, with high penetration of wind generators based on Wavelet transform, bivariate Auto-Regressive Integrated Moving Average (ARIMA method and Radial Basis Function Neural Network (RBFN. To this end, a weighted time series for wind dominated power systems is calculated and added to a bivariate ARIMA model along with the price time series. Moreover, RBFN is applied as a tool to correct the estimation error, and particle swarm optimization (PSO is used to optimize the structure and adapt the RBFN to the particular training set. This method is evaluated on the Spanish electricity market, which shows the efficiency of this approach. This method has less error compared with other methods especially when it considers the effects of large-scale wind generators.

  2. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

    International Nuclear Information System (INIS)

    Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

    2016-01-01

    Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

  3. Fuzzy knowledge bases integration based on ontology

    OpenAIRE

    Ternovoy, Maksym; Shtogrina, Olena

    2012-01-01

    the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

  4. Foundation: Transforming data bases into knowledge bases

    Science.gov (United States)

    Purves, R. B.; Carnes, James R.; Cutts, Dannie E.

    1987-01-01

    One approach to transforming information stored in relational data bases into knowledge based representations and back again is described. This system, called Foundation, allows knowledge bases to take advantage of vast amounts of pre-existing data. A benefit of this approach is inspection, and even population, of data bases through an intelligent knowledge-based front-end.

  5. Paper based electronics platform

    KAUST Repository

    Nassar, Joanna Mohammad; Sevilla, Galo Andres Torres; Hussain, Muhammad Mustafa

    2017-01-01

    A flexible and non-functionalized low cost paper-based electronic system platform fabricated from common paper, such as paper based sensors, and methods of producing paper based sensors, and methods of sensing using the paper based sensors

  6. A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response

    International Nuclear Information System (INIS)

    Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui

    2016-01-01

    Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could

  7. Daily river flow prediction based on Two-Phase Constructive Fuzzy Systems Modeling: A case of hydrological - meteorological measurements asymmetry

    Science.gov (United States)

    Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann

    2018-03-01

    Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.

  8. Hidden power system inflexibilities imposed by traditional unit commitment formulations

    International Nuclear Information System (INIS)

    Morales-España, Germán; Ramírez-Elizondo, Laura; Hobbs, Benjamin F.

    2017-01-01

    Highlights: • Quality and accuracy of traditional-energy- and power-based UCs are evaluated. • Real-time performance evaluation simulating “perfect” stochastic UCs. • Ideal energy-based stochastic UC formulations impose hidden system inflexibilities. • A deterministic power-based UC may outperform an ideal energy-based stochastic UC. • Power-based UC overcomes flaws of energy-based UC: lower cost and wind curtailment. - Abstract: Approximations made in traditional day-ahead unit commitment model formulations can result in suboptimal or even infeasible schedules for slow-start units and inaccurate predictions of actual costs and wind curtailment. With increasing wind penetration, these errors will become economically more significant. Here, we consider inaccuracies from three approximations: the use of hourly intervals in which energy production from each generator is modeled as being constant; the disregarding of startup and shutdown energy trajectories; and optimization based on expected wind profiles. The results of unit commitment formulations with those assumptions are compared to models that: (1) use a piecewise-linear power profiles of generation, load and wind, instead of the traditional stepwise energy profiles; (2) consider startup/shutdown trajectories; and (3) include many possible wind trajectories in a stochastic framework. The day-ahead hourly schedules of slow-start generators are then evaluated against actual wind and load profiles using a model real-time dispatch and quick-start unit commitment with a 5 min time step. We find that each simplification usually causes expected generation costs to increase by several percentage points, and results in significant understatement of expected wind curtailment and, in some cases, load interruptions. The inclusion of startup and shutdown trajectories often yielded the largest improvements in schedule performance.

  9. Impact of Public Aggregate Wind Forecasts on Electricity Market Outcomes

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Kazempour, Jalal; Pinson, Pierre

    2017-01-01

    Following a call to foster a transparent and more competitive market, member states of the European transmission system operator are required to publish, among other information, aggregate wind power forecasts. The publication of the latter information is expected to benefit market participants...... by offering better knowledge of the market operation, leading subsequently to a more competitive energy market. Driven by the above regulation, we consider an equilibrium study to address how public information of aggregate wind power forecasts can potentially affect market results, social welfare as well...... as the profits of participating power producers. We investigate, therefore, a joint day-ahead energy and reserve auction, where producers offer their conventional power strategically based on a complementarity approach and their wind power at generation cost based on a forecast. In parallel, an iterative game...

  10. Equilibrium prices supported by dual price functions in markets with non-convexities

    International Nuclear Information System (INIS)

    Bjoerndal, Mette; Joernsten, Kurt

    2004-06-01

    The issue of finding market clearing prices in markets with non-convexities has had a renewed interest due to the deregulation of the electricity sector. In the day-ahead electricity market, equilibrium prices are calculated based on bids from generators and consumers. In most of the existing markets, several generation technologies are present, some of which have considerable non-convexities, such as capacity limitations and large start up costs. In this paper we present equilibrium prices composed of a commodity price and an uplift charge. The prices are based on the generation of a separating valid inequality that supports the optimal resource allocation. In the case when the sub-problem generated as the integer variables are held fixed to their optimal values possess the integrality property, the generated prices are also supported by non-linear price-functions that are the basis for integer programming duality. (Author)

  11. Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila

    2013-10-01

    Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

  12. Belpex and trilateral market coupling

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-01-15

    on the interconnections, Aspects of current explicit day-ahead allocation, Daily Market Process, Road-map by Regulators, CRE-CREG-DTE Road-map: Extension to NorNed and other areas, Further steps, Transmission Rights, Flow-based transmission model, Towards an Open and Multilateral Market Coupling). (J.S.)

  13. The physics data base

    International Nuclear Information System (INIS)

    Gault, F.D.

    1984-01-01

    The physics data base is introduced along with its associated data base management system. The emphasis is on data and their use and a classification of data and of data bases is developed to distinguish compilation organizations. The characteristics of these organizations are examined briefly and the long term consequences of the physics data base discussed. (orig.)

  14. Solid Base Catalysis

    CERN Document Server

    Ono, Yoshio

    2011-01-01

    The importance of solid base catalysts has come to be recognized for their environmentally benign qualities, and much significant progress has been made over the past two decades in catalytic materials and solid base-catalyzed reactions. The book is focused on the solid base. Because of the advantages over liquid bases, the use of solid base catalysts in organic synthesis is expanding. Solid bases are easier to dispose than liquid bases, separation and recovery of products, catalysts and solvents are less difficult, and they are non-corrosive. Furthermore, base-catalyzed reactions can be performed without using solvents and even in the gas phase, opening up more possibilities for discovering novel reaction systems. Using numerous examples, the present volume describes the remarkable role solid base catalysis can play, given the ever increasing worldwide importance of "green" chemistry. The reader will obtain an overall view of solid base catalysis and gain insight into the versatility of the reactions to whic...

  15. Real-time Energy Resource Scheduling considering a Real Portuguese Scenario

    DEFF Research Database (Denmark)

    Silva, Marco; Sousa, Tiago; Morais, Hugo

    2014-01-01

    The development in power systems and the introduction of decentralized gen eration and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which...... scheduling in smart grids, considering day - ahead, hour - ahead and real - time scheduling. The case study considers a 33 - bus distribution network with high penetration of distributed energy resources . The wind generation profile is base d o n a rea l Portuguese wind farm . Four scenarios are presented...... taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour - ahead and real - time scheduling...

  16. A virtual power plant model for time-driven power flow calculations

    Directory of Open Access Journals (Sweden)

    Gerardo Guerra

    2017-11-01

    Full Text Available This paper presents the implementation of a custom-made virtual power plant model in OpenDSS. The goal is to develop a model adequate for time-driven power flow calculations in distribution systems. The virtual power plant is modeled as the aggregation of renewable generation and energy storage connected to the distribution system through an inverter. The implemented operation mode allows the virtual power plant to act as a single dispatchable generation unit. The case studies presented in the paper demonstrate that the model behaves according to the specified control algorithm and show how it can be incorporated into the solution scheme of a general parallel genetic algorithm in order to obtain the optimal day-ahead dispatch. Simulation results exhibit a clear benefit from the deployment of a virtual power plant when compared to distributed generation based only on renewable intermittent generation.

  17. Trading strategies for distribution company with stochastic distributed energy resources

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chunyu; Wang, Qi; Wang, Jianhui; Korpås, Magnus; Pinson, Pierre; Østergaard, Jacob; Khodayar, Mohammad E.

    2016-09-01

    This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO’s profit across these markets. The PDISCO’s strategic offers/bids interactively influence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal–dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC). The effectiveness of the proposed model is verified by case studies.

  18. Dispatch Method for Independently Owned Hydropower Plants in the Same River Flow

    Directory of Open Access Journals (Sweden)

    Slavko Krajcar

    2012-09-01

    Full Text Available This paper proposes a coexistence model for two independent companies both operating hydropower plants in the same river flow, based on a case study of the Cetina river basin in Croatia. Companies are participants of the day-ahead electricity market. The incumbent company owns the existing hydropower plants and holds concessions for the water. The new company decides to build a pump storage hydropower plant that uses one of the existing reservoirs as its lower reservoir. Meeting reservoir water balance is affected by decisions by both companies which are independently seeking maximal profit. Methods for water use settlement and preventing of spillage are proposed. A mixed-integer linear programming approach is used. Head effects on output power levels are also considered. Existences of dispatches that satisfy both companies are shown.

  19. Trading Strategies for Distribution Company with Stochastic Distributed Energy Resources

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Wang, Qi; Wang, Jianhui

    2016-01-01

    This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower......-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO's prot across these markets. The PDISCO's strategic oers....../bids interactively in uence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal-dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC...

  20. Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

    Science.gov (United States)

    Ng, Kar Yong; Awang, Norhashidah

    2018-01-06

    Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

  1. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  2. Spot Markets Indices as Benchmarks of Formation of Future Price Trends in the Power Exchanges of Eastern Europe

    Directory of Open Access Journals (Sweden)

    Polikevych Nataliya I.

    2016-01-01

    Full Text Available The article is concerned with a theoretical generalization of the use of indices for electric power at the European spot exchanges and elaborating proposals on establishment of a similar spot index for the Ukrainian power exchange. 16 indices that are published daily by the power exchanges BSP Regional Energy Exchange, Power Exchange Central Europe, Polish Power Exchange and Opcom have been analyzed. It has been indicated that these indices are used for electricity price forecasting and monitoring the situation in the power market. The article examines the way spot indices are calculated by power exchanges, based on the value of the arithmetic average of market prices «day ahead». Imperfection of such way of calculation for price index values has been substantiated. The key characteristics of the future price index for Ukrainian spot market as benchmarks within the introduction of futures contracts for electricity have been identified.

  3. A stochastic framework for clearing of reactive power market

    International Nuclear Information System (INIS)

    Amjady, N.; Rabiee, A.; Shayanfar, H.A.

    2010-01-01

    This paper presents a new stochastic framework for clearing of day-ahead reactive power market. The uncertainty of generating units in the form of system contingencies are considered in the reactive power market-clearing procedure by the stochastic model in two steps. The Monte-Carlo Simulation (MCS) is first used to generate random scenarios. Then, in the second step, the stochastic market-clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. In each of these deterministic optimization problems, the objective function is total payment function (TPF) of generators which refers to the payment paid to the generators for their reactive power compensation. The effectiveness of the proposed model is examined based on the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS). (author)

  4. Multiobjective clearing of reactive power market in deregulated power systems

    International Nuclear Information System (INIS)

    Rabiee, A.; Shayanfar, H.; Amjady, N.

    2009-01-01

    This paper presents a day-ahead reactive power market which is cleared in the form of multiobjective context. Total payment function (TPF) of generators, representing the payment paid to the generators for their reactive power compensation, is considered as the main objective function of reactive power market. Besides that, voltage security margin, overload index, and also voltage drop index are the other objective functions of the optimal power flow (OPF) problem to clear the reactive power market. A Multiobjective Mathematical Programming (MMP) formulation is implemented to solve the problem of reactive power market clearing using a fuzzy approach to choose the best compromise solution according to the specific preference among various non-dominated (pareto optimal) solutions. The effectiveness of the proposed method is examined based on the IEEE 24-bus reliability test system (IEEE 24-bus RTS). (author)

  5. Energy and ancillary service dispatch through dynamic optimal power flow

    International Nuclear Information System (INIS)

    Costa, A.L.; Costa, A. Simoes

    2007-01-01

    This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system. (author)

  6. Determination of the Prosumer's Optimal Bids

    Science.gov (United States)

    Ferruzzi, Gabriella; Rossi, Federico; Russo, Angela

    2015-12-01

    This paper considers a microgrid connected with a medium-voltage (MV) distribution network. It is assumed that the microgrid, which is managed by a prosumer, operates in a competitive environment and participates in the day-ahead market. Then, as the first step of the short-term management problem, the prosumer must determine the bids to be submitted to the market. The offer strategy is based on the application of an optimization model, which is solved for different hourly price profiles of energy exchanged with the main grid. The proposed procedure is applied to a microgrid and four different its configurations were analyzed. The configurations consider the presence of thermoelectric units that only produce electricity, a boiler or/and cogeneration power plants for the thermal loads, and an electric storage system. The numerical results confirmed the numerous theoretical considerations that have been made.

  7. Methods and Algorithms for Economic MPC in Power Production Planning

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil

    in real-time. A generator can represent a producer of electricity, a consumer of electricity, or possibly both. Examples of generators are heat pumps, electric vehicles, wind turbines, virtual power plants, solar cells, and conventional fuel-fired thermal power plants. Although this thesis is mainly...... concerned with EMPC for minutes-ahead production planning, we show that the proposed EMPC scheme can be extended to days-ahead planning (including unit commitment) as well. The power generation from renewable energy sources such as wind and solar power is inherently uncertain and variable. A portfolio...... design an algorithm based on the alternating direction method of multipliers (ADMM) to solve input-constrained OCPs with convex objective functions. The OCPs that occur in EMPC of dynamically decoupled subsystems, e.g. power generators, have a block-angular structure. Subsystem decomposition algorithms...

  8. Marketing of wind power; Vermarktung von Windenergie

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von [Forschungsstelle fuer Energiewirtschaft e.V., Muenchen (Germany)

    2011-07-01

    With the integration of the fluctuating production in the system of power supply, there is the question about the impact on the electricity market. The special features of the commercialization of wind energy are: (1) The production exclusively takes place supply-dependent; (2) With fex exceptions, the supplied current is compensated according to the Renewable Energy Law; (3) The actual sale is performed by the operators of transmission systems; (4) The marginal cost are close to zero; (5) The day-ahead marketing solely based on a faulty prognosis. The author of the contribution under consideration reports on the actors and the process of wind power marketing. The alternative of direct marketing and the associated barriers and opportunities are discussed. The impact of the marketing of wind power on pricing in the electricity market is shown by means of an empirical analysis. The compensation amounts are be quantified, and the resulting cost to the balance of the forecast error are estimated.

  9. Audit of the process of determination of available cross-border electricity transmission capacity in the Netherlands

    International Nuclear Information System (INIS)

    Haubrich, H.J.; Fritz, W.

    2001-02-01

    The objective of this audit has been to analyse and to evaluate the process of determination of available cross-border electricity transmission capacity in the Netherlands as applied by the Dutch transmission system operator TenneT. In particular, the scope has been to give a survey of the corresponding responsibilities of TenneT as defined primarily by the Dutch Grid Code, to analyse the way TenneT fulfils these responsibilities, and to analyse and evaluate the decisions taken and the methods applied by TenneT for each step of this process. In addition, recommendations regarding possibilities of netting imports and exports in day-ahead capacity allocation have been requested. We have based this audit on comprehensive meetings with TenneT, on publicly available documents mainly from DTe and TenneT, and on non-public documents made available to us by TenneT. 26 refs

  10. From probabilistic forecasts to statistical scenarios of short-term wind power production

    DEFF Research Database (Denmark)

    Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

    2009-01-01

    on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

  11. Data on Support Vector Machines (SVM model to forecast photovoltaic power

    Directory of Open Access Journals (Sweden)

    M. Malvoni

    2016-12-01

    Full Text Available The data concern the photovoltaic (PV power, forecasted by a hybrid model that considers weather variations and applies a technique to reduce the input data size, as presented in the paper entitled “Photovoltaic forecast based on hybrid pca-lssvm using dimensionality reducted data” (M. Malvoni, M.G. De Giorgi, P.M. Congedo, 2015 [1]. The quadratic Renyi entropy criteria together with the principal component analysis (PCA are applied to the Least Squares Support Vector Machines (LS-SVM to predict the PV power in the day-ahead time frame. The data here shared represent the proposed approach results. Hourly PV power predictions for 1,3,6,12, 24 ahead hours and for different data reduction sizes are provided in Supplementary material.

  12. Electric energy storage systems in a market-based economy. Comparison of emerging and traditional technologies

    International Nuclear Information System (INIS)

    Kazempour, S. Jalal; Moghaddam, M. Parsa; Haghifam, M.R.; Yousefi, G.R.

    2009-01-01

    Unlike markets for storable commodities, electricity markets depend on the real-time balance of supply and demand. Although much of the present-day grid operate effectively without storage technologies, cost-effective ways of storing electrical energy can make the grid more efficient and reliable. This work addresses an economic comparison between emerging and traditional Electric Energy Storage (EES) technologies in a competitive electricity market. In order to achieve this goal, an appropriate Self-Scheduling (SS) approach must first be developed for each of them to determine their maximum potential of expected profit among multi-markets such as energy and ancillary service markets. Then, these technologies are economically analyzed using Internal Rate of Return (IRR) index. Finally, the amounts of needed financial supports are determined for choosing the emerging technologies when an investor would like to invest on EES technologies. Among available EES technologies, we consider NaS battery (Natrium Sulfur battery) and pumped-storage plants as emerging and traditional technologies, respectively. (author)

  13. Forecasting of Groundwater Level using Artificial Neural Network by incorporating river recharge and river bank infiltration

    Directory of Open Access Journals (Sweden)

    Nizar Shamsuddin Mohd Khairul

    2017-01-01

    Full Text Available Groundwater tables forecasting during implemented river bank infiltration (RBI method is important to identify adequate storage of groundwater aquifer for water supply purposes. This study illustrates the development and application of artificial neural networks (ANNs to predict groundwater tables in two vertical wells located in confined aquifer adjacent to the Langat River. ANN model was used in this study is based on the long period forecasting of daily groundwater tables. ANN models were carried out to predict groundwater tables for 1 day ahead at two different geological materials. The input to the ANN models consider of daily rainfall, river stage, water level, stream flow rate, temperature and groundwater level. Two different type of ANNs structure were used to predict the fluctuation of groundwater tables and compared the best forecasting values. The performance of different models structure of the ANN is used to identify the fluctuation of the groundwater table and provide acceptable predictions. Dynamics prediction and time series of the system can be implemented in two possible ways of modelling. The coefficient correlation (R, Mean Square Error (MSE, Root Mean Square Error (RMSE and coefficient determination (R2 were chosen as the selection criteria of the best model. The statistical values for DW1 are 0.8649, 0.0356, 0.01, and 0.748 respectively. While for DW2 the statistical values are 0.7392, 0.0781, 0.0139, and 0.546 respectively. Based on these results, it clearly shows that accurate predictions can be achieved with time series 1-day ahead of forecasting groundwater table and the interaction between river and aquifer can be examine. The findings of the study can be used to assist policy marker to manage groundwater resources by using RBI method.

  14. Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach

    International Nuclear Information System (INIS)

    Sarıca, Kemal; Kumbaroğlu, Gürkan; Or, Ilhan

    2012-01-01

    In this study, a model is developed to investigate the implications of an hourly day-ahead competitive power market on generator profits, electricity prices, availability and supply security. An integrated simulation/optimization approach is employed integrating a multi-agent simulation model with two alternative optimization models. The simulation model represents interactions between power generator, system operator, power user and power transmitter agents while the network flow optimization model oversees and optimizes the electricity flows, dispatches generators based on two alternative approaches used in the modeling of the underlying transmission network: a linear minimum cost network flow model and a non-linear alternating current optimal power flow model. Supply, demand, transmission, capacity and other technological constraints are thereby enforced. The transmission network, on which the scenario analyses are carried out, includes 30 bus, 41 lines, 9 generators, and 21 power users. The scenarios examined in the analysis cover various settings of transmission line capacities/fees, and hourly learning algorithms. Results provide insight into key behavioral and structural aspects of a decentralized electricity market under network constraints and reveal the importance of using an AC network instead of a simplified linear network flow approach. -- Highlights: ► An agent-based simulation model with an AC transmission environment with a day-ahead market. ► Physical network parameters have dramatic effects over price levels and stability. ► Due to AC nature of transmission network, adaptive agents have more local market power than minimal cost network flow. ► Behavior of the generators has significant effect over market price formation, as pointed out by bidding strategies. ► Transmission line capacity and fee policies are found to be very effective in price formation in the market.

  15. Beyond Zero Based Budgeting.

    Science.gov (United States)

    Ogden, Daniel M., Jr.

    1978-01-01

    Suggests that the most practical budgeting system for most managers is a formalized combination of incremental and zero-based analysis because little can be learned about most programs from an annual zero-based budget. (Author/IRT)

  16. VectorBase

    Data.gov (United States)

    U.S. Department of Health & Human Services — VectorBase is a Bioinformatics Resource Center for invertebrate vectors. It is one of four Bioinformatics Resource Centers funded by NIAID to provide web-based...

  17. Mobile Inquiry Based Learning

    NARCIS (Netherlands)

    Specht, Marcus

    2012-01-01

    Specht, M. (2012, 8 November). Mobile Inquiry Based Learning. Presentation given at the Workshop "Mobile inquiry-based learning" at the Mobile Learning Day 2012 at the Fernuniversität Hagen, Hagen, Germany.

  18. Microbead agglutination based assays

    KAUST Repository

    Kodzius, Rimantas; Castro, David; Foulds, Ian G.; Parameswaran, Ash M.; Sumanpreet, K. Chhina

    2013-01-01

    We report a simple and rapid room temperature assay for point-of-care (POC) testing that is based on specific agglutination. Agglutination tests are based on aggregation of microbeads in the presence of a specific analyte thus enabling

  19. Carbon Based Nanotechnology: Review

    Science.gov (United States)

    Srivastava, Deepak; Saini, Subhash (Technical Monitor)

    1999-01-01

    This presentation reviews publicly available information related to carbon based nanotechnology. Topics covered include nanomechanics, carbon based electronics, nanodevice/materials applications, nanotube motors, nano-lithography and H2O storage in nanotubes.

  20. Multi-market energy procurement for a large consumer using a risk-aversion procedure

    International Nuclear Information System (INIS)

    Zare, Kazem; Conejo, Antonio J.; Carrion, Miguel; Moghaddam, Mohsen Parsa

    2010-01-01

    This paper provides a technique to derive the bidding strategy in the day-ahead market of a large consumer that procures its electricity demand in both the day-ahead market and a subsequent adjustment market. Price uncertainty is modeled using concepts derived from information gap decision theory, which allows deriving robust decisions with respect to price volatility. Risk aversion is built implicitly within the proposed model. Correlations among prices in the day-ahead and the adjustment markets are properly modeled. The proposed technique is illustrated through a realistic case study. (author)

  1. Indicators of gas gross markets - November 2009-December 2012

    International Nuclear Information System (INIS)

    2012-12-01

    For each month from November 2009 until December 2012, this document proposes a set of graphs which illustrate the evolution of gas price (day-ahead price in France, difference between the North gas exchange point and South exchange point, price volatility, difference between M + 1 PEG price and day-ahead price, day-ahead price in Belgium, Germany and Netherlands, relationship between import price and market price), the development of gas trade in France (transactions, volumes, supplied volume in European countries) and indicators related to infrastructures (availability in gas entry points, use of infrastructure with respect to price difference on markets)

  2. Multi-market energy procurement for a large consumer using a risk-aversion procedure

    Energy Technology Data Exchange (ETDEWEB)

    Zare, Kazem [Tarbiat Modares University, Tehran, P.O. Box 14115-111 (Iran); Conejo, Antonio J. [Castilla-La Mancha University, Ciudad Real (Spain); Carrion, Miguel [Castilla-La Mancha University, Toledo (Spain); Moghaddam, Mohsen Parsa [Tarbiat Modares University, Tehran (Iran)

    2010-01-15

    This paper provides a technique to derive the bidding strategy in the day-ahead market of a large consumer that procures its electricity demand in both the day-ahead market and a subsequent adjustment market. Price uncertainty is modeled using concepts derived from information gap decision theory, which allows deriving robust decisions with respect to price volatility. Risk aversion is built implicitly within the proposed model. Correlations among prices in the day-ahead and the adjustment markets are properly modeled. The proposed technique is illustrated through a realistic case study. (author)

  3. The ground based plan

    International Nuclear Information System (INIS)

    1989-01-01

    The paper presents a report of ''The Ground Based Plan'' of the United Kingdom Science and Engineering Research Council. The ground based plan is a plan for research in astronomy and planetary science by ground based techniques. The contents of the report contains a description of:- the scientific objectives and technical requirements (the basis for the Plan), the present organisation and funding for the ground based programme, the Plan, the main scientific features and the further objectives of the Plan. (U.K.)

  4. Stolen Base Physics

    Science.gov (United States)

    Kagan, David

    2013-01-01

    Few plays in baseball are as consistently close and exciting as the stolen base. While there are several studies of sprinting, the art of base stealing is much more nuanced. This article describes the motion of the base-stealing runner using a very basic kinematic model. The model will be compared to some data from a Major League game. The…

  5. Convergent Filter Bases

    Directory of Open Access Journals (Sweden)

    Coghetto Roland

    2015-09-01

    Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

  6. Cholinesterase-based biosensors.

    Science.gov (United States)

    Štěpánková, Šárka; Vorčáková, Katarína

    2016-01-01

    Recently, cholinesterase-based biosensors are widely used for assaying anticholinergic compounds. Primarily biosensors based on enzyme inhibition are useful analytical tools for fast screening of inhibitors, such as organophosphates and carbamates. The present review is aimed at compilation of the most important facts about cholinesterase based biosensors, types of physico-chemical transduction, immobilization strategies and practical applications.

  7. Effects of climate change on water requirements and phenological period of major crops in Heihe River basin, China - Based on the accumulated temperature threshold method

    Science.gov (United States)

    Han, Dongmei; Xu, Xinyi; Yan, Denghua

    2016-04-01

    In recent years, global climate change has significantly caused a serious crisis of water resources throughout the world. However, mainly through variations in temperature, climate change will affect water requirements of crop. It is obvious that the rise of temperature affects growing period and phenological period of crop directly, then changes the water demand quota of crop. Methods including accumulated temperature threshold and climatic tendency rate were adopted, which made up for the weakness of phenological observations, to reveal the response of crop phenological change during the growing period. Then using Penman-Menteith model and crop coefficients from the United Nations Food& Agriculture Organization (FAO), the paper firstly explored crop water requirements in different growth periods, and further forecasted quantitatively crop water requirements in Heihe River Basin, China under different climate change scenarios. Results indicate that: (i) The results of crop phenological change established in the method of accumulated temperature threshold were in agreement with measured results, and (ii) there were many differences in impacts of climate warming on water requirement of different crops. The growth periods of wheat and corn had tendency of shortening as well as the length of growth periods. (ii)Results of crop water requirements under different climate change scenarios showed: when temperature increased by 1°C, the start time of wheat growth period changed, 2 days earlier than before, and the length of total growth period shortened 2 days. Wheat water requirements increased by 1.4mm. However, corn water requirements decreased by almost 0.9mm due to the increasing temperature of 1°C. And the start time of corn growth period become 3 days ahead, and the length of total growth period shortened 4 days. Therefore, the contradiction between water supply and water demands are more obvious under the future climate warming in Heihe River Basin, China.

  8. Impact of wind power uncertainty forecasting on the market integration of wind energy in Spain

    International Nuclear Information System (INIS)

    González-Aparicio, I.; Zucker, A.

    2015-01-01

    Highlights: • Reduction wind power forecasting uncertainty for day ahead and intraday markets. • Statistical relationship between total load and wind power generation. • Accurately forecast expected revenues from wind producer’s perspective. - Abstract: The growing share of electricity production from variable renewable energy sources increases the stochastic nature of the power system. This has repercussions on the markets for electricity. Deviations from forecasted production schedules require balancing of a generator’s position within a day. Short term products that are traded on power and/or reserve markets have been developed for this purpose, providing opportunities to actors who can offer flexibility in the short term. The value of flexibility is typically modelled using stochastic scenario extensions of dispatch models which requires, as a first step, understanding the nature of forecast uncertainties. This study provides a new approach for determining the forecast errors of wind power generation in the time period between the closure of the day ahead and the opening of the first intraday session using Spain as an example. The methodology has been developed using time series analysis for the years 2010–2013 to find the explanatory variables of the wind error variability by applying clustering techniques to reduce the range of uncertainty, and regressive techniques to forecast the probability density functions of the intra-day price. This methodology has been tested considering different system actions showing its suitability for developing intra-day bidding strategies and also for the generation of electricity generated from Renewable Energy Sources scenarios. This methodology could help a wind power producer to optimally bid into the intraday market based on more accurate scenarios, increasing their revenues and the system value of wind.

  9. Remedial transactions curtailment via optimization

    Directory of Open Access Journals (Sweden)

    Maksimović Viktor

    2009-01-01

    Full Text Available The new method developed in this paper is aiming at transmission congestion management (CM. The new, Optimal Transactions Management method (OTM, is based on linear programming (LP, DC load flow (DCLF and linear security constraints. The OTM method is embedded in Available Transfer Capabilities (ATCs and Power Transfer Distribution Factors (PTDFs definitions' environment. Well-suited for both preventive and corrective modes of operation, the OTM method aids transmission system operator in running a congested power system network, where congestions are due to transactions. Potential congestion threat is solved by finding the 'culprit' transaction and its optimal reduction. Besides the proposed downsizing of scheduled and/or committed transactions, controls of the OTM method also include redispatching of generation and load levels. The task is to establish a system state without constraint violations. To ensure the feasible network solution, both DC and AC power flows are used. The common 5 nodes/7 lines Ward&Hale sample power system is used to clarify the OTM method. Besides, six other power system networks including the real-life power system network of Serbia, Macedonia and Montenegro (part of the South East Europe - SEE grid are used to test remedial potentials and CPU-time performances of the method. The 24-hour daily demand diagram is used with all test networks to study the effects of transactions as they are being superimposed to the regional grid. The remedial, transactions-curtailing OTM method is found well suited for market-related analyses precluding the hour-ahead, the day-ahead dispatch, as well as the real-time generation dispatch. It could also suit for the novel, Day Ahead Congestion Forecast (DACF procedure used in power markets. .

  10. Practical operation strategies for pumped hydroelectric energy storage (PHES) utilising electricity price arbitrage

    International Nuclear Information System (INIS)

    Connolly, D.; Lund, H.; Finn, P.; Mathiesen, B.V.; Leahy, M.

    2011-01-01

    In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360 MW pump, 300 MW turbine, and a 2 GWh storage utilising price arbitrage on 13 electricity spot markets. The results indicate that almost all (∼97%) of the profits can be obtained by a PHES facility when it is optimised using the 24Optimal strategy developed, which optimises the energy storage based on the day-ahead electricity prices. However, to maximise profits with the 24Optimal strategy, the day-ahead electricity prices must be the actual prices which the PHES facility is charged or the PHES operator must have very accurate price predictions. Otherwise, the predicted profit could be significantly reduced and even become a loss. Finally, using the 24Optimal strategy, the PHES profit can surpass the annual investment repayments required. However, over the 5-year period investigated (2005-2009) the annual profit from the PHES facility varied by more than 50% on five out of six electricity markets considered. Considering the 40-year lifetime of PHES, even with low investment costs, a low interest rate, and a suitable electricity market, PHES is a risky investment without a more predictable profit. - Highlights: → Electricity generators typically operate on a market, including energy storage. → This paper assesses how energy storage can maximise its profits on a market. → Four operating strategies are assessed on 13 markets using a case study.→ One operating strategy achieves 97% of the profits feasible.→ However, the profit varies a lot depending on the market and capital costs.

  11. Optimal planning and operation of aggregated distributed energy resources with market participation

    International Nuclear Information System (INIS)

    Calvillo, C.F.; Sánchez-Miralles, A.; Villar, J.; Martín, F.

    2016-01-01

    Highlights: • Price-maker optimization model for planning and operation of aggregated DER. • 3 Case studies are proposed, considering different electricity pricing scenarios. • Analysis of benefits and effect on electricity prices produced by DER aggregation. • Results showed considerable benefits even for relatively small aggregations. • Results suggest that the impact on prices should not be overlooked. - Abstract: This paper analyzes the optimal planning and operation of aggregated distributed energy resources (DER) with participation in the electricity market. Aggregators manage their portfolio of resources in order to obtain the maximum benefit from the grid, while participating in the day-ahead wholesale electricity market. The goal of this paper is to propose a model for aggregated DER systems planning, considering its participation in the electricity market and its impact on the market price. The results are the optimal planning and management of DER systems, and the appropriate energy transactions for the aggregator in the wholesale day-ahead market according to the size of its aggregated resources. A price-maker approach based on representing the market competitors with residual demand curves is followed, and the impact on the price is assessed to help in the decision of using price-maker or price-taker approaches depending on the size of the aggregated resources. A deterministic programming problem with two case studies (the average scenario and the most likely scenario from the stochastic ones), and a stochastic one with a case study to account for the market uncertainty are described. For both models, market scenarios have been built from historical data of the Spanish system. The results suggest that when the aggregated resources have enough size to follow a price-maker approach and the uncertainty of the markets is considered in the planning process, the DER systems can achieve up to 50% extra economic benefits, depending on the market

  12. ARAC terrain data base

    International Nuclear Information System (INIS)

    Walker, H.

    1982-11-01

    A terrain data base covering the continental United States at 500-meter resolution has been generated. Its function is to provide terrain data for input to mesoscale atmospheric models that are used as part of the Atmospheric Release Advisory Capability at Lawrence Livermore Laboratory (LLNL). The structure of the data base as it exists on the LLNL computer system is described. The data base has been written to tapes for transfer to other systems and the format of these tapes is also described

  13. Base Station Performance Model

    OpenAIRE

    Walsh, Barbara; Farrell, Ronan

    2005-01-01

    At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

  14. Value-based pricing

    OpenAIRE

    Netseva-Porcheva Tatyana

    2010-01-01

    The main aim of the paper is to present the value-based pricing. Therefore, the comparison between two approaches of pricing is made - cost-based pricing and value-based pricing. The 'Price sensitively meter' is presented. The other topic of the paper is the perceived value - meaning of the perceived value, the components of perceived value, the determination of perceived value and the increasing of perceived value. In addition, the best company strategies in matrix 'value-cost' are outlined. .

  15. Network-Based Effectiveness

    National Research Council Canada - National Science Library

    Friman, Henrik

    2006-01-01

    ...) to increase competitive advantage, innovation, and mission effectiveness. Network-based effectiveness occurs due to the influence of various factors such as people, procedures, technology, and organizations...

  16. Case-based reasoning

    CERN Document Server

    Kolodner, Janet

    1993-01-01

    Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions whe

  17. Strengths-based Learning

    DEFF Research Database (Denmark)

    Ledertoug, Mette Marie

    -being. The Ph.D.-project in Strength-based learning took place in a Danish school with 750 pupils age 6-16 and a similar school was functioning as a control group. The presentation will focus on both the aware-explore-apply processes and the practical implications for the schools involved, and on measurable......Strength-based learning - Children͛s Character Strengths as Means to their Learning Potential͛ is a Ph.D.-project aiming to create a strength-based mindset in school settings and at the same time introducing strength-based interventions as specific tools to improve both learning and well...

  18. Monitoring Knowledge Base (MKB)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Monitoring Knowledge Base (MKB) is a compilation of emissions measurement and monitoring techniques associated with air pollution control devices, industrial...

  19. Imagery Data Base Facility

    Data.gov (United States)

    Federal Laboratory Consortium — The Imagery Data Base Facility supports AFRL and other government organizations by providing imagery interpretation and analysis to users for data selection, imagery...

  20. Game-Based Teaching

    DEFF Research Database (Denmark)

    Hanghøj, Thorkild

    2013-01-01

    This chapter outlines theoretical and empirical perspectives on how Game-Based Teaching can be integrated within the context of formal schooling. Initially, this is done by describing game scenarios as models for possible actions that need to be translated into curricular knowledge practices...... approaches to game-based teaching, which may or may not correspond with the pedagogical models of particular games....

  1. Secure base stations

    NARCIS (Netherlands)

    Bosch, Peter; Brusilovsky, Alec; McLellan, Rae; Mullender, Sape J.; Polakos, Paul

    2009-01-01

    With the introduction of the third generation (3G) Universal Mobile Telecommunications System (UMTS) base station router (BSR) and fourth generation (4G) base stations, such as the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) Evolved Node B (eNB), it has become important to

  2. Hydrogel based occlusion systems

    NARCIS (Netherlands)

    Stam, F.A.; Jackson, N.; Dubruel, P.; Adesanya, K.; Embrechts, A.; Mendes, E.; Neves, H.P.; Herijgers, P.; Verbrugghe, Y.; Shacham, Y.; Engel, L.; Krylov, V.

    2013-01-01

    A hydrogel based occlusion system, a method for occluding vessels, appendages or aneurysms, and a method for hydrogel synthesis are disclosed. The hydrogel based occlusion system includes a hydrogel having a shrunken and a swollen state and a delivery tool configured to deliver the hydrogel to a

  3. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Fogh Olsen, Ole; Sporring, Jon

    2007-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  4. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Olsen, Ole Fogh; Sporring, Jon

    2006-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  5. Zero-Based Budgeting.

    Science.gov (United States)

    Wichowski, Chester

    1979-01-01

    The zero-based budgeting approach is designed to achieve the greatest benefit with the fewest undesirable consequences. Seven basic steps make up the zero-based decision-making process: (1) identifying program goals, (2) classifying goals, (3) identifying resources, (4) reviewing consequences, (5) developing decision packages, (6) implementing a…

  6. Office-based anaesthesia

    African Journals Online (AJOL)

    infection, and consistency in nursing personnel. In the USA 17 -. 24% of all elective ambulatory surgery is ... knowledge base or personality to deal with the OBA environment. Compared with hospitals, office-based facilities currently ... disease or major cardiovascular risk factors). Intravenous access via a flexible cannula is.

  7. Knowledge base mechanisms

    Energy Technology Data Exchange (ETDEWEB)

    Suwa, M; Furukawa, K; Makinouchi, A; Mizoguchi, T; Mizoguchi, F; Yamasaki, H

    1982-01-01

    One of the principal goals of the Fifth Generation Computer System Project for the coming decade is to develop a methodology for building knowledge information processing systems which will provide people with intelligent agents. The key notion of the fifth generation computer system is knowledge used for problem solving. In this paper the authors describe the plan of Randd on knowledge base mechanisms. A knowledge representation system is to be designed to support knowledge acquisition for the knowledge information processing systems. The system will include a knowledge representation language, a knowledge base editor and a debugger. It is also expected to perform as a kind of meta-inference system. In order to develop the large scale knowledge base systems, a knowledge base mechanism based on the relational model is to be studied in the earlier stage of the project. Distributed problem solving is also one of the main issues of the project. 19 references.

  8. Skull base tumours

    Energy Technology Data Exchange (ETDEWEB)

    Borges, Alexandra [Instituto Portugues de Oncologia Francisco Gentil, Servico de Radiologia, Rua Professor Lima Basto, 1093 Lisboa Codex (Portugal)], E-mail: borgesalexandra@clix.pt

    2008-06-15

    With the advances of cross-sectional imaging radiologists gained an increasing responsibility in the management of patients with skull base pathology. As this anatomic area is hidden to clinical exam, surgeons and radiation oncologists have to rely on imaging studies to plan the most adequate treatment. To fulfil these endeavour radiologists need to be knowledgeable about skull base anatomy, about the main treatment options available, their indications and contra-indications and needs to be aware of the wide gamut of pathologies seen in this anatomic region. This article will provide a radiologists' friendly approach to the central skull base and will review the most common central skull base tumours and tumours intrinsic to the bony skull base.

  9. Evidence-based radiography

    International Nuclear Information System (INIS)

    Hafslund, Bjorg; Clare, Judith; Graverholt, Birgitte; Wammen Nortvedt, Monica

    2008-01-01

    Evidence-based practice (EBP) offers the integration of the best research evidence with clinical knowledge and expertise and patient values. EBP is a well known term in health care. This paper discusses the implementation of EBP into radiography and introduces the term evidence-based radiography. Evidence-based radiography is radiography informed and based on the combination of clinical expertise and the best available research-based evidence, patient preferences and resources available. In Norway, EBP in radiography is being debated and radiographers are discussing the challenges of implementing EBP in both academic and clinical practice. This discussion paper explains why EBP needs to be a basis for a radiography curriculum and a part of radiographers' practice. We argue that Norwegian radiographers must increase participation in research and developing practice within their specific radiographic domain

  10. Skull base tumours

    International Nuclear Information System (INIS)

    Borges, Alexandra

    2008-01-01

    With the advances of cross-sectional imaging radiologists gained an increasing responsibility in the management of patients with skull base pathology. As this anatomic area is hidden to clinical exam, surgeons and radiation oncologists have to rely on imaging studies to plan the most adequate treatment. To fulfil these endeavour radiologists need to be knowledgeable about skull base anatomy, about the main treatment options available, their indications and contra-indications and needs to be aware of the wide gamut of pathologies seen in this anatomic region. This article will provide a radiologists' friendly approach to the central skull base and will review the most common central skull base tumours and tumours intrinsic to the bony skull base

  11. The role of co-located storage for wind power producers in conventional electricity markets

    KAUST Repository

    Bitar, E.; Rajagopal, R.; Khargonekar, P.; Poolla, K.

    2011-01-01

    In this paper we study the problem of optimizing contract offerings for an independent wind power producer (WPP) participating in conventional day-ahead forward electricity markets for energy. As wind power is an inherently variable source of energy

  12. Electricity market clearing with improved dispatch of stochastic production

    DEFF Research Database (Denmark)

    Morales González, Juan Miguel; Zugno, Marco; Pineda, Salvador

    2014-01-01

    In this paper, we consider an electricity market that consists of a day-ahead and a balancing settlement, and includes a number of stochastic producers. We first introduce two reference procedures for scheduling and pricing energy in the day-ahead market: on the one hand, a conventional network...... attains higher market efficiency in expectation than the conventional day-ahead auction, it suffers from fundamental drawbacks with a view to its practical implementation. In particular, it requires flexible producers (those that make up for the lack or surplus of stochastic generation) to accept losses...... in some scenarios. Using a bilevel programming framework, we then show that the conventional auction, if combined with a suitable day-ahead dispatch of stochastic producers (generally different from their expected production), can substantially increase market efficiency and emulate the advantageous...

  13. Design-Based Research

    DEFF Research Database (Denmark)

    Gynther, Karsten; Christensen, Ove; Petersen, Trine Brun

    2012-01-01

    I denne artikel introduceres Design Based Research for første gang på dansk i et videnskabeligt tidsskrift. Artiklen præsenterer de grundlæggende antagelser, som ligger til grund for Design Based Research-traditionen, og artiklen diskuterer de principper, som ligger til grund for gennemførelse af...... et DBR-forskningsprojekt. Med udgangspunkt i forsknings- og udviklingsprojektet ELYK: E-læring, Yderområder og Klyngedannelse, præsenteres den innovationsmodel, som projektet har udviklet med udgangspunkt i Design Based Research traditionen. ELYKs DBR innovationsmodel har vist sig effektiv i forhold...

  14. Nature-based integration

    DEFF Research Database (Denmark)

    Pitkänen, Kati; Oratuomi, Joose; Hellgren, Daniela

    Increased attention to, and careful planning of the integration of migrants into Nordic societies is ever more important. Nature based integration is a new solution to respond to this need. This report presents the results of a Nordic survey and workshop and illustrates current practices of nature...... based integration by case study descriptions from Denmark, Sweden Norway and Finland. Across Nordic countries several practical projects and initiatives have been launched to promote the benefits of nature in integration and there is also growing academic interest in the topic. Nordic countries have...... the potential of becoming real forerunners in nature based integration even at the global scale....

  15. Data base management study

    Science.gov (United States)

    1976-01-01

    Data base management techniques and applicable equipment are described. Recommendations which will assist potential NASA data users in selecting and using appropriate data base management tools and techniques are presented. Classes of currently available data processing equipment ranging from basic terminals to large minicomputer systems were surveyed as they apply to the needs of potential SEASAT data users. Cost and capabilities projections for this equipment through 1985 were presented. A test of a typical data base management system was described, as well as the results of this test and recommendations to assist potential users in determining when such a system is appropriate for their needs. The representative system tested was UNIVAC's DMS 1100.

  16. Value-based pricing

    Directory of Open Access Journals (Sweden)

    Netseva-Porcheva Tatyana

    2010-01-01

    Full Text Available The main aim of the paper is to present the value-based pricing. Therefore, the comparison between two approaches of pricing is made - cost-based pricing and value-based pricing. The 'Price sensitively meter' is presented. The other topic of the paper is the perceived value - meaning of the perceived value, the components of perceived value, the determination of perceived value and the increasing of perceived value. In addition, the best company strategies in matrix 'value-cost' are outlined. .

  17. QuickBase

    CERN Document Server

    Conner, Nancy

    2007-01-01

    Ready to put Intuit's QuickBase to work? Our new Missing Manual shows you how to capture, modify, share, and manage data and documents with this web-based data-sharing program quickly and easily. No longer do you have to coordinate your team through a blizzard of emails or play frustrating games of "guess which document is the right one."QuickBase saves your organization time and money, letting you manage and share the information that makes your business tick: sales figures, project timelines, drafts of documents, purchase or work requests--whatever information you need to keep business flowi

  18. Cheboygan Vessel Base

    Data.gov (United States)

    Federal Laboratory Consortium — Cheboygan Vessel Base (CVB), located in Cheboygan, Michigan, is a field station of the USGS Great Lakes Science Center (GLSC). CVB was established by congressional...

  19. Hanscom Air Force Base

    Data.gov (United States)

    Federal Laboratory Consortium — MIT Lincoln Laboratory occupies 75 acres (20 acres of which are MIT property) on the eastern perimeter of Hanscom Air Force Base, which is at the nexus of Lexington,...

  20. Network-Based Effectiveness

    National Research Council Canada - National Science Library

    Friman, Henrik

    2006-01-01

    ... (extended from Leavitt, 1965). This text identifies aspects of network-based effectiveness that can benefit from a better understanding of leadership and management development of people, procedures, technology, and organizations...

  1. WormBase

    Data.gov (United States)

    U.S. Department of Health & Human Services — WormBase is an international consortium of biologists and computer scientists dedicated to providing the research community with accurate, current, accessible...

  2. Kelomehele preemia Baseli festivalil

    Index Scriptorium Estoniae

    2000-01-01

    Baselis festivalil "VIPER - International Festival for Film Video and New Media" tunnistati parimaks CD-ROMiks Gustav Deutschi/Anna Schimeki "Odysee today", netiprojektiks itaallaste "01.ORG", äramärkimispreemia - Raivo Kelomehe "Videoweaver"

  3. Risk based modelling

    International Nuclear Information System (INIS)

    Chapman, O.J.V.; Baker, A.E.

    1993-01-01

    Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

  4. Problem Based Learning

    DEFF Research Database (Denmark)

    de Graaff, Erik; Guerra, Aida

    , the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... model and in general problem based and project based learning. We apply the principle of teach as you preach. The poster aims to outline the visitors’ workshop programme showing the results of some recent evaluations.......Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However...

  5. Biomimetics: nature based innovation

    National Research Council Canada - National Science Library

    Bar-Cohen, Yoseph

    2012-01-01

    "Based on the concept that nature offers numerous sources of inspiration for inventions related to mechanisms, materials, processes, and algorithms, this book covers the topic of biomimetics and the inspired innovation...

  6. BaseMap

    Data.gov (United States)

    California Natural Resource Agency — The goal of this project is to provide a convenient base map that can be used as a starting point for CA projects. It's simple, but designed to work at a number of...

  7. PHENANTHROLINE TEMPLATED SCHIFF BASE

    African Journals Online (AJOL)

    DNA in intercalative mode and in the development of unique chemotherapeutics where they impact on the ... between base pairs of DNA. .... h, i, j, k belong to fragmentation products of impap. ..... Sm(III) complex and herring sperm DNA. Bull.

  8. Lunar resource base

    Science.gov (United States)

    Pulley, John; Wise, Todd K.; Roy, Claude; Richter, Phil

    A lunar base that exploits local resources to enhance the productivity of a total SEI scenario is discussed. The goals were to emphasize lunar science and to land men on Mars in 2016 using significant amounts of lunar resources. It was assumed that propulsion was chemical and the surface power was non-nuclear. Three phases of the base build-up are outlined, the robotic emplacement of the first elements is detailed and a discussion of future options is included.

  9. Participatory design based research

    DEFF Research Database (Denmark)

    Dau, Susanne; Bach Jensen, Louise; Falk, Lars

    This poster reveal how participatory design based research by the use of a CoED inspired creative process can be used for designing solutions to problems regarding students study activities outside campus.......This poster reveal how participatory design based research by the use of a CoED inspired creative process can be used for designing solutions to problems regarding students study activities outside campus....

  10. Maintaining Relationship Based Procurement

    OpenAIRE

    Davis, Peter

    2012-01-01

    Alliance and relationship projects are increasingin number and represent a large pool of work. Tobe successful relationship style contracts dependon soft-dollar factors, particularly the participants'ability to work together within an agreedframework, generally they are not based on lowbid tendering. Participants should be prepared todo business in an open environment based ontrust and mutually agreed governance. Theresearch evaluates relationship maintenance inthe implementation phase of con...

  11. Game-based telerehabilitation.

    Science.gov (United States)

    Lange, B; Flynn, Sheryl M; Rizzo, A A

    2009-03-01

    This article summarizes the recent accomplishments and current challenges facing game-based virtual reality (VR) telerehabilitation. Specifically this article addresses accomplishments relative to realistic practice scenarios, part to whole practice, objective measurement of performance and progress, motivation, low cost, interaction devices and game design. Furthermore, a description of the current challenges facing game based telerehabilitation including the packaging, internet capabilities and access, data management, technical support, privacy protection, seizures, distance trials, scientific scrutiny and support from insurance companies.

  12. REST based mobile applications

    Science.gov (United States)

    Rambow, Mark; Preuss, Thomas; Berdux, Jörg; Conrad, Marc

    2008-02-01

    Simplicity is the major advantage of REST based webservices. Whereas SOAP is widespread in complex, security sensitive business-to-business aplications, REST is widely used for mashups and end-user centric applicatons. In that context we give an overview of REST and compare it to SOAP. Furthermore we apply the GeoDrawing application as an example for REST based mobile applications and emphasize on pros and cons for the use of REST in mobile application scenarios.

  13. Swarm-based medicine.

    Science.gov (United States)

    Putora, Paul Martin; Oldenburg, Jan

    2013-09-19

    Occasionally, medical decisions have to be taken in the absence of evidence-based guidelines. Other sources can be drawn upon to fill in the gaps, including experience and intuition. Authorities or experts, with their knowledge and experience, may provide further input--known as "eminence-based medicine". Due to the Internet and digital media, interactions among physicians now take place at a higher rate than ever before. With the rising number of interconnected individuals and their communication capabilities, the medical community is obtaining the properties of a swarm. The way individual physicians act depends on other physicians; medical societies act based on their members. Swarm behavior might facilitate the generation and distribution of knowledge as an unconscious process. As such, "swarm-based medicine" may add a further source of information to the classical approaches of evidence- and eminence-based medicine. How to integrate swarm-based medicine into practice is left to the individual physician, but even this decision will be influenced by the swarm.

  14. Evidence-Based Toxicology.

    Science.gov (United States)

    Hoffmann, Sebastian; Hartung, Thomas; Stephens, Martin

    Evidence-based toxicology (EBT) was introduced independently by two groups in 2005, in the context of toxicological risk assessment and causation as well as based on parallels between the evaluation of test methods in toxicology and evidence-based assessment of diagnostics tests in medicine. The role model of evidence-based medicine (EBM) motivated both proposals and guided the evolution of EBT, whereas especially systematic reviews and evidence quality assessment attract considerable attention in toxicology.Regarding test assessment, in the search of solutions for various problems related to validation, such as the imperfectness of the reference standard or the challenge to comprehensively evaluate tests, the field of Diagnostic Test Assessment (DTA) was identified as a potential resource. DTA being an EBM discipline, test method assessment/validation therefore became one of the main drivers spurring the development of EBT.In the context of pathway-based toxicology, EBT approaches, given their objectivity, transparency and consistency, have been proposed to be used for carrying out a (retrospective) mechanistic validation.In summary, implementation of more evidence-based approaches may provide the tools necessary to adapt the assessment/validation of toxicological test methods and testing strategies to face the challenges of toxicology in the twenty first century.

  15. LDEF materials data bases

    Science.gov (United States)

    Funk, Joan G.; Strickland, John W.; Davis, John M.

    1993-01-01

    The Long Duration Exposure Facility (LDEF) and the accompanying experiments were composed of and contained a wide variety of materials representing the largest collection of materials flown in low Earth orbit (LEO) and retrieved for ground based analysis to date. The results and implications of the mechanical, thermal, optical, and electrical data from these materials are the foundation on which future LEO space missions will be built. The LDEF Materials Special Investigation Group (MSIG) has been charged with establishing and developing data bases to document these materials and their performance to assure not only that the data are archived for future generations but also that the data are available to the spacecraft user community in an easily accessed, user-friendly form. This paper discusses the format and content of the three data bases developed or being developed to accomplish this task. The hardware and software requirements for each of these three data bases are discussed along with current availability of the data bases. This paper also serves as a user's guide to the MAPTIS LDEF Materials Data Base.

  16. Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators

    OpenAIRE

    Saber Talari; Miadreza Shafie-khah; Gerardo J. Osório; Fei Wang; Alireza Heidari; João P. S. Catalão

    2017-01-01

    Price forecasting plays a vital role in the day-ahead markets. Once sellers and buyers access an accurate price forecasting, managing the economic risk can be conducted appropriately through offering or bidding suitable prices. In networks with high wind power penetration, the electricity price is influenced by wind energy; therefore, price forecasting can be more complicated. This paper proposes a novel hybrid approach for price forecasting of day-ahead markets, with high penetration of wind...

  17. Powernext newsletter n. 27

    International Nuclear Information System (INIS)

    2005-02-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange market. This issue of Powernext newsletter presents the highlights of the European power trade markets during January, February and March 2005. It reports on some daily market statistics related to prices and volumes traded on Powernext Day-Ahead TM in the case of day-ahead contracts, and on Powernext Futures TM in the case of medium-term contracts. (J.S.)

  18. Powernext newsletter n. 28

    International Nuclear Information System (INIS)

    2005-04-01

    Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange market. This issue of Powernext newsletter presents the highlights of the European power trade markets during February, March and April 2005. It reports on some daily market statistics related to prices and volumes traded on Powernext Day-Ahead TM in the case of day-ahead contracts, and on Powernext Futures TM in the case of medium-term contracts. (J.S.)

  19. Paper based electronics platform

    KAUST Repository

    Nassar, Joanna Mohammad

    2017-07-20

    A flexible and non-functionalized low cost paper-based electronic system platform fabricated from common paper, such as paper based sensors, and methods of producing paper based sensors, and methods of sensing using the paper based sensors are provided. A method of producing a paper based sensor can include the steps of: a) providing a conventional paper product to serve as a substrate for the sensor or as an active material for the sensor or both, the paper product not further treated or functionalized; and b) applying a sensing element to the paper substrate, the sensing element selected from the group consisting of a conductive material, the conductive material providing contacts and interconnects, sensitive material film that exhibits sensitivity to pH levels, a compressible and/or porous material disposed between a pair of opposed conductive elements, or a combination of two of more said sensing elements. The method of sensing can further include measuring, using the sensing element, a change in resistance, a change in voltage, a change in current, a change in capacitance, or a combination of any two or more thereof.

  20. Gossip-Based Dissemination

    Science.gov (United States)

    Friedman, Roy; Kermarrec, Anne-Marie; Miranda, Hugo; Rodrigues, Luís

    Gossip-based networking has emerged as a viable approach to disseminate information reliably and efficiently in large-scale systems. Initially introduced for database replication [222], the applicability of the approach extends much further now. For example, it has been applied for data aggregation [415], peer sampling [416] and publish/subscribe systems [845]. Gossip-based protocols rely on a periodic peer-wise exchange of information in wired systems. By changing the way each peer is selected for the gossip communication, and which data are exchanged and processed [451], gossip systems can be used to perform different distributed tasks, such as, among others: overlay maintenance, distributed computation, and information dissemination (a collection of papers on gossip can be found in [451]). In a wired setting, the peer sampling service, allowing for a random or specific peer selection, is often provided as an independent service, able to operate independently from other gossip-based services [416].

  1. Iron-based superconductivity

    CERN Document Server

    Johnson, Peter D; Yin, Wei-Guo

    2015-01-01

    This volume presents an in-depth review of experimental and theoretical studies on the newly discovered Fe-based superconductors.  Following the Introduction, which places iron-based superconductors in the context of other unconventional superconductors, the book is divided into three sections covering sample growth, experimental characterization, and theoretical understanding.  To understand the complex structure-property relationships of these materials, results from a wide range of experimental techniques and theoretical approaches are described that probe the electronic and magnetic proper

  2. Evidence-Based Development

    DEFF Research Database (Denmark)

    Hertzum, Morten; Simonsen, Jesper

    2004-01-01

    Systems development is replete with projects that represent substantial resource investments but result in systems that fail to meet users’ needs. Evidence-based development is an emerging idea intended to provide means for managing customer-vendor relationships and working systematically toward...... meeting customer needs. We are suggesting that the effects of the use of a system should play a prominent role in the contractual definition of IT projects and that contract fulfilment should be determined on the basis of evidence of these effects. Based on two ongoing studies of home-care management...

  3. Video-based rendering

    CERN Document Server

    Magnor, Marcus A

    2005-01-01

    Driven by consumer-market applications that enjoy steadily increasing economic importance, graphics hardware and rendering algorithms are a central focus of computer graphics research. Video-based rendering is an approach that aims to overcome the current bottleneck in the time-consuming modeling process and has applications in areas such as computer games, special effects, and interactive TV. This book offers an in-depth introduction to video-based rendering, a rapidly developing new interdisciplinary topic employing techniques from computer graphics, computer vision, and telecommunication en

  4. Process-based costing.

    Science.gov (United States)

    Lee, Robert H; Bott, Marjorie J; Forbes, Sarah; Redford, Linda; Swagerty, Daniel L; Taunton, Roma Lee

    2003-01-01

    Understanding how quality improvement affects costs is important. Unfortunately, low-cost, reliable ways of measuring direct costs are scarce. This article builds on the principles of process improvement to develop a costing strategy that meets both criteria. Process-based costing has 4 steps: developing a flowchart, estimating resource use, valuing resources, and calculating direct costs. To illustrate the technique, this article uses it to cost the care planning process in 3 long-term care facilities. We conclude that process-based costing is easy to implement; generates reliable, valid data; and allows nursing managers to assess the costs of new or modified processes.

  5. Inkjet-based micromanufacturing

    CERN Document Server

    Korvink, Jan G; Shin, Dong-Youn; Brand, Oliver; Fedder, Gary K; Hierold, Christofer; Tabata, Osamu

    2012-01-01

    Inkjet-based Micromanufacturing Inkjet technology goes way beyond putting ink on paper: it enables simpler, faster and more reliable manufacturing processes in the fields of micro- and nanotechnology. Modern inkjet heads are per se precision instruments that deposit droplets of fluids on a variety of surfaces in programmable, repeating patterns, allowing, after suitable modifications and adaptations, the manufacturing of devices such as thin-film transistors, polymer-based displays and photovoltaic elements. Moreover, inkjet technology facilitates the large-scale production of flexible RFID tr

  6. On multivariate Wilson bases

    DEFF Research Database (Denmark)

    Bownik, Marcin; Jakobsen, Mads Sielemann; Lemvig, Jakob

    2017-01-01

    A Wilson system is a collection of finite linear combinations of time frequency shifts of a square integrable function. In this paper we give an account of the construction of bimodular Wilson bases in higher dimensions from Gabor frames of redundancy two.......A Wilson system is a collection of finite linear combinations of time frequency shifts of a square integrable function. In this paper we give an account of the construction of bimodular Wilson bases in higher dimensions from Gabor frames of redundancy two....

  7. Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2017-11-01

    Full Text Available The optimal dispatching model for a stand-alone microgrid (MG is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL and multi-distributed generations (DGs. The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend and weather categories (sunny or rainy to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation.

  8. Supramolecular fluorene based materials

    NARCIS (Netherlands)

    Abbel, R.J.

    2008-01-01

    This thesis describes the use of noncovalent interactions in order to manipulate and control the self-assembly and morphology of electroactive fluorene-based materials. The supramolecular arrangement of p-conjugated polymers and oligomers can strongly influence their electronic and photophysical

  9. EPICS based DAQ system

    International Nuclear Information System (INIS)

    Cheng Weixing; Chen Yongzhong; Zhou Weimin; Ye Kairong; Liu Dekang

    2002-01-01

    EPICS is the most popular developing platform to build control system and beam diagnostic system in modern physics experiment facilities. An EPICS based data acquisition system was built in Redhat 6.2 operation system. The system is successfully used in the beam position monitor mapping, it improves the mapping process a lot

  10. Scenario-based strategizing

    DEFF Research Database (Denmark)

    Lehr, Thomas; Lorenz, Ullrich; Willert, Markus

    2017-01-01

    -based efficacy and robustness. To facilitate the colla- borative strategizing in teams, we propose a matrix with robustness and efficacy as the two axes, which we call the Parmenides Matrix. We assess the impact of the novel approach by applying it in two cases, at a govern- mental agency (German Environmental...

  11. Dictionary Based Image Segmentation

    DEFF Research Database (Denmark)

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets...

  12. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  13. Surfel Based Geometry Resonstruction

    DEFF Research Database (Denmark)

    Andersen, Vedrana; Aanæs, Henrik; Bærentzen, Jakob Andreas

    2010-01-01

    We propose a method for retrieving a piecewise smooth surface from noisy data. In data acquired by a scanning process sampled points are almost never on the discontinuities making reconstruction of surfaces with sharp features difficult. Our method is based on a Markov Random Field (MRF) formulat...

  14. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Sporring, Jon; Fogh Olsen, Ole

    2008-01-01

    . To address this problem, we introduce a photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way, we preserve important illumination features, while...

  15. Evidence-based policy

    DEFF Research Database (Denmark)

    Vohnsen, Nina Holm

    2013-01-01

    -makers and the research community (e.g. Boden & Epstein 2006; House of Commons 2006; Cartwright et al 2009; Rod 2010; Vohnsen 2011). This article intends to draw out some general pitfalls in the curious meeting of science and politics by focusing on a particular attempt to make evidence-based legislation in Denmark (for...

  16. Project-Based Science

    Science.gov (United States)

    Krajcik, Joe

    2015-01-01

    Project-based science is an exciting way to teach science that aligns with the "Next Generation Science Standards" ("NGSS"). By focusing on core ideas along with practices and crosscutting concepts, classrooms become learning environments where teachers and students engage in science by designing and carrying out…

  17. Financing Competency Based Programs.

    Science.gov (United States)

    Daniel, Annette

    Literature on the background, causes, and current prevalence of competency based programs is synthesized in this report. According to one analysis of the actual and probable costs of minimum competency testing, estimated costs for test development, test administration, bureaucratic structures, and remedial programs for students who cannot pass the…

  18. Computer Based Expert Systems.

    Science.gov (United States)

    Parry, James D.; Ferrara, Joseph M.

    1985-01-01

    Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

  19. Community-Based Care

    Science.gov (United States)

    ... our e-newsletter! Aging & Health A to Z Community-Based Care Basic Facts & Information A variety of healthcare options ... day care centers are either in churches or community centers. Adult day care is commonly used to care for people who ...

  20. Polymer based tunneling sensor

    Science.gov (United States)

    Cui, Tianhong (Inventor); Wang, Jing (Inventor); Zhao, Yongjun (Inventor)

    2006-01-01

    A process for fabricating a polymer based circuit by the following steps. A mold of a design is formed through a lithography process. The design is transferred to a polymer substrate through a hot embossing process. A metal layer is then deposited over at least part of said design and at least one electrical lead is connected to said metal layer.

  1. Evidence-based guidelines

    DEFF Research Database (Denmark)

    Rovira, Àlex; Wattjes, Mike P; Tintoré, Mar

    2015-01-01

    diagnosis in patients with MS. The aim of this article is to provide guidelines for the implementation of MRI of the brain and spinal cord in the diagnosis of patients who are suspected of having MS. These guidelines are based on an extensive review of the recent literature, as well as on the personal...

  2. School Based Health Centers

    Science.gov (United States)

    Children's Aid Society, 2012

    2012-01-01

    School Based Health Centers (SBHC) are considered by experts as one of the most effective and efficient ways to provide preventive health care to children. Few programs are as successful in delivering health care to children at no cost to the patient, and where they are: in school. For many underserved children, The Children's Aid Society's…

  3. Internet based benchmarking

    DEFF Research Database (Denmark)

    Bogetoft, Peter; Nielsen, Kurt

    2005-01-01

    We discuss the design of interactive, internet based benchmarking using parametric (statistical) as well as nonparametric (DEA) models. The user receives benchmarks and improvement potentials. The user is also given the possibility to search different efficiency frontiers and hereby to explore...

  4. Problem-based learning

    NARCIS (Netherlands)

    Loyens, Sofie; Kirschner, Paul A.; Paas, Fred

    2010-01-01

    Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2011). Problem-based learning. In S. Graham (Editor-in-Chief), A. Bus, S. Major, & L. Swanson (Associate Editors), APA educational psychology handbook: Vol. 3. Application to learning and teaching (pp. 403-425). Washington, DC: American Psychological

  5. Base tree property

    Czech Academy of Sciences Publication Activity Database

    Balcar, B.; Doucha, Michal; Hrušák, M.

    2015-01-01

    Roč. 32, č. 1 (2015), s. 69-81 ISSN 0167-8094 R&D Projects: GA AV ČR IAA100190902 Institutional support: RVO:67985840 Keywords : forcing * Boolean algebras * base tree Subject RIV: BA - General Mathematics Impact factor: 0.614, year: 2015 http://link.springer.com/article/10.1007/s11083-013-9316-2

  6. unsymmetrical Schiff base complexes

    Indian Academy of Sciences (India)

    the effect of the substitutional groups of the Schiff base on the oxidation and reduction potentials, we used ... Electrochemistry of these complexes showed that the presence of electron .... a solution of the ligand (1 mmol) in methanol (15 mL).

  7. Home-based care

    African Journals Online (AJOL)

    Mrs. Patience Edoho Samson-Akpan

    study was to ascertain the relationship between home-based care and quality of life of PLWHA in support groups in. Calabar South Local Government Area. A correlational design was utilized and a purposive sample of 74 PLWHA participated in the study. A self developed and well validated questionnaire was used for data ...

  8. Mutually unbiased bases

    Indian Academy of Sciences (India)

    Mutually unbiased bases play an important role in quantum cryptography [2] and in the optimal determination of the density operator of an ensemble [3,4]. A density operator ρ in N-dimensions depends on N2 1 real quantities. With the help of MUB's, any such density operator can be encoded, in an optimal way, in terms of ...

  9. Scenario-based strategizing

    DEFF Research Database (Denmark)

    Lehr, Thomas; Lorenz, Ullrich; Willert, Markus

    2017-01-01

    For over 40 years, scenarios have been promoted as a key technique for forming strategies in uncertain en- vironments. However, many challenges remain. In this article, we discuss a novel approach designed to increase the applicability of scenario-based strategizing in top management teams. Drawi...... Ministry) and a firm affected by disruptive change (Bosch, leading global supplier of technology and solutions)....

  10. 80537 based distance relay

    DEFF Research Database (Denmark)

    Pedersen, Knud Ole Helgesen

    1999-01-01

    A method for implementing a digital distance relay in the power system is described.Instructions are given on how to program this relay on a 80537 based microcomputer system.The problem is used as a practical case study in the course 53113: Micocomputer applications in the power system.The relay...

  11. Mojave Base Station Implementation

    Science.gov (United States)

    Koscielski, C. G.

    1984-01-01

    A 12.2 meter diameter X-Y mount antenna was reconditioned for use by the crustal dynamic project as a fixed base station. System capabilities and characteristics and key performance parameters for subsystems are presented. The implementation is completed.

  12. Model-based consensus

    NARCIS (Netherlands)

    Boumans, M.; Martini, C.; Boumans, M.

    2014-01-01

    The aim of the rational-consensus method is to produce "rational consensus", that is, "mathematical aggregation", by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  13. Model-based consensus

    NARCIS (Netherlands)

    Boumans, Marcel

    2014-01-01

    The aim of the rational-consensus method is to produce “rational consensus”, that is, “mathematical aggregation”, by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  14. Animation-based Sketching

    DEFF Research Database (Denmark)

    Vistisen, Peter

    This thesis is based on the results of a three-year long PhD-study at the Department of Communication and Psychology at Aalborg University. The thesis consist of five original papers, a book manuscript, as well as a linking text with the thesis’ research questions, research design, and summary...

  15. Refractive index based measurements

    DEFF Research Database (Denmark)

    2014-01-01

    In a method for performing a refractive index based measurement of a property of a fluid such as chemical composition or temperature, a chirp in the local spatial frequency of interference fringes of an interference pattern is reduced by mathematical manipulation of the recorded light intensity...

  16. Performance based fault diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik

    2002-01-01

    Different aspects of fault detection and fault isolation in closed-loop systems are considered. It is shown that using the standard setup known from feedback control, it is possible to formulate fault diagnosis problems based on a performance index in this general standard setup. It is also shown...

  17. Schiff base ligand

    Indian Academy of Sciences (India)

    Unknown

    Low-temperature stoichiometric Schiff base reaction in air in 3 : 1 mole ratio between benz- aldehyde and triethylenetetramine (trien) in methanol yields a novel tetraaza µ-bis(bidentate) acyclic ligand L. It was .... electrochemical work was performed as reported in ..... change in ligand shape through change in oxidation.

  18. ISFET based enzyme sensors

    NARCIS (Netherlands)

    van der Schoot, Bart H.; Bergveld, Piet

    1987-01-01

    This paper reviews the results that have been reported on ISFET based enzyme sensors. The most important improvement that results from the application of ISFETs instead of glass membrane electrodes is in the method of fabrication. Problems with regard to the pH dependence of the response and the

  19. Microcontroller base process emulator

    OpenAIRE

    Jovrea Titus Claudiu

    2009-01-01

    This paper describes the design of a microcontroller base emulator for a conventional industrial process. The emulator is made with microcontroller and is used for testing and evaluating the performances of the industrial regulators. The parameters of the emulated process are fully customizable online and downloadable thru a serial communication from a personal computer.

  20. REST based service composition

    DEFF Research Database (Denmark)

    Grönvall, Erik; Ingstrup, Mads; Pløger, Morten

    2011-01-01

    This paper presents an ongoing work developing and testing a Service Composition framework based upon the REST architecture named SECREST. A minimalistic approach have been favored instead of a creating a complete infrastructure. One focus has been on the system's interaction model. Indeed, an aim...

  1. Convolution based profile fitting

    International Nuclear Information System (INIS)

    Kern, A.; Coelho, A.A.; Cheary, R.W.

    2002-01-01

    Full text: In convolution based profile fitting, profiles are generated by convoluting functions together to form the observed profile shape. For a convolution of 'n' functions this process can be written as, Y(2θ)=F 1 (2θ)x F 2 (2θ)x... x F i (2θ)x....xF n (2θ). In powder diffractometry the functions F i (2θ) can be interpreted as the aberration functions of the diffractometer, but in general any combination of appropriate functions for F i (2θ) may be used in this context. Most direct convolution fitting methods are restricted to combinations of F i (2θ) that can be convoluted analytically (e.g. GSAS) such as Lorentzians, Gaussians, the hat (impulse) function and the exponential function. However, software such as TOPAS is now available that can accurately convolute and refine a wide variety of profile shapes numerically, including user defined profiles, without the need to convolute analytically. Some of the most important advantages of modern convolution based profile fitting are: 1) virtually any peak shape and angle dependence can normally be described using minimal profile parameters in laboratory and synchrotron X-ray data as well as in CW and TOF neutron data. This is possible because numerical convolution and numerical differentiation is used within the refinement procedure so that a wide range of functions can easily be incorporated into the convolution equation; 2) it can use physically based diffractometer models by convoluting the instrument aberration functions. This can be done for most laboratory based X-ray powder diffractometer configurations including conventional divergent beam instruments, parallel beam instruments, and diffractometers used for asymmetric diffraction. It can also accommodate various optical elements (e.g. multilayers and monochromators) and detector systems (e.g. point and position sensitive detectors) and has already been applied to neutron powder diffraction systems (e.g. ANSTO) as well as synchrotron based

  2. Integrated Case Based and Rule Based Reasoning for Decision Support

    OpenAIRE

    Eshete, Azeb Bekele

    2009-01-01

    This project is a continuation of my specialization project which was focused on studying theoretical concepts related to case based reasoning method, rule based reasoning method and integration of them. The integration of rule-based and case-based reasoning methods has shown a substantial improvement with regards to performance over the individual methods. Verdande Technology As wants to try integrating the rule based reasoning method with an existing case based system. This project focu...

  3. Rock properties data base

    Energy Technology Data Exchange (ETDEWEB)

    Jackson, R.; Gorski, B.; Gyenge, M.

    1991-03-01

    As mining companies proceed deeper and into areas whose stability is threatened by high and complex stress fields, the science of rock mechanics becomes invaluable in designing underground mine strata control programs. CANMET's Mining Research Laboratories division has compiled a summary of pre- and post-failure mechanical properties of rock types which were tested to provide design data. The 'Rock Properties Data Base' presents the results of these tests, and includes many rock types typical of Canadian mine environments. The data base also contains 'm' and 's' values determined using Hoek and Brown's failure criteria for both pre- and post-failure conditions. 7 refs., 3 tabs., 9 figs., 1 append.

  4. Sparse approximation with bases

    CERN Document Server

    2015-01-01

    This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications.  The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...

  5. Problem Based Game Design

    DEFF Research Database (Denmark)

    Reng, Lars; Schoenau-Fog, Henrik

    2011-01-01

    At Aalborg University’s department of Medialogy, we are utilizing the Problem Based Learning method to encourage students to solve game design problems by pushing the boundaries and designing innovative games. This paper is concerned with describing this method, how students employ it in various ...... projects and how they learn to analyse, design, and develop for innovation by using it. We will present various cases to exemplify the approach and focus on how the method engages students and aspires for innovation in digital entertainment and games.......At Aalborg University’s department of Medialogy, we are utilizing the Problem Based Learning method to encourage students to solve game design problems by pushing the boundaries and designing innovative games. This paper is concerned with describing this method, how students employ it in various...

  6. Technology based Education System

    DEFF Research Database (Denmark)

    Kant Hiran, Kamal; Doshi, Ruchi; Henten, Anders

    2016-01-01

    Abstract - Education plays a very important role for the development of the country. Education has multiple dimensions from schooling to higher education and research. In all these domains, there is invariably a need for technology based teaching and learning tools are highly demanded in the acad......Abstract - Education plays a very important role for the development of the country. Education has multiple dimensions from schooling to higher education and research. In all these domains, there is invariably a need for technology based teaching and learning tools are highly demanded...... in the academic institutions. Thus, there is a need of comprehensive technology support system to cater the demands of all educational actors. Cloud Computing is one such comprehensive and user-friendly technology support environment that is the need of an hour. Cloud computing is the emerging technology that has...

  7. Knowledge based maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Sturm, A [Hamburgische Electacitaets-Werke AG Hamburg (Germany)

    1998-12-31

    The establishment of maintenance strategies is of crucial significance for the reliability of a plant and the economic efficiency of maintenance measures. Knowledge about the condition of components and plants from the technical and business management point of view therefore becomes one of the fundamental questions and the key to efficient management and maintenance. A new way to determine the maintenance strategy can be called: Knowledge Based Maintenance. A simple method for determining strategies while taking the technical condition of the components of the production process into account to the greatest possible degree which can be shown. A software with an algorithm for Knowledge Based Maintenance leads the user during complex work to the determination of maintenance strategies for this complex plant components. (orig.)

  8. Knowledge based maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Sturm, A. [Hamburgische Electacitaets-Werke AG Hamburg (Germany)

    1997-12-31

    The establishment of maintenance strategies is of crucial significance for the reliability of a plant and the economic efficiency of maintenance measures. Knowledge about the condition of components and plants from the technical and business management point of view therefore becomes one of the fundamental questions and the key to efficient management and maintenance. A new way to determine the maintenance strategy can be called: Knowledge Based Maintenance. A simple method for determining strategies while taking the technical condition of the components of the production process into account to the greatest possible degree which can be shown. A software with an algorithm for Knowledge Based Maintenance leads the user during complex work to the determination of maintenance strategies for this complex plant components. (orig.)

  9. Conducting Polymer Based Nanobiosensors

    Directory of Open Access Journals (Sweden)

    Chul Soon Park

    2016-06-01

    Full Text Available In recent years, conducting polymer (CP nanomaterials have been used in a variety of fields, such as in energy, environmental, and biomedical applications, owing to their outstanding chemical and physical properties compared to conventional metal materials. In particular, nanobiosensors based on CP nanomaterials exhibit excellent performance sensing target molecules. The performance of CP nanobiosensors varies based on their size, shape, conductivity, and morphology, among other characteristics. Therefore, in this review, we provide an overview of the techniques commonly used to fabricate novel CP nanomaterials and their biosensor applications, including aptasensors, field-effect transistor (FET biosensors, human sense mimicking biosensors, and immunoassays. We also discuss prospects for state-of-the-art nanobiosensors using CP nanomaterials by focusing on strategies to overcome the current limitations.

  10. Fusion safety data base

    International Nuclear Information System (INIS)

    Laats, E.T.; Hardy, H.A.

    1983-01-01

    The purpose of this Fusion Safety Data Base Program is to provide a repository of data for the design and development of safe commercial fusion reactors. The program is sponsored by the United States Department of Energy (DOE), Office of Fusion Energy. The function of the program is to collect, examine, permanently store, and make available the safety data to the entire US magnetic-fusion energy community. The sources of data will include domestic and foreign fusion reactor safety-related research programs. Any participant in the DOE Program may use the Data Base Program from his terminal through user friendly dialog and can view the contents in the form of text, tables, graphs, or system diagrams

  11. Maintaining Relationship Based Procurement

    Directory of Open Access Journals (Sweden)

    Peter Davis

    2012-11-01

    Full Text Available Alliance and relationship projects are increasingin number and represent a large pool of work. Tobe successful relationship style contracts dependon soft-dollar factors, particularly the participants'ability to work together within an agreedframework, generally they are not based on lowbid tendering. Participants should be prepared todo business in an open environment based ontrust and mutually agreed governance. Theresearch evaluates relationship maintenance inthe implementation phase of constructionalliances - a particular derivative of relationshipstyle contracts. To determine the factors thatcontribute to relationship maintenance forty-nineexperienced Australian alliance projectmanagers were interviewed. The main findingswere; the development of relationships early inthe project form building blocks of success fromwhich relationships are maintained and projectvalue added; quality facilitation plays animportant part in relationship maintenance and ahybrid organisation created as a result of alliancedevelopment overcomes destructiveorganisational boundaries. Relationshipmaintenance is integral to alliance project controland failure to formalise it and pay attention toprocess and past outcomes will undermine analliance project's potential for success.

  12. Location-based Scheduling

    DEFF Research Database (Denmark)

    Andersson, Niclas; Christensen, Knud

    on the market. However, CPM is primarily an activity based method that takes the activity as the unit of focus and there is criticism raised, specifically in the case of construction projects, on the method for deficient management of construction work and continuous flow of resources. To seek solutions...... to the identified limitations of the CPM method, an alternative planning and scheduling methodology that includes locations is tested. Location-based Scheduling (LBS) implies a shift in focus, from primarily the activities to the flow of work through the various locations of the project, i.e. the building. LBS uses...... the graphical presentation technique of Line-of-balance, which is adapted for planning and management of work-flows that facilitates resources to perform their work without interruptions caused by other resources working with other activities in the same location. As such, LBS and Lean Construction share...

  13. Trajectory Based Traffic Analysis

    DEFF Research Database (Denmark)

    Krogh, Benjamin Bjerre; Andersen, Ove; Lewis-Kelham, Edwin

    2013-01-01

    We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point-and-click a......We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point......-and-click analysis, due to a novel and efficient indexing structure. With the web-site daisy.aau.dk/its/spqdemo/we will demonstrate several analyses, using a very large real-world data set consisting of 1.9 billion GPS records (1.5 million trajectories) recorded from more than 13000 vehicles, and touching most...

  14. Carbon Nanotube based Nanotechnolgy

    Science.gov (United States)

    Meyyappan, M.

    2000-10-01

    Carbon nanotube(CNT) was discovered in the early 1990s and is an off-spring of C60(the fullerene or buckyball). CNT, depending on chirality and diameter, can be metallic or semiconductor and thus allows formation of metal-semiconductor and semiconductor-semiconductor junctions. CNT exhibits extraordinary electrical and mechanical properties and offers remarkable potential for revolutionary applications in electronics devices, computing and data storage technology, sensors, composites, storage of hydrogen or lithium for battery development, nanoelectromechanical systems(NEMS), and as tip in scanning probe microscopy(SPM) for imaging and nanolithography. Thus the CNT synthesis, characterization and applications touch upon all disciplines of science and engineering. A common growth method now is based on CVD though surface catalysis is key to synthesis, in contrast to many CVD applications common in microelectronics. A plasma based variation is gaining some attention. This talk will provide an overview of CNT properties, growth methods, applications, and research challenges and opportunities ahead.

  15. Spintronics-based computing

    CERN Document Server

    Prenat, Guillaume

    2015-01-01

    This book provides a comprehensive introduction to spintronics-based computing for the next generation of ultra-low power/highly reliable logic, which is widely considered a promising candidate to replace conventional, pure CMOS-based logic. It will cover aspects from device to system-level, including magnetic memory cells, device modeling, hybrid circuit structure, design methodology, CAD tools, and technological integration methods. This book is accessible to a variety of readers and little or no background in magnetism and spin electronics are required to understand its content.  The multidisciplinary team of expert authors from circuits, devices, computer architecture, CAD and system design reveal to readers the potential of spintronics nanodevices to reduce power consumption, improve reliability and enable new functionality.  .

  16. Knowledge Based Economy Assessment

    OpenAIRE

    Madalina Cristina Tocan

    2012-01-01

    The importance of knowledge-based economy (KBE) in the XXI century is evident. In the article the reflection of knowledge on economy is analyzed. The main point is targeted to the analysis of characteristics of knowledge expression in economy and to the construction of structure of KBE expression. This allows understanding the mechanism of functioning of knowledge economy. The authors highlight the possibility to assess the penetration level of KBE which could manifest itself trough the exist...

  17. Luxury-based Growth

    OpenAIRE

    Shiro Kuwahara

    2006-01-01

    Assuming that there exists a preference for luxury goods and a knowledge spillover from luxury goods production to goods production, this paper constructs an endogenous economic growth model. The model predicts two steady states: one is a steady positive growth state with regard to luxury goods production, and the other is a zero growth state in the absence of luxury goods production. Thus, this study examines the polarization of economies based on luxury goods consumption

  18. Base Stability of Aminocyclopropeniums

    Science.gov (United States)

    2017-11-01

    PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) US Army Research Laboratory Weapons and Materials Research Directorate (ATTN: RDRL-WMM-G) 2800 Powder...Mill Road Adelphi, MD 20783-1138 8. PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-8204 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES...fuel cells to test their utility in anion exchange membranes. While the aminocyclopropeniums showed poor base stability, the cyclopropenium cation

  19. Granular loess classification based

    International Nuclear Information System (INIS)

    Browzin, B.S.

    1985-01-01

    This paper discusses how loess might be identified by two index properties: the granulometric composition and the dry unit weight. These two indices are necessary but not always sufficient for identification of loess. On the basis of analyses of samples from three continents, it was concluded that the 0.01-0.5-mm fraction deserves the name loessial fraction. Based on the loessial fraction concept, a granulometric classification of loess is proposed. A triangular chart is used to classify loess

  20. Educational Process Material Base

    OpenAIRE

    Olga Ozerova; Irina Zabaturina; Vera Kuznetsova; Galina Kovaleva

    2012-01-01

    Based on the data obtained by the Institute for Statistical Studies and the Economics of Knowledge, National Research University - Higher School of Economics Olga Ozerova - Head of the Department for Statistics of Education, Institute for Statistical Studies and the Economics of Knowledge, National Research University - Higher School of Economics, Moscow, Russian Federation. Email: Address: 18 Myasnitskaya St., Moscow, 101000, Russian Federation.Irina Zabaturina - senior resea...

  1. Supramolecular fluorene based materials

    OpenAIRE

    Abbel, R.J.

    2008-01-01

    This thesis describes the use of noncovalent interactions in order to manipulate and control the self-assembly and morphology of electroactive fluorene-based materials. The supramolecular arrangement of p-conjugated polymers and oligomers can strongly influence their electronic and photophysical properties. Therefore, a detailed understanding of such organisation processes is essential for the optimisation of the performance of these materials as applied in optoelectronic devices. In order to...

  2. Graphene-based Nanoelectronics

    Science.gov (United States)

    2013-02-01

    Electrodes were fabricated by drop casting solutions containing the graphene oxide (GO)/CNT/MnAc materials onto titanium (Ti) or stainless steel current...silicon carbide (SiC) substrate can induce a splitting of up to 0.3 eV between the maximum of the valence and minimum of the conduction bands at the...simultaneously hinders the formation of multilayer graphene domains. These results are based on a diffusion-segregation model for carbon precipitation on a Ni

  3. Spiritual-based Leadership

    DEFF Research Database (Denmark)

    Pruzan, Peter

    2015-01-01

    Although far from mainstream, the concept of spiritual-based leadership is emerging as an inclusive and yet highly personal approach to leadership that integrates a leader’s inner perspectives on identity, purpose, responsibility and success with her or his decisions and actions in the outer world...... of business—and therefore it is also emerging as a significant framework for understanding, practicing, communicating and teaching the art and profession of leadership....

  4. Arduino based laser control

    OpenAIRE

    Bernal Muñoz, Ferran

    2015-01-01

    ARDUINO is a vey usefull platform for prototypes. In this project ARDUINO will be used for controling a Semiconductor Tuneable Laser. [ANGLÈS] Diode laser for communications control based on an Arduino board. Temperature control implementation. Software and hardware protection for the laser implementation. [CASTELLÀ] Control de un láser de comunicaciones ópticas desde el ordenador utilizando una placa Arduino. Implementación de un control de temperatura y protección software y hardware ...

  5. Design bases - Concrete structures

    International Nuclear Information System (INIS)

    Diaz-Llanos Ros, M.

    1993-01-01

    The most suitable title for Section 2 is 'Design Bases', which covers not only calculation but also the following areas: - Structural design concepts. - Project criteria. - Material specifications. These concepts are developed in more detail in the following sections. The numbering in this document is neither complete nor hierarchical since, for easier cross referencing, it corresponds to the paragraphs of Eurocode 2 Part 1 (hereinafter 'EUR-2') which are commented on. (author)

  6. Biosphere data base revision

    International Nuclear Information System (INIS)

    Bergstroem, U.; Andersson, K.; Sundblad, B.

    1985-12-01

    The turnover of long-lived radionuclides in the biosphere has been modelled some time ago and the exposure to man was calculated. The nuclides were long-lived actinides and fission products leaking from a simulated deep rock repository for spent nuclear fuel. The data base for these calculations has been updated in the present work and in addition a number of nuclides that were not included in the earlier work have been treated. (G.B.)

  7. Air Force Smart Bases

    Science.gov (United States)

    2017-10-19

    initiates notification to all personnel on the base, the giant voice announces a lock down, everyone’s smart device shows an alarm requesting...location of the detected sound, they easily find a hunter and send his picture back to the IOC, where the hunter’s identity is verified through facial...computer goes into sleep mode, the thermostat goes back to unoccupied mode and his door locks as he walks through. Meanwhile over in the IOC

  8. Polypeptide based hydrogels

    OpenAIRE

    Hanay, Saltuk

    2018-01-01

    There is a need for biocompatible, biodegradable, 3-D printable and stable hydrogels especially in the areas of tissue engineering, drug delivery, bio-sensing technologies and antimicrobial coatings. The main aim of this Ph.D. work was to fabricate polypeptide based hydrogel which may find a potential application in those fields. Focusing on tyrosine or tryptophan-containing copolypeptides prepared by NCarboxyanhydride (NCA) polymerizations, three different crosslinking strategies have been t...

  9. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  10. Knowledge-based utility

    International Nuclear Information System (INIS)

    Chwalowski, M.

    1997-01-01

    This presentation provides industry examples of successful marketing practices by companies facing deregulation and competition. The common thread through the examples is that long term survival of today's utility structure is dependent on the strategic role of knowledge. As opposed to regulated monopolies which usually own huge physical assets and have very little intelligence about their customers, unregulated enterprises tend to be knowledge-based, characterized by higher market value than book value. A knowledge-based enterprise gathers data, creates information and develops knowledge by leveraging it as a competitive weapon. It institutionalizes human knowledge as a corporate asset for use over and over again by the use of databases, computer networks, patents, billing, collection and customer services (BCCS), branded interfaces and management capabilities. Activities to become knowledge-based such as replacing inventory/fixed assets with information about material usage to reduce expenditure and achieve more efficient operations, and by focusing on integration and value-adding delivery capabilities, were reviewed

  11. Microbead agglutination based assays

    KAUST Repository

    Kodzius, Rimantas

    2013-01-21

    We report a simple and rapid room temperature assay for point-of-care (POC) testing that is based on specific agglutination. Agglutination tests are based on aggregation of microbeads in the presence of a specific analyte thus enabling the macroscopic observation. Such tests are most often used to explore antibody-antigen reactions. Agglutination has been used for protein assays using a biotin/streptavidin system as well as a hybridization based assay. The agglutination systems are prone to selftermination of the linking analyte, prone to active site saturation and loss of agglomeration at high analyte concentrations. We investigated the molecular target/ligand interaction, explaining the common agglutination problems related to analyte self-termination, linkage of the analyte to the same bead instead of different microbeads. We classified the agglutination process into three kinds of assays: a two- component assay, a three-component assay and a stepped three- component assay. Although we compared these three kinds of assays for recognizing DNA and protein molecules, the assay can be used for virtually any molecule, including ions and metabolites. In total, the optimized assay permits detecting analytes with high sensitivity in a short time, 5 min, at room temperature. Such a system is appropriate for POC testing.

  12. As bases do petismo

    Directory of Open Access Journals (Sweden)

    David Samuels

    2004-10-01

    Full Text Available A partir dos dados do ESEB de 2002 o autor realiza um estudo das bases eleitorais do PT e de hipóteses sobre a natureza do petismo. Através de técnicas estatísticas multivariadas, são testadas relações do petismo com variáveis demográficas, socioeconômicas e variáveis relativas a questões políticas específicas. Os resultados apontam que apenas a escolaridade tem uma associação específica com o petismo, com implicações para o seu comportamento sócio-político.Based on the results of the 2002 Brazilian Electoral Study, the author analyses the electoral bases of the Worker´s Party and the factors associated with the "petismo". The relationships between the "petismo"and the socioeconomic, demographic and political variables are tested using multivariate analysis. The results indicate that the only "social category"associated with "petismo"is level of education, and it has clear implications to their social and political behavior.

  13. Value-based genomics.

    Science.gov (United States)

    Gong, Jun; Pan, Kathy; Fakih, Marwan; Pal, Sumanta; Salgia, Ravi

    2018-03-20

    Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

  14. Nanoplatform-based molecular imaging

    National Research Council Canada - National Science Library

    Chen, Xiaoyuan

    2011-01-01

    "Nanoplathform-Based Molecular Imaging provides rationale for using nanoparticle-based probes for molecular imaging, then discusses general strategies for this underutilized, yet promising, technology...

  15. Polyolefin-Based Aerogels

    Science.gov (United States)

    Lee, Je Kyun; Gould, George

    2012-01-01

    An organic polybutadiene (PB) rubberbased aerogel insulation material was developed that will provide superior thermal insulation and inherent radiation protection, exhibiting the flexibility, resiliency, toughness, and durability typical of the parent polymer, yet with the low density and superior insulation properties associated with the aerogels. The rubbery behaviors of the PB rubber-based aerogels are able to overcome the weak and brittle nature of conventional inorganic and organic aerogel insulation materials. Additionally, with higher content of hydrogen in their structure, the PB rubber aerogels will also provide inherently better radiation protection than those of inorganic and carbon aerogels. Since PB rubber aerogels also exhibit good hydrophobicity due to their hydrocarbon molecular structure, they will provide better performance reliability and durability as well as simpler, more economic, and environmentally friendly production over the conventional silica or other inorganic-based aerogels, which require chemical treatment to make them hydrophobic. Inorganic aerogels such as silica aerogels demonstrate many unusual and useful properties. There are several strategies to overcoming the drawbacks associated with the weakness and brittleness of silica aerogels. Development of the flexible fiber-reinforced silica aerogel composite blanket has proven one promising approach, providing a conveniently fielded form factor that is relatively robust toward handling in industrial environments compared to silica aerogel monoliths. However, the flexible silica aerogel composites still have a brittle, dusty character that may be undesirable, or even intolerable, in certain applications. Although the cross-linked organic aerogels such as resorcinol-formaldehyde (RF), polyisocyanurate, and cellulose aerogels show very high impact strength, they are also very brittle with little elongation (i.e., less rubbery). Also, silica and carbon aerogels are less efficient

  16. Characteristics Data Base

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, E.D.; Moore, R.S. (Automated Sciences Group, Inc., Oak Ridge, TN (USA))

    1990-08-01

    The LWR Serial Numbers Database System (SNDB) contains detailed data about individual, historically discharged LWR spent fuel assemblies. This data includes the reactor where used, the year the assemblies were discharged, the pool where they are currently stored, assembly type, burnup, weight, enrichment, and an estimate of their radiological properties. This information is distributed on floppy disks to users in the nuclear industry to assist in planning for the permanent nuclear waste repository. This document describes the design and development of the SNDB. It provides a complete description of the file structures and an outline of the major code modules. It serves as a reference for a programmer maintaining the system, or for others interested in the technical detail of this database. This is the initial version of the SNDB. It contains historical data through December 31, 1987, obtained from the Energy Information Administration (EIA). EIA obtains the data from the utility companies via the RW-859 Survey Form. It evaluates and standardizes the data and distributes the resulting batch level database as a large file on magnetic tape. The Characteristics Data Base obtains this database for use in the LWR Quantities Data Base. Additionally, the CDB obtains the individual assembly level detail from EIA for use in the SNDB. While the Quantities Data Base retains only the level of detail necessary for its reporting, the SNDB does retain and use the batch level data to assist in the identification of a particular assembly serial number. We expect to update the SNDB on an annual basis, as new historical data becomes available.

  17. Vision-based interaction

    CERN Document Server

    Turk, Matthew

    2013-01-01

    In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, there has been an increasing interest in computer vision as an input modality in the context of human-computer interaction. Such vision-based interaction can endow interactive systems with visual capabilities similar to those important to human-human interaction, in order to perceive non-verbal cues and incorporate this information in applications such

  18. Knowledge based Entrepreneurship

    DEFF Research Database (Denmark)

    Heebøll, John

    This book is dedicated enterprising people with a technical or a scientific background who consider commercializing ideas and inventions within their field of expertise via a new business activity or a new company. It aims at distilling experiences from many successful and not so successful start......-up ventures from the Technical University of Denmark, 1988 – 2008 into practical, portable knowledge that can be used by future knowledge-based entrepreneurs to set up new companies efficiently or to stay away from it; to do what’s needed and avoid the pitfalls....

  19. Polymerization Using Phosphazene Bases

    KAUST Repository

    Zhao, Junpeng

    2015-09-01

    In the recent rise of metal-free polymerization techniques, organic phosphazene superbases have shown their remarkable strength as promoter/catalyst for the anionic polymerization of various types of monomers. Generally, the complexation of phosphazene base with the counterion (proton or lithium cation) significantly improves the nucleophilicity of the initiator/chain end resulting in highly enhanced polymerization rates, as compared with conventional metalbased initiating systems. In this chapter, the general features of phosphazenepromoted/catalyzed polymerizations and the applications in macromolecular engineering (synthesis of functionalized polymers, block copolymers, and macromolecular architectures) are discussed with challenges and perspectives being pointed out.

  20. Web Based Customized Design

    OpenAIRE

    Moi, Morten Benestad

    2013-01-01

    This thesis studies the methods needed to create a web based application to remotely customize a CAD model. This includes customizing a CAD model by using a graphical user interface to be able to remotely control the inputs to- and outputs from the model in NX, and to get the result sent back to the user. Using CAD systems such as NX requires intensive training, is often a slow process and gives a lot of room for errors. An intuitive, simple user interface will eliminate the need for CAD trai...

  1. Location-based games

    DEFF Research Database (Denmark)

    Ejsing-Duun, Stine

    In this dissertation, it is explored which prerequisites are necessary in location-based games (LBGs) to make meaningful the meeting between players and spatiality with an emphasis on physical locations. Throughout the dissertation, it has been shown that LBGs affect players’ perception of and be...... possible. The practical contribution is my creation of the LBG Visions of Sara. People continue to play this game in Odense more than two years after its launch, and DJEEO uses it as a showcase, enabling the company to sell similar LBGs....

  2. LIGHTWEIGHT CONCRETE BASED GRANSHLAK

    Directory of Open Access Journals (Sweden)

    NETESA M. I.

    2016-02-01

    Full Text Available Raising of problem. Concrete advisable to obtain a low strength with local secondary resources for recycling and reduce the environmental burden on the environment. But it is important to design such concrete compositions with a reduced flow of cement. It is known that the coefficient of efficiency of use of cement in the concrete of the heavy and B10 is less than about 0.5, which is almost two times smaller than in class B15 concrete and above. Even lower coefficient of efficiency in light concrete cement low strength. Therefore, it is important to find patterns determining the composition of lightweight concrete based on local-products industry with more efficient use of cement in them. Purpose.. Based on the analysis of earlier research results, including with the use of methods of mathematical planning of experiments to determine the concrete contents, which can provide the requirements for the underlying layers of the floor, the compressive strength of which should correspond to the class B5. It is important to provide the required strength at minimum flow of the cement, which is the most expensive and energy-intensive part of concrete. Conclusion. Analysis of the test results of control samples of concrete in 28-day-old, the following laws. The required tensile strength of concrete compressive strength of 7.0 MPa can be obtained in the test range when used in formulations as a filler as the Dnieper hydroelectric power station fly ash and tailings Krivoy Rog iron ore YuGOK. To ensure providing the required characteristic strength of the concrete in the underlying layers of the floor is advisable to use a nominal composition per cubic meter of concrete: cement 160 kg granshlaka Plant named after Petrovsky, 675 kg of fly ash Dnieper HPP 390 kg, 400 kg of sand, 230 liters of water. Thus, while ensuring rational grain composition components can obtain the desired strength lightweight concrete based granshlaka plant Petrovsky, using as fillers

  3. Accelerator-based BNCT.

    Science.gov (United States)

    Kreiner, A J; Baldo, M; Bergueiro, J R; Cartelli, D; Castell, W; Thatar Vento, V; Gomez Asoia, J; Mercuri, D; Padulo, J; Suarez Sandin, J C; Erhardt, J; Kesque, J M; Valda, A A; Debray, M E; Somacal, H R; Igarzabal, M; Minsky, D M; Herrera, M S; Capoulat, M E; Gonzalez, S J; del Grosso, M F; Gagetti, L; Suarez Anzorena, M; Gun, M; Carranza, O

    2014-06-01

    The activity in accelerator development for accelerator-based BNCT (AB-BNCT) both worldwide and in Argentina is described. Projects in Russia, UK, Italy, Japan, Israel, and Argentina to develop AB-BNCT around different types of accelerators are briefly presented. In particular, the present status and recent progress of the Argentine project will be reviewed. The topics will cover: intense ion sources, accelerator tubes, transport of intense beams, beam diagnostics, the (9)Be(d,n) reaction as a possible neutron source, Beam Shaping Assemblies (BSA), a treatment room, and treatment planning in realistic cases. © 2013 Elsevier Ltd. All rights reserved.

  4. Cellular based cancer vaccines

    DEFF Research Database (Denmark)

    Hansen, M; Met, Ö; Svane, I M

    2012-01-01

    Cancer vaccines designed to re-calibrate the existing host-tumour interaction, tipping the balance from tumor acceptance towards tumor control holds huge potential to complement traditional cancer therapies. In general, limited success has been achieved with vaccines composed of tumor...... to transiently affect in vitro migration via autocrine receptor-mediated endocytosis of CCR7. In the current review, we discuss optimal design of DC maturation focused on pre-clinical as well as clinical results from standard and polarized dendritic cell based cancer vaccines....

  5. WAP - based telemedicine applications

    International Nuclear Information System (INIS)

    Hung, K.; Zhang, Y.T.

    2001-01-01

    Telemedicine refers to the utilization of telecommunication technology for medical diagnosis, treatment, and patient care. Its aim is to provide expert-based health care to remote sites through telecommunication and information technologies. The significant advances in technologies have enabled the introduction of a broad range of telemedicine applications, which are supported by computer networks, wireless communication, and information superhighway. For example, some hospitals are using tele-radiology for remote consultation. Such a system includes medical imaging devices networked with computers and databases. Another growing area is patient monitoring, in which sensors are used to acquire biomedical signals, such as electrocardiogram (ECG), blood pressure, and body temperature, from a remote patient, who could be in bed or moving freely. The signals are then relayed to remote systems for viewing and analysis. Telemedicine can be divided into two basic modes of operations: real-time mode, in which the patient data can be accessed remotely in real-time, and store-and-forward mode, in which the acquired data does not have to be accessed immediately. In the recent years, many parties have demonstrated various telemedicine applications based on the Internet and cellular phone as these two fields have been developing rapidly. A current, recognizable trend in telecommunication is the convergence of wireless communication and computer network technologies. This has been reflected in recently developed telemedicine systems. For example, in 1998 J. Reponen, et al. have demonstrated transmission and display of computerized tomography (CT) examinations using a remote portable computer wirelessly connected to a computer network through TCP/IP on a GSM cellular phone. Two years later, they carried out the same tests with a GSM-based wireless personal digital assistant (PDA). The WAP (Wireless Application Protocol) Forum was founded in 1997 to create a global protocol

  6. Mars base buildup scenarios

    International Nuclear Information System (INIS)

    Blacic, J.D.

    1985-01-01

    Two surface base build-up scenarios are presented in order to help visualize the mission and to serve as a basis for trade studies. In the first scenario, direct manned landings on the Martian surface occur early in the missions and scientific investigation is the main driver and rationale. In the second scenario, early development of an infrastructure to exploite the volatile resources of the Martian moons for economic purposes is emphasized. Scientific exploration of the surface is delayed at first, but once begun develops rapidly aided by the presence of a permanently manned orbital station

  7. Agent-Based Optimization

    CERN Document Server

    Jędrzejowicz, Piotr; Kacprzyk, Janusz

    2013-01-01

    This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve  difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

  8. Refractive index based measurements

    DEFF Research Database (Denmark)

    2014-01-01

    In a method for performing a refractive index based measurement of a property of a fluid such as chemical composition or temperature by observing an apparent angular shift in an interference fringe pattern produced by back or forward scattering interferometry, ambiguities in the measurement caused...... by the apparent shift being consistent with one of a number of numerical possibilities for the real shift which differ by 2n are resolved by combining measurements performed on the same sample using light paths therethrough of differing lengths....

  9. Sustainability Base Construction Update

    Science.gov (United States)

    Mewhinney, Michael

    2012-01-01

    Construction of the new Sustainability Base Collaborative support facility, expected to become the highest performing building in the federal government continues at NASA's Ames Research Center, Moffet Field, Calif. The new building is designed to achieve a platinum rating under the leadership in Energy and Environment Design (LEED) new construction standards for environmentally sustainable construction developed by the U. S. Green Building Council, Washington, D. C. When completed by the end of 2011, the $20.6 million building will feature near zero net energy consumption, use 90 percent less potable water than conventionally build buildings of equivalent size, and will result in reduced building maintenance costs.

  10. Chitosan-based nanocomposites

    CSIR Research Space (South Africa)

    Kesavan Pillai, Sreejarani

    2012-08-01

    Full Text Available , and hygiene devices. They thus represent a strong and emerging answer for improved and eco-friendly materials. This chapter reviews the recent developments in the area of chitosan-based nanocomposites, with a special emphasis on clay-containing nanocomposites...-sized mineral fillers like silica, talc, and clay are added to reduce the cost and improve chitosan’s performance in some way. However, the mechanical properties such as elongation at break and tensile strength of these composites decrease with the incorporation...

  11. Droplet based microfluidics

    International Nuclear Information System (INIS)

    Seemann, Ralf; Brinkmann, Martin; Pfohl, Thomas; Herminghaus, Stephan

    2012-01-01

    Droplet based microfluidics is a rapidly growing interdisciplinary field of research combining soft matter physics, biochemistry and microsystems engineering. Its applications range from fast analytical systems or the synthesis of advanced materials to protein crystallization and biological assays for living cells. Precise control of droplet volumes and reliable manipulation of individual droplets such as coalescence, mixing of their contents, and sorting in combination with fast analysis tools allow us to perform chemical reactions inside the droplets under defined conditions. In this paper, we will review available drop generation and manipulation techniques. The main focus of this review is not to be comprehensive and explain all techniques in great detail but to identify and shed light on similarities and underlying physical principles. Since geometry and wetting properties of the microfluidic channels are crucial factors for droplet generation, we also briefly describe typical device fabrication methods in droplet based microfluidics. Examples of applications and reaction schemes which rely on the discussed manipulation techniques are also presented, such as the fabrication of special materials and biophysical experiments.

  12. DVD Based Electronic Pulser

    International Nuclear Information System (INIS)

    Morris, Scott J.; Pratt, Rick M.; Hughes, Michael A.; Kouzes, Richard T.; Pitts, W K.; Robinson, Eric E.

    2005-01-01

    This paper describes the design, construction, and testing of a DVD based electronic pulser system (DVDEPS). Such a device is used to generate pulse streams for simulation of both gamma and neutron detector systems. The DVDEPS reproduces a random pulse stream of a full HPGe spectrum as well as a digital pulse stream representing the output of a neutron multiplicity detector. The exchangeable DVD media contains over an hour of data for both detector systems and can contain an arbitrary gamma spectrum and neutron pulse stream. The data is written to the DVD using a desktop computer program from either actual or simulated spectra. The targeted use of the DVDEPS is authentication or validation of monitoring equipment for non-proliferation purposes, but it is also of general use whenever a complex data stream is required. The DVD based pulser combines the storage capacity and simplicity of DVD technology with commonly available electronic components to build a relatively inexpensive yet highly capable testing instrument

  13. Evidence-based surgery

    Directory of Open Access Journals (Sweden)

    Miran Rems

    2007-04-01

    Full Text Available Background: Surgery is setting a new ground by the reign of evidence that was brought up by the Evidence Based Medicine (EBM. While experiences and opinion of an expert count the least by the principles of EBM, randomized controlled trials (RCT and other comparative studies have gained their importance. Recommendations that were included in guidelines represent a demanding shift in surgeon’s professional thinking. Their thinking and classical education have not yet been completely based on the results of such studies and are still very very much master-pupil centred. Assessment of someone’s own experiences is threatened by objectivity as negative experiences get recorded in deeper memory. Randomized studies and meta-analyses do appear also in surgery. However, they demand an extra knowledge about critical assessment.Conclusions: Setting a patient to the foreground brings a surgeon’s decision to the field of EBM. The process has already begun and cannot be avoided. Decision hierarchy moves from the experience field to the evidence territory but to a lesser extent when compared to the rest of medicine. There exist objective restrictions with approving a new paradigm. However, these should not stop the process of EBM implementation. Finally, there is an ethic issue to be considered. Too slow activities in research, education and critical assessment can bring the surgeon to the position when a well-informed patient loses his/her trust.

  14. Microlaser-based displays

    Science.gov (United States)

    Bergstedt, Robert; Fink, Charles G.; Flint, Graham W.; Hargis, David E.; Peppler, Philipp W.

    1997-07-01

    Laser Power Corporation has developed a new type of projection display, based upon microlaser technology and a novel scan architecture, which provides the foundation for bright, extremely high resolution images. A review of projection technologies is presented along with the limitations of each and the difficulties they experience in trying to generate high resolution imagery. The design of the microlaser based projector is discussed along with the advantage of this technology. High power red, green, and blue microlasers have been designed and developed specifically for use in projection displays. These sources, in combination with high resolution, high contrast modulator, produce a 24 bit color gamut, capable of supporting the full range of real world colors. The new scan architecture, which reduces the modulation rate and scan speeds required, is described. This scan architecture, along with the inherent brightness of the laser provides the fundamentals necessary to produce a 5120 by 4096 resolution display. The brightness and color uniformity of the display is excellent, allowing for tiling of the displays with far fewer artifacts than those in a traditionally tiled display. Applications for the display include simulators, command and control centers, and electronic cinema.

  15. SPACE BASED INTERCEPTOR SCALING

    Energy Technology Data Exchange (ETDEWEB)

    G. CANAVAN

    2001-02-01

    Space Based Interceptor (SBI) have ranges that are adequate to address rogue ICBMs. They are not overly sensitive to 30-60 s delay times. Current technologies would support boost phase intercept with about 150 interceptors. Higher acceleration and velocity could reduce than number by about a factor of 3 at the cost of heavier and more expensive Kinetic Kill Vehicles (KKVs). 6g SBI would reduce optimal constellation costs by about 35%; 8g SBI would reduce them another 20%. Interceptor ranges fall rapidly with theater missile range. Constellations increase significantly for ranges under 3,000 km, even with advanced interceptor technology. For distributed launches, these estimates recover earlier strategic scalings, which demonstrate the improved absentee ratio for larger or multiple launch areas. Constellations increase with the number of missiles and the number of interceptors launched at each. The economic estimates above suggest that two SBI per missile with a modest midcourse underlay is appropriate. The SBI KKV technology would appear to be common for space- and surface-based boost phase systems, and could have synergisms with improved midcourse intercept and discrimination systems. While advanced technology could be helpful in reducing costs, particularly for short range theater missiles, current technology appears adequate for pressing rogue ICBM, accidental, and unauthorized launches.

  16. Challenge Based Innovation gala

    CERN Multimedia

    CERN. Geneva; Utriainen, Tuuli Maria; Toivonen, Harri; Nordberg, Markus

    2014-01-01

    Challenge Based Innovation gala   There’s a new experiment starting in CERN called IdeaLab where we work together with detector R&D researchers to help them to bridge their knowledge into a more human, societally oriented context. Currently we are located in B153, but will move our activities to a new facility next to the Globe in May 2014. One of our first pilot projects is a 5 month course CBI (Challenge Based Innovation) where two multidisciplinary student teams join forces with Edusafe & TALENT projects at CERN. Their goal is to discover what kind of tools for learning could be created in collaboration with the two groups. After months of user interviews and low resolution prototyping they are ready to share the results with us in the form of an afternoon gala. We warmly welcome you to join us to see the students' results and experience the prototypes they have conceived. The event is in three parts, you are welcome to visit all of them,...

  17. [Competence based medical education].

    Science.gov (United States)

    Bernabó, Jorge G; Buraschi, Jorge; Olcese, Juan; Buraschi, María; Duro, Eduardo

    2007-01-01

    The strategy of curriculum planning in the majority of the Schools of Medicine has shifted, in the past years, from curriculum models based in contents to outcome oriented curricula. Coincidently the interest in defining and evaluating the clinical competences that a graduate must have has grown. In our country, and particularly in the Associated Hospitals belonging to the Unidad Regional de Enseñanza IV of the UBA School of Medicine, evidence has been gathered showing that the acquisition of clinical competences during the grade is in general insufficient. The foundations and characteristics of PREM (Programa de Requisitos Esenciales Mínimos) are described. PREM is a tool to promote the apprenticeship of abilities and necessary skills for the practice of medicine. The objective of the program is to promote the apprenticeship of a well defined list of core competences considered indispensable for a general practitioner. An outcome oriented curriculum with a clear definition of the expected knowledge, skills and attitudes of a graduate of the programme, the promotion of learning experiences centered in the practice and evaluation tools based in direct observation of the student's performance should contribute to close the gap between what the Medicine Schools traditionally teach and evaluate, and what the doctor needs to know and needs to do to perform correctly its profession.

  18. Constraint-based reachability

    Directory of Open Access Journals (Sweden)

    Arnaud Gotlieb

    2013-02-01

    Full Text Available Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.

  19. Metasurface-Based Polarimeters

    Directory of Open Access Journals (Sweden)

    Fei Ding

    2018-04-01

    Full Text Available The state of polarization (SOP is an inherent property of light that can be used to gain crucial information about the composition and structure of materials interrogated with light. However, the SOP is difficult to experimentally determine since it involves phase information between orthogonal polarization states, and is uncorrelated with the light intensity and frequency, which can be easily determined with photodetectors and spectrometers. Rapid progress on optical gradient metasurfaces has resulted in the development of conceptually new approaches to the SOP characterization. In this paper, we review the fundamentals of and recent developments within metasurface-based polarimeters. Starting by introducing the concepts of generalized Snell’s law and Stokes parameters, we explain the Pancharatnam–Berry phase (PB-phase which is instrumental for differentiating between orthogonal circular polarizations. Then we review the recent progress in metasurface-based polarimeters, including polarimeters, spectropolarimeters, orbital angular momentum (OAM spectropolarimeters, and photodetector integrated polarimeters. The review is ended with a short conclusion and perspective for future developments.

  20. Risk-based safety indicators

    International Nuclear Information System (INIS)

    Szikszai, T.

    1997-01-01

    The presentation discusses the following issues: The objectives of the risk-based indicator programme. The characteristics of the risk-based indicators. The objectives of risk-based safety indicators - in monitoring safety; in PSA applications. What indicators? How to produce the risk based indicators? PSA requirements

  1. MS Based Metabonomics

    Energy Technology Data Exchange (ETDEWEB)

    Want, Elizabeth J.; Metz, Thomas O.

    2010-03-01

    Metabonomics is the latest and least mature of the systems biology triad, which also includes genomics and proteomics, and has its origins in the early orthomolecular medicine work pioneered by Linus Pauling and Arthur Robinson. It was defined by Nicholson and colleagues in 1999 as the quantitative measurement of perturbations in the metabolite complement of an integrated biological system in response to internal or external stimuli, and is often used today to describe many non-global types of metabolite analyses. Applications of metabonomics are extensive and include toxicology, nutrition, pharmaceutical research and development, physiological monitoring and disease diagnosis. For example, blood samples from millions of neonates are tested routinely by mass spectrometry (MS) as a diagnostic tool for inborn errors of metabolism. The metabonome encompasses a wide range of structurally diverse metabolites; therefore, no single analytical platform will be sufficient. Specialized sample preparation and detection techniques are required, and advances in NMR and MS technologies have led to enhanced metabonome coverage, which in turn demands improved data analysis approaches. The role of MS in metabonomics is still evolving as instrumentation and software becomes more sophisticated and as researchers realize the strengths and limitations of current technology. MS offers a wide dynamic range, high sensitivity, and reproducible, quantitative analysis. These attributes are essential for addressing the challenges of metabonomics, as the range of metabolite concentrations easily exceeds nine orders of magnitude in biofluids, and the diversity of molecular species ranges from simple amino and organic acids to lipids and complex carbohydrates. Additional challenges arise in generating a comprehensive metabolite profile, downstream data processing and analysis, and structural characterization of important metabolites. A typical workflow of MS-based metabonomics is shown in Figure

  2. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  3. Plasma based accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Caldwell, Allen [Max-Planck-Institut fuer Physik, Muenchen (Germany)

    2015-05-01

    The concept of laser-induced plasma wakefields as a technique to accelerate charged particles was introduced 35 years ago as a means to go beyond the accelerating gradients possible with metallic cavities supporting radio frequency electromagnetic fields. Significant developments in laser technology have made possible the pulse intensity needed to realize this concept, and rapid progress is now underway in the realization of laser-driven plasma wakefield acceleration. It has also been realized that similar accelerating gradients can be produced by particle beams propagating in plasmas, and experimental programs have also been undertaken to study this possibility. Positive results have been achieved with electron-driven plasma wakefields, and a demonstration experiment with proton-driven wakefields is under construction at CERN. The concepts behind these different schemes and their pros and cons are described, as well as the experimental results achieved. An outlook for future practical uses of plasma based accelerators will also be given.

  4. Gossip-Based Broadcast

    Science.gov (United States)

    Leitão, João; Pereira, José; Rodrigues, Luís

    Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives on large scale peer-to-peer networks. Epidemic protocols are scalable because they distribute the load among all nodes in the system and resilient because they have an intrinsic level of redundancy that masks node and network failures. This chapter provides an introduction to gossip-based broadcast on large-scale unstructured peer-to-peer overlay networks: it surveys the main results in the field, discusses techniques to build and maintain the overlays that support efficient dissemination strategies, and provides an in-depth discussion and experimental evaluation of two concrete protocols, named HyParView and Plumtree.

  5. Sensory bases of navigation.

    Science.gov (United States)

    Gould, J L

    1998-10-08

    Navigating animals need to know both the bearing of their goal (the 'map' step), and how to determine that direction (the 'compass' step). Compasses are typically arranged in hierarchies, with magnetic backup as a last resort when celestial information is unavailable. Magnetic information is often essential to calibrating celestial cues, though, and repeated recalibration between celestial and magnetic compasses is important in many species. Most magnetic compasses are based on magnetite crystals, but others make use of induction or paramagnetic interactions between short-wavelength light and visual pigments. Though odors may be used in some cases, most if not all long-range maps probably depend on magnetite. Magnetitebased map senses are used to measure only latitude in some species, but provide the distance and direction of the goal in others.

  6. Graphene based biosensors

    Energy Technology Data Exchange (ETDEWEB)

    Gürel, Hikmet Hakan, E-mail: hhakan.gurel@kocaeli.edu.tr [Kocaeli University, Kocaeli (Turkey); Salmankurt, Bahadır [Sakarya University, Sakarya (Turkey)

    2016-03-25

    Nanometer-sized graphene as a 2D material has unique chemical and electronic properties. Because of its unique physical, chemical, and electronic properties, its interesting shape and size make it a promising nanomaterial in many biological applications. It is expected that biomaterials incorporating graphene will be developed for the graphene-based drug delivery systems and biomedical devices. The interactions of biomolecules and graphene are long-ranged and very weak. Development of new techniques is very desirable for design of bioelectronics sensors and devices. In this work, we present first-principles calculations within density functional theory to calculate effects of charging on nucleobases on graphene. It is shown that how modify structural and electronic properties of nucleobases on graphene by applied charging.

  7. Integrated data base program

    International Nuclear Information System (INIS)

    Notz, K.J.

    1981-01-01

    The IDB Program provides direct support to the DOE Nuclear Waste Management and Fuel Cycle Programs and their lead sites and support contractors by providing and maintaining a current, integrated data base of spent fuel and radioactive waste inventories and projections. All major waste types (HLW, TRU, and LLW) and sources (government, commerical fuel cycle, and I/I) are included. A major data compilation was issued in September, 1981: Spent Fuel and Radioactive Waste Inventories and Projections as of December 31, 1980, DOE/NE-0017. This report includes chapters on Spent Fuel, HLW, TRU Waste, LLW, Remedial Action Waste, Active Uranium Mill Tailings, and Airborne Waste, plus Appendices with more detailed data in selected areas such as isotopics, radioactivity, thermal power, projections, and land usage. The LLW sections include volumes, radioactivity, thermal power, current inventories, projected inventories and characteristics, source terms, land requirements, and a breakdown in terms of government/commercial and defense/fuel cycle/I and I

  8. Nickel base alloys

    International Nuclear Information System (INIS)

    Gibson, R.C.; Korenko, M.K.

    1980-01-01

    Nickel based alloy, the characteristic of which is that it mainly includes in percentages by weight: 57-63 Ni, 7-18 Cr, 10-20 Fe, 4-6 Mo, 1-2 Nb, 0.2-0.8 Si, 0.01-0.05 Zr, 1.0-2.5 Ti, 1.0-2.5 Al, 0.02-0.06 C and 0.002-0.015 B. The aim is to create new nickel-chromium alloys, hardened in a solid solution and by precipitation, that are stable, exhibit reduced swelling and resistant to plastic deformation inside the reactor. These alloys of the gamma prime type have improved mechanical strengthm swelling resistance, structural stability and welding properties compared with Inconel 625 [fr

  9. Rate based failure detection

    Science.gov (United States)

    Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

    2018-01-02

    This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or data paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.

  10. Behavior based safety

    International Nuclear Information System (INIS)

    Sudhikumaran, T.V.; Mehta, S.C.; Goyal, D.K.

    2009-01-01

    Behaviour Based Safety (popularly known as BBS) is a new methodology for achieving injury free work place and total Safety Culture. BBS is successfully being implemented and is being practiced as a work methodology for achieving a loss and injury free work environment and work practice. Through BBS, it was brought out that the root causes of all Industrial accidents some how originate from the 'at risk' behaviour of some individual or group of individuals at some level. The policy of NPCIL is to excel in the field of Industrial and Fire Safety in comparison to international standards. This article indents to bring out the various parameters helping in installing BBS programme at any plant. (author)

  11. Fuel cycle based safeguards

    International Nuclear Information System (INIS)

    De Montmollin, J.M.; Higinbotham, W.A.; Gupta, D.

    1985-07-01

    In NPT safeguards the same model approach and absolute-quantity inspection goals are applied at present to all similar facilities, irrespective of the State's fuel cycle. There is a continuing interest and activity on the part of the IAEA in new NPT safeguards approaches that more directly address a State's nuclear activities as a whole. This fuel cycle based safeguards system is expected to a) provide a statement of findings for the entire State rather than only for individual facilities; b) allocate inspection efforts so as to reflect more realistically the different categories of nuclear materials in the different parts of the fuel cycle and c) provide more timely and better coordinated information on the inputs, outputs and inventories of nuclear materials in a State. (orig./RF) [de

  12. Bases para proyectiles dirigidos

    Directory of Open Access Journals (Sweden)

    Editorial, Equipo

    1959-03-01

    Full Text Available Aunque actualmente no se ha llegado a una línea general de métodos o sistemas que gobiernen un tipo característico de rampa y servicios auxiliares necesarios para el lanzamiento al espacio de proyectiles dirigidos a grandes alturas y distancias, las experiencias obtenidas en diferentes ensayos, utilizando distintos tipos de proyectiles y trayectorias balísticas, han sentado toda una serie de procedimientos, datos y conclusiones de gran valor balístico que, aun teniendo en cuenta la continua evolución del proyectil, sus formas, combustibles y alcances, se conocen ya, con bastante aproximación, las condiciones mínimas que ha de reunir una base dedicada a este tipo de lanzamientos.

  13. Situation based housing

    DEFF Research Database (Denmark)

    Duelund Mortensen, Peder; Welling, Helen; Wiell Nordberg, Lene

    2007-01-01

    of the average family's lifestyle. These dwellings were ground-breaking when they were built, but today are clearly a product of their time. The reaction to functionalism and the postwar mass production gave rise to flexible dwelling with countless possibilities for room division. The housing of this period has...... characteristics which in the long run have proven to be unfortunate both in terms in terms of durability and architectural quality. Today there is a focus on the development of more open and functionally non-determined housing. A number of new housing schemes in and around Copenhagen reveal a variety...... of approaches to these goals. This working paper reviews not only a selection of new housing types, but also dwellings from the past, which each contain an aspect of changeability. Our study is based on information from users in the selected housing schemes, gathered from questionnaires, information about...

  14. Liaison based assembly design

    Energy Technology Data Exchange (ETDEWEB)

    Ames, A.; Kholwadwala, D.; Wilson, R.H.

    1996-12-01

    Liaison Based Assembly Design extends the current information infrastructure to support design in terms of kinematic relationships between parts, or liaisons. These liaisons capture information regarding contact, degrees-of-freedom constraints and containment relationships between parts in an assembly. The project involved defining a useful collection of liaison representations, investigating their properties, and providing for maximum use of the data in downstream applications. We tested our ideas by implementing a prototype system involving extensions to Pro/Engineer and the Archimedes assembly planner. With an expanded product model, the design system is more able to capture design intent. When a product update is attempted, increased knowledge availability improves our ability to understand the effect of design changes. Manufacturing and analysis disciplines benefit from having liaison information available, so less time is wasted arguing over incomplete design specifications and our enterprise can be more completely integrated.

  15. Touching base with OPERA

    CERN Multimedia

    CERN Bulletin

    2011-01-01

    Three seminars – at CERN, at Gran Sasso and in Japan – and an article calling for the scrutiny of the scientific community: the OPERA Collaboration opened its research publicly. In addition to huge press coverage, this triggered welcome reactions from colleagues around the world, many of whom will attempt to independently interpret and reproduce the measurement. OPERA’s Spokesperson touches base with the Bulletin.   The CERN Main Auditorium was crowded as OPERA Physics co-ordinator Dario Autiero presented the results of their research (23 September 2011). According to the OPERA strategy, the results of the measurements are in the hands of the scientific community and, as for any other scientific result, several months will be needed before other groups will be able to perform an independent measurement. In the meantime, the OPERA Collaboration is dealing with an avalanche of emails from the scientific community, members of the general public, and the press. &...

  16. Pathway-based analyses.

    Science.gov (United States)

    Kent, Jack W

    2016-02-03

    New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

  17. Refractive index based measurements

    DEFF Research Database (Denmark)

    2014-01-01

    A refractive index based measurement of a property of a fluid is measured in an apparatus comprising a variable wavelength coherent light source (16), a sample chamber (12), a wavelength controller (24), a light sensor (20), a data recorder (26) and a computation apparatus (28), by - directing...... coherent light having a wavelength along an input light path, - producing scattering of said light from each of a plurality of interfaces within said apparatus including interfaces between said fluid and a surface bounding said fluid, said scattering producing an interference pattern formed by said...... scattered light, - cyclically varying the wavelength of said light in said input light path over a 1 nm to 20nm wide range of wavelengths a rate of from 10Hz to 50 KHz, - recording variation of intensity of the interfering light with change in wavelength of the light at an angle of observation...

  18. Transaction based approach

    Science.gov (United States)

    Hunka, Frantisek; Matula, Jiri

    2017-07-01

    Transaction based approach is utilized in some methodologies in business process modeling. Essential parts of these transactions are human beings. The notion of agent or actor role is usually used for them. The paper on a particular example describes possibilities of Design Engineering Methodology for Organizations (DEMO) and Resource-Event-Agent (REA) methodology. Whereas the DEMO methodology can be regarded as a generic methodology having its foundation in the theory of Enterprise Ontology the REA methodology is regarded as the domain specific methodology and has its origin in accountancy systems. The results of these approaches is that the DEMO methodology captures everything that happens in the reality with a good empirical evidence whereas the REA methodology captures only changes connected with economic events. Economic events represent either change of the property rights to economic resource or consumption or production of economic resources. This results from the essence of economic events and their connection to economic resources.

  19. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  20. Telephone-Based Coaching.

    Science.gov (United States)

    Boccio, Mindy; Sanna, Rashel S; Adams, Sara R; Goler, Nancy C; Brown, Susan D; Neugebauer, Romain S; Ferrara, Assiamira; Wiley, Deanne M; Bellamy, David J; Schmittdiel, Julie A

    2017-03-01

    Many Americans continue to smoke, increasing their risk of disease and premature death. Both telephone-based counseling and in-person tobacco cessation classes may improve access for smokers seeking convenient support to quit. Little research has assessed whether such programs are effective in real-world clinical populations. Retrospective cohort study comparing wellness coaching participants with two groups of controls. Kaiser Permanente Northern California, a large integrated health care delivery system. Two hundred forty-one patients who participated in telephonic tobacco cessation coaching from January 1, 2011, to March 31, 2012, and two control groups: propensity-score-matched controls, and controls who participated in a tobacco cessation class during the same period. Wellness coaching participants received an average of two motivational interviewing-based coaching sessions that engaged the patient, evoked their reason to consider quitting, and helped them establish a quit plan. Self-reported quitting of tobacco and fills of tobacco cessation medications within 12 months of follow-up. Logistic regressions adjusting for age, gender, race/ethnicity, and primary language. After adjusting for confounders, tobacco quit rates were higher among coaching participants vs. matched controls (31% vs. 23%, p Coaching participants and class attendees filled tobacco-cessation prescriptions at a higher rate (47% for both) than matched controls (6%, p coaching was as effective as in-person classes and was associated with higher rates of quitting compared to no treatment. The telephonic modality may increase convenience and scalability for health care systems looking to reduce tobacco use and improve health.