The Experts below are selected from a list of 17973 Experts worldwide ranked by ideXlab platform
P. Rastgoufard - One of the best experts on this subject based on the ideXlab platform.
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Control area performance improvement by extended security constrained Economic Dispatch
IEEE Transactions on Power Systems, 1997Co-Authors: W.r. Barcelo, P. RastgoufardAbstract:An algorithm for solving the extended security constrained Economic Dispatch (ESCED) problem with real-time Economic Dispatch grade speed and reliability is presented. The ESCED problem is formulated by adding a regulating margin and ramp rate constraints to the network security constrained Economic Dispatch problem previously solved by the CEDC algorithm. Starting with Newton's method to optimize the Lagrangian, the ESCED is developed by superimposing on Newton's method eight major components called tracking start initialization, hessian pre-elimination, implicit dual variable calculations, regulating margin sensitivity coefficient calculations, traumatic event evaluation, constraint relaxation, implicit ramp rate constraint implementation, and relaxed incremental cost calculations. Test results are also presented.
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Dynamic Economic Dispatch using the extended security constrained Economic Dispatch algorithm
IEEE Transactions on Power Systems, 1997Co-Authors: W.r. Barcelo, P. RastgoufardAbstract:An algorithm for solving the power system multi-stage dynamic Economic Dispatch (MDED) problem in real-time is presented. The MDED problem is formulated by formally adding ramp rate constraints to the extended security constrained Economic Dispatch (ESCED) problem for all stages beyond the first stage. The MDED problem is then solved using the ESCED algorithm with ramp rate constraint sensitivity coefficients. A new two-component method of observing regulating margin constraints is also introduced and test results are presented comparing the one and two-stage dynamic EDC results.
W.r. Barcelo - One of the best experts on this subject based on the ideXlab platform.
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Control area performance improvement by extended security constrained Economic Dispatch
IEEE Transactions on Power Systems, 1997Co-Authors: W.r. Barcelo, P. RastgoufardAbstract:An algorithm for solving the extended security constrained Economic Dispatch (ESCED) problem with real-time Economic Dispatch grade speed and reliability is presented. The ESCED problem is formulated by adding a regulating margin and ramp rate constraints to the network security constrained Economic Dispatch problem previously solved by the CEDC algorithm. Starting with Newton's method to optimize the Lagrangian, the ESCED is developed by superimposing on Newton's method eight major components called tracking start initialization, hessian pre-elimination, implicit dual variable calculations, regulating margin sensitivity coefficient calculations, traumatic event evaluation, constraint relaxation, implicit ramp rate constraint implementation, and relaxed incremental cost calculations. Test results are also presented.
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Dynamic Economic Dispatch using the extended security constrained Economic Dispatch algorithm
IEEE Transactions on Power Systems, 1997Co-Authors: W.r. Barcelo, P. RastgoufardAbstract:An algorithm for solving the power system multi-stage dynamic Economic Dispatch (MDED) problem in real-time is presented. The MDED problem is formulated by formally adding ramp rate constraints to the extended security constrained Economic Dispatch (ESCED) problem for all stages beyond the first stage. The MDED problem is then solved using the ESCED algorithm with ramp rate constraint sensitivity coefficients. A new two-component method of observing regulating margin constraints is also introduced and test results are presented comparing the one and two-stage dynamic EDC results.
V P Jagathy Raj - One of the best experts on this subject based on the ideXlab platform.
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Reinforcement Learning approaches to Economic Dispatch problem
International Journal of Electrical Power & Energy Systems, 2011Co-Authors: E A Jasmin, T. P. Imthias Ahamed, V P Jagathy RajAbstract:This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.
Diego Patino - One of the best experts on this subject based on the ideXlab platform.
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ISGT - Predictive Economic Dispatch on microgrid with high penetration of renewable energy sources
2016 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2016Co-Authors: David Mejia, Diego PatinoAbstract:In this work, a framework for incorporating renewable energy sources into the Economic Dispatch problem of microgrid system is presented. It shows the possible advantages of adopting a predictive Economic Dispatch approach. In particular, simulation of the Economic Dispatch solution for a microgrid system -with both solar and wind technologies and also a battery storage system- illustrates the conditions under which the operation of power systems, with conventional Economic Dispatch algorithms do not provide a suitable solution. In addition, the purposed predictive strategy shows that it can leads to technical as well as Economical improvements depending on the composition of the generation portfolio.
Enrique Mallada - One of the best experts on this subject based on the ideXlab platform.
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Understanding the Inefficiency of Security-Constrained Economic Dispatch
arXiv: Systems and Control, 2017Co-Authors: Mohammad H. Hajiesmaili, Desmond Cai, Enrique MalladaAbstract:The security-constrained Economic Dispatch (SCED) problem tries to maintain the reliability of a power network by ensuring that a single failure does not lead to a global outage. The previous research has mainly investigated SCED by formulating the problem in different modalities, e.g. preventive or corrective, and devising efficient solutions for SCED. In this paper, we tackle a novel and important direction, and analyze the Economic cost of incorporating security constraints in Economic Dispatch. Inspired by existing inefficiency metrics in game theory and computer science, we introduce notion of price of security as a metric that formally characterizes the Economic inefficiency of security-constrained Economic Dispatch as compared to the original problem without security constraints. Then, we focus on the preventive approach in a simple topology comprising two buses and two lines, and investigate the impact of generation availability and demand distribution on the price of security. Moreover, we explicitly derive the worst-case input instance that leads to the maximum price of security. By extensive experimental study on two test-cases, we verify the analytical results and provide insights for characterizing the price of security in general networks.
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distributed optimization decomposition for joint Economic Dispatch and frequency regulation
IEEE Transactions on Power Systems, 2017Co-Authors: Desmond Cai, Enrique Mallada, Adam WiermanAbstract:Economic Dispatch and frequency regulation are typically viewed as fundamentally different problems in power systems and, hence, are typically studied separately. In this paper, we frame and study a joint problem that co-optimizes both slow timescale Economic Dispatch resources and fast timescale frequency regulation resources. We show how the joint problem can be decomposed without loss of optimality into slow and fast timescale subproblems that have appealing interpretations as the Economic Dispatch and frequency regulation problems, respectively. We solve the fast timescale subproblem using a distributed frequency control algorithm that preserves network stability during transients. We solve the slow timescale subproblem using an efficient market mechanism that coordinates with the fast timescale subproblem. We investigate the performance of our approach on the IEEE 24-bus reliability test system.
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distributed optimization decomposition for joint Economic Dispatch and frequency regulation
arXiv: Optimization and Control, 2016Co-Authors: Desmond Cai, Enrique Mallada, Adam WiermanAbstract:Economic Dispatch and frequency regulation are typically viewed as fundamentally different problems in power systems and, hence, are typically studied separately. In this paper, we frame and study a joint problem that co- optimizes both slow timescale Economic Dispatch resources and fast timescale frequency regulation resources. We show how the joint problem can be decomposed without loss of optimality into slow and fast timescale sub-problems that have appealing interpretations as the Economic Dispatch and frequency regulation problems respectively. We solve the fast timescale sub-problem using a distributed frequency control algorithm that preserves the stability of the network during transients. We solve the slow timescale sub-problem using an efficient market mechanism that coordinates with the fast timescale sub-problem. We investigate the performance of the decomposition on the IEEE 24-bus reliability test system.
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distributed optimization decomposition for joint Economic Dispatch and frequency regulation
Conference on Decision and Control, 2015Co-Authors: Desmond Cai, Enrique Mallada, Adam WiermanAbstract:Economic Dispatch and frequency regulation are typically viewed as fundamentally different problems in power systems, and hence are typically studied separately. In this paper, we frame and study a joint problem that optimizes both slow timescale Economic Dispatch resources and fast timescale frequency regulation resources. We provide sufficient conditions under which the joint problem can be decomposed without loss of optimality into slow and fast timescale problems. These slow and fast timescale problems have appealing interpretations as the Economic Dispatch and frequency regulation problems respectively. Moreover, the fast timescale problem can be solved using a distributed algorithm that preserves the stability of the network during transients. We also apply this optimal decomposition to propose an efficient market mechanism for Economic Dispatch that coordinates with frequency regulation.
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distributed optimization decomposition for joint Economic Dispatch and frequency regulation
Allerton Conference on Communication Control and Computing, 2015Co-Authors: Desmond Cai, Enrique Mallada, Adam WiermanAbstract:Networked markets typically operate on multiple time scales. For example, electricity markets are split into slow timescale Economic Dispatch and fast timescale frequency regulation markets. Nevertheless, the different time scales are typically viewed as fundamentally different problems and hence are studied separately. In this paper, we frame and study a joint problem that optimizes both slow and fast timescale resources in electricity markets. We provide necessary and sufficient conditions under which the joint problem can be decomposed without loss of optimality into slow and fast timescale problems. These slow and fast timescale problems have appealing interpretations as the Economic Dispatch and frequency regulation problems respectively. Moreover, the fast timescale problem can be solved using a distributed algorithm that preserves the stability of the network during transients. We apply our result to propose an efficient market mechanism for coordinating Economic Dispatch and frequency regulation resources.
