The Experts below are selected from a list of 5328 Experts worldwide ranked by ideXlab platform
Guolian Hou - One of the best experts on this subject based on the ideXlab platform.
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ICSI (1) - A new particle swarm optimization solution to nonconvex Economic Dispatch Problem
Lecture Notes in Computer Science, 2010Co-Authors: Jianhua Zhang, Rui Wang, Yingxin Wang, Guolian HouAbstract:This paper presents an optimal Economic Dispatch for power plants by using modified particle swarm optimization (PSO) algorithm The Economic Dispatch Problem in power systems is to determine the optimal combination of power outputs for all generating units in order that the total fuel cost can be minimized, furthermore, all practical constraints can be satisfied Several key factors in terms of valve-point effects of coal cost functions, unit operation constraints and power balance are considered in the computation models Consequently, a new adaptive PSO technique is utilized for solving Economic Dispatch Problems The proposed algorithm is compared with other PSO algorithms Simulation results show that the proposed method is feasible and efficient.
John S Baras - One of the best experts on this subject based on the ideXlab platform.
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ACC - The effect of delays in the Economic Dispatch Problem for smart grid architectures
2016 American Control Conference (ACC), 2016Co-Authors: Christoforos Somarakis, Dipankar Maity, John S BarasAbstract:We consider the Economic Dispatch Problem (EDP) in power systems for a smart-grid friendly environment. We develop a consensus based decentralized optimization algorithm that evolves in a time-varying communication network that suffers from multiple propagation time-dependent delays. This paper, being an improvisation of an earlier work of ours, addresses the effects of time dependent delays in a fully decentralized network. We show analytically and by simulation that propagation delays may not only affect the performance of the dynamic algorithm that solves the EDP but can also destabilize the system.
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distributed solution of the Economic Dispatch Problem in smart grid power systems framework with delays
Conference on Decision and Control, 2015Co-Authors: Christoforos Somarakis, John S BarasAbstract:We consider the Economic Dispatch Problem in power systems in a smart-grid architecture friendly environment. The Problem is tackled with the use of multiple decentralized controllers that execute parallel distributed consensus algorithms. The scenario takes into account the presence of multiple time-varying communication delays.
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CDC - Distributed solution of the Economic Dispatch Problem in smart grid power systems framework with delays
2015 54th IEEE Conference on Decision and Control (CDC), 2015Co-Authors: Christoforos Somarakis, John S BarasAbstract:We consider the Economic Dispatch Problem in power systems in a smart-grid architecture friendly environment. The Problem is tackled with the use of multiple decentralized controllers that execute parallel distributed consensus algorithms. The scenario takes into account the presence of multiple time-varying communication delays.
Jianhua Zhang - One of the best experts on this subject based on the ideXlab platform.
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Economic Dispatch Problem Based on Improved Particle Swarm Optimization
Journal of Engineering Science and Technology Review, 2014Co-Authors: Wenxia Liu, Jianhua ZhangAbstract:An improved particle swarm optimization (IPSO) is used to solve Economic Dispatch Problem (EDP). The IPSO has two position updating strategies. In the early stage of iteration, the individual in the population updates the position according to its own best experience with a large probability. In the later stage of iteration, the individual updates the position according to the best experience in the population with a large probability. In addition, the IPSO introduces a mutation operator after position updating, which can increase the diversity of population and prevent the premature convergence. IPSO has been used to solve EDP with valve point effect. The experimental results show that IPSO is an effective algorithm to solve EDP.
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ICSI (1) - A new particle swarm optimization solution to nonconvex Economic Dispatch Problem
Lecture Notes in Computer Science, 2010Co-Authors: Jianhua Zhang, Rui Wang, Yingxin Wang, Guolian HouAbstract:This paper presents an optimal Economic Dispatch for power plants by using modified particle swarm optimization (PSO) algorithm The Economic Dispatch Problem in power systems is to determine the optimal combination of power outputs for all generating units in order that the total fuel cost can be minimized, furthermore, all practical constraints can be satisfied Several key factors in terms of valve-point effects of coal cost functions, unit operation constraints and power balance are considered in the computation models Consequently, a new adaptive PSO technique is utilized for solving Economic Dispatch Problems The proposed algorithm is compared with other PSO algorithms Simulation results show that the proposed method is feasible and efficient.
Yongqiang Wang - One of the best experts on this subject based on the ideXlab platform.
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chaotic self adaptive particle swarm optimization algorithm for dynamic Economic Dispatch Problem with valve point effects
Expert Systems With Applications, 2011Co-Authors: Ying Wang, Jianzhong Zhou, Hui Qin, Yongqiang WangAbstract:Abstract This paper presents a chaotic self-adaptive particle swarm optimization algorithm (CSAPSO) to solve dynamic Economic Dispatch Problem (DED) with value-point effects. The proposed algorithm takes PSO as the main evolution method. The velocity, a sensitive parameter of PSO, is adjusted dynamically to increase the precision of PSO. To overcome the drawback of premature in PSO, chaotic local search is imported into proposed algorithm. Moreover, a new strategy is proposed to handle the various constraints of DED Problem in this paper, the results solved by proposed strategy can satisfy the constraints of DED Problem well. Finally, the high feasibility and effectiveness of proposed CSAPSO algorithm is validated by three test systems consisting of 10 and extended 30 generators while compared with the experimental results calculated by the other methods reported in this literature.
Christoforos Somarakis - One of the best experts on this subject based on the ideXlab platform.
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ACC - The effect of delays in the Economic Dispatch Problem for smart grid architectures
2016 American Control Conference (ACC), 2016Co-Authors: Christoforos Somarakis, Dipankar Maity, John S BarasAbstract:We consider the Economic Dispatch Problem (EDP) in power systems for a smart-grid friendly environment. We develop a consensus based decentralized optimization algorithm that evolves in a time-varying communication network that suffers from multiple propagation time-dependent delays. This paper, being an improvisation of an earlier work of ours, addresses the effects of time dependent delays in a fully decentralized network. We show analytically and by simulation that propagation delays may not only affect the performance of the dynamic algorithm that solves the EDP but can also destabilize the system.
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distributed solution of the Economic Dispatch Problem in smart grid power systems framework with delays
Conference on Decision and Control, 2015Co-Authors: Christoforos Somarakis, John S BarasAbstract:We consider the Economic Dispatch Problem in power systems in a smart-grid architecture friendly environment. The Problem is tackled with the use of multiple decentralized controllers that execute parallel distributed consensus algorithms. The scenario takes into account the presence of multiple time-varying communication delays.
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CDC - Distributed solution of the Economic Dispatch Problem in smart grid power systems framework with delays
2015 54th IEEE Conference on Decision and Control (CDC), 2015Co-Authors: Christoforos Somarakis, John S BarasAbstract:We consider the Economic Dispatch Problem in power systems in a smart-grid architecture friendly environment. The Problem is tackled with the use of multiple decentralized controllers that execute parallel distributed consensus algorithms. The scenario takes into account the presence of multiple time-varying communication delays.
