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A New Multiobjective Design For Optimal Placement of Gas Turbines Considering Blackstart Capability Improvement
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نویسنده
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Esmaili Mohammad Reza ,Khodabakhshian Amin ,Hooshmand Rahmat-Allah
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منبع
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هوش محاسباتي در مهندسي برق - 2019 - دوره : 10 - شماره : 1 - صفحه:19 -30
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چکیده
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Installing new energy sources as redundant blackstart (bs) units is an efficient way to enhance the speed of power system restoration, especially when there is a high risk that the available power plants considered as bs units fail to operate. in this regard, this paper provides a new optimal design for the placement of the gas turbine (gt) as the redundant energy source to improve the power system performance during both restoration and normal conditions. in doing so, there will be contradictory objective functions to be minimized. therefore, a multiobjective problem (mop), as a mixed integer linear programming (milp), is defined. the pareto optimal solutions of the mop are obtained by using a new populationbased metaheuristic technique, called crow search algorithm (csa). two power systems are used for the validation of the proposed method. the simulation results show that the system can benefit from this method not only to increase the capability of blackstart generation, but also to improve the power system performance in normal conditions. during the restoration process, it also provides the optimal startup sequences of nonblackstart (nbs) units with the optimal transmission paths.
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کلیدواژه
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Power System Restoration ,Black-Start Units ,Crow Search Algorithm ,Multi-Objective Design ,Pareto Optimal Set.
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آدرس
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Esfahan Regional Electric Company, Iran, University Of Isfahan, Faculty Of Electrical Engineering, Department Of Electrical Engineering, Iran, University Of Isfahan, Faculty Of Electrical Engineering, Department Of Electrical Engineering, Iran
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پست الکترونیکی
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hooshmand_r@eng.ui.ac.ir
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A New MultiObjective Design for Optimal Placement of Gas Turbines considering Blackstart Capability Improvement
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Authors
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Khodabakhshian Amin ,Esmaili Mohammadreza ,Hooshmand Rahmatallah
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Abstract
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Installing new energy sources as redundant blackstart (BS) units is an efficient way to enhance the speed of power system restoration, especially when there is a high risk that the available power plants considered as BS units fail to operate. In this regard, this paper provides a new optimal design for the placement of the Gas Turbine (GT) as the redundant energy source to improve the power system performance during both restoration and normal conditions. In doing so, there will be contradictory objective functions to be minimized. Therefore, a multiobjective problem (MOP), as a mixed integer linear programming (MILP), is defined. The Pareto optimal solutions of the MOP are obtained by using a new populationbased metaheuristic technique, called Crow Search Algorithm (CSA). Two power systems are used for the validation of the proposed method. The simulation results show that the system can benefit from this method not only to increase the capability of blackstart generation, but also to improve the power system performance in normal conditions. During the restoration process, it also provides the optimal startup sequences of nonblackstart (NBS) units with the optimal transmission paths.
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Keywords
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