University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 10 1 2019 05 22 A New Multi-Objective Design for Optimal Placement of Gas Turbines considering Black-start Capability Improvement A New Multi-Objective Design for Optimal Placement of Gas Turbines considering Black-start Capability Improvement 19 32 23247 10.22108/isee.2018.110997.1122 FA Mohammadreza Esmaili Esfahan Regional Electric Company, Isfahan, Iran Amin Khodabakhshian Department of Electrical Engineering, Faculty of Electrical Engineering, University of Isfahan, Isfahan, Iran Rahmatallah Hooshmand Department of Electrical Engineering, Faculty of Electrical Engineering, University of Isfahan, Isfahan, Iran Journal Article 2018 05 15 Installing new energy sources as redundant black-start (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 multi-objective problem (MOP), as a mixed integer linear programming (MILP), is defined. The Pareto optimal solutions of the MOP are obtained by using a new population-based meta-heuristic 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 black-start generation, but also to improve the power system performance in normal conditions. During the restoration process, it also provides the optimal start-up sequences of non-black-start (NBS) units with the optimal transmission paths. Installing new energy sources as redundant black-start (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 multi-objective problem (MOP), as a mixed integer linear programming (MILP), is defined. The Pareto optimal solutions of the MOP are obtained by using a new population-based meta-heuristic 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 black-start generation, but also to improve the power system performance in normal conditions. During the restoration process, it also provides the optimal start-up sequences of non-black-start (NBS) units with the optimal transmission paths. https://isee.ui.ac.ir/article_23247_a9d7d6a9d57204edc38517b1d7320421.pdf