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Active Distribution System Planning Considering Battery Swapping Station for Low-carbon Objective using Immune Binary Firefly Algorithm
Ji-Ying Shi*, Ya-Jing Li*, Fei Xue, Le-Tao Ling*, Wen-An Liu**, Da-Ling Yuan* and Ting Yang *
Abstract Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cutting carbon emission and improving system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.
Keyword Active distribution system planning, Low carbon, Distributed generation, Flexible load, Battery swapping station, Immune binary firefly algorithm
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