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논문 기본 정보

자료유형
학술저널
저자정보
Ji-Ying Shi (Tianjin University) Ya-Jing Li (Tianjin University) Fei Xue (State Grid Ningxia Electric Power Company) Le-Tao Ling (Tianjin University) Wen-An Liu (ZiBo Power Supply Company) Da-Ling Yuan (Tianjin University) Ting Yang (Tianjin University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.13 No.2
발행연도
2018.3
수록면
580 - 590 (11page)

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초록· 키워드

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Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve 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.

목차

Abstract
1. Introduction
2. ADS Planning Model
3. Immune Binary Firefly Algorithm
4. Case Study
5. Conclusion
References

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