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입자 군집 최적화를 이용한 전지전력저장시스템의 충·방전 운전계획에 관한 연구

Study on BESS Charging and Discharging Scheduling Using Particle Swarm Optimization

  • Park, Hyang-A (Smart Distribution Research Center, Advanced Power Grid Research Division, Korea Electrotechnology Research Institute) ;
  • Kim, Seul-Ki (Smart Distribution Research Center, Advanced Power Grid Research Division, Korea Electrotechnology Research Institute) ;
  • Kim, Eung-Sang (Smart Distribution Research Center, Advanced Power Grid Research Division, Korea Electrotechnology Research Institute) ;
  • Yu, Jung-Won (Dept. of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Sung-Shin (Dept. of Electrical and Computer Engineering, Pusan National University)
  • 투고 : 2014.12.30
  • 심사 : 2016.03.01
  • 발행 : 2016.04.01

초록

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

키워드

참고문헌

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