Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Rule-based Hybrid Discretization of Discrete Particle Swarm Optimization for Optimal PV System Allocation

PV 시스템의 최적 배치 문제를 위한 이산 PSO에서의 규칙 기반 하이브리드 이산화

  • 송화창 (서울과학기술대학교 전기공학과) ;
  • 고재환 (서울과학기술대학교 전기공학과) ;
  • 최병욱 (서울과학기술대학교 전기공학과)
  • Received : 2011.10.20
  • Accepted : 2011.12.08
  • Published : 2011.12.25
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Abstract

This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.

본 논문은 배전망에서의 PV (photovoltaic) 발전 시스템의 최적 배치 문제를 이산 입자 군집 최적화 (DPSO, discrete particle swarm optimization)를 이용하여 해를 구할 때 DPSO에 포함되어야 하는 이산화 단계를 위한 하이브리드 이산화 기법의 적용에 대하여 논한다. 이를 위해 PSO 반복단계에서 목적 함수 값과 최적화 속도를 입력 파라미터로 하는 규칙 기반 전문가 시스템을 제안하고 이산 변수를 포함하여 표현되는 PV 시스템 배치 문제의 최적해를 구하는데 적용하였다. 다수준 이산화를 위하여 간단한 라운딩과 sigmoid 함수를 이용한 3단계 및 5단계 이산화 기법을 하이브리드 형태로 적용하였다. 규칙 기반 전문가 시스템을 적용하여 각 PSO 과정에서 적절한 이산화 기법을 선택함으로써 기존의 DPSO보다 좋은 성능의 최적화가 가능하도록 하였다.

Keywords

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