Photovoltaic System Allocation Using Discrete Particle Swarm Optimization with Multi-level Quantization

  • Song, Hwa-Chang ;
  • Diolata, Ryan ;
  • Joo, Young-Hoon
  • Published : 2009.06.30


This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.


Multi-level quantization;Optimal allocation;Discrete particle swarm optimization;Photovoltaic systems


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