A comparison of heuristic optimization techniques for optimal placement and sizing of photovoltaic based distributed generation in a distribution system. (15th December 2016)

• Record Type: Journal Article
• Authors: Daud, S.; Kadir, A.F.A.; Gan, C.K.; Mohamed, A.; Khatib, Tamer
• Is Part Of: Solar energy. Volume 140(2016)
• Page Start: 219
• Page End: 226
• Publication Date: 2016-12-15
• Subjects: Photovoltaic -- Distributed generation -- Heuristic techniques -- Optimization; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2016.11.013
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: We conduct a comparison of three AI techniques for optimal placement and sizing of PVDG. The optimization considers power loss, voltage deviation and dip magnitude and THDv. Results show that IGSA outperformed PSO and GSA with better and accurate solution. Abstract: This paper presents the application of heuristic optimization techniques for determining optimal placement and sizing of photovoltaic-based distributed generation (PVDG) in a distribution system. The objective functions of the optimization problem, consider a real power loss, voltage deviation, average voltage total harmonic distortion (THD) and system average voltage dip magnitude (SAVDM). Various heuristic optimization techniques were applied and compared in order to determine the optimum placements and sizing of PVDG in IEEE 69-bus radial distribution system. This paper proposed the improved gravitational search algorithm (IGSA) and its performances are compared with two other algorithms such as the gravitational search algorithm (GSA) and particle swarm optimization (PSO). A comparison of the performances is also made using optimization techniques when PVDGs are fixed at critical buses. The test results showed that IGSA outperformed GSA and PSO in finding the optimal PVDG locations and sizes.