Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network. (March 2015)

• Record Type: Journal Article
• Authors: Kayal, Partha; Chanda, C.K.
• Is Part Of: Renewable energy. Volume 75(2015)
• Page Start: 173
• Page End: 186
• Publication Date: 2015-03
• Subjects: Renewable distributed generations -- Particle swarm optimization -- Mixed solar-wind system -- Network performance indices; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2014.10.003
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Renewable energy sources are gaining more and more interest because they are nonpolluting and sustainable. Recently, a notable number of renewable distributed generations (DGs) having intermittent generation patterns are being interconnected with the distribution network to meet growing load demand and nullify environmental threats. Appropriate integration of renewable DGs in distribution networks is crucial to guarantee the qualitative network operational benefits. In this paper a simple but efficient approach has been proposed for optimal placement and sizing of solar and wind DGs in distribution territory by considering electrical network power loss minimization, voltage stability and network security improvement. The stochastic nature of solar irradiance and wind speed are accounted using suitable probabilistic models. Weighted aggregation particle swarm optimization technique is employed to optimize the objective functions considering bus voltage limit, line loading capacity, discrete size limit and penetration constraints of DGs. Strategic weight selection technique has been adopted to assess the well trade-off solution by persuasion of multiple objectives regarding the performance of distribution network. The proposed method has been applied to a typical Indian rural distribution network, and the satisfactory results are obtained. Highlights: Simultaneous placement and sizing of solar and wind based distributed generations. Uncertainty modeling of resources using probability distribution functions. Robust planning with multiple objectives and constraints regarding performance of distribution network. Systematic weight selection technique for weighted aggregation multi-objective optimization.