Optimal planning of distribution system considering distributed generators

• Published in: CIRED 2012 Workshop: Integration of Renewables into the Distribution Grid p. 179
• Main Authors: Liang, Huishi, Liu, Sige, Su, Jian
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2012; The Institution of Engineering & Technology
• Subjects: Distributed power generation; Distribution networks; Optimisation techniques; Power system management, operation and economics; Power system planning and layout; Substations; customer-owned DG; electric generators; power generation planning; particle swarm optimisation; power distribution planning; computational geometry; distributed power generation; peak load demand; substations sizing; distributed generators; DSM; utility DG; peak load shaving; investment; distribution system; new-built utility DG capacity; particle swarm optimization; substations; substation optimal planning; PSO; substations location; Voronoi diagram method; demand side management; T&D system construction; demand-side management
• ISBN: 1849196281; 9781849196284
• DOI: 10.1049/cp.2012.0792

This paper presents a methodology for substation optimal planning considering DG for peak shaving. Utility can take effective demand-side management (DSM) to encourage customer-owned DG to participate in peak load shaving, and it can also construct utility DG to meet the peak load demand. In this paper, the impact of DG on peak load shaving is analyzed, and DG is taken as a complement to T&D system to meet load demand, which is considered in the substation planning. Substations sizing and location and new-built utility DG capacity is optimized using Particle Swarm Optimization (PSO), in which supply area of each substation is obtained by Voronoi diagram method. Case study shows that planning result considering DG for peak shaving can defer T&D system expansion so that considerable investment can be saved. Especially for those areas with high cost of T&D system construction, constructing DG to meet peak load demand would be a more economic way. (4 pages)