Optimal Placement and Sizing of Distributed Generation in Radial Distribution System Using Differential Evolution Algorithm
Integration of renewable energy based distributed generation (DG) units provides potential benefits to conventional distribution systems. The power injections from renewable DG units located close to the load centers provide an opportunity for system voltage support, reduction in energy losses and emissions, and reliability improvement. Therefore, the allocation of DG units should be carefully determined with the consideration of different planning incentives. Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. This paper proposes a Differential Evolution Algorithm (DEA) for optimal placement and sizing of distributed generation (DG) in radial distribution system to minimize the total real power loss and improve the voltage profile within the frame work of system operation and security constraints. The proposed DE algorithm is also used to determine optimal sizes and locations of multi-DGs. The proposed method is tested on standard IEEE 69-bus test system and the results are presented and compared with different approaches available in the literature. The proposed method has outperformed than the other methods in terms of the quality of solution and computational efficiency.
KeywordsDistribute Generation Optimal Placement Differential Evolution Algorithm Voltage Profile Load Flow
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- 3.Hung, D.Q., Mithulanathan, N., Bansal, R.C.: Multiple distributed generators placement in primary distribution networks for loss reduction. IEEE Transactions on Industrial Electronics (in press)Google Scholar
- 4.Ziari, I., Ledwich, G., Ghosh, A., Cornforth, D., Wishart, M.: Optimal allocation and sizing of DGs in distribution networks. In: IEEE Power and Energy Society General Meeting, pp.1–8 (2010)Google Scholar
- 7.Storn, R., Price, K.: Differential Evolution – “A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces”, Technical Report TR-95-012, ICSI (1995)Google Scholar