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A hybrid distribution state estimation algorithm with regard to distributed generations
Published in CRC Press/Balkema
Pages: 383 - 386
Nowadays, power flow is no longer the same as in the conventional systems, since the dispersed generating plants provide power at the distribution grid level too. Connecting generating plants to distribution grids is impossible unless some special control and monitoring tools are available and utilized. The state estimation in these kinds of networks is often called mixtribution. Actually, state estimation is an optimization problem including discrete and continuous variables, whose objective function is to minimize the difference between calculated and measured values of variables, i.e., node voltage and active and reactive powers, in the branches. In this paper, a new hybrid approach based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) is proposed to solve this optimization problem using Distributed Generation (DG). The feasibility of the proposed approach is demonstrated and compared separately for the IEEE 34 bus radial distribution test systems. © 2016 Taylor & Francis Group, London.
About the journal
JournalFoundations and Frontiers in Computer, Communication and Electrical Engineering - Proceedings of the 3rd International Conference on Foundations and Frontiers in Computer, Communication and Electrical Engineering, C2E2 - 2016
PublisherCRC Press/Balkema