A Fundamental Study Of Distributed Generation Sizing And Allocation Simultaneously By Using Improved Evolutionary Swarm Particle Optimization (IEPSO) For Loss Minimization

Baharom, Mohamad Faizal and Sulaima, Mohamad Fani and Mohd Dahalan, Wardiah and Abdul Kadir, Aida Fazliana and Bohari, Zul Hasrizal and Napis, Nur Faziera (2017) A Fundamental Study Of Distributed Generation Sizing And Allocation Simultaneously By Using Improved Evolutionary Swarm Particle Optimization (IEPSO) For Loss Minimization. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Distribution network planning and operation require the identification of the best allocation and size of Distributed Generation (DG) that is able to fulfil the power demand with minimum power loss. The conventional heuristic method such as PSO cannot solve the optimal problem with superlative results due to less of ranking and evolutionary concept in it process of searching. An efficient hybridization of Improved Evolutionary Particle Swarm Optimization (IEPSO) is introduced to identify the best size and location of the DG’s operation plans for distribution power network system. The new fundamental hybridization method which is IEPSO is investigated in-terms of mutations and searching process that improve the conventional PSO. The proposed method is used to optimized the optimal size and location of DG concurrently. The main objective of this study is to reduce the power losses in the distribution network system by using the new hybridization optimization method. A comprehensive performance analysis is carried out on IEEE distribution network. The proposed method is applied and its impact to the network system in terms of real power loss and voltage profiles is investigated accordingly by simulation. The results are compared with conventional method of PSO and IPSO. This research has contributed to help power system engineers in maintaining a reliable and to secure the system economically.

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