Composition Assessment of a Power Distribution System with Optimal Dispatching of Distributed Generation

Muhammad Afzal  -  School of Engineering, University of Birmingham, Birmingham,, United Kingdom
Manuel S. Alvarez-Alvarado  -  3Faculty of Engineering in Electricity and Computing, Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador
*Zafar A. Khan  -  Department of Electrical Engineering, Mirpur University of Science and Technology (MUST), Mirpur A.K, Pakistan
Mohammed Alghassab  -  Department of Electrical and Computer Engineering, Shaqra University, Riyadh,, Saudi Arabia
Received: 8 Jul 2020; Revised: 21 Aug 2020; Accepted: 26 Aug 2020; Published: 15 Oct 2020; Available online: 27 Aug 2020.
Open Access Copyright (c) 2020 The authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
License URL: http://creativecommons.org/licenses/by-sa/4.0

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Section: Original Research Article
Language: EN
Statistics: 429 198
Abstract
Increasing penetration of distributed generation (DG) is imminent in the new age of power distribution networks, which are smarter than the conventional grids. They enable the integration of DG into the power distribution network. This paper presents an assessment methodology for determining the optimal capacity and location of DG to ensure high reliability in a radial distribution network. The approach considers cost and the impact of aging on the DG and network topology for interconnection using genetic algorithm, which is a robust technique with wide solution space searchability and can potentially find global optima with fewer chances of getting trapped into local optima. A case study is simulated using three different scenarios to evaluate the impact of DG interconnection on the 13.8 kV power distribution network. The scenarios comprise of situations without any DG, with DG interconnection and optimization of DG interconnection. The case study shows that the penetration of DG increases the reliability of the distribution network while reducing the expected energy not supplied (EENS). Although, the difference between EENS in the optimized DG integration and non-optimized DG integration is not very significant in a small network, however, it becomes apparent with the aging curve that optimized allocation of DG possesses significant benefits.
Keywords: aging factor; distribution generation; genetic algorithm; Monte Carlo simulation; photovoltaic system

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