Optimization of distributed generation using mix-integer optimization by genetic algorithm (MIOGA) Considering Load Growth

Che Muhamad Asad Safwan, Che Aziz and Norhafidzah, Mohd Saad and Mohammad Fadhil, Abas and Suliana, Ab Ghani and Ali, Abid (2022) Optimization of distributed generation using mix-integer optimization by genetic algorithm (MIOGA) Considering Load Growth. In: Lecture Notes in Electrical Engineering; 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021 , 23 August 2021 , Kuantan, Pahang. pp. 245-255., 842 (274719). ISSN 1876-1100 ISBN 978-981168689-4

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Abstract

In this paper, the planning of distributed generation (DG) is presented with a metaheuristic technique called mix-integer optimization by genetic algorithm (MIOGA). The solution of the distribution power flow is based on the backward/forward sweep method to compute the voltage at every node of the buses followed by the determination of power loss. The main idea of the proposed method is to determine the size and location for the DG to be installed in the radial distribution network (RDN). The method is tested in 69 bus RDN in MATLAB. From the simulation results, the reduction in total power loss and improvement in bus voltage magnitudes are observed for the system with the installation of DG. The results show that power loss can be reduced up to 63.03% with DG installation at bus 61 at 1.8727 MW. Apart from the reductions in losses, the installation of DG using MIOGA also helps to improve the voltage profile of the RDN. The critical bus voltage at bus 65 has successfully been improved from 0.9092 p.u. to 0.9806 p.u. The results indicate that load growth has no effect on the optimal position, and only the optimal size of the DG unit is changed. The results also reveal that load growth will increase the power losses. Since the DG in this study solely supplies active power, the impact of DG in reducing power losses is more visible for the case real power demand is increased rather than the case when the reactive power demand is increased.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Backward/Forward sweep method; Distributed generation; Load growth; Mix integer optimization by genetic algorithm; Radial distribution network
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	College of Engineering Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	06 Dec 2023 03:09
Last Modified:	06 Dec 2023 03:09
URI:	http://umpir.ump.edu.my/id/eprint/39524
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