An Application of Genetic Algorithm for Optimizing Demand Side Management Problem in Distribution Network Systems

Ngo Minh  Khoa; Tran Tien  Dat; Nguyen Vu  Hoa

doi:10.6180/jase.202410_27(10).0008

An Application of Genetic Algorithm for Optimizing Demand Side Management Problem in Distribution Network Systems

Electrical Engineering Mathematics / Statistics

Ngo Minh KhoaThis email address is being protected from spambots. You need JavaScript enabled to view it., Tran Tien Dat, and Nguyen Vu Hoa

Faculty of Engineering and Technology, Quy Nhon University, Binh Dinh, Vietnam

Received: May 2, 2023
Accepted: November 12, 2023
Publication Date: December 29, 2023

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202410_27(10).0008

The demand side management (DSM) is one of the most vital techniques which electric utilities have applied to control their electricity demand by incentivizing customers to modify their energy consumption patterns during peak hours or reduce their overall energy consumption. This paper studied the application of genetic algorithm (GA) to optimize the DSM problem to bring economic efficiency to electric customers. The objective function of the optimal problem was the maximum loading factor or the minimum energy cost. In addition, the equality and inequality constraints of DSM techniques were also set so that the GA can be applied to find the optimal solution for customers. The optimization toolbox in the Matlab software was applied to establish the mathematical model of the optimization problem. The test system including a synthetic load and three large-capacity boilers was carried out to validate the method. The optimal simulation results of the proposed method indicated clearly that the loading profiles of the loads in the test system were flexibly adjusted to maximize the loading factor as well as to minimize the energy cost of the whole system.

Keywords: Demand side management, loading profile, loading factor, objective function, optimization tools

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