A Multi-Objective Demand/Generation Scheduling Model-Based Microgrid Energy Management System

Ali M. Jasim (), Basil H. Jasim, Habib Kraiem () and Aymen Flah
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Ali M. Jasim: Electrical Engineering Department, University of Basrah, Basrah 61001, Iraq
Basil H. Jasim: Electrical Engineering Department, University of Basrah, Basrah 61001, Iraq
Habib Kraiem: Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 73222, Saudi Arabia
Aymen Flah: National Engineering School of Gabès, Processes, Energy, Environment and Electrical Systems, University of Gabès, LR18ES34, Gabes 6072, Tunisia

Sustainability, 2022, vol. 14, issue 16, 1-28

Abstract: In recent years, microgrids (MGs) have been developed to improve the overall management of the power network. This paper examines how a smart MG’s generation and demand sides are managed to improve the MG’s performance in order to minimize operating costs and emissions. A binary orientation search algorithm (BOSA)-based optimal demand side management (DSM) program using the load-shifting technique has been proposed, resulting in significant electricity cost savings. The proposed optimal DSM-based energy management strategy considers the MG’s economic and environmental indices to be the key objective functions. Single-objective particle swarm optimization (SOPSO) and multi-objective particle swarm optimization (MOPSO) were adopted in order to optimize MG performance in the presence of renewable energy resources (RERs) with a randomized natural behavior. A PSO algorithm was adopted due to the nonlinearity and complexity of the proposed problem. In addition, fuzzy-based mechanisms and a nonlinear sorting system were used to discover the optimal compromise given the collection of Pareto-front space solutions. To test the proposed method in a more realistic setting, the stochastic behavior of renewable units was also factored in. The simulation findings indicate that the proposed BOSA algorithm-based DSM had the lowest peak demand (88.4 kWh) compared to unscheduled demand (105 kWh); additionally, the operating costs were reduced by 23%, from 660 USD to 508 USD, and the emissions decreased from 840 kg to 725 kg, saving 13.7%.

Keywords: microgrid; binary orientation search algorithm; demand side management; real-time pricing; energy management; multi-objective management; generation power uncertainty; operating cost (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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