Open Access

ARTICLE

Implementing an Optimal Energy Management System for a Set of Microgrids Using the Harmony Search Algorithm

by Xiangjian Shi^1,*, Teng Liu², Wei Mu², Jianfeng Zhao¹

1 School of Electrical Engineering, Southeast University, Nanjing, 210096, China
2 NR Electric Co., Ltd., Nanjing, 211106, China

* Corresponding Author: Xiangjian Shi. Email:

(This article belongs to the Special Issue: Application of Artificial Intelligence for Energy and City Environmental Sustainability)

Energy Engineering 2022, 119(5), 1843-1860. https://doi.org/10.32604/ee.2022.020787

Received 12 December 2021; Accepted 25 February 2022; Issue published 21 July 2022

Abstract

A microgrid (MG) refers to a set of loads, generation resources and energy storage systems acting as a controllable load or a generator to supply power and heating to a local area. The MG-generated power management is a central topic for MG design and operation. The existence of dispersed generation (DG) resources has faced MG management with new issues. Depending on the level of exchanges between an MG and the main grid, the MG operation states can be divided into independent or grid-connected ones. Energy management in MGs aims to supply power at the lowest cost for optimal load response. This study examines MG energy management in two operational modes of islanded and grid-connected, and proposes a structure with two control layers (primary and secondary) for energy management. At the principal level of control, the energy management system is determined individually for all MG by taking into consideration the probability constraints and RES uncertainty by the Weibull the probability density function (PDF), generation resources’ power as well as the generation surplus and deficit of each MG. Then, the information of the power surplus and deficit of each MG must be sent to the central energy management system. To confirm the proposed structure, a case system with two MGs and a condensive load is simulated by using a multi-time harmony search algorithm. Several scenarios are applied to evaluate the performance of this algorithm. The findings clearly show the effectiveness of the proposed system in the energy management of several MGs, leading to the optimal performance of the resources per MG. Moreover, the proposed control scheme properly controls the MG and grid’s performance in their interactions and offers a high level of robustness, stable behavior under different conditions and high quality of power supply.

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Keywords

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