Using an evolutionary algorithm for optimal planning of integrated microgrids considering distributed energy

Article type: Research Article

Authors: Wang, Jing^{; *} | Wang, Ting

Affiliations: State Grid Shaanxi Electric Power Company Limited, Xi’an, Shaanxi, China

Correspondence: [*] Corresponding author. Jing Wang. E-mail: wjjh1233@163.com.

Abstract: Microgrids (MGs) are defined as a set of loads, generation sources and energy storage devices that act as a controllable load or generator, and can supply power and heat to local areas. Management of generated power in MGs is among the main topics that should be addressed for MG design and operation. The existence of distributed generation (DG) resources has caused MG management to face new issues. Depending on the level of exchange between the MG and main grid, MG operation can be classified into two modes: off-grid (islanded) and grid-connected. Optimal energy management in the systems with multiple MGs has created new challenges in power systems. Therefore, it is important to develop energy management systems (EMSs) focusing on the optimal performance of MG resources and controlling power exchange between the grid and MGs. The present study aims to present a structure with two control layers, called primary and secondary control, for energy management in the systems with multiple MGs and different ownership. Moreover, a flexible distributed EMS is proposed to coordinate the operation of interconnected MGs. Each MG is regarded as an independent unit with local objectives to optimize its operating costs and exchanged power. It is assumed that interconnected MGs are connected to each other by a common bus, through which they can exchange power. MG planning is simulated considering load flow equations and voltage constraints in a system consisting of multiple MGs over a 24-h period. The simulation results indicate using the proposed EMS can improve MG efficiency and reliability. The simulation is performed in MATLAB software by grasshopper optimization algorithm (GOA). Uncertainties and scenario generation and reduction are considered in modeling.

Keywords: Distributed energy management system, Microgrid (MG), distributed generation resource, power exchange

DOI: 10.3233/JIFS-220568

Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7949-7961, 2022