Open Access

ARTICLE

Multifunction Battery Energy Storage System for Distribution Networks

Omar H. Abdalla^1,*, Gamal Abdel-Salam², Azza A. A. Mostafa³

1 Department of Electrical Power & Machines, Helwan University, Cairo, Egypt
2 Technical Affairs Sectors, South Cairo Electricity Distribution Company, Cairo, Egypt
3 Department of Energy Efficiency and Renewables, Egyptian Electric Utility and Customer Protection Regulatory Agency, Cairo, Egypt

* Corresponding Author: Omar H. Abdalla. Email:

(This article belongs to this Special Issue: Advances in Modern Electric Power and Energy Systems)

Energy Engineering 2022, 119(2), 569-589. https://doi.org/10.32604/ee.2022.018693

Received 11 August 2022; Accepted 22 October 2021; Issue published 24 January 2022

Abstract

Battery Energy Storage System (BESS) is one of the potential solutions to increase energy system flexibility, as BESS is well suited to solve many challenges in transmission and distribution networks. Examples of distribution network’s challenges, which affect network performance, are: (i) Load disconnection or technical constraints violation, which may happen during reconfiguration after fault, (ii) Unpredictable power generation change due to Photovoltaic (PV) penetration, (iii) Undesirable PV reverse power, and (iv) Low Load Factor (LF) which may affect electricity price. In this paper, the BESS is used to support distribution networks in reconfiguration after a fault, increasing Photovoltaic (PV) penetration, cutting peak load, and loading valley filling. The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes. For determining the maximum power generation change due to PV, actual power registration of connected PV plants in South Cairo Electricity Distribution Company (SCEDC) was considered for a year. In addition, the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as: the ability to absorb PV power surplus, cut peak load and fill load valley for improving network’s performances. The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone. The simulation studies are performed using the DIgSILENT PowerFactory software and DPL programming language. The Mixed Integer Linear Programming optimization technique (MILP) in MATLAB is employed to choose the best locations and sizing of BESS.

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Keywords

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