Battery energy storage system sizing using PSO algorithm in DIgSILENT powerfactory

Gan, Chin Kim and Tan, Pi Hua and Al-Areqi, Khaldon Ahmed Qaid and Tee, Wei Hown (2022) Battery energy storage system sizing using PSO algorithm in DIgSILENT powerfactory. International Journal of Renewable Energy Research, 12 (4). pp. 2142-2150. ISSN 1309-0127

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Abstract

The usage of battery energy storage system (BESS) can be a significant technology to improve the performance of power systems. Optimal sizing of BESS can reduce power losses, improve voltage profile and relieve peak demand in power systems. This paper aims to establish a simulation-based optimization in DIgSILENT Programming Language (DPL) script in DIgSILENT PowerFactory environment, which is more efficient for data exchange between operations. Problem for optimization of BESS sizing and placement are formulated in DPL script with analytic algorithm and particle swarm optimization (PSO) with loadflow simulation. The IEEE 9-bus system is the test case used to demonstrate and discuss the application of algorithms in DPL script. The placement of BESS is identified to be optimal with lowest power losses of 4.962 MW at bus 5 and the optimal BESS size of 47.168 MW with operation cost of 4852.65 $/h are determined. The output of the study concludes that optimal sizing of BESS can be applied in solving power system problems effectively with DPL operations. This paper serves as a reference for researchers to study and implement optimization approach in DIgSILENT DPL script.

Item Type:	Article
Uncontrolled Keywords:	DIgSILENT PowerFactory, Analytic algorithm, Particle swarm optimization, Battery energy storage system
Divisions:	Faculty of Electrical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	02 Mar 2023 12:15
Last Modified:	02 Mar 2023 12:15
URI:	http://eprints.utem.edu.my/id/eprint/26232
Statistic Details:	View Download Statistic

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