A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks

• Main Authors: Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohd Shawal, Jadin
• Format: Article
• Language: English
• Published: Elsevier Inc. 2023
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/37579/1/A%20simulation-metaheuristic%20approach%20for%20finding%20the%20optimal%20allocation%20of%20the%20battery.pdf; http://umpir.ump.edu.my/id/eprint/37579/; https://doi.org/10.1016/j.dajour.2023.100208; https://doi.org/10.1016/j.dajour.2023.100208
• Institution: Universiti Malaysia Pahang

This paper proposes a simulation study to solve the optimal allocation of the Battery Energy Storage System (BESS) problem in distribution networks. The effect of BESS's installation in the selected distribution networks is surveyed for a 24-hour period, where time-of-use electricity charges are divided into three periods: standard, peak, and off-peak hours. This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. The objective function is to minimize the combined cost of purchasing electricity and energy loss, where the optimal location of BESS and its operated power at each hour are treated as the control variables to be optimized. Two distribution systems are utilized, viz. 18-node and 33-node systems are considered to assess the performance of TLBO in solving the mentioned problem, where a comparison with other recent metaheuristic algorithms also have been conducted. The study's findings demonstrated the promising results of TLBO in terms of minimizing the energy cost and significantly reducing the peak loads during peak hours in the 24 h. The simulations also show that TLBO can be used as an effective tool for position and power of BESS optimization solution, where for the 18-node system, there is about 3.7 % cost reduction and for the 33-node system, about 12% cost saving for power purchased for the surveyed 24-h period.