Optimal Planning and Operation of Battery Energy Storage Systems in Smart Grids Using Improved Genetic Algorithm Based Intelligent Optimization Tool

• Main Authors: Kannathat Mansuwan, Peerapol Jirapong, Sattawat Burana, Panida Thararak
• Format: Conference Proceeding
• Published: 2019
• Subjects: Energy
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85062876981&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/65578
• Institution: Chiang Mai University

© 2018 Asian Institute of Technology. In this paper, an improved genetic algorithm (IGA) implemented with reliable power system analysis tool is developed to determine the optimal planning and operation of battery energy storage system (BESS) in smart grid with photovoltaic (PV) generation. The main objectives are maximizing benefit from energy losses reduction and energy shaving enhancement, while minimizing the investment cost. Double layers optimization technique is implemented for determining the BESS siting and sizing in the first layer, while the maximum energy shaving is calculated in the second layer. The IGA implemented in MATLAB and DIgSILENT programs utilizing an automatic data exchange process is utilized for solving the optimal solution. This approach is tested on a practical 22 kV distribution network of Thailand to present the effectiveness of decision-making support tool. The simulation results show that the optimal BESS planning results in mitigating PV intermittency and improvement in smart grid efficiency.