Dynamic modelling and optimization of battery energy storage sizing for solar plant

Abstract Malaysian government is in strong push to increase the penetration of renewable energy (RE), particularly solar into the national energy mix, aiming for 58% solar out of 70% RE target set by National Energy Transition Roadmap (NETR) by 2050. At such, the intermittent and variable nature of solar photovoltaic (PV) generation presents a significant challenge to grid stability. A promising solution to this issue is the integration of battery energy storage system (BESS) with solar PV installations to smooth out power output fluctuations. This study presents a dynamic sizing model developed to mitigate solar power variability using two filtering techniques namely the Moving Average and Savitzky-Golay filters to generate smoothed power output profiles. The difference between original and filtered output curves determines the required charging and discharging power, which forms the basis for calculating the optimal battery capacity for effective power smoothing. Additionally, an alternative battery sizing model that based on peak clipping and energy shifting of original solar power output is also formulated that aims at enhancing energy management of solar power output. Applying both models to a simulated case study of a hypothetical grid-connected solar plant in Bukit Selambau, Kedah, it was found that the power smoothing method resulted an optimal battery capacity of 388 kWh for the same capacity solar system. These results aligned with the latest regulation by the Energy Commission of Malaysia, which mandates that the minimum battery storage capacity must be at least 30% of the solar plant’s registered capacity. The proposed methodology serves as a practical guideline for designing efficient, cost-effective and regulation-compliant BESS solutions for solar PV applications in Malaysia.