Optimal Placement and Sizing of Energy Storage Systems in Low Voltage Distribution Network

This paper investigates the integration of solar rooftop systems within low-voltage distribution networks. Although these decentralized systems are gaining popularity due to their cost-effectiveness and renewable energy potential, they pose significant operational challenges, such as voltage instability and transformer overloading. To mitigate these issues, we propose the incorporation of battery storage systems (BSS) to stabilize voltage levels and alleviate thermal stress on feeders and distribution transformers. The study utilizes a genetic algorithm (GA) for the optimal sizing and placement of BSS, coupled with power flow analysis conducted using DIgSILENT PowerFactory software. The optimization framework is tested on a 16-bus low-voltage distribution system featuring solar rooftops, providing a thorough assessment of its impacts on voltage regulation and load conditions. The results indicate that the proposed methodology effectively identifies optimal BSS placement and sizing, improving grid reliability and operational efficiency. Additionally, it ensures voltage levels at customer buses remain within permissible limits and prevents overloading of distribution transformers and feeders.