Smart control for battery energy storage system in a community grid

Distributed renewable energy generators: wind turbines, photovoltaics and other Renewable Energy Source of Electricity (RES-E) are coupled with energy storage system to supply power to the local consumers in the micro-grid network. This system requires a wide-range of control to ensure system security, optimal operation and emission reduction. This paper proposes a variable-threshold methodology for control of energy storage unit within a micro-grid. With each stage of the decision making for optimal energy distribution adopting, an Adaptive Intelligence Technique (AIT) was applied on system variables for efficient power management. The AIT brings about optimal energy distribution across peak period, demand smoothening and high efficiency battery utilization. The proposed method was evaluated using onsite measured RES output data. The results show that this method can achieve load curve smoothing and maximum local utilization of the RES energy without requirement of precise load and RES forecasting. Compared with the traditional methods which either uses a fixed threshold or requires forecasting for battery charging/discharging, the proposed algorithm provides a variable energy regulation reference which is intelligently updated every sample step. The improvement is demonstrated using the simulation testing results.