Risk constrained battery energy storage planning in active distribution networks

This paper proposes a stochastic planning framework for the battery energy storage system (BESS) with abundant distributed renewable energy sources. The uncertainties of wind power, solar power, and load demand variations are modeled through the scenario analysis. The risks of the planner in the uncertain environment is also considered. The conditional value at risk (CVaR) theory is introduced into the objective model to model the risk. A series of case studies are conducted to validate the efficiency of the proposed method.