Adaptive planning of multi-type energy storage for urban distribution networks with increasing penetration of renewable energy

To address the challenge of source-load mismatch and low renewable energy utilization rate caused by increasing penetration of renewable energy such as wind and photovoltaics (PV) in urban distribution networks, this paper proposes an adaptive planning method for multi-type energy storage that enhances renewable energy utilization rate and maintains source–load balance while minimizing the overall system costs. The overall system cost is composed of energy storage investment costs, residual value of storage systems, and operating costs. For operating costs, a multi-time-scale operation model is established to comprehensively consider system characteristics across different time scales. By incorporating the maximum operating costs across time scales into objective, the model ensures cost-effective and reliable operation throughout the planning horizon. Simulation model based on historical wind, PV, and load data in an urban distribution network validates the proposed method. The results verify that the proposed method can improve the utilization rate of renewable energy resources at a relatively low cost.