A resilience-oriented optimal planning of energy storage systems in high renewable energy penetrated systems

Natural events having a low occurrence probability and high impacts, such as windstorms and earthquakes, pose a danger to the distribution networks' optimal performance. To increase network resiliency, several operational solutions are necessary. This paper shows how to restore prioritized loads while meeting topological and operational constraints using mixed-integer linear programming. The model presents a plan for enhancing the interconnection of renewable energy sources (RESs), stationary battery energy storage systems (SBESSs), and power electric vehicles parking lots (PEV-PLs), which are used in the distribution system (DS), to get the optimal planning under normal and resilient operation. The stochastic optimization technique is used to model the in-fluence of upstream grid pricing uncertainty on the optimal scheduling of (DS). Other major uncertainties, such as wind power, photovoltaic (PV), and active/reactive power for different types of electrical loads, are also simulated using stochastic optimization. In addition, demand response programs (DRP) and interruptible loads are introduced to enhance the resilient operation of the DS. The suggested planning model is tested on the IEEE 33-bus benchmark test system. The results confirm the feasibility and effectiveness of the suggested model in normal and resilient operation and to assess its performance.

Automated summary

This paper presents a mixed-integer linear programming approach to restore prioritized loads and enhance the interconnection of renewable energy sources, energy storage systems, and electric vehicle charging stations in the distribution system. Stochastic optimization techniques are used to model uncertainties and demand response programs and interruptible loads are introduced to improve the resilient operation of the distribution system. The proposed planning model is tested on a benchmark test system and found to be feasible, effective, and efficient in normal and resilient operation.