A Resilience Enhancement Planning Framework Capturing Customers’ Participation in Distribution Systems

Abstract

This paper presents a novel planning framework to enhance the resilience of energy supply to customers in power distribution systems. The framework involves three key stakeholders: the regulator as the governing entity that enforces regulatory mechanisms to oversee the performance of the distribution system operator (DSO); the DSO that reinforces the infrastructure by placing emergency distributed generations and hardening sections, implements necessary operational decisions, and facilitates customers’ participation by introducing appropriate incentives; and customers who may (i) gain the desired resilience through investing in self-generation, (ii) rely on the resilience provided by the DSO along with paying the agreed-upon insurance premiums, or (iii) opt for a mix of both approaches. The proposed framework is designed through a four-step process. First, the regulatory mechanisms are established by setting a standard resilience index for the penalty and reward model as well as a revenue cap for the DSO under a revenue-cap regulation using customized optimization problems aimed at optimizing DSO’s costs without customers’ participation. Next, an integrated resilience enhancement optimization problem that coordinates the strategies of the DSO and customers is formulated as a mixed-integer linear programming model, focusing on the global objective functions of the DSO and customers. Finally, the economic benefits are distributed between the DSO and customers who are justified for investment in self-generation using a suggested method based on Monte-Carlo estimation, in which the Fisher-Yates shuffle technique and a designated optimization problem are employed. Applied to the IEEE 33-bus test system for two case studies, the proposed framework is proven to be effective in enhancing resilience, achieving regulatory objectives, and providing economic benefits for both the DSO and customers, creating a mutually beneficial scenario for all parties involved.