A Multi-Stakeholder Coordinated Planning Method for Self-Healing Distribution Networks

With the increasing penetration of distributed renewable energy sources (DERs) in distribution systems and the widespread integration of energy storage systems (ESS), the need for a coordinated planning approach combining the distribution system, renewable energy, and ESS is crucial. Additionally, frequent extreme events in recent years have caused significant damage to the power system, highlighting the importance of enhancing self-healing capabilities. This paper presents a coordinated planning method for distributed intelligent distribution networks, considering the interests of various stakeholders while effectively improving self-healing capability. First, a density-peak-based improved k-means clustering algorithm is employed to establish typical scenarios. Next, a two-level coordinated planning model is developed, where the upper-level optimization targets the economic efficiency and self-healing capability of the distribution network, while the lower-level focuses on optimizing the benefits of distributed generation (DG) and ESS, as well as the optimal output of ESS. The bat algorithm is applied to solve the model on the improved IEEE 69-bus system, where operating costs decrease by 2.173 % and load loss by over 20 % under extreme events, validating the effectiveness of the proposed method.