Three-layer day-ahead scheduling for active distribution network by considering multiple stakeholders. (15th September 2020) - Zhou, Yulu; Zhang, Jingrui
Abstract: The increasing penetration of renewable energy resources (RES) has prompted the gradual evolution of distribution systems from passive networks to active ones. The independent operators of various microgirds and active users urgently need a new optimization scheme to replace the traditional centralized scheduling method in active distribution network (ADN). This paper proposes a three-layer day-ahead optimal schedule mechanism taking account of multi-stakeholders in ADN. In the proposed mechanism, the distribution network (DN) is divided into three layers structurally: User layer, microgrid (MG) layer and DN layer. Meanwhile, the corresponding three-layer optimization method is proposed correspondingly. Firstly, the optimal user power consumption scheme and the optimal user energy storage operation scheme can be obtained by minimizing the total cost of an active user. Subsequently, the MG economic dispatch is performed within the obtained user power purchase information from the User layer. By ensuring the interests of active users, an optimal MG economic dispatch scheme can be obtained, in which the information of the connection point between the DN and the MG is transmitted to the upper DN as one of the constraints in the optimization of DN layer. Finally, the third-layer optimization is performed to obtain the optimization results of the DN layer. An actual 47-bus distribution system is employed to verify the proposed three-layer optimizing framework and the results show the effectiveness of the proposed method. Highlights: Three-layer day-ahead scheduling mechanism is proposed to coordinate optimizations in ADN. Benefits of multi-stakeholders including DN, MGs and users are considered in the mechanism. DE algorithm is employed to solve the coordination optimization between MGs and users. TOU price-based demand response program integrating elastic coefficient is used for MG loads. Parallel computing strategy in MG level is used to save time and increase computation efficiency.