Research on the stability evolution mechanism and combinatorial optimization decision‐making of multitype heterogeneous energy cooperative operation

Abstract

Abstract Considering the cooperative willingness of multiple heterogeneous energy sources to participate in the alliance, the stability of the cooperative operation of each entity (hereinafter referred to as stability) and the supporting mechanism of its optimal combination to realize the high proportion of new energy generation are studied. Through simulating load peak‐cutting and valley‐filling in the power system, the difference between the load value and the base load in the 24 h of the daily load curve is used as the calculation condition for the supply balance of the alliance. Based on the source‐load power balance model, the feasibility of power data normalization is derived and demonstrated. Simultaneously, taking into account the time‐of‐use price cost of each entity, a multiscale operation cost allocation and stability evolution analysis model for the alliance is constructed using the Shapley value and the largest consistent set method. By comparing the willingness of each entity to engage in the alliance, as well as the multiscale operation stability and economic change rule of different alliances, the results demonstrate that: (1) Alliance 1 has the advantage of economic operation. (2) The common stability period of different alliances is influenced by the participation preferences of each entity (wind power, photovoltaic, and thermal power tend to participate in Alliance 1, while hydropower tends to participate in Alliance 2). (3) Alliance internal restructuring can be carried out by utilizing spatial and temporal difference characteristics of different entities’ participation in alliance preferences, thereby achieving alliance stability and efficient operation. This study provides a theoretical basis for making decisions regarding the optimized stable operation of the alliance.

Keywords

• cooperative operation stability
• heterogeneous energy alliance
• optimization decision
• Shapley value method