Spatiotemporal Optimization–Based Assessment of Mutual‐Aid Capacity for Interconnected Distribution Areas Considering Internal and External Energy Interactions

In order to accurately evaluate and tap the mutual‐aid capacity potential of interconnected power stations under the scenario of peak‐to‐peak compensation between new energy output and load demand, this paper uses Copula function to describe the correlation structure of wind, light, and load from the perspective of source–load matching, quantify the complementary degree of residual power and new energy output after source–load matching, and determine the feasible interval of mutual aid. On this basis, a space–time mutual‐aid capacity optimization model with the goal of minimizing the total operating cost of the interconnected area is constructed. The model takes the principle of priority mutual aid in the station area and comprehensively considers the internal and external energy interaction constraints such as the transaction cost of purchasing and selling electricity with the superior power grid, the two‐way power constraints of the tie line, the transformer capacity, and the renewable energy output constraints. Finally, the model is solved efficiently by the CPLEX solver of MATLAB. The simulation results of the example show that the proposed method can automatically establish cross‐regional mutual power channels in the period of significant complementarity and significantly improve the renewable energy consumption level and overall operation economy of the station area while ensuring load power supply.