Research on Collaborative Resource Allocation in Microgrids Based on the Integration of Design and Operation

This paper proposes a method for microgrid capacity allocation and operation optimization. By collecting various historical data, a prediction model is constructed using an LSTM neural network to obtain microgrid load forecasting results. Based on this, a configuration model targeting power supply revenue and stability is established. The load forecasting results are input into this model, and an operation optimization scheme is iteratively formed. Practical cases demonstrate that the method proposed in this paper, which comprehensively considers various influencing factors of microgrids, can effectively enhance the design configuration and operational capabilities of microgrids.