Collaborative Optimization Strategy of Network-Load-Storage for Peak Load Shifting of Power System

As the integration of advanced power electronic technologies like microgrids, distributed generation, and energy storage systems gains momentum, the conventional passive and unidirectional mode of power supply encounters significant challenges. These advancements have brought about issues such as voltage instability due to the mismatch between energy supply and demand. In response, this research proposes a collaborative optimization strategy of network load and storage for peak load transfer. The objective is to harmonize the interaction between the distribution network, the load, and the energy storage segments, thereby leveraging various controllable assets to enhance the efficiency of energy resource utilization. The methodology begins by leveraging the predictive capabilities of the Long Short-Term Memory (LSTM) network for voltage analysis. Then, informed by the projected voltage operation trends, the Network-Load-Storage (NLS) coordination strategy is employed. This strategy optimizes the energy storage's charge and discharge cycles to shave peak demand and bolster the load during periods of low demand. Comparative simulations demonstrate that the optimization approach presented in this study effectively enhances voltage stability, with the optimization scheduling yielding favorable outcomes.