Research and Application of User-Side Optical Storage Optimization Operation Strategy

In the context of China's carbon peak and carbon neutrality goals, numerous distributed generations such as photovoltaic and energy storage are being deployed on the user side. This study addresses the challenges of optimizing operational scheduling to enhance economic benefits and elevate user satisfaction levels. This paper uses Quantum-behaved Particle Swarm Optimization (QPSO) algorithm to optimize the hyperparameters and network topology of Long Short-Term Memory (LSTM). Consequently, a QPSO-LSTM short-term load prediction model was developed alongside an optimization scheduling model for user micro grids, which was solved using the CPLEX solver. The proposed model effectively integrates photovoltaic and energy storage resources to optimize micro grid operation. The results indicate that this optimal scheduling method not only ensures stable micro grid operation but also reduces power consumption on the user side and enhances user satisfaction.