Research on Time-of-Use Pricing Optimization and Load Adjustment in Distributed Energy Systems

To address the challenges of integrating high propor-tions of renewable energy into the grid amid the energy transition, this paper proposes a time-of-use pricing-based electricity optimiza-tion model for distributed wind-solar hybrid systems. The model aims to guide load demand through price signals, achieving synergistic optimization of efficient energy consumption and economical system operation. Addressing the limitations of traditional single-objective optimization, this study constructs a multi-objective optimization framework centered on maximizing wind power consumption and minimizing operational costs. A hybrid optimization strategy inte-grating the Hierarchical Evolution Algorithm (HEA) and Tabu Search (TS) is designed to enhance global search capability and con-vergence efficiency. The model comprehensively considers key condi-tions such as power balance constraints, dynamic characteristics of energy storage systems, and equipment operational limitations, estab-lishing a systematic power output and multi-objective optimization function. Simulation results demonstrate that the proposed method effectively smooths load curves, enhances grid stability, and signifi-cantly improves renewable energy utilization rates. This research offers an innovative solution for balancing renewable energy integra-tion with economic efficiency within electricity market environments, validating the practical application potential of time-of-use pricing strategies in advancing energy internet development. Translated with DeepL.com (free version)