Economic dispatch model of renewable energy system considering demand response

Due to the intermittency and volatility of renewable energy, the system stability is poor and the operating cost is high. This study proposes an economic dispatch model for renewable energy systems based on a demand response model and differential evolution algorithm. A demand response model based on real-time flexible tariffs is combined with charging and discharging strategies for electric vehicles to optimize flexible load dispatch in the system. This combination is intended to improve the efficiency and reliability of grid operation. The traditional differential evolution algorithm is prone to getting stuck in local optima. Given this, this study introduces a deterministic sequence-improved differential evolution algorithm to enhance population diversity and local search ability, significantly improving the global search performance and convergence efficiency of the algorithm. To validate the effectiveness of the model, function extremum and system operation simulation experiments are designed. The results showed that the improved algorithm had a variance of 0 and an optimal value of 10-30 on multi-modal functions, and a variance of 0 and an optimal value of 10-3.5 on fixed dimensional functions. After considering demand response, the peak valley difference in electricity consumption between renewable energy systems A and B was 90.15MW and 527.55MW, with fluctuations of 36.57MW and 201.79MW, and operating costs of 46058.76 yuan and 52.3315 million yuan, respectively. Research findings indicate that the electric energy coordination and economic management of this model have been significantly enhanced. These enhancements effectively ensure efficient energy utilization, facilitate the safe and stable operation of the system, and provide a novel theoretical foundation for the optimization and scheduling of renewable energy systems.