Collaborative Control Algorithm for Multi-Source Energy Supply Under Load Response Optimization

Multi source energy supply systems are affected by various uncertain factors in actual operation, such as the volatility of renewable energy, uncertainty of load demand, equipment failures, etc. In order to cope with these uncertain factors and address the problems of poor reliability and low response speed, this paper proposes a multi-source energy supply collaborative control algorithm under load response optimization. Calculate the load of multi-source energy supply, and construct a multi-source energy supply collaborative control model with the annual investment and operation cost, CO2 pollutant emissions, and multi-source energy supply interruption rate as objective functions. On this basis, a multi-objective hybrid particle swarm algorithm is adopted to establish an external Pareto solution set archive, record all non dominated collaborative control schemes, solve the multi-source energy supply collaborative control model, and achieve multi-source energy supply collaborative control. The experimental results show that the proposed method has a good collaborative control effect on multi-source energy supply, which can effectively improve the economy, environmental protection, and reliability of multi-source energy supply, and has a high response speed.