Green Energy Management of the Energy Internet Based on Service Composition Quality

The realization of dynamic service combinations to meet the requirements of green energy management and match supply and demand has become a large problem in the energy Internet (EI). We propose a method of service combination for quality-oriented green energy management of the EI, introduce the most economical control theory, and set the service quality obtained from unit energy consumption as the most economical objective control function to realize a Pareto-efficient energy service management configuration of the EI under quality of service demands. Then, this paper introduces a multi-objective dragonfly algorithm that takes advantage of rapid convergence to solve the model. A back propagation neural network is adopted to train the model and obtain a multi-objective parameter weight configuration to accommodate measured data. The experimental results show that this method can efficiently determine service combinations for an economical, quality-oriented EI and green Pareto-efficient energy management.