A Bcs-Gde Multi-Objective Optimization Algorithm for Cchp Model with Decision Strategies

District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. However, not only the correlation between multiple optimization objectives, but also the time-varying energy demand is ignored when establishing and solving the optimization model. In this paper, the combined cooling heating and power economic emission dispatch (CCHPEED) model is established with the objective of economic cost, primary energy consumption, and pollutant emissions. Another two decision-making strategies are proposed for the hourly level demand of the whole year. Besides, a generalized differential evolution with the best compromise solution processing mechanism (BCS-GDE) is proposed to solve the model, which optimizes three conflicting objections simultaneously without using weights. Then, the best compromise solution selection strategy can be used to select the appropriate optimization scheme as needed. The simulation is conducted in three application scenarios, and resource dispatching is performed according to the different energy demands of hotels, offices, and residential buildings on the whole day. The simulation results show that the model established in this paper can reduce economic cost by 72%, the primary energy consumption by 73%, and the pollutant emission by 88%. Concurrently, the solutions obtain by BCS-GDE also has better convergence and diversity than the classic algorithms