Fuzzy modeling and particle swarm optimization based on energy consumption data of the combined cold-heat and power system

Modeling and multi-objective optimization of a Combined Cold-Heat and Power (CCHP) system are studied on the basis of the Transient System Simulation Program (TRNSYS). After the CCHP system is built on the TRNSYS plant, data is collected on the operation of the CCHP system. Based on the semi-tensor product theory, a fuzzy matrix model that can accurately reflect the characteristics and relationship among the input and output variables is established. Then, an objective function of the CCHP system is optimized by using the improved particle swarm search strategy based on the sub-time electricity price. Finally, the weight of each objective function is determined by a two-element comparison method. The multi-objective optimization of the CCHP system is also investigated by using a norm-weighting method. The results indicate when the local optimal cost and operation cost, environmental cost, and configuration cost are reached, the global optimal cost of each typical day can operate well under the strategy of the total cost and the overall cost of the production system.