An Adaptive Chaotic Particle Swarm Optimization Based Scheduling Strategy for Combined Cooling, Heating and Power System

To further increase the energy supply proportion of new energy in combined, cooling, heating and power system (CCHP), on the basis of traditional CCHP a renewable energy supply technology was led in and a new CCHP with high proportion of new energy (HPNE) was constructed. To make the operation of the constructed HPNE-CCHP system more economic, the total operation cost of HPNE-CCHP system was taken as the objective function and a hybrid integer economic scheduling model was constructed, and then, an adaptive chaotic particle swarm optimization (ACPSO) was proposed to solve the constructed model. Taking a certain building located in North China for example, an HPNE-CCHP system for this building was constructed, and the proposed model and solving algorithm were applied to the calculation example based on the data of the typical day of this building. The Calculation results were compared with the CCHP without solar heat supply. Simulation results show that the constructed mode can be applied to the scheduling of this HPNE-CCHP system to improve the utilization efficiency of renewable energy, and make the HPNE-CCHP system can be operated in more economic modes.