基于自适应混沌粒子群算法的冷-热-电联供系统调度策略
摘要：为进一步提高新能源在冷-热-电联供系统(combined cooling heating and power system，CCHP)中的供能比例，在传统CCHP的基础之上，引入新能源供能技术，构建了一种高比例新能源接入的冷-热-电联供系统(high proportion of new energy access combined cooling heating and power system，HPNE-CCHP)。为了使系统运行更加经济，以HPNE-CCHP系统的总运行成本为目标函数，搭建了混合整数经济调度模型，提出一种自适应混沌粒子群算法(adaptive chaotic particle swarm optimization，ACPSO)对模型进行求解。以中国北方某楼宇为例，构建了HPNE-CCHP系统，将所提模型及求解算法应用于该建筑的典型日的实际算例中，并与不含太阳能供热的CCHP系统进行了对比。仿真结果表明，该模型可以有效对系统进行调度，提高新能源的利用效率，使系统以更加经济的方式运行。
Abstract: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.
标题：基于自适应混沌粒子群算法的冷-热-电联供系统调度策略
英文标题：An Adaptive Chaotic Particle Swarm Optimization Based Scheduling Strategy for Combined Cooling, Heating and Power System
