基于市场交易-粒子群算法的地源热泵系统节能优化方法

Energy Saving Optimization Method of Ground Source Heat Pump System Based on Exchange Market-particle Swarm Algorithm

针对地源热泵低效控制导致系统运行效率低下、能耗增加问题,本文提出了一种基于市场交易-粒子群算法(EMA-PSO)的地源热泵系统节能优化方法。建立了以易于传感器采集参数为输入值、系统控制参数为输出值的地源热泵系统优化模型,使用EMA-PSO对模型进行求解,改善了传统粒子群算法(PSO)的缺陷。本文以上海某办公楼地源热泵系统为研究对象,基于历史运行数据进行了系统建模和仿真分析,结果表明:相较于PSO,EMA-PSO具有更佳的寻优稳定性和更小的寻优结果;在夏季典型日,相较于原有控制模式,EMA-PSO实现了24.82%的节能率。

Aiming at the problem of low efficiency and energy consumption increase of the ground source heat pump caused by the inefficient control.An energy-saving optimization method of the ground source heat pump system based on the exchange market-particle swarm algorithm(EMA-PSO)is presented in this paper.An optimization model of ground source heat pump water system with easy-to-sensor acquisition parameters as input and system control parameters as output is established.The model is solved by using EMA-PSO,which improves the shortcomings of traditional PSO.The ground source heat pump system of an office building in Shanghai is taken as the research object,and system modeling and simulation analysis based on historical operating data are conducted.The results show that compared with PSO,EMA-PSO has better optimization stability and smaller optimization results.On a typical summer day,EMA-PSO achieves an energy saving rate of 24.82%compared to the original control mode.