基于k-means聚类的地源热泵机组运行策略优化研究

Study on Operation Strategy Optimization of Ground Source Heat Pump Unit based on K-means Clustering

以上海某地源热泵为研究对象,基于长期实测数据对全年工况性能特性进行了研究。通过k-means对全年工况的日逐时负荷进行聚类分析,获得采暖、制冷和过渡季节等不同季节最佳族数及对应族下典型日负荷曲线特性。构建地源机组的性能仿真模型,通过实测数据获得模型相关参数值。分别以最优制热制冷性能系数为目标,建立了运行负荷配比优化模型,并将模型应用于上述不同季节典型工况,对各典型工况下的运行策略进行优化,获得各工况下最优运行策略。通过与实测数据的对比,运行策略优化有效提高了热泵系统的能效。

This paper analyses the performance characteristics of a ground source heat pump in Shanghai based on the longterm measured data.A new cluster analysis method,k-means algorithm,is presented to reduce a complete 365 days energy demand profiles into a limited number of typical days,and obtains the optimum clustering-number for different seasons and their typical daily load curves.This paper constructs the performance simulation model of the ground source heat pump unit,obtains the relevant parameters of the model by the measured data,and develops a simple operation optimization model for the ground source heat pump system aiming to maximize the system performance coefficient.An illustrative example study is discussed to demonstrate the proposed method and model.The operation strategy for each typical working condition is optimized.Compared with the measured data,the system performance coefficient of ground source heat pump is greatly improved by operation strategy optimization.