Research on predictive control strategy for central heating system based on LightGBM
A predictive control strategy for centralized heating systems based on Light Gradient Boos-ting Machine(LightGBM)is proposed to address the current situation of large time delay nonlinearity in urban centralized heating systems,excessive reliance on manual experience in load prediction and regula-tion of heat exchange stations,imprecise and untimely system prediction and regulation processes,and high system energy consumption.Firstly,based on the principle of climate compensation technology in heating systems,a LightGBM heat exchange station return water temperature prediction model was estab-lished to ensure the timeliness and reliability of the return water temperature prediction target.Secondly,a prediction function based on the moving weighted average algorithm was designed,and combined with the PID control algorithm,precise load prediction and high-performance regulation of the centralized heating system were achieved.The practical results show that the proposed LightGBM based predictive control strategy for central heating systems can accurately predict the operating load of heat exchange sta-tions in a timely manner and has better advanced control effects,effectively improving the reliability and stability performance of the central heating control system.
central heating systemLightGBMload forecastingmoving weighted average algo-rithmpredictive control
万方数据
维普
