随着我国电力需求侧管理(DSM)的日益深入和分时电价制度的日益完善,蓄热式电锅炉的应用将越来越广泛.利用人工神经网络的BP预测模型对蓄热式电锅炉供热系统进行了热负荷预测.并以某医院1 200kW蓄热式电锅炉优化运行的研究为例,得到了某日预测的逐时热负荷与实际热负荷的对比关系,预测值与实际值吻合良好.

Along with the generalization of DSM and time-sharing price system, the use of electric boiler with heat reservoir becomes more and more extensive. Load forecasting of heat supply system is an important base in the study of economical operation of electric boiler with heat reservoir under time-sharing price. The BP ANN modeling of the load forecasting for a 1200 kW electric boiler is discussed. The result of hourly heat load forecasting accords well with the real heat load.

TK227