采暖系统利用神经网络的运行方案

An Operating Method for Heating System Using Neural Network Theory

由于不带恒温阀的常规采暖系统在一定时期内还会大量存在 ,而现有的质量并调方案建立在“静态”基础上 ,忽略了系统的热惰性 ,使系统逐时供热量与需热量不一致 ,造成系统热用户室温偏高或偏低 ,即降低了供热品质 ,又浪费能源。本文利用神经网络理论 ,建立了一种常规采暖系统的自适应控制方案。模拟结果显示 ,这种“动态”运行方案克服了常规“静态”

The heating system without thermostatic valves will still exist in our country for a long time. Since at present the operating methods of heating system are based on the 'thermal static', it results in the difference between the quantity of supply heat and the one demanded with the room temperatures of the heated buildings often beyond the design values,resulting in more energy consumption and affecting the heating quality.In order to improve the operational performance of heating system,a self-adaptable dynamic operating method is established based on the neural network theory in this article.The simulated results have shown that the dynamic operating method can resolve the problem resulted from the static one.