Abstract: With popularity of heating metering system, system can be adjusted according to the change of load, and the resistance coefficient of pipe network change. Optimal identification of variable resistance coefficient is an effective means to understand the real-time operation of heating network. We present an optimal identification method for variable resistance coefficient of heat supply network based on flow observation data. Genetic algorithm is used to solve the problem. Relative error of the identification results is less than 5% in practical verification example. It shows that the method can obtain variable resistance coefficient of heating network with high accuracy when only flow observation data is available. It can provide guidance for the operation and regulation of heating systems.