Planning method of pipe diameter renovation of a large-scale centralized heating network based on load prediction

This paper presents a pipe diameter renovation planning method based on the heating load prediction model for all heat users in the whole network and the improved genetic algorithm. The heating load prediction model for all heat users in the whole network is proven to be able to quickly and accurately predict the heating load of all heat users in the whole network by selecting typical residential and public building users and extending their heating load characteristics to the whole network. The improved genetic algorithm screens out pipe sections that can profit from renovation as optimization variables through renovating potential index, which can significantly reduce the number of optimization variables of the genetic algorithm. By comparing with the traditional genetic algorithm, it is found that it has higher computational efficiency and better optimization ability. Applying the above method to the pipe diameter renovation planning of a large-scale centralized heating network in Xi’an, it is found that the optimization variables can be reduced from 246 to 13. Moreover, the final optimization result shows that an annual renovation profit of 1.73 million yuan can be obtained by only renovating three pipe sections.