In three-north regions of China

power regulating abilities of cogeneration units are constrained significantly by their compulsory heat outputs. Such regulation mode is one of the key reasons for the large amounts of wind curtailment in the last few years in winter. Introducing electric heating boilers and thermal energy devices are effective ways to promote wind power integration and reduce the energy consumption of district heat and power system. In order to get the optimal economic configurations of the clean heating reconstruction projects

a two-layer optimization model based on the genetic algorithms and traditional unit commitments is proposed in this paper. First

by analysing the supply and demand relationship of heat and power

a typical structure of the district energy system (DES) in northern China was given. Then

the daily net benefits were defined as the quantitative economic indexes for any reconstruction projects. Finally

the two-layer optimization model was obtained by integrating short-term dispatch models of the DES. In this model

the genetic algorithms are used to search for the most economical configuration combinations globally

and the fitness values of the population are solved by the inner linear programming. Case studies indicate that the optimal configurations of the clean heating project were affected by several factors including the heat and power demands

characteristic of the wind power outputs

and socioeconomic conditions. Although differences exist between several independent genetic optimizations

any of these solutions are good enough to meet the requirements of engineering application. In addition

although more wind power can be integrated by introducing electric heating boilers and thermal energy devices

there is no need to integrate all wind power because of the law of diminishing return.