Multi-objective optimization of district heating systems with turbine-driving fans and pumps considering economic, exergic, and environmental aspects

District heating is an effective way to improve energy efficiency and decrease emissions. In studies, district heating multi-objective optimization only focuses on the fourth-generation system's planning but ignores the operation optimization of the third-generation. The exergy-related multi-objective optimization is usually combined with economy, while the environmental aspects, especially carbon emissions trading is rarely introduced. Auxiliaries consume lots of energy but are seldom considered both in modeling and optimization. Thus, this paper develops a multi-objective optimization model integrating exergy, environment, and economy with careful consideration of auxiliary equipment modeling and carbon emission trading. The model is validated by a special third-generation district heating system with turbine-driving fans and pumps located in Shenyang, Northeast China. The non-dominated sorting genetic algorithm is used to solve the model. No power generation, self-use priority, and on-grid priority are optimized and the exergy efficiency is improved by about 3–4%. Variable speed of auxiliary equipment can reduce power consumption in the cubic form of the variable speed ratio's reciprocal, and four times the carbon trading price of the current can lead to a one-third proportion in expenditure. The outcomes can be referred to make energy policy and operation decisions related to district heating.