In this study, the decision variable was based on the heat storage volume of each part of the heat storage system, and the optimization model of the heat storage system was established with the total present value of the total life cycle cost of the heat storage system as the optimization target, and the solution was obtained by Hooke-Jeeves optimization algorithm. Taking a small district in Xining city as an example, the result shows that the optimal ratio between the total heat storage capacity of users and the centralized heat storage capacity is 3∶2. Compared with the calculation results of heat storage volume of traditional solar energy system, the optimal heat storage volume reduced by more than 40%. Moreover, it is found that with the increase of the volume of the heat storage tank, the heating capacity of the auxiliary heat source of the system decreases first and then increases, and the heat generated by the solar energy increases first and then tends to be fixed, the initial investment of the system presents an increasing trend, and the total present value of the operation investment and the life cycle cost of the heat storage system presents a decreasing trend and then increases. Finally, the life cycle cost saving percentage is used as the evaluation index to analyze the influence degree of the influencing factors, and the sensitivity is the boiler heating unit price > discount rate > life cycle.
Key words
distributed /
solar energy /
central heating /
heat storage system /
transient system simulation program（TRNSYS）
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