Research on multi-objective optimization of control strategies and equipment parameters for a combined heating system of geothermal and solar energy in cold and arid regions based on TRNSYS

Abstract

Focusing on the multiple objectives of maximum solar heating capacity, maximum COP of heat pump and minimum soil heating capacity, a model of one typical building and two heating strategies was established in the TRNSYS. Non-dominated Sorting Genetic Algorithm (NSGA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on entropy weight are used to optimize operation parameters. Optimized control strategies and equipment parameters of a combined geothermal and solar system in cold and arid regions were taken as the research objects. The final optimized strategy and the original strategy of the single ground source heat pump heating system were compared. Research results show that the optimized control strategy of the geothermal solar heating system transforms solar hot water from the storage tank to heating terminals in the heating season and transforms solar hot water to the ground heat exchanger in the non-heating season. Compared to GSHP, the optimizing strategy saves 16.8 MWh annually, and the energy saving rate is 20.59%. Soil temperature drop increases from 2.74 °C to 0 °C. The annual electricity saving cost intensity is about 4 yuan/m2, and the CO2 emission reduction intensity is 4.3 kg CO2/m2. This study provides a solution for soil temperature reduction in one year and low-cost operation in cold and arid regions during ground source heat pump applications.

Keywords

• Multi-objective optimization
• Ground heat recovery
• Control strategy
• TRNSYS
• NSGA-Ⅱ