Capacity optimisation and multi-dimensional analysis of air-source heat pump heating system: A case study

The utilisation of air-source heat pumps (ASHPs) for heating is a pivotal technology for enhancing the environmental friendliness of building heating and striving towards carbon neutrality within buildings. This study establishes an optimal configuration method for ASHP and electric heating (EH) systems based on the economic equilibrium-point temperature and number of unsatisfied hours per year derived from an hourly heating load analysis of the building. Additionally, it evaluates the performance of ASHP-EH, gas-fired boiler (GB), coal-fired boiler (CB), and electric boilers (EB) under varying Proportion of Renewable Energy Power Generation (PREPG), utilising the Technique for order preference by similarity to an ideal solution (TOPSIS) method with the entropy weight (EW) method, considering primary energy consumption, CO2 emissions, and heating cost as evaluation indicators. In a case study on a industrial plant heating capacity configuration in Yulin City, the system configuration was based on an optimal economic equilibrium-point of −12 °C, with five unsatisfied hours per year. The ASHP-EH are configured with capacities of 97 kW and 70 kW, respectively, representing a 33% reduction in heat pump capacity compared to the design point temperature of −22 °C. The calculated scores for different heating methods, including ASHP-EH, GB, CB, and EB, were 0.2563, 0.3225, 0.2953, and 0.1260, respectively, under the current 31.6% PREPG. The results of the calculations indicate that the overall score of the heat-pump heating system does not exhibit a significant advantage under the influence of factors such as CO2 emissions and initial investment. However, as the proportion of PREPG increased to 50% and 75%, the normalised scores for ASHP-EH also increased to 0.3163 and 0.3508, respectively, indicating a significantly greater advantage for this solution. This analysis method can offer valuable insights into system optimisation and decision support in the realm of clean energy-heating retrofits within buildings.