Multi-objective integrated optimization of smart zero-carbon parks

Abstract

Under the dual-carbon transition, park-scale heating systems in cold regions need to reduce carbon emissions while keeping long-term costs acceptable. This thesis investigates the multi-objective optimisation of a zero-carbon park heating system in Gaocheng District, Shijiazhuang. The studied system includes a shallow-geothermal subsystem, an air-source heat pump and a hot-water thermal storage tank connected through a district-heating network. nPro is used to build the model and compare two scenarios under the same annual heat demand and the same system boundary. Scenario A uses a fixed electricity price and load-following operation, while Scenario B uses the South Hebei time-of-use electricity tariff and storage-oriented dispatch. The optimisation objectives are life-cycle economic performance and annual operational carbon emissions. The results show that Scenario B changes both equipment sizing and system operation. The ASHP capacity decreases from 6,735 kWth to 3,399 kWth, while the storage volume increases from 3.01 m³to 1,906.88 m³. Annual storage charging and discharging increase to 8,519 MWh and 8,355 MWh, respectively. The geothermal heat share rises from 85.2% to 96.1%, and the system COP improves from 2.748 to 2.963. Compared with Scenario A, Scenario B reduces grid electricity import by 7.3%, primary energy consumption by 7.3% and CO₂ emissions by 7.3%. It also reduces electricity cost from CNY 148.07 million to CNY 120.14 million and total cost excluding revenue from CNY 245.10 million to CNY 214.71 million. The payback period is shortened from 11 years to 9 years. These results indicate that time-of-use pricing and sufficient thermal storage can support both low-carbon operation and better economic performance in the Gaocheng zero-carbon park case.