Techno-economic control strategy optimization for water-source heat pump coupled with ice storage district cooling system

Abstract

Incorporating low-temperature renewable energy sources such as geothermal energy, solar energy, and waste heat into district heating and cooling systems is expected to be an effective solution for reducing fossil energy consumption and carbon emissions. This study aims to propose an optimal intelligent control strategy for the water-source heat pump coupled with an ice storage district cooling system, which can fully maximize the economic potential of renewable energy and ice storage systems. The proposed control strategy treats the ice melt cooling rate, water supply temperature, and cooling ratio of the water source heat pump as three independent control variables. The minimum operating cost per unit of cooling supply is identified as the optimal objective function of the genetic algorithm. An integrated heat transfer model of the water-source heat pump coupled with an ice storage district cooling system was developed, and experimental test data verified its accuracy. Compared with the ice melting priority control strategy and the water-source heat pump priority control strategy, the GA-based optimal control strategy saved 8.7–9.3% of the operating cost while maintaining a relatively good energy-saving performance. This proposed intelligent control strategy can stimulate the tremendous economic potential of the ice storage district cooling system coupled with renewable energy sources.