Dynamic Performance and Intelligent Control Optimization Algorithm of a Novel Solar-assisted Multi-source Heat Pump Heating System

Li, Yunhai

Abstract

With the increasing challenges of climate change, carbon reduction and carbon neutrality are raising great attention from countries around the world. In the increasing global primary energy consumption, building heating takes up around 48% proportion. However, building heating still highly relies on fossil energy, of which decarbonization has become the key to global carbon neutrality. Solar-assisted heat pump (SAHP), as an energy-efficient low-carbon heating technology, has been widely promoted by the government and supported by many policies. However, the SAHPs are still under poor application because of a series of inherent performance issues, such as the deteriorating heating capacity and COP, the energy-consuming defrosting issue, and the poor solar thermal efficiency under an increasingly cold climate and high supply water temperature conditions.
To overcome the performance issues of SAHPs, a core component, the innovative two-stage heat-recovery heat pump (THRHP) unit was first proposed by ingeniously combining the advantages of the two-stage evaporation, two-stage compression, multiple heat sources, and waste heat recovery. Then, a first-of-its-kind low-carbon solar-assisted multi-source heat pump heating system (LSMHS) prototype was proposed by integrating the innovative THRHP with a novel solar thermal collector connection and a novel storage tank connection.
The core component THRHP unit can theoretically achieve a stable heating capacity and higher COP by innovatively extracting building exhaust air as the second heat source after the outdoor air. Based on the theoretical design, the innovative THRHP prototype was successfully established and experimentally tested in the environmental laboratory, of which optimal COPs under different ambient temperatures and water temperatures were obtained. The experiment results show that the THRHP prototype can provide a stable heating capacity of 23.2 kW-39.1 kW with a high COP ranging from 2.17 to 4.12. Compared to conventional HPs, the COP of THRHP is 20.1% higher, and the novel exhaust air defrosting method is efficient and effective with only 0.46 kW and 4 minutes. The experiment results under various conditions give insights into the characteristics of the THRHP, leading to the optimal control program of the THRHP prototype and important guidance for the development of the first-of-its-kind LSMHS.
Based on the conceptual design and operation principle of the proposed LSMHS, the first-of-its-kind LSMHS prototype was constructed in real life and integrated into the Hull Central Library to implement dynamic performance testing. By connecting the HP circuit and SC circuit in a parallel manner through a novel connection arrangement in the storage tank, the first-of-its-kind LSMHS prototype utilizes the exhaust air and outdoor air through the innovative THRH unit and collects the renewable solar radiation by novel multi-throughout-flowing solar thermal collector arrays. Through the real-life experiment, the dynamic operation characteristics and seasonal energetic and eco-economic performances of the LSMHS were disclosed for the first time in a building heating scenario. The three-month experiment results reveal that the LSMHS prototype successfully maximized the advantages of each component and achieved a high monthly average system COP ranging from 2.12 to 2.68. Compared to the traditional gas boiler heating system of the library, the LSMHS prototype eventually provides a total bill saving of 0.73% with a significant carbon reduction of 63.69%, achieving an equivalent bill saving of £6.7 for every tone of carbon reduction.
To completely explore the performance advantages of the innovative LSMHS, a comprehensive literature review is conducted for the advanced building energy system control methods. However, the existing advanced control methods either require a high level of specialized knowledge and system parameter details, or a large amount of training and learning database, which are not directly applicable to the groundbreaking LSMHS. Therefore, to investigate the optimal performance and maximum application potential of LSMHS even further, a pioneering control optimization algorithm needs to be developed. Aiming to establish the control optimization algorithm, a high-precision dynamic simulation model capable of predicting the operating characteristics and heating performance of the LSMHS is particularly essential.
Based on the theory of the first-of-its-kind LSMHS, the LSMHS grey-box dynamic simulation model was therefore proposed for the first time. Based on the substantial experimental data, the LSMHS grey-box dynamic simulation model was fully validated in different weather conditions and time spans, which can precisely simulate the dynamic operation characteristics of the LSMHS with errors of less than 6.59% and performs high predicting accuracy in long-term performance simulation with errors of less than 6.61%.
By integrating the high-precision LSMHS grey-box dynamic simulation model with the Ant Colony Optimization (ACO) metaheuristic, the pioneering LSMHS-ACO algorithm was proposed to optimize the operation strategy according to inputted weather data. Through the in-depth case studies, the optimization characteristics of the LSMHS-ACO algorithm are fully analysed under different weather conditions. Eventually, the LSMHS with the algorithm-optimized control strategy performs 32.58% higher average COP, 35.82% lower heating cost and 36.73% carbon reduction in annual operation when compared to the LSMHS under standard operation strategy.
Thereafter, the application potential of LSMHS and the LSMHS-ACO algorithm are deeply investigated by comparing with conventional solar-assisted heating systems. The LSMHS with the intelligent control algorithm achieves 36.68% cost saving and 38.21% carbon reduction compared to the conventional solar-assisted heat pump system, and still provides 25.71% cost saving and 72.41% carbon reduction when compared to the solar-assisted gas boiler system, thus having strong market competition and application potential.
To sum up, this PhD research proposes and conducts comprehensive studies on a series of groundbreaking low-carbon heating technologies around the LSMHS, and eventually provides a theoretical foundation and optimization tool for low-carbon building heating and opens up a channel for wide deployment of the innovative LSMHS, thus contributing to fossil fuel energy saving, carbon emission reduction and climate change mitigation.

Citation

Li, Y. (2024). Dynamic Performance and Intelligent Control Optimization Algorithm of a Novel Solar-assisted Multi-source Heat Pump Heating System. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4913242

• Thesis Type: Thesis
• Deposit Date: Nov 13, 2024
• Publicly Available Date: Oct 15, 2029
• Public URL: https://hull-repository.worktribe.com/output/4913242
• Additional Information: School of Engineering; University of Hull
• Award Date: Oct 14, 2024