A Simulation-Assisted Field Investigation on Control System Upgrades for a Sustainable Heat Pump Heating

Dehu Qv (), Jijin Wang, Luyang Wang and Risto Kosonen ()
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Dehu Qv: Department of Building Environment and Energy Application Engineering, School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Jijin Wang: School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Luyang Wang: Department of Building Environment and Energy Application Engineering, School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Risto Kosonen: Department of Mechanical Engineering, Aalto University, P.O. Box 14400, 00076 Aalto, Finland

Sustainability, 2024, vol. 16, issue 22, 1-20

Abstract: Heat pump-based renewable energy and waste heat recycling have become a mainstay of sustainable heating. Still, configuring an effective control system for these purposes remains a worthwhile research topic. In this study, a Smith-predictor-based fractional-order PID cascade control system was fitted into an actual clean heating renovation project and an advanced fireworks algorithm was used to tune the structural parameters of the controllers adaptively. Specifically, three improvements in the fireworks algorithm, including the Cauchy mutation strategy, the adaptive explosion radius, and the elite random selection strategy, contributed to the effectiveness of the tuning process. Simulation and field investigation results demonstrated that the fitted control system counters the adverse effects of time lag, reduces overshoot, and shortens the settling time. Further, benefiting from a delicate balance between heating demand and supply, the heating system with upgraded management increases the average exergetic efficiency by 11.4% and decreases the complaint rate by 76.5%. It is worth noting that the advanced fireworks algorithm mitigates the adverse effect of capacity lag and simultaneously accelerates the optimizing and converging processes, exhibiting its comprehensive competitiveness among this study’s three intelligent optimization algorithms. Meanwhile, the forecast and regulation of the return water temperature of the heating system are independent of each other. In the future, an investigation into the implications of such independence on the control strategy and overall efficiency of the heating system, as well as how an integral predictive control structure might address this limitation, will be worthwhile.

Keywords: changing consumption and production patterns of heating; renewable sources of energy; clean heating upgrade; heat pump heating; cascade control; fractional-order PID controller; advanced fireworks algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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