Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China
Abstract
1. Introduction
- Quantitative comparison of heating and power generation performance among the three operational modes was performed under consistent environmental conditions (ambient temperature 5.3 °C, solar irradiance 875 W/m2).
- Through experimental data fitting, the response relationships of evaporation temperature to solar irradiance and ambient temperature for the three modes were systematically quantified.
- A data-driven prediction method was proposed, with three mathematical models established based on experimental datasets to achieve the following objectives: prediction of the thermal efficiency of the PVT mode; estimation of the system COP; and determination of the matching relationship between heating capacity and PVT area.
2. System Design
2.1. Description of Dual-Source Heat Pump System
2.2. Instrumentation for System Testing
3. Performance Evaluation
4. Results and Discussion
4.1. Heating-Power Generation Performance Comparison Among Three Modes
4.2. Analysis of Evaporation Temperature
4.3. Data-Driven Modeling of the PVT Mode
- (a)
- The instantaneous thermal efficiency of the PVT mode is calculated using Equations (18) and (19);
- (b)
- The COP of the PVT heat pump is determined using Equations (20) and (21);
- (c)
- Equation (26) provides a dual-function capability, enabling either the calculation of system heating capacity for a given PVT collector area or the reverse-calculation of the required collector area for a target heating capacity.
4.4. Economic Analysis
5. Conclusions
- (1)
- With an average ambient temperature of 5.3 °C and solar irradiance of 875 W/m2, three integrated heating-power generation systems were evaluated: (1) PVT mode, (2) PVT/air dual-source mode, and (3) PV/air-source mode. Field measurements demonstrate that, compared to mode (3), mode (1) achieves a 5.76% increase in heating capacity and an 11.56% improvement in electrical efficiency. Mode (2) exhibits a 12.23% greater heating capacity and a 9.14% increase in electrical efficiency.
- (2)
- The research results on evaporation temperature indicate that in both the PVT and dual-source modes, the evaporation temperature increases with rising solar irradiance and ambient temperature. Compared to the PVT mode, the dual-source mode is less affected by solar irradiance. In contrast, in the air-source mode, the evaporation temperature depends solely on the ambient temperature.
- (3)
- This study developed a data-driven methodology for predicting PVT heat pump performance, which provides three key functions:
- (a)
- Calculating the instantaneous thermal efficiency of the PVT mode;
- (b)
- Predicting the heating COP;
- (c)
- Determining system heating capacity given a fixed collector area, or deriving the required PVT collector area for a target heating load.
- (4)
- From an economic perspective, the dual-source heat pump system demonstrates economic feasibility. Its unit heating cost (RMB 0.1125/kWh) is lower than that of electric boilers, gas boilers, and traditional air-source heat pump systems. Meanwhile, the payback period of 6.4 years is considerably shorter than its design service life of 10 to 12 years, proving its economic benefits over the entire life cycle.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| cp | specific heat of the liquid, kJ/kg·°C |
| ta | ambient temperature, °C |
| tc | condensation temperature, °C |
| te | evaporation temperature, °C |
| ti,w | inlet temperature of water, °C |
| to,w | outlet temperature of water, °C |
| top | operation time, h |
| ηe | electrical efficiency |
| ηth | thermal efficiency |
| APVT | area of the PVT panels, m2 |
| ASHP | air source heat pump |
| COP | coefficient of performance |
| Cair | air-source unit cost, RMB |
| Cele | electricity price, RMB |
| Cinv | total investment cost, RMB |
| Cm | maintenance cost, RMB |
| Cop | operating cost, RMB |
| Cpur | purchase cost, RMB |
| Cpvt | PVT panel cost, RMB |
| Csa | annual cost savings, RMB |
| Ctot | total cost, RMB |
| Cwater | water system cost, RMB |
| E | the system’s power generation, W |
| EEVs | electronic expansion valves |
| EVA | ethylene vinyl acetate copolymer |
| G | irradiance, W/m2 |
| PPR | polypropylene-random |
| PV | photovoltaic |
| PVT | photovoltaic-thermal |
| PVT-ASHP | PVT/air-source dual-source heat pump |
| Qh | heating capacity, kW |
| TES | thermal energy storage |
| QPVT | heating capacity of the PVT, kW |
| TCOPhp* | normalized temperature difference, °C/(°C + W/m2) |
| Tth* | normalized temperature difference, °C·m2/W |
| W | power consumption, W |
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| References | Experiment/Region | Simulation/Method | PVT Mode | ASHP Mode | PVT/ASHP Mode | Medium (PVT) | COP (Heating) |
|---|---|---|---|---|---|---|---|
| [4] | Shanghai | Matlab (https://www.mathworks.com/products/matlab.html) | √ | / | / | Refrigerant | 3.10 |
| [5,6] | Dalian | / | √ | / | / | Refrigerant | 2.97, 2.92 |
| [15] | Beijing | Matlab | / | / | √ | Refrigerant | 3.59 |
| [16] | Shanghai | / | √ | √ | / | Refrigerant | 5.1 (PVT); 3.7 (ASHP) |
| [17] | Hefei | / | / | / | √ | Refrigerant | 1.87~3.8 |
| [18] | / | TRNSYS (http://www.trnsys.com/) | / | √ | √ | Water | 3.55 (ASHP); 6.27 (PVT/ ASHP) |
| [19] | Nanjing | EES (https://fchartsoftware.com/ees/) | / | √ | √ | Refrigerant | 2.47 (ASHP); 3.14 (PVT/ ASHP) |
| [20] | Busan | / | / | √ | √ | Water | 4.05 (ASHP); 4.12 (PVT/ ASHP) |
| [21] | Beijing | / | √ | / | √ | Water | 1.40 (PVT); 2.49 (PVT/ ASHP) |
| [22] | / | Python (https://www.python.org/) | / | / | √ | Refrigerant | 1.49~5.64 |
| [23] | / | TRNSYS | / | / | √ | Air | 3.45 |
| [24] | / | TRNSYS | / | √ | √ | Air, Water | 4.17 (ASHP); air cooling: 5.12, water cooling: 3.92 (PVT/ASHP) |
| [25] | Zibo | / | √ | √ | √ | Refrigerant | 3.6 (PVT); 2.1 (ASHP; 2.0 (PVT/ASHP) |
| [26] | / | TRNSYS | / | / | √ | Water | 3.92 |
| [27] | Beijing | TRNSYS | √ | √ | / | Water | 7.0 (PVT); 5.0 (ASHP) |
| [28] | / | Matlab | / | / | √ | Refrigerant | 4.62 |
| [29] | / | Matlab | √ | / | √ | Refrigerant | 1.44~3.42 (PVT); 1.42~3.44 (PVT/ASHP) |
| [30] | Hefei | / | / | / | √ | Refrigerant | 4.73 |
| Component | Model | Parameters |
|---|---|---|
| PVT Collector | PVT-M3/60320 | Length: 1.77 m, Width: 1.05 m, Rated Power: 320 W |
| Compressor | WHP15600AEKPC9EQ | Rated Power: 3720 W, Displacement: 41.8 mL/rev |
| Plate heat exchanger | KAORI-K030S | Length: 194 mm, Width: 80 mm, Quantity: 20 pieces |
| Tube-in-tube heat exchangers | SS-H6000307-F-F1 | Maximum water-side pressure: 1.5 MPa, Maximum refrigerant-side pressure: 4.2 MPa |
| EEVs | TS132C | Full-open pulse: 500, Valve-opening pulse: 32 ± 20 |
| Water pump | CMF8-20T-A-W-G-BQBE | Maximum head: 34 m, Rated flow rate: 8 m3/h |
| Fan-coil units | FP-204LM | Airflow volume: 2040 m3/h, Heat output: 16,200 W |
| Component | Model | Span | Accuracy |
|---|---|---|---|
| Solar Irradiance Meter | MS-80 Pyranometer | 0–4000 W/m2 | ±0.2% |
| Temperature Sensor | Keshun PT100 Surface Mount Waterproof Temperature Sensor | −200–260 °C | 0.1%FS (Actual uncertainty: 0.46 °C) |
| Heat Meter | Feilong FLD-R-LSH Series Cold/Hot Water Electromagnetic Flow Meter | Mass flow rate: 0.8–8 m3/h | ±0.5%R (Actual uncertainty ± 0.0015 m3/s) |
| Inverter | GoodWe GW8000-SDT-30 | Maximum Output Power: 8.8 kW | 2% |
| Electricity Meter | Haixing Electric DDZY747 Single Phase Smart Electric Energy Meter | Voltage: 90% Un −110% Un | ±1% |
| Mode | Variable | Value |
|---|---|---|
| PVT | a | −12.667 |
| b | 1.848 × 10−2 | |
| c | −4.505 × 10−5 | |
| d | 3.560 × 10−8 | |
| e | 0.764 | |
| PVT/Air-source | a | −8.5901 |
| b | 2.426 × 10−3 | |
| c | 1.000 | |
| d | −1.197 × 10−3 | |
| Air-source | a | −9.276 |
| b | 0.914 | |
| c | 3.518 × 10−3 |
| Mode | Metrics | Value |
|---|---|---|
| PVT Mode | R2 | 0.976 |
| RMSE | 0.701 | |
| MAE | 0.56 | |
| Uncertainty | 3.43% | |
| PVT/Air-source Mode | R2 | 0.990 |
| RMSE | 0.637 | |
| MAE | 0.51 | |
| Uncertainty | 4.55% | |
| Air-source Mode | R2 | 0.989 |
| RMSE | 0.673 | |
| MAE | 0.54 | |
| Uncertainty | 4.20% |
| Equipment | Unit | Purchase Cost |
|---|---|---|
| PVT | RMB/panel | 1200 |
| Air-source unit | RMB | 18,000 |
| Water system | RMB | 3000 |
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Jia, X.; Wang, H.; Li, S.; Jiang, S.; Ning, Y.; Chen, H.; Hasanuzzaman, M.; Wang, S. Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China. Buildings 2026, 16, 1242. https://doi.org/10.3390/buildings16061242
Jia X, Wang H, Li S, Jiang S, Ning Y, Chen H, Hasanuzzaman M, Wang S. Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China. Buildings. 2026; 16(6):1242. https://doi.org/10.3390/buildings16061242
Chicago/Turabian StyleJia, Xin, He Wang, Shuangshuang Li, Shuang Jiang, Ye Ning, Hu Chen, M. Hasanuzzaman, and Shugang Wang. 2026. "Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China" Buildings 16, no. 6: 1242. https://doi.org/10.3390/buildings16061242
APA StyleJia, X., Wang, H., Li, S., Jiang, S., Ning, Y., Chen, H., Hasanuzzaman, M., & Wang, S. (2026). Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China. Buildings, 16(6), 1242. https://doi.org/10.3390/buildings16061242

