Experimental studies on photovoltaic-thermal heat pump water heaters using variable frequency drive compressors

James, Alosh; Mohanraj, M.; Raj, Arun; Jayaraj, S.

doi:10.1016/j.seta.2021.101152

Cited by 9 publications

(5 citation statements)

References 55 publications

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“…Annual savings (AS) come from the energy generated by the PV and ESS. Initial investment, annual operating cost, and annual savings can be calculated according to Equations ( 8)- (10).…”

Section: Economic Analysismentioning

confidence: 99%

“…AS = (E PV + E ESS ) × P electricity (10) where C AWHP , C PV , and C ESS are the cost of AWHP, PV, and ESS. E AWHP is the annual energy consumption of the AWHP (kWh).…”

Section: Economic Analysismentioning

confidence: 99%

“…This involves improving the insulation performance of buildings, enhancing the efficiency of heating, ventilation, and air conditioning (HVAC) systems, and integrating renewable energy sources like photovoltaic (PV) panels. Research is underway to improve the efficiency of PV panels, particularly in terms of thermal performance, and to explore the potential of photovoltaic-thermal (PV/T) systems that can simultaneously generate electricity and heat [6][7][8][9][10]. As the electrification of major energy sources becomes more widespread, the use of solar energy is expected to increase significantly [11].…”

Section: Introductionmentioning

confidence: 99%

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Achieving Energy Self-Sufficiency in a Dormitory Building: An Experimental Analysis of a PV–AWHP-ERV Integrated System

Yang,

Kang,

Ahn

2024

Buildings

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In this study, we investigated the performance of air-to-water heat pump (AWHP) and energy recovery ventilator (ERV) systems combined with photovoltaics (PV) to achieve the energy independence of a dormitory building and conducted an analysis of the energy independence rate and economic feasibility by using energy storage devices. Our data were collected for 5 months from July to November, and the building energy load, energy consumption, and system performance were derived by measuring the PV power generation, purchase, sales volume, AWHP inlet and outlet water temperature, and ERV outdoor, supply, and exhaust temperature. When analyzing representative days, the PV–AWHP integrated system achieved an energy efficiency ratio (EER) of 4.49 and a coefficient of performance (COP) of 2.27. Even when the generated electrical energy exceeds 100% of the electricity consumption, the energy self-sufficiency rate remains at 24% due to the imbalance between energy consumption and production. The monthly average energy self-sufficiency rate changed significantly during the measurement period, from 20.27% in November to 57.95% in September, highlighting the importance of energy storage for self-reliance. When using a 4 kWp solar power system and 4 kWh and 8 kWh batteries, the annual energy self-sufficiency rate would increase to 67.43% and 86.98%, respectively, and our economic analysis showed it would take 16.5 years and more than 20 years, respectively, to become profitable compared to the operation of an AWHP system alone.

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“…Annual savings (AS) come from the energy generated by the PV and ESS. Initial investment, annual operating cost, and annual savings can be calculated according to Equations ( 8)- (10).…”

Section: Economic Analysismentioning

confidence: 99%

“…AS = (E PV + E ESS ) × P electricity (10) where C AWHP , C PV , and C ESS are the cost of AWHP, PV, and ESS. E AWHP is the annual energy consumption of the AWHP (kWh).…”

Section: Economic Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Achieving Energy Self-Sufficiency in a Dormitory Building: An Experimental Analysis of a PV–AWHP-ERV Integrated System

Yang,

Kang,

Ahn

2024

Buildings

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“…Uncertainty analysis was conducted on the experimental parameters to consider the accuracies of the experimental devices and errors owing to probe position, calibration, and measurement [36,37]. The accuracies labeled with the T-type thermocouples, Pt-100 temperature sensors, DC loader, data logger, and pump were ±0.5%, ±0.25%, ±0.1%, ±0.1%, and ±0.2%, respectively.…”

Section: Experimental Parameters and Uncertainty Analysismentioning

confidence: 99%

Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling

Garud,

Han,

Hwang

et al. 2023

Batteries

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The limitations of existing commercial indirect liquid cooling have drawn attention to direct liquid cooling for battery thermal management in next-generation electric vehicles. To commercialize direct liquid cooling for battery thermal management, an extensive database reflecting performance and operating parameters needs to be established. The development of prediction models could generate this reference database to design an effective cooling system with the least experimental effort. In the present work, artificial neural network (ANN) modeling is demonstrated to predict the thermal and electrical performances of batteries with direct oil cooling based on various operating conditions. The experiments are conducted on an 18650 battery module with direct oil cooling to generate the learning data for the development of neural network models. The neural network models are developed considering oil temperature, oil flow rate, and discharge rate as the input operating conditions and maximum temperature, temperature difference, heat transfer coefficient, and voltage as the output thermal and electrical performances. The proposed neural network models comprise two algorithms, the Levenberg–Marquardt (LM) training variant with the Tangential-Sigmoidal (Tan-Sig) transfer function and that with the Logarithmic-Sigmoidal (Log-Sig) transfer function. The ANN_LM-Tan algorithm with a structure of 3-10-10-4 shows accurate prediction of thermal and electrical performances under all operating conditions compared to the ANN_LM-Log algorithm with the same structure. The maximum prediction errors for the ANN_LM-Tan and ANN_LM-Log algorithms are restricted within ±0.97% and ±4.81%, respectively, considering all input and output parameters. The ANN_LM-Tan algorithm is suggested to accurately predict the thermal and electrical performances of batteries with direct oil cooling based on a maximum determination coefficient (R2) and variance coefficient (COV) of 0.99 and 1.65, respectively.

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“…Taking this into account, the lower COP of AHPs is not as low as how it is usually compared with that of the VCHPs, and it should not be seen to be such a big disadvantage. There are systems being developed that are addressing this handicap of VCHPs by using photovoltaic panels, but the compressors are always electricity dependent [12,13].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of a Coated Tube Adsorber for Adsorption Heat Pumps

Dias

Costa

2021

Energies

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This work investigates the effects of several parameters on the coefficient of performance (COP) and the specific heating power (SHP) of a coated-tube adsorber for adsorption heat pumps (AHP) suitable for water heating (space and/or domestic water heating). The COP and SHP are obtained based on physical models that have already been proven to adequately describe this type of adsorber. Several parameters are tested, namely, the regeneration, condenser and evaporator temperatures, the heat transfer fluid velocity, the tube diameter, the adsorbent coating thickness, the metal–adsorbent heat transfer coefficient, and the cycle time. Two different scenarios were tested, corresponding to distinct working conditions. The working conditions for Scenario A are suitable for pre-heating water in mild climates. Scenario B’s working conditions are based on the European standard EN16147. The maximum COP is obtained for regeneration temperatures of 75 °C and 95 °C for Scenarios A and B, respectively. The COP increases for longer cycle times (more complete adsorption and desorption processes) whilst the SHP decreases (less complete cycles by unit time). Hence, the right balance between the COP and the SHP must be found for each particular scenario to have the best whole performance of the AHP. A metal–adsorbent heat transfer coefficient lower than 200 W·m−2·K−1 leads to reduced SHP. Lower adsorbent coating thicknesses lead to higher SHP and can still provide reasonably high COP. However, low coating thicknesses would require a too-high number of tubes to achieve the desired adsorbent mass to deliver the required useful heating power, resulting in too-large systems. Due to this, the best relationship between the SHP and the size of the system must be selected for each specific application.

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Experimental studies on photovoltaic-thermal heat pump water heaters using variable frequency drive compressors

Cited by 9 publications

References 55 publications

Achieving Energy Self-Sufficiency in a Dormitory Building: An Experimental Analysis of a PV–AWHP-ERV Integrated System

Achieving Energy Self-Sufficiency in a Dormitory Building: An Experimental Analysis of a PV–AWHP-ERV Integrated System

Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling

Modeling and Analysis of a Coated Tube Adsorber for Adsorption Heat Pumps

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