A study of photovoltaic/thermal (PVT)-ground source heat pump hybrid system by using fuzzy logic control

Putrayudha, S Andrew; Kang, Eun Ju; Evgueniy, E.; Yang, Libing; Lee, Euy Joon

doi:10.1016/j.applthermaleng.2015.06.019

Cited by 70 publications

(14 citation statements)

References 11 publications

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“…FL deals with the ranges of the various parameters rather than data points hence, FL could predict accurate results for all data points within the ranges of various parameters. [46][47][48] Accuracy of FL depends on the human knowledge. 49 Figure 4 shows the general diagram of fuzzy model.…”

Section: Fuzzy Logic (Fl)mentioning

confidence: 99%

“…Obtained results show that, FL-based controller has reduced the energy consumption by 13.3% for GSHP system and 18.3% for PVT-GSHP system compared to conventional controller. 48 Danandeh et al have proposed a hybrid model of FL integrated with incremental conduction (INC) which is 32 times faster than INC method alone for tracking maximum power point in PV cells. Inputs of error and change in error are used to predict the change of duty cycle ratio using triangular membership function of each input and output variable.…”

Section: Prediction Of Performance Characteristics Of Solar Photovomentioning

confidence: 99%

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A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models

2020

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The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.

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Section: Fuzzy Logic (Fl)mentioning

confidence: 99%

Section: Prediction Of Performance Characteristics Of Solar Photovomentioning

confidence: 99%

A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models

2020

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“…when compared to a conventional on-off control. Putrayudha [17] developed a fuzzy logic controller to minimize the energy consumption of a GSHP-PVT system in a single residential house in Incheon, South Korea. The results showed that this fuzzy logic controller was able to reduce the annual energy consumption by 18.3% in comparison to a conventional on-off control.…”

Section: Introductionmentioning

confidence: 99%

A model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors

Xia

Kokogiannakis

et al. 2018

Applied Energy

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This paper presents a model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors (GSHP-PVT). The control strategy was formulated using simplified adaptive models and a genetic algorithm (GA) to identify energy efficient control settings for GSHP-PVT systems. The simplified adaptive models were used to predict the system energy performance under various working conditions and control settings, and the model parameters were continuously updated using the recursive least squares (RLS) estimation technique with exponential forgetting. The performances of the adaptive models and the control strategy were evaluated based on a virtual simulation system representing a GSHP-PVT system for residential applications. The performance of the major adaptive models was also validated using the experimental data. The results showed that the simplified adaptive models used were able to provide acceptable energy performance prediction. The optimal control strategy can save energy consumption by 7.8%, 7.1% and 7.5%, and increase electricity generation by 4.4%, 6.2% and 5.1%, during the whole cooling, heating and transition periods considered, respectively, in comparison to a conventional control strategy. The findings obtained from this study could be potentially used to drive the development of advanced control strategies suitable for real-time applications.

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“…Furthermore, the study in [16] shows that the idea of PVT system is economically feasible. However, the hot water produced by PVT system cannot meet the application requirements of temperature, from [17][18][19], it is demonstrated that working with a heat pump, PVT system will significantly increase system efficiency and provides both electricity and thermal energy for end users. Fuzzy Logic control has been applied to optimize the energy consumption of the PVT system [17].…”

Section: Introductionmentioning

confidence: 99%

“…However, the hot water produced by PVT system cannot meet the application requirements of temperature, from [17][18][19], it is demonstrated that working with a heat pump, PVT system will significantly increase system efficiency and provides both electricity and thermal energy for end users. Fuzzy Logic control has been applied to optimize the energy consumption of the PVT system [17]. A thermodynamics model is built for a refrigerant-based PVT assisted heat pump water heater system in [18].…”

Section: Introductionmentioning

confidence: 99%

Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach

et al. 2018

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Community Energy Internet (CEI) integrates electric network and thermal network based on combined heat and power (CHP) to improve the economy of energy system in Smart Community. In the CEI, an energy sharing framework for prosumers equipped with photovoltaic-thermal (PVT) system and heat pump (HP) is introduced. Supporting by the PVT and HP, the prosumer has four role attributes with either heat or electricity producer/consumer. A social welfare maximization model is built for the CEI, including PVT-HP prosumers, CHP system, and utility grid. Considering there are multiply participants in the local market of CEI, the social welfare maximization problem is decoupled by using Lagrange multiplier method. Moreover, a consensus-based fully distributed algorithm is designed to solve the problem. Finally, six residential buildings are selected as the case study to validate the effectiveness of the proposed method.

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A study of photovoltaic/thermal (PVT)-ground source heat pump hybrid system by using fuzzy logic control

Cited by 70 publications

References 11 publications

A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models

A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models

A model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors

Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach

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