Public awareness and willingness to adopt ground source heat pumps for domestic heating and cooling

Karytsas, Spyridon; Theodoropoulou, Helen

doi:10.1016/j.rser.2014.02.008

Cited by 105 publications

(61 citation statements)

References 63 publications

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“…We also agree that education appears to be linked to the adoption of renewable energy systems. In particular, the type of education specialization; for example, when potential adopters had engineering or environmental backgrounds, this led individuals to be more likely to adopt renewable energy systems than those having other educational backgrounds [56,57].…”

Section: Discussionmentioning

confidence: 99%

Understanding Stakeholders’ Views and the Influence of the Socio-Cultural Dimension on the Adoption of Solar Energy Technology in Lebanon

2018

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Abstract:In light of climate change and global commitments, a great amount of programs and policies have been implemented by governments targeting the diffusion of renewable energy technologies. Successful diffusion relies on the understanding, persuasion and acceptance by consumers and other stakeholders. This article investigates the views, roles and influence of stakeholders on the adoption of solar energy technology in Lebanon. The main research questions are: What are the stakeholders' views, roles and influence on the diffusion process of solar energy technologies? And are specific socio-cultural factors therein that influenced adoption? The influence of different stakeholders (end users, public representatives, banking sector, suppliers, consultants and NGOs) was assessed via qualitative data analysis, in particular semi-structured interviews. Our research perspective combines grounded and critical theoretical approaches with a case study research design allowing for a semi-inductive process to elaborate and complement new insights to the current body of literature on adoption of clean technology innovation, with a particular focus on the socio-cultural dimension. The results show that contextual factors, specifically related to the social, cultural, geographic and market dimensions, played a crucial role in shaping market development, especially in relation to the uptake of solar energy technology by different consumer groups. Based on the results of this study we argue that more scholarly attention should be awarded to the influence of the socio-cultural dimension and stakeholders' perspectives on adoption of renewable energy technology.

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Section: Discussionmentioning

confidence: 99%

Understanding Stakeholders’ Views and the Influence of the Socio-Cultural Dimension on the Adoption of Solar Energy Technology in Lebanon

2018

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“…GSHP attract worldwide interest due to their environmental protection, 4 energy efficiency and from being a renewable energy form [6,7,8,9]. 5 In dynamic simulation applications, such as in the modeling of heat pump systems integrated to 6 buildings, it is required to evaluate the heat pump performance under particular operating performance, and thus increase the potential of GSHP implementation in buildings.…”

Section: Introductionmentioning

confidence: 99%

“…In order to make it 5 easier for engineers when it comes to GSHP selection and sizing for a particular building, GSHP 6 manufacturers offer performance data tables from their catalogue. In heating mode, such 7 specification tables give data of compressor power input (P), heat extracted (HE), heat capacity 8 (HC) and COP as a function of the inlet and outlet load temperatures (t il and t ol ) of the distribution 9 circuit fluid entering and leaving the heat pump condenser, the inlet and outlet source temperatures and the ground circuits are respectively the source and the load side in cooling mode. Table 1 16 provides the technical features of the three commercially available GSHPs considered in the study 17 (called HP1, HP2 and HP3).…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, the proposed method can be applied to any GSHP, to 7 determine HC and COP in heating mode or CC and EER in cooling mode using their 8 corresponding performance data tables. 9 Using multiple regression calculation demonstrates that it is possible to rapidly create equation Results from the proposed parsimonious MR models point out that manufacturer data may be 10 generated from proprietary regression models. Since no goodness-of-fit of the latter is provided, 11 some caution must be exercised in the use of such data and corresponding models identified.…”

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confidence: 99%

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Developing multiple regression models from the manufacturer's ground-source heat pump catalogue data

et al. 2016

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16The performance of ground-source heat pumps (GSHP), often expressed as Power drawn and/or 17 the COP, depends on several operating parameters. Manufacturers usually publish such data in 18 tables for certain discrete values of the operating fluid temperatures and flow rates conditions. In 19 actual applications, such as in dynamic simulations of heat pump system integrated to buildings, 20 there is a need to determine equipment performance under operating conditions other than those 21 listed. This paper describes a simplified methodology for predicting the performance of GSHPs 22 using multiple regression (MR) models as applicable to manufacturer data. We find that fitting 23 second-order MR models with eight statistically significant x-variables from 36 observations 24 appropriately selected in the manufacturer catalogue can predict the system global behavior with 25 good accuracy. For the three studied GSHPs, the external prediction error of the MR models 26 identified following the methodology are 0.2%, 0.9% and 1% for heating capacity (HC) 27 predictions and 2.6%, 4.9% and 3.2% for COP predictions. No correlation is found between 28 residuals and the response, thus validating the models. The operational approach appears to be a 29 reliable tool to be integrated in dynamic simulation codes, as the method is applicable to any 30 GSHP catalogue data.

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“…The successful acceptance of any new building heating/cooling technology depends on its efficiency, performance reliability, costeffectiveness, and durability [1]. Several technologies available for heating/cooling differ in terms of energy saving potential, GHG emissions mitigation and dependency on fossil fuels.…”

Section: Introductionmentioning

confidence: 99%

Heating and cooling performance characterisation of ground source heat pump system by testing and TRNSYS simulation

2015

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a b s t r a c tIn this paper the performance of a ground source heat pump (GSHP) system with horizontal coupled ground loop pipes was monitored, analysed, extrapolated and numerically simulated. The state-of-art facility of the Kortright Centre was used to experimentally monitor the performance of GSHP. The main objective was to develop cooling/heating performance curves based on the building loads and the source temperatures. In addition, it was aimed to evaluate the efficiency of the heat pump at different load/source temperatures and measure the cycling characteristics of the compressor. Furthermore, the heat pump was modelled using the performance curves obtained from the experimental investigation. TRNSYS was used to model the house as well as the heat pump. The model was validated using the daily thermal output and it was determined that the COP ranged from 3.05 (at an ELT of 44.4 C and an EST of 2.7 C) to 3.44 (at an ELT of 41.5 C and an EST of 5.48 C). The system was also investigated for potential improvements in the control strategies. The aim was to identify issues with the current controls of as installed system and determine methods for possible improvement in the overall efficiency.

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Public awareness and willingness to adopt ground source heat pumps for domestic heating and cooling

Cited by 105 publications

References 63 publications

Understanding Stakeholders’ Views and the Influence of the Socio-Cultural Dimension on the Adoption of Solar Energy Technology in Lebanon

Understanding Stakeholders’ Views and the Influence of the Socio-Cultural Dimension on the Adoption of Solar Energy Technology in Lebanon

Developing multiple regression models from the manufacturer's ground-source heat pump catalogue data

Heating and cooling performance characterisation of ground source heat pump system by testing and TRNSYS simulation

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