Potential of renewable energy system utilisation at decentralised level in the state of Uttarakhand in India

Yaqoot, Mohammed; Kandpal, Tara C.

doi:10.1080/01430750.2018.1517679

Cited by 1 publication

(2 citation statements)

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“…The high purchase and installation expenditures negatively influence the adoption of these systems, leading to governmental support being the most common predictor in research. State financial motivations adjust the dynamics of total expenses by linking the gap between network power and solar costs and involve two incentive mechanisms: reducing purchase or installation prices [40][41][42] and alleviating RoI by applying FiT mechanisms [43][44][45]. Moreover, a relationship between 'financial incentives reducing purchase or installation costs and the adoption decision has repeatedly been found.…”

Section: Economic Predictorsmentioning

confidence: 99%

“…Tax deduction [84] and tax credit programs [85] have been estimated to be effective financial policy measures for promoting the diffusion of SWHs in the residential sector. Furthermore, low-interest finance mechanisms [43] and soft loan schemes [40] are among other appropriate financial intermediaries that authorities could consider in RE system deployment.…”

Section: Economic Predictors Versus Technical Predictorsmentioning

confidence: 99%

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Residential Solar Water Heater Adoption Behaviour: A Review of Economic and Technical Predictors and Their Correlation with the Adoption Decision

et al. 2021

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The successful deployment of the solar water heater (SWH) in the residential sector relies on the household’s bounded rational decision-makers to accept this system. The decision is shaped by a wide spectrum of predictors that form heterogeneous behaviour. Over the past years, research has employed a wide range of these predictors to understand their role in the decision and predict the behaviour and diffusion rate of SWHs. This review primarily identifies economic and technical predictors of 100 quantitative and qualitative studies on the residential SWH adoption decision. For the identified predictors, their characteristics and popularity are explored in a structured and coherent framework. The review further investigates the correlation between the identified predictors and the adoption decision from 97 of the 100 initially reviewed studies. The outcome of the research revealed 123 (56 economic and 67 technical) predictors that were classified into seven categories. ‘Financial incentives’ and ‘perceived attitude towards government policies’ are among the most popular economic predictors, whereas ‘house type’ and ‘knowledge of SWH’ were the most frequent technical factors in the research. Analysing the correlation between 99 predictors and the decision also unfolded that certain attitudinal attributes have a stronger influence on the residential SWH take-up than some common factors (e.g., electricity cost, technical variables).

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