Framework for estimation of the direct rebound effect for residential photovoltaic systems

Toroghi, Shahaboddin Hashemi; Oliver, Matthew E.

doi:10.1016/j.apenergy.2019.113391

Cited by 31 publications

(8 citation statements)

References 73 publications

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“…The benefits of renewable energy are clear, but there may be unintended consequences. The solar rebound is defined as the percentage increase in total energy consumption resulting from the adoption of solar photovoltaic (PV) (Toroghi & Oliver, 2019). Rebounds erode a significant proportion of the energy/emissions saving (Sorrell et al, 2020).…”

Section: The Solar Rebound Effect Antecedents and Mitigating Factorsmentioning

confidence: 99%

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Renewable Energy Householders in the Sunshine State

McCarthy¹

2022

JRE

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Rooftop solar PV installations have experienced rapid and unprecedented growth in Australia. However, one issue that contributes to inefficiencies in the electricity market is the ‘solar rebound effect’ which refers to the reduction in expected gains from eco-efficient technologies due to an increase in the use of the resource. However, little literature exists that incorporates consumers’ cognitions into studies of the solar rebound effect in Australia. This study aims to bridge a research gap by examining consumer perceptions of the solar rebound effect after installing rooftop solar, along with the psychological factors that might play a role in mitigating the solar rebound effects. A quantitative methodology was adopted, and a pilot survey was administered to residents (n=68) in a regional city. Frequency distributions and non-parametric tests were undertaken. The results indicate significant differences between those who report a solar rebound effect and those who do not, relating to factors such as thermal comfort, bill consciousness and an environmental self-identity. Implications for future research and practice are outlined in the paper.

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Section: The Solar Rebound Effect Antecedents and Mitigating Factorsmentioning

confidence: 99%

“…Scholars conclude that the 'solar rebound effect' exists, which is defined as the percentage increase in total energy consumption resulting from the adoption of a PV (Toroghi & Oliver, 2019). Although studies suggest that rebound effects are modest (i.e.…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy Householders in the Sunshine State

McCarthy¹

2022

JRE

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“…In some cases, the information of the solar potential available in a specific region is used to estimate the electricity cost reduction (in urban areas) or the energy supply (in rural areas) [13] [19]. All sizing methodologies for PV systems consider technical and financial aspects that allow the use of this renewable technology, however, some aspects are not considered concerning small scale PV applications, like residential use, where the benefits of the investment are not reflected in the daily consumption [20].…”

Section: Introductionmentioning

confidence: 99%

Sizing methodology for photovoltaic systems considering coupling of solar energy potential and the electric load: dynamic simulation and financial assessment

et al. 2020

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A reliable methodology for the dimensioning of photovoltaic systems is presented in this paper. This method generates technical-financial variables that aid in the choice of the most adequate photovoltaic power system for each project. The techniques that are usually used determine the size of PV power plants considering the monthly average of the solar energy potential of the month with the lowest solar radiation and the electricity to be supplied to satisfy the demand. These conventional techniques generate an uncertainty of at least 40 %, mainly due to the daily dispersion of the solar energy availability and of the electric load. The proposed methodology takes into account a region’s own photovoltaic energy potential and the detailed characteristics of the electric load, matching both with different PV power plants sizes, and analyzing the whole during a time period that guarantees the reliability of the results. The energy coupling is performed integrating the energy parameters (solar energy and electric load) in short time intervals (30 minutes maximum) to determine the supplied energy, the unsupplied energy demand and the unused solar energy. The daily integration of the three factors, using a dynamic simulation and performing a financial evaluation, allows for the identification of the most appropriate PV power plant size for every project. The results indicate that this methodology reduces the uncertainty of the solar power-electric load coupling from 40 % to 2.2 %, which allows a better definition of the financial variables that determine the most appropriate installed solar power for a photovoltaic project.

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“…See, for example,Toroghi and Oliver (2019), who find such a result using data for the Atlanta region.…”

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confidence: 99%