Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns

Guidolin, Mariangela; Mortarino, Cinzia

doi:10.1016/j.techfore.2009.07.003

Cited by 128 publications

(67 citation statements)

References 14 publications

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“…Despite their identified shortcomings, diffusion of innovation models have been used to analyse renewable energy technology diffusion, deriving p and q from empirical data to predict diffusion [11]. In the impact assessment produced as part of the UK feed-in tariff policy design, an S-curve model is used to predict adoption due to the incentives proposed [12,Figure 4].…”

Section: Technology Adoptionmentioning

confidence: 99%

Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

Snape

2016

Energies

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Distributed renewable electricity generators facilitate decarbonising the electricity network, and the smart grid allows higher renewable penetration while improving efficiency. Smart grid scenarios often emphasise localised control, balancing small renewable generation with consumer electricity demand. This research investigates the applicability of proposed decentralised smart grid scenarios utilising a mixed strategy: quantitative analysis of PV adoption data and qualitative policy analysis focusing on policy design, apparent drivers for adoption of the deviation of observed data from the feed-in tariff impact assessment predictions. Analysis reveals that areas of similar installed PV capacity are clustered, indicating a strong dependence on local conditions for PV adoption. Analysing time series of PV adoption finds that it fits neither neo-classical predictions, nor diffusion of innovation S-curves of adoption cleanly. This suggests the influence of external factors on the decision making process. It is shown that clusters of low installed PV capacity coincide with areas of high population density and vice versa, implying that while visions of locally-balanced smart grids may be viable in certain rural and suburban areas, applicability to urban centres may be limited. Taken in combination, the data analysis, policy impact and socio-psychological drivers of adoption demonstrate the need for a multi-disciplinary approach to understanding and modelling the adoption of technology necessary to enable the future smart grid.

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Section: Technology Adoptionmentioning

confidence: 99%

Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

Snape

2016

Energies

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“…Studies have shown that the prevalence of a new technology has a significant effect on the rate of uptake [3,4,18,25]. Moreover, the results of our variance tests indicate the best features for segmenting customers into categories with different likelihoods of adoption.…”

Section: Adoption Modelmentioning

confidence: 62%

“…The latter is important as financial savings could be the underlying driver of adoption and simply correlated with income. In addition, prior attempts to build a diffusion based adoption model have not factored in the financial savings when fitting model parameters with historical data [5,18,4,21].…”

Section: Introductionmentioning

confidence: 99%

A model for residential adoption of photovoltaic systems

Agarwal¹,

Cai²,

Shah³

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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AcknowledgementsFirst and foremost, I would like to thank my adviser Prof. Mani Chandy. He took a chance on me even though I was by no means qualified. In addition, there were moments along the way when things looked quite stark and Mani's support was invaluable in me getting through it. For this, I will always be in his debt. He is one of a handful of researchers I have met that manages to conduct research that has both academic merit and yet a large societal impact. Still, the most valuable thing I have learned from Mani is how to be a good person. AbstractThe rapid rise in the residential photo voltaic (PV) adoptions in the past half decade has created a need in the electricity industry for a widely-accessible model that estimates PV adoption based on a combination of different business and policy decisions. This work analyzes historical adoption patterns and finds fiscal savings to be the single most important factor in PV adoption, with significantly greater predictive power compared to all other socioeconomic factors including income and education. We can create an application available on Google App Engine (GAE) based on our findings that allows all stakeholders including policymakers, power system researchers and regulators to study the complex and coupled relationship between PV adoption, utility economics and grid sustainability. The application allows users to experiment with different customer demographics, tier structures and subsidies, hence allowing them to tailor the application to the geographic region they are studying. This study then demonstrates the different type of analyses possible with the application by studying the relative impact of different policies regarding tier structures, fixed charges and PV prices on PV adoption. vi

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“…A comparable study by Guidolin et al also found that positive government policies in form of incentives and subsidies positively influenced PV N. Opiyo diffusions across 11 countries [9]. Wustenhagen found that positive government policies, especially feed-in-tariffs (FiT), were largely responsible for the boom in PV installation in Germany [10].…”

Section: Impacts Of Subsidies On Pv Diffusionsmentioning

confidence: 89%

Modelling Impacts of Socio-Economic Factors on Temporal Diffusion of PV-Based Communal Grids

Opiyo¹

2015

SGRE

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Impacts of socio-economic factors on temporal diffusions of solar electricity microgeneration systems in a rural developing community are modelled and simulated using an agent-based model (ABM). ABMs seek to capture the overall macro-effects of different micro-decisions in a virtual world; they model individual entities within a complex system and the rules that govern them to capture the overall effects of their interactions. Results showed that falling PV costs coupled with generally increasing grid electricity costs would lead to increased uptake of PV systems in such communities. On the other hand, high lending rates in most developing nations would stifle use of credit facilities in purchases of PV systems and thus diminishing their uptakes. Results also showed that introduction of favourable government policies in forms of subsidies would strongly stimulate PV installations in such communities. Social acceptance is important for diffusion of any new technology into a given market and more so with solar systems; results show that neighbourhood influence plays major roles in PV diffusions with many households installing PV systems if their neighbours within a given sensing radius do the same. Results also showed that requiring a certain percentage of neighbours to have installed PV before a household considered doing the same could have negative effects on PV installations as decisions to install PV are influenced by many independent and dependent factors and not by neighbourhood threshold alone.

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Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns

Cited by 128 publications

References 14 publications

Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

A model for residential adoption of photovoltaic systems

Modelling Impacts of Socio-Economic Factors on Temporal Diffusion of PV-Based Communal Grids

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