Examining the Influence of Solar Panel Installers on Design Innovation and Market Penetration

Sinitskaya, Ekaterina; Gomez, Kelley J.; Bao, Qifang; Yang, Maria C.; MacDonald, Erin F.

doi:10.1115/1.4042343

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…Homeowners who live in detached houses are modeled as agents. In line with [45], a second agent active in the model is the PV and BS promoters, including both manufacturers and installers. Their role is to contact homeowners and explain the technical and financial characteristics of their products.…”

Section: Agent-based Model Designmentioning

confidence: 99%

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

et al. 2023

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Rooftop solar photovoltaic (PV) systems could significantly contribute to renewable energy production and reduce domestic energy costs. In Italy, as in other countries, the current incentives generate a modest annual increase after the generous fiscal incentives that kick-started the PV market in the 2008–2013 period. Several factors are, however, at play that can speed up the installation process, such as the improvements in PV technology at declining prices, the increased availability of battery-storage (BS) systems, the growing use of electric appliances, the uptake of electric cars, and the increased environmental awareness. We integrate two research methodologies, discrete choice modeling and agent-based modeling, to understand how these factors will influence households’ decisions regarding PV and BS installations and how agents interact in their socioeconomic environment. We predict that in Italy, given the preference structure of homeowners, the continuing decline in costs, and the social interaction, 40–45% of homeowners will have PV or PV and BS installed by 2030, thanks to the existing investment tax credit policy.

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Section: Agent-based Model Designmentioning

confidence: 99%

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

et al. 2023

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“…Sinitskaya et al [38] describe an agent-based model to explore the impact of installers of PV panels on the adoption rate of PV technology among residential households. PV installers and PV household buyers are modeled as agents and the explicit goal is to maximise the profits for panels installers-hence their work is not directly comparable to our methodology.…”

Section: Related Workmentioning

confidence: 99%

Merging Observed and Self-Reported Behaviour in Agent-Based Simulation: A Case Study on Photovoltaic Adoption

Borghesi

Milano

2019

Applied Sciences

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Designing and evaluating energy policies is a difficult challenge because the energy sector is a complex system that cannot be adequately understood without using models merging economic, social and individual perspectives. Appropriate models allow policy makers to assess the impact of policy measures, satisfy strategic objectives and develop sustainable policies. Often the implementation of a policy cannot be directly enforced by governments, but falls back to many stakeholders, such as private citizens and enterprises. We propose to integrate two basic cornerstones to devise realistic models: the self-reported behaviour, derived from surveys, and the observed behaviour, from historical data. The self-reported behaviour enables the identification of drivers and barriers pushing or limiting people in their decision making process, while the observed behaviour is used to tune these drivers/barriers in a model. We test our methodology on a case-study: the adoption of photovoltaic panels among private citizens in the Emilia–Romagna region, Italy. We propose an agent-based model devised using self-reported data and then empirically tuned using historical data. The results reveal that our model can predict with great accuracy the photovoltaic (PV) adoption rate and thus support the energy policy-making process.

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Agent-Based Modeling of Decisions and Developer Actions in Wind Farm Landowner Contract Acceptance

Syal

Ding

MacDonald

2020

Journal of Mechanical Design

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This paper presents an agent-based model to investigate interactions between wind farm developers and landowners. Wind farms require hundreds of square miles of land for development and developers typically interact with landowners to lease land for construction and operations. Landowners sign land lease contracts without knowing the turbine layout, which affects aesthetics of property as well as value of the lease contract. Having a turbine placed on one's land is much more lucrative than alternative land uses, but landowners must sign over the use of their land without knowing whether they will receive this financial benefit or not. This process, typically referred to as “Landowner Acquisition,” is highly uncertain for both stakeholders—a source stated up to 50% of wind projects fail due to landowner acquisition issues. We present an agent-based model to study the landowner acquisition period with unique decision-making characteristics for nine landowners and a developer. Citizen participation is crucial to the acceptance of wind farms; thus, we use past studies to quantify three actions a developer can take to influence landowners: (1) community engagement meetings, (2) preliminary environmental studies, and (3) sharing the wind turbine layout with the landowner. Results show how landowner acceptance rates can change over time based on what actions the developer takes. While still in the “proof of concept” stage, this model provides a framework for quantifying wind stakeholder interactions and potential developer actions. Suggestions for how to validate the framework in the future are included in the discussion.

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Examining the Influence of Solar Panel Installers on Design Innovation and Market Penetration

Cited by 5 publications

References 30 publications

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

Merging Observed and Self-Reported Behaviour in Agent-Based Simulation: A Case Study on Photovoltaic Adoption

Agent-Based Modeling of Decisions and Developer Actions in Wind Farm Landowner Contract Acceptance

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