Hybrid agent-based modeling of rooftop solar photovoltaic adoption by integrating the geographic information system and data mining technique

Lee, Minhyun; Hong, Taehoon

doi:10.1016/j.enconman.2018.12.096

Cited by 48 publications

(44 citation statements)

References 32 publications

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“…Lee et al [39] propose to combine ABMs with a logistic regression model to estimate the correct values for the model parameters. They apply this hybrid scheme to the case study of rooftop PV panels adoption in a neighborhood located in Seoul, South Korea.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…While there are recent works that strive to bridge the gap between self-reported and observed behavior (for instance [37,39]), they do not explicitly frame the problem in these terms, thus they only consider a partial aspect of the overall issue. For example, Lee et al [39] do not consider self-reported behaviour. Furthermore, the majority of the approaches terminate their analysis at the first step of the validation phase: the ABM parameters are tuned using historical, observed data but no study on the prediction capability of the model is performed.…”

Section: Related Workmentioning

confidence: 99%

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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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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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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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“…In Brazil, studies have been conducted on photovoltaic generation scenarios, opportunities, challenges, and panoramas [58][59][60], and also the diffusion to this technology and barriers to its accession [61]. Thus, it is possible to observe that the literature presents different analyses, seeking to understand specific aspects for the investigation of adoption and growth of photovoltaic diffusion in environmental, technical, political, economic, and social dimensions in isolation or in combination way [37,40,[61][62][63][64][65]. Therefore, none of the studies presented the same focus of this article, highlighting the uniqueness of this research.…”

Section: Introductionmentioning

confidence: 99%

Factors for Measuring Photovoltaic Adoption from the Perspective of Operators

et al. 2020

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The diffusion of photovoltaic distributed generation is relevant for addressing the political, economic, and environmental issues in the electricity sector. However, the proliferation of distributed generation brings new administrative and operational challenges for the sustainability of electric power utilities. Electricity distributors operate in economies of scale, and the high photovoltaic penetration means that these companies have economic and financial impacts, in addition to influencing the migration of other consumers. Thus, this paper aims to systematically identify and evaluate critical factors and indicators that may influence electricity distributors in predicting their consumers' adoption of photovoltaic technology, which were subjected to the analysis of 20 industry experts. Results show that the cost of electricity, generation capacity, and cost of the photovoltaic systems are the most relevant indicators, and it is possible to measure a considerable part of them using the internal data of the electricity distributors. The study contributes to the understanding of the critical factors for the forecast of the adoption of consumers to distributed photovoltaic generation, to assist the distribution network operators in the decision making, and the distribution sustainability. Also, it establishes the theoretical, political, and practical implications for the Brazilian scenario and developing countries.

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“…Also, for California, ABMs employing GIS [35] and social behavior [36,37] methodologies have been applied as well. In [38], an ABM with the geographic information system and logistic regression has been developed to simulate the adoption of the rooftop solar PV system in a district of Gangnam in South Korea. In [39], an ABM based on logistic regressions with explanatory variables the payback period, eco-friendliness, budget, and peer effects is developed to assess the diffusion of solar PV in Germany.…”

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confidence: 99%

Long-Term Solar Photovoltaics Penetration in Single- and Two-Family Houses in Switzerland

Panos

Margelou²

2019

Energies

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The Swiss energy strategy aims at increasing electricity generation from solar power by 2050, to fulfil Switzerland's commitments in the Paris Agreement. However, the market of singleand two-family houses is characterized by low return rates for excess power injected to the grid, and the installation of rooftop solar photovoltaic (PV) is sensitive to financial incentives. We assess the drivers influencing the diffusion of rooftop solar PV systems until 2050, by employing an agent-based model. An agent is a single-or two-family house, and its decision to invest depends on the economic profitability of the investment, the agent's income, environmental benefits (injunctive social norm), awareness and knowledge about the solar PV technology, and the impact of the social network (descriptive social norm). The model includes a synthetic population of agents, statistically equivalent to the true population. We also investigate the impact of different support policies, technology learning rates, electricity prices, and discount rates on the investment decision. We find that the concept of prosumer emerges, mainly via self-consumption strategies. The diffusion process of rooftop solar PV systems in single-and two-family houses gains momentum in the future. In the near-term, PV deployment is sensitive to the profitability of the investment, while after the year 2030, peer effects play an increasing role in the agents' investment decisions.Energies 2019, 12, 2460 2 of 33 comparison, the EU average is 0.21 kW per capita in the same year. Among the European countries, Germany has the highest installed solar PV capacity per inhabitant (0.51 kW), followed by Italy (0.34 kWp), Belgium (0.33 kW) and Greece (0.25 kW) [7]. Energies 2019, 12, x FOR PEER REVIEW 2 of 35 Energies 2019, 12, 2460 3 of 33Accelerating the deployment of solar PV systems on residential buildings is claimed as an effective decarbonization strategy [2]. However, the market of single-and two-family houses in Switzerland has shown a deceleration of the annual sales of solar PV systems between 2014 and 2016 ( Figure 3), mainly attributable to the revision of the policy. As there are low return rates for excess power injected to the grid, system owners dimension their PV systems as small as possible to optimize their consumption. Given that the single and two-family houses constitute more than two thirds of the residential building stock in Switzerland [8], it is crucial to increase the adoption rate of solar PV technology in this sector to meet the climate change mitigation objectives (see for example [9]). Hence, the importance of singleand two-family houses in achieving a low-carbon energy system and the dependence of this particular market segment on the level and type of policy support [10], constitutes an interesting case study to examine and understand the dynamics of the adoption (i.e., investing) of the solar PV technology.Energies 2019, 12, x FOR PEER REVIEW 3 of 35Energies 2019, 12, 2460 4 of 33 versus leasing). Installers and experts can help to lift t...

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Hybrid agent-based modeling of rooftop solar photovoltaic adoption by integrating the geographic information system and data mining technique

Cited by 48 publications

References 32 publications

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

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

Factors for Measuring Photovoltaic Adoption from the Perspective of Operators

Long-Term Solar Photovoltaics Penetration in Single- and Two-Family Houses in Switzerland

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