Decarbonizing via disparities: Problematizing the relationship between social identity and solar energy transitions in the United States

Tidwell, Jacqueline Hettel; Tidwell, Abraham

doi:10.1016/j.erss.2021.102099

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…Studies from various countries have identified an urban-rural divide in solar PV deployment, although the direction of this divide varies depending on the study context. For instance, rural municipalities have more solar PV projects per capita in Switzerland [20], while urban counties have more solar installations per capita in Georgia, USA [21]. Recent research has also found that solar deployment occurs in many Republican households, but to a greater extent in Democratic households [22].…”

Section: Related Workmentioning

confidence: 99%

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

et al. 2023

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Solar photovoltaic (PV) deployment plays a crucial role in the transition to renewable energy. However, comprehensive models that can effectively explain the variations in solar PV deployment are lacking. This study aims to address this gap by introducing two innovative models: (i) a computer vision model that can estimate spatial distribution of solar PV deployment across neighborhoods using satellite images and (ii) a machine learning (ML) model predicting such distribution based on 43 factors. Our computer vision model using Faster Regions with Convolutional Neural Network (Faster RCNN) achieved a mean Average Precision (mAP) of 81% for identifying solar panels and 95% for identifying roofs. Using this model, we analyzed 652,795 satellite images from Colorado, USA, and found that approximately 7% of households in Colorado have rooftop PV systems, while solar panels cover around 2.5% of roof areas in the state as of early 2021. Of our 16 predictive models, the XGBoost models performed the best, explaining approximately 70% of the variance in rooftop solar deployment. We also found that the share of Democratic party votes, hail and strong wind risks, median home value, the percentage of renters, and solar PV permitting timelines are the key predictors of rooftop solar deployment in Colorado. This study provides insights for business and policy decision making to support more efficient and equitable grid infrastructure investment and distributed energy resource management.

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Section: Related Workmentioning

confidence: 99%

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

et al. 2023

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“…Solar energy presents particular promise in this regard because photovoltaic solar energy can be (and has been, in many cases) developed in a decentralized fashion at scale to serve a particular location's energy needs, such as on rooftops or in an empty city lot. However, the build‐out of large‐scale, photovoltaic solar facilities, also known as “solar farms” or utility‐scale solar (USS) is rapidly increasing in rural America (Hettel Tidwell and Tidwell 2021; Mulvaney 2017, 2019; Pascaris et al 2021) and—critically for our work—outpacing the development of decentralized (e.g., rooftop or other distributed generation) solar (Davis et al 2022). This pattern is seemingly consistent around other regions of the world (Brock, Sovacool, and Hook 2021; Measham et al 2021; Rignall 2016; Roddis et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Reacting to the Rural Burden: Understanding Opposition to Utility‐Scale Solar Development in Upstate New York^☆

Nilson

Stedman

2023

Rural Sociology

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Rural landscapes are under increasing development pressure from utility-scale solar (USS) energy facilities while public attitudes toward these facilities remain poorly documented and understood. This study explores whether opposition to USS in upstate New York is shaped at least in part by perceived rural burden-the idea that rural people and places are unfairly expected to provide new renewable energy in response to urban demand. We explore the idea of rural burden with measures of distributive injustice, procedural injustice, periphery identity, and place attachment. We use a survey (N = 421) of residents of western and northern New York, regions with substantial new and pending USS development. We find that 42 percent of residents oppose USS installations in or near their local communities, 14 percent neither support nor oppose, and 44 percent support. Perceived distributive and procedural injustice, along with place attachment have the strongest effect on opposition, while socio-demographic attributes, political ideology, and climate change beliefs were insignificant. These findings suggest that opposition to large scale renewable energy development exemplifies a rural environmental justice concern justified for many by the perceived legacy of exploitation in natural resource development.

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“…It is worth mentioning that there are many factors driving the solar energy transition, such as incentives, policy, regulations, behavior, and sustainability [10][11][12]. Many parameters affect PV panel performance, such as technology, design, irradiance, dust, humidity, ambient temperatures, and other environmental parameters [13,14]. These cells are affected by many environmental influences, such as shadows, temperature, relative humidity, and dust [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…As the bulk of the solar radiation is absorbed by the cell to increase its temperature, the smaller part goes to generate electricity. High cell temperature causes a decrease in the generated power and a deterioration in the electrical efficiency of the system [13]. The researchers proposed to reduce the negative effects of this thorny issue (since the best fields for creating photovoltaic fields are in deserts with high solar radiation) by using PVT systems [19].…”

Section: Introductionmentioning

confidence: 99%

Effect of Different Preparation Parameters on the Stability and Thermal Conductivity of MWCNT-Based Nanofluid Used for Photovoltaic/Thermal Cooling

et al. 2023

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The thermal conductivity and stability of any nanofluid are essential thermophysical properties. These properties are affected by many parameters, such as the nanoparticles, the base fluid, the surfactant, and the sonication time used for mixing. In this study, multi-walled carbon nanotubes (MWCNTs) were selected as additive particles, and the remaining variables were tested to reach the most suitable nanofluid that can be used to cool photovoltaic/thermal (PVT) systems operating in the harsh summer conditions of the city of Baghdad. Among the tested base fluids, water was chosen, although ethylene glycol (EG), propylene glycol (PG), and heat transfer oil (HTO) were available. The novelty of the current study contains the optimization of nanofluid preparation time to improve MWCNTs’ PVT performance with different surfactants (CTAB, SDS, and SDBS) and base fluids (water, EG, PG, and oil). When 1% MWCNT mass fraction was added, the thermal conductivity (TC) of all tested fluids increased, and the water + nano-MWCNT advanced all TC (EG, PG, and oil) by 119.5%, 308%, and 210%, respectively. The aqueous nanofluids’ stability also exceeded the EG, PG, and oil at the mass fraction of 0.5% MWCNTs by 11.6%, 20.3%, and 16.66%, respectively. A nanofluid consisting of 0.5% MWCNTs, water (base fluid), and CTAB (surfactant) was selected with a sonication time of three and quarter hours, considering that these preparation conditions were practically the best. This fluid was circulated in an installed outdoor, weather-exposed PVT system. Experiments were carried out in the harsh weather conditions of Baghdad, Iraq, to test the effectiveness of the PVT system and the nanofluid. The nanofluid-cooled system achieved an electrical efficiency increase of 88.85% and 44% compared to standalone PV and water-cooled PVT systems, respectively. Additionally, its thermal efficiency was about 20% higher than that of a water-cooled PVT system. With the effect of the high temperature of the PV panel (at noon), the electrical efficiency of the systems was decreased, and the least affected was the nanofluid-cooled PVT system. The thermal efficiency of the nanofluid-cooled PVT system was also increased under these conditions. This success confirms that the prepared nanofluid cooling of the PVT system approach can be used in the severe weather of the city of Baghdad.

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Decarbonizing via disparities: Problematizing the relationship between social identity and solar energy transitions in the United States

Cited by 10 publications

References 36 publications

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

Reacting to the Rural Burden: Understanding Opposition to Utility‐Scale Solar Development in Upstate New York^☆

Effect of Different Preparation Parameters on the Stability and Thermal Conductivity of MWCNT-Based Nanofluid Used for Photovoltaic/Thermal Cooling

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Decarbonizing via disparities: Problematizing the relationship between social identity and solar energy transitions in the United States

Cited by 10 publications

References 36 publications

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

Spatial distribution of solar PV deployment: an application of the region-based convolutional neural network

Reacting to the Rural Burden: Understanding Opposition to Utility‐Scale Solar Development in Upstate New York☆

Effect of Different Preparation Parameters on the Stability and Thermal Conductivity of MWCNT-Based Nanofluid Used for Photovoltaic/Thermal Cooling

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Reacting to the Rural Burden: Understanding Opposition to Utility‐Scale Solar Development in Upstate New York^☆