The Challenges of Coal Phaseout: Coal Plant Development and Foreign Finance in Indonesia and Vietnam

Nanosensors have gained significant attention in recent years for improving energy conversion and storage performance in solar cells. These nanosensors, typically made from nanoparticles or nanowires, can be embedded within the solar cell to monitor parameters like temperature and light intensity. By monitoring these parameters, nanosensors provide real-time feedback and control to optimize the efficiency and performance of the solar cell. They also play a role in detecting potential issues, such as defects, for proactive maintenance and troubleshooting. The integration of nanosensors in solar cells enables the development of smart energy systems, leading to increased power output, improved stability, and a longer lifespan of solar cells. The deployment of nanosensors in solar cells offer promising trajectory for advancing energy conversion, utilization, and storage capabilities. This review summarizes recent advances in nanosensors in solar cells, with a focus on the role they play in enhancing energy conversion, utilization, and storage performance. 

Advances in Nano sensors for Monitoring and Optimal Performance Enhancement in Photovoltaic Cells

Rooftop and community solar are alternative product classes for residential solar in the United States. Community solar, where multiple households buy solar from shared systems, could make solar more accessible by reducing initial costs and removing adoption barriers for renters and multifamily building occupants. Here we test whether community solar has expanded solar access in the United States. On the basis of a sample of 11 states, we find that community solar adopters are about 6.1 times more likely to live in multifamily buildings than rooftop solar adopters, 4.4 times more likely to rent and earn 23% less annual income. We do not find that community solar expands access in terms of race. These differences are driven, roughly evenly, by inherent differences between the two solar products and by policies to promote low-income community solar adoption. The results suggest that alternative solar products can expand solar access and that policy could augment such benefits. Drawing from data on 11 US states, here the authors find evidence to suggest that community solar and other alternative solar products have the potential to expand solar access among lower-income and renter households.

Evaluating community solar as a measure to promote equitable clean energy access

On the 10th anniversary of the Belt and Road Initiative (BRI), we present this special symposium to advance knowledge on environmental governance of China's overseas engagement. While China's fast-growing investments across the world have large implications for global and local environmental politics, this phenomenon has so far received insufficient attention of students of environmental politics. Moreover, China has become increasingly proactive in promoting green development in the BRI, but little research has assessed relevant governance initiatives. Recognising this research gap, contributors to the symposium provide rigorous analysis on institutional interactions involving China and host country actors as well as forces driving new governance initiatives aiming to green the BRI. Building on the insights drawn from the symposium, we propose a research agenda to focus on the effects of China-US geopolitical rivalry, institutional evolution, and agency of host countries to understand the evolving system governing environmental impacts of China's overseas engagement. 

Environmental governance of China’s Belt and Road Initiative

The use of solar energy has shown the fastest global growth of all renewable energy sources. Efforts towards careful evaluation are required to select optimal locations for the installation of photovoltaics (PV) because their effectiveness is strongly reliant on exposure to solar irradiation. Assessing the shadows cast by nearby buildings and vegetation is essential, especially at the city scale. Due to urban complexity, conventional methods using Digital Surface Models (DSM) overestimate solar irradiation in dense urban environments. To provide further insights into this dilemma, a new modeling technique was developed for integrated 3D city modeling and solar potential assessment on building roofs using light detection and ranging (LiDAR) data. The methodology used hotspot analysis to validate the workflow in both site and without-site contexts (e.g., trees that shield small buildings). Field testing was conducted, covering a total area of 4975 square miles and 10,489 existing buildings. The results demonstrate a considerable impact of large, dense trees on the solar irradiation received by smaller buildings. Considering the site’s context, a mean annual solar estimate of 99.97 kWh/m2/year was determined. Without considering the site context, this value increased by 9.3% (as a percentage of total rooftops) to 109.17 kWh/m2/year, with a peak in July and troughs in December and January. The study suggests that both factors have a substantial impact on solar potential estimations, emphasizing the importance of carefully considering the shadowing effect during PV panel installation. The research findings reveal that 1517 buildings in the downtown area of Austin have high estimated radiation ranging from 4.7 to 6.9 kWh/m2/day, providing valuable insights for the identification of optimal locations highly suitable for PV installation. Additionally, this methodology can be generalized to other cities, addressing the broader demand for renewable energy solutions.

An Integrated Approach for 3D Solar Potential Assessment at the City Scale

Hard to say goodbye: South Korea, Japan, and China as the last lenders for coal

While it is widely recognized that energy injustices are prevalent in the clean energy transition process, there has been limited research attention on policy efforts aiming to mitigate these inequities. In this paper, we use solar equity policies as an empirical case study to understand how social equity considerations are conceptualized and operationalized in energy policy content. We build upon the policy design literature and code institutional statements of 54 solar equity policies adopted between 2001 and 2021 in the United States. In our comparative analysis, we focus on three levels of policy design elements that can be directly observed in written policy language: macro-policy goal construction, meso-policy instrument choices, and micro-level policy settings and calibrations. We find that the policy goal of energy justice is multifaceted, with a great emphasis on solar energy accessibility and provision of economic benefits and security for disadvantaged communities. There is a dominant preference by policymakers to use redistributive policies and community solar programs to advance energy justice-related goals. Solar equity policy instruments on-the-ground measures have also been calibrated to target specific disadvantaged populations in the energy system, which focus mostly on income-based vulnerability. 尽管能源不公平在清洁能源转型过程中普遍存在，但有限的研究聚焦于旨在缓解这类不公平的政策举措。本文中，我们使用太阳能公平政策作为实证案例研究，以理解社会公平的相关考量如何在能源政策内容中被概念化和操作化。我们的研究基于政策设计文献，并对 2001–2021 年间美国采纳的 54 项太阳能公平政策的制度声明进行编码。我们的比较分析聚焦于政策设计要素的三个层面，这些要素能在书面政策语言中直接观察到:即宏观政策目标构建、中观政策工具选择、以及微观政策设置与校准。我们发现，能源正义的政策目标是多方面的，特别强调太阳能的可及性以及为弱势社区提供经济利益和安全。政策制定者普遍倾向于使用再分配政策和社区太阳能计划来推进与能源正义相关的目标。太阳能公平政策工具的实地措施也经过校准，以能源系统中的特定弱势群体为目标，这些措施主要聚焦于基于收入的脆弱性。 Si bien se reconoce ampliamente que las injusticias energéticas prevalecen en el proceso de transición a la energía limpia, la atención de la investigación sobre los esfuerzos políticos destinados a mitigar estas desigualdades ha sido limitada. En este documento, utilizamos las políticas de equidad solar como un estudio de caso empírico para comprender cómo las consideraciones de equidad social se conceptualizan y operacionalizan en el contenido de la política energética. Nos basamos en la literatura de diseño de políticas y codificamos declaraciones institucionales de 54 políticas de equidad solar adoptadas entre 2001 y 2021 en los Estados Unidos. En nuestro análisis comparativo, nos enfocamos en tres niveles de elementos de diseño de políticas que se pueden observar directamente en el lenguaje escrito de políticas: construcción de metas de políticas macro, opciones de instrumentos de políticas meso y configuraciones y calibraciones de políticas a nivel micro. Encontramos que el objetivo de la política de justicia energética es multifacético, con un gran énfasis en la accesibilidad de la energía solar y la provisión de beneficios económicos y seguridad para las comunidades desfavorecidas. Existe una preferencia dominante por parte de los formuladores de políticas de utilizar políticas redistributivas y programas solares comunitarios para avanzar en los objetivos relacionados con la justicia energética. Las medidas sobre el terreno de los instrumentos de política de equidad solar también se han calibrado para dirigirse a poblaciones desfavorecidas específicas en el sistema energético, que se centran principalmente en la vulnerabilidad basada en los ingresos. Appendix I Appendix II Appendix III Appendix IV Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. 

Operationalizing social equity in public policy design: A comparative analysis of solar equity policies in the United States

Support for climate policy researchers

Abstract Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demonstrate the value of a shift from significance-based methodologies to prediction-oriented models to better identify PV adopters and reduce soft costs. We employ machine learning to predict PV adopters and non-adopters, and compare its prediction performance with logistic regression, the dominant significance-based method in technology adoption studies. Our results show that machine learning substantially enhances adoption prediction performance: The true positive rate of predicting adopters increased from 66 to 87%, and the true negative rate of predicting non-adopters increased from 75 to 88%. We attribute the enhanced performance to complex variable interactions and nonlinear effects incorporated by machine learning. With more accurate predictions, machine learning is able to reduce customer acquisition costs by 15% ($0.07/Watt) and identify new market opportunities for solar companies to expand and diversify their customer bases. Our research methods and findings provide broader implications for the adoption of similar clean energy technologies and related policy challenges such as market growth and energy inequality. 

/pdf/machine-learning-reduces-soft-costs-for-residential-solar-3i4dmo16.pdf

Machine learning reduces soft costs for residential solar photovoltaics

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Hard to say goodbye: South Korea, Japan, and China as the last lenders for coal

Operationalizing social equity in public policy design: A comparative analysis of solar equity policies in the United States

Support for climate policy researchers

Machine learning reduces soft costs for residential solar photovoltaics