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This paper explores business models for community energy storage (CES) and examines their potential and feasibility at the local level. By leveraging Multi Criteria Decision Making (MCDM) approaches and real-world case studies in Europe and India, it presents insights into CES deployment opportunities, challenges, and best practices. Different business models, including community energy cooperatives, utility–community partnerships, demand response, energy services, and market mechanisms, are analyzed. The proposed method combines the MCDM method PROMETHEE II with the fuzzy set theory to obtain a complete CES business model ranking, addressing project uncertainties. The analysis emphasizes CES's role in balancing local renewable energy supply and demand, facilitating energy sharing, and achieving energy independence. Findings prioritize models like Community Cooperative, Energy Arbitrage, and Energy Arbitrage Peak Shaving for CES with renewables. Environmental benefits include reduced diesel use and greenhouse gas emissions. Efficient cooperatives are advocated to recover costs and enable competitive energy prices. The paper highlights the need for novel value propositions to boost the energy transition in local communities. This research contributes to the discourse on CES business models, fostering knowledge exchange and promoting effective strategies for sustainable energy systems. [ABSTRACT FROM AUTHOR]

Literature has highlighted the existence of a gap in clean fuel usage between the social groups in most emerging nations across the world, which is detrimental to global efforts to achieve Sustainable Development Goal (SDG) 7 (access to clean energy) and SDG 10 (reducing inequalities) and just energy transition with recognition justice. This paper, assesses the clean fuel gap across social groups in India using three rounds of representative data (2004, 2014, and 2018) by applying the logit model, exogenous switching treatment effect regression (ESTER), and the Blinder–Oaxaca Decomposition Model. Such an analysis is instrumental in identifying the clean energy usage gap and its causes, thereby providing insight to policymakers to design policies to achieve just energy transition and carbon neutrality by 2060. The results show a substantive clean fuel gap between social groups in India, which is a cause of concern for just energy transition. Clean energy utilization gaps among social groups are alarming across geographical locations and consumption quartiles, highlighting the importance of recognition justice for just energy transition. The results show that in rural areas, only 19.6 % of the General Caste households and 14.5 % of the disadvantaged social groups (Scheduled Tribes, Scheduled Castes, and Other Backward Class) in quartile one use clean energy, while in urban areas, the shares are 60.4 % and 46.3 %, respectively. To achieve a just distribution of the benefits of energy transition, energy policies should focus on disadvantaged social groups and simultaneously target General Caste households from a lower economic status and those residing in rural areas, indicating the need for targeting the neglected regions. [Display omitted] • Clean energy use has steadily increased among all social groups in India, indicating some improvement in energy justice. • Clean energy access gap among social groups has declined, but this gap still persists. • Scheduled Castes and Scheduled Tribes are the most disadvantaged social groups in terms of clean energy. • All social groups from low-income families have limited access to clean energy. • All social groups from households with low education have limited access to clean energy. [ABSTRACT FROM AUTHOR]

In this paper, we suggest how India can become atmanirbhar (i.e. self-reliant) in development of green energy technologies- solar, battery storage and green hydrogen, given its stated commitments in clean energy. First, we introduce a generalized policy design – a set of ten policy measures: seven necessary and three sufficient- with the former being on the supply side and the latter on the demand side. The paper argues that while the ideal policy mix would be technology dependent, based on technology maturity and the strategic positioning of the country, it should draw both from supply side (i.e., for domestic development) and demand side (i.e., for scale deployment). Then, we suggest the required individual strategies for each of the three technologies- such as a manufacturing focused policy for solar solely to develop competence in manufacturing; a bottom-up, manufacturing-led policy for battery storage with focus on deployment in parallel with technology development; and traditional top-down, research-led strategy for green hydrogen by entering via development through supply side and complementing via deployment through demand side. Finally, we compare these with the existing domestic energy industrial policies as well as those prevalent in other jurisdictions such as the US and China. • Create self-reliance for India in green energy technologies. • Develop generalized policy design with supply and demand side measures. • For solar, manufacturing focused policy for competence solely in manufacturing. • For battery storage, bottom-up manufacturing-led policy with deployment alongside development. • For green hydrogen, top-down research-led strategy where deployment follows development. [ABSTRACT FROM AUTHOR]

In view of the climate emergency, it is necessary to model and forecast road transport emissions for implementing more effective climate policy. This paper fills an important research gap by quantifying the challenges, barriers and remedies of achieving road transport emission reduction and air quality improvement in developing countries. It contributes to the debate on top-down and bottom-up approaches to reconcile carbon and other transport related emissions. China and India are chosen as case studies. Using various official statistics and proxy variables, we estimate and compare the road transport carbon emissions of the two countries systematically from 2009 to 2020. Insights from detailed mode-specific estimations of the bottom-up approach are valuable for targeted policies and measures. An analysis of the major components of road transport carbon emissions points to strategies of promoting electric vehicles, reducing transport demand, accelerating modal shift to low-carbon modes, and cleaner electricity to achieve climate policy. [ABSTRACT FROM AUTHOR]