This paper introduces a novel Multi-Criteria Decision Analysis (MCDA) framework for systematic evaluation and alignment of business models for community microgrids within local energy markets (LEMs). Our approach uniquely integrates social capital as a critical metric for assessing the success of these models. The framework's robustness is demonstrated through a case study application, showcasing its utility as a decision-support tool. This tool effectively bridges the gap between the operational and technical aspects of microgrids with the socio-economic context of the communities they serve. A key contribution is the establishment of a systematic categorisation of business models and LEMs facilitated by the MCDA framework. This approach emphasises the importance of analysing the synergy between business model components (ownership, revenue/pricing, activities, value proposition) and the corresponding market mechanisms, infrastructure, and ICT frameworks. The results demonstrate how the framework guides an informed and context-sensitive selection of business models, leveraging the interconnected socio-technical dynamics inherent to community energy systems.   

A community microgrid comes with the introduction of non-conventional distributed renewable energy infrastructure, affecting the behaviour of community members and their relationship with energy. The aspects of ownership, trust, collaboration and its often-discursive structure will be reflected in the cultural and social factors, such as norms and values in a community. The success of specific community microgrids is widely dependent on the community's ability to engage in various activities connected to the microgrid installation and operation. This paper conceptualises existing literature on community microgrids, focusing on the representation and inclusion of community preferences, needs and behaviour across the development stages. From this analysis, a conceptual-theoretical framework is proposed based on social capital theory for identifying community characteristics to determine key needs and considerations for microgrid adoption.  

Over the last five decades, there have been several phases of interest in the so-called hydrogen economy, stemming from the need for either energy security enhancement or climate change mitigation. None of these phases has been successful in terms of a major market development, mainly due to the lack of cost competitiveness and partially due to technology readiness challenges. Nevertheless, a new phase has begun very recently, which despite holding original objectives has the new motivation to be fully green, based on renewable energy. This new movement has already initiated bipartisan cooperation of some energy importing countries and those with abundant renewable energy resources and supporting infrastructure. One key challenge in this context is the diversity of pathways for the (national and international) export of non-electricity renewable energy. This poses another challenge, i.e., the need for an agnostic tool for comparing various supply chain pathways fairly while considering various techno-economic factors such as renewable energy sources, hydrogen production and conversion technologies, transport, and destination markets, along with all associated uncertainties.

This paper addresses the above challenge by introducing a probabilistic decision analysis cycle methodology for evaluating various renewable energy supply chain pathways based on the hydrogen vector. The decision support tool is generic and can accommodate any kind of renewable chemical and fuel supply chain option. 

Data from across the world shows that office building energy systems are not highly interactive with the number of occupants. During the COVID-19 pandemic, when the occupancy rates of buildings dropped notably, energy consumption didn’t decrease that much, and as a result, the per-capita energy consumption increased significantly. Some statistics are here in the paper by Sara Tavakoli and her collaborators from NEX.T LAB. 

Investment in #hydrogen supply chain is a challenging high-risk decision-making activity. Part of the complexity comes from the existence of diverse hydrogen carriers. There are multiple decision factors including cost, technical readiness, safety, environmental impacts, and ease of handling. In this paper, Oytun Öner introduces a user-friendly and adaptive decision support tool for helping such decisions.

Although bioethanol production is considered to be sustainable from a global warming perspective, its dependence on agricultural systems, land management, and geographical limitations has sparked concern. The electrocatalytic CO2 reduction reaction (CO2RR) is a promising alternative pathway to produce fuels, such as ethanol, through captured CO2 and electricity. The CO2RR has been studied exhaustively in the literature, but the potential environmental impacts of producing ethanol in a practical process on a large scale are unknown. In this paper, we perform a life cycle assessment to quantify the potential environmental benefits of ethanol production via a proposed electrocatalytic captured CO2 reduction (ECCR) system coupled with an innovative product separation design at a commercially relevant scale. The production of bioethanol via grain fermentation was used as the reference in the comparison of nine environmental impact categories. Results indicate that ethanol via ECCR has a lower or comparable associated impact in all examined environmental categories, depending on the nature of the energy supplied to the system. Specifically for global warming, the ECCR becomes competitive against the reference when the electricity supplied has a carbon intensity lower than 63 gCO2eq per kWh. Overall, the proposed ECCR system is a modular and versatile alternative that presents a clear advantage on land use and water consumption. This early-stage technology has the capability of producing ethanol sustainably whilst offering the associated benefits of a carbon capture and utilisation pathway.