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• We assess impacts of risks associated with a solar-based energy transition in Greece. • Possible transition barriers and consequences are pinpointed by engaged stakeholders. • The possible socioeconomic consequences are explored by means of a modeling ensemble. • Optimizing self-consumption must consider system flexibility and new business models. • A wide-scale solar-based transition is socioeconomically beneficial in the long term. In Greece, the renewable energy potential and a low-quality building stock constitute the background of a possible low-carbon energy transition. This transition, however, faces significant uncertainties, ranging from long-term effects of the ongoing economic recession and technological lock-ins, to the stability of the regulatory framework and issues of public acceptance. Such uncertainties may eventually give rise to significant barriers to, as well as severe economic and social consequences of, the envisaged transition. Here, in a structured approach to eliciting the knowledge embedded in stakeholders, we identify such risks and explore their dynamics and role in a sustainable transition to a power system that is based on large-scale solar projects and prosuming in the residential sector. We then employ a modelling ensemble, consisting of a macroeconomic dynamic stochastic general equilibrium model and a business strategy assessment model, in order to quantify and evaluate the extent of the identified risks' impact. [ABSTRACT FROM AUTHOR]

Abstract Given the international efforts in tackling climate change as well as the potential dependence on conventional energy imports and the adverse economic environment, countries in the European Union face significant challenges in the critical task of enhancing energy efficiency. Approaches exclusively oriented on detailed quantitative modelling tools like energy system and climate-economy models, however, tend to exclude certain policy instruments and risks, and be too formalised or complex for policymakers to participate, understand and trust. Several decision support frameworks have been proposed for bridging the policy-model gap and helping policymakers confidently select among a number of alternative strategies. This paper employs the expert-driven method of fuzzy cognitive mapping, a semi-quantitative modelling technique in which system dynamics are captured and simulated against different scenarios. To this end, an innovative decision support tool for building and simulating complex fuzzy cognitive maps for assessing policy strategies with the help of experts, ESQAPE, is introduced and presented. An application in Greece shows that long-term energy efficiency measures focusing mainly on behavioural change in the residential sector – as opposed to services in the private and public sectors – are perceived to be more sustainable in a socio-economically optimistic future; this is not the case when challenges across the mitigation and adaptation axes are expected to be higher. Highlights • Supporting decisions in energy efficiency policy design is a challenging task. • An expert-driven semi-quantitative modelling system is developed and presented. • The proposed tool is based on fuzzy cognitive maps and introduces the time dimension. • The framework is implemented in Greece in consideration of key implementation risks. • Experts seem to favour different policy strategies depending on future expectations. [ABSTRACT FROM AUTHOR]

Abstract: Indeed, in the recent years, important efforts in applying energy management processes have been focused on the building sector, which demonstrates the increasing energy intensity and energy consumption indexes. The role of the building energy management systems (BEMS) is known and significant in this respect, for the management of the daily energy operations of a typical building. Effective energy management however requires the use of tools and methodologies that support the strategic decision making process of selecting energy saving measures, which are viable and environmental friendly. The aim of this paper is the presentation of an innovative intelligent decision support model for the identification of the need for intervention and further evaluation of energy saving measures in a typical existing building, based on the systematic incorporation of BEMS data (loads, demands and user requirements). The operation of the model is supportive to the decision makers authorized with the energy-efficient performance of the building and responsible for its management (energy auditors and building administration). In addition, the corresponding computerized decision support system and the appraisal of its pilot application to a typical existing office building in Athens, Greece, are presented and discussed. [Copyright &y& Elsevier]