• Energy Research
• 2016-2025close
• IT close
• CA close
• Sapienza University of Rome close

The aggregation of data concerned 103 Italian cities and for each city 45 indicators were considered

The complex interaction between city and climate crisis is converting design-based disciplines from deterministic to flexible approaches. In this regard, Decision-Making Under Deep Uncertainty (DMDU) methods and operational strategies can be valuable support mechanisms to cope with the emerging climate fragilities of urban systems. In light of recent advances in the field of adaptive approaches, this paper discusses key concepts, current limitations and the potential to introduce the DMDU in the method and practices of regenerative design. Our critical discussion aims to restore the designer’s role within the DMDU and to reduce current and future climate fragilities in European cities.

Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.

Abstract Reaching universal access to electricity by 2030 requires a massive deployment of mini-grids in rural areas of developing countries. Among the many challenges hindering this process, there are the high uncertainties in assessing demand patterns in rural communities, the costs of field survey campaigns, and the absence of ample and reliable datasets coming from existing projects. This paper tries to address these issues by presenting and discussing a database of load profiles from sixty-one off-grid mini-grids from developing countries worldwide, gathered from the literature, private developers and fieldworks, and reported with technical, socio-economic and geographical characterization factors. A clustering procedure led to the identification of five archetypal load profile clusters, which are presented and analyzed together with their load duration curves. Subsequently, the distribution among the clusters of the various characterization factors selected is studied. The proposed approach allows to widen the range of load profiles usually considered, and to seek correlations between the load profile shapes, the peak power and average energy consumption per connection, the number of customers, the age of measurement, geographical position, operator model, type of tariff and generation technologies present. This work establishes a first step in the creation of a shared database for load profiles of rural mini-grids, helping to overcome the lack of available data and difficulties of demand assessment, proposing original insights for researchers to understand load patterns, and contributing to reduce risks and uncertainties for mini-grid developers.

Energy system modeling has a central role in assessing the future energy system and helping policy makers to set targets and subsidizing mechanisms. In the years, different energy system models have been developed with the aim of supporting political decision-makers in the design of energy policies. It is relevant to compare and cross-validate these models in order to add robustness to the final results and technical feasibility of the identified transition pathways. Two main methods to compare these models exist i) comparison of the technical features and characteristics of the models and ii) comparison of the final results. While there are several reviews focusing on the comparison of models based on their technical characteristics and features, to the authors’ knowledge, no review article exists on comparison techniques based on final results. The scope of this paper is to carry out a review of existing methods and techniques to compare energy system frameworks, models, and scenario results regarding their final results. ; sì

SummaryMultithreaded applications facilitate the exploitation of the computing power of multicore architectures. On the other hand, these applications can become extremely energy‐intensive, in contrast with the need for limiting the energy usage of computing systems. In this article, we explore the design of techniques enabling multithreaded applications to maximize their performance under a power cap. We consider two control parameters: the number of cores used by the application, and the core power state. We target the design of an autotuning power‐capping technique with minimal intrusiveness and high portability, which is agnostic about the workload profile of the application. We investigate two different approaches for building the strategy for selecting the best configuration of the parameters under control, namely a heuristic approach and a model‐based approach. Through an extensive experimental study, we evaluate the effectiveness of the proposed technique considering two different selection strategies, and we compare them with existing solutions.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

Nowadays, most countries of the world are implementing the transition to the low-carbon economy which implies the need to carry out a full-scale eco-modernization of the energy sector. Green energy may be identified as one of the core concerns of energy sector modernization as it allows a considerable decrease in emissions of harmful substances into the atmosphere. Therefore, nuclear and renewable energy may become key areas of global energy development in the near future, which is also in agreement with circular economy concepts. However, public opinion (and other controversial visions/aspects) is one of the barriers to their development. The purpose of this study is to analyze the relationship between attitudes towards nuclear and renewable energy in two countries: a EU country (Italy) and a non-EU country (Russia), considering the level of their development. The authors conducted a survey among residents regarding their attitude towards nuclear and renewable energy, as well as their attitude to the present energy policy. The cluster analysis technique was used to analyze the results. The obtained results confirmed the dependence between the level of development of nuclear and renewable energy and the public attitude towards it. The national energy policy also might influence public opinion on the development of nuclear or renewable energy. The authors identified public attitude as one of the key factors in the development of energy and the achievement of environmental and social sustainability.