• Energy Research
• 2021-2025close
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New energy generation and storage systems are continuously being developed due to climate change, resource scarcity, and environmental laws. Some systems are incremental innovations of existing systems while others are radical innovations. Radical innovation systems are risky investments due to their relevant technical and economic uncertainties. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. Real options analysis is the project appraisal approach for these assessments. This paper aims to introduce and test an algorithm based on real options analysis to quantitatively assess the “option to prototype” in the energy sector. First, the interrelated research areas of prototyping, energy systems, and real options analysis are reviewed. Then, a novel algorithm is presented and applied to an innovative Generation Integrated Energy Storage system: Wind-driven Thermal Pumping to demonstrate the effectiveness of option to prototype and the main parameters influencing this decision. Results show that the cost of the prototype and the market size (number of identical systems to build) are key parameters.

Within the Best Estimate Plus Uncertainty framework for the safety analysis of Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal-Hydraulics (T-H) codes used is crucial. For this, Inverse Uncertainty Quantification (IUQ) methodologies are being developed for determining the probability density functions of relevant T-H codes input parameters, based on experimental data from Separate Effect Tests (SETs) experimental facilities. In practice, IUQ is challenged by the large range of variability of the experimental data in terms of Initial and Boundary Conditions (ICs & BCs), because the experimental campaigns are designed to cover the widest possible domain of conditions with the smallest number of experiments, so that same or similar ICs and BCs are seldomly repeated. To address this issue, we propose to use global sensitivity analysis, to tailor the IUQ on specific sub-regions described by segmented ICs & BCs domains. The methodology proposed is exemplified on two SETs, namely Sozzi-Sutherland and Super Moby Dick, whose experimental databases have been made available in the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the OECD/NEA/CSNI. The results obtained are superior to those of traditional IUQ methodologies for models highly sensitive to ICs & BCs.

Sustainability is characterized by a growing trend in the number of papers published in the last years, for an increasing impact factor and because today a large number of experts and researchers dealing with this issue have published in this journal [...]

In this study, an innovative Low Temperature Combustion (LTC) system named Temperature Controlled Reactivity Compression Ignition (TCRCI) is presented, and a numerical optimization of the hardware and the operating parameters is proposed. The studied combustion system aims to reduce the complexity of the Reaction Controlled Compression Ignition engine (RCCI), replacing the direct injection of high reactivity fuel with a heated injection of low reactivity fuel. The combustion system at the actual state of development is presented, and its characteristics are discussed. Hence, it is clear that the performances are highly limited by the actual diesel-derived hardware, and a dedicated model must be designed to progress in the development of this technology. A Computational Fluid Dynamics (CFD) model suitable for the simulation of this type of combustion is proposed, and it is validated with the available experimental operating conditions. The Particle Swarm Optimization (PSO) algorithm was integrated with the Computational Fluid Dynamic (CFD) software to optimize the engine combustion system by means of computational simulation. The operating condition considered has a relatively high load with a fixed fuel mass and compression ratio. The parameters to optimize are the piston bowl geometry, injection parameters and the boosting pressure. The achieved system configuration is characterized by a wider piston bowl and injection angle, and it is able to increase the net efficiency of 3% and to significantly reduce CO emissions from 0.407 to 0.136 mg.

This paper presents a novel clustering model predictive control technique where transitions to the best cooperation topology are planned over the prediction horizon. A new variable, the so-called transition horizon, is added to the optimization problem to calculate the optimal instant to introduce the next topology. Accordingly, agents can predict topology transitions to adapt their trajectories while optimizing their goals. Moreover, conditions to guarantee recursive feasibility and robust stability of the system are provided. Finally, the proposed control method is tested via a simulated eight-coupled tanks plant. Ministerio de Ciencia e Innovación FPU18{04476 Ministerio de Economía DPI2017-86918-R Ministerio de Economía DPI2015-67341-C02-01 Unión Europea No. 789051

The Social Sciences and Humanities (SSH) have a key role to play in understanding which factors and policies would motivate, encourage and enable different actors to adopt a wide range of sustainable energy behaviours and support the required system changes and policies. The SSH can provide critical insights into how consumers could be empowered to consistently engage in sustainable energy behaviour, support and adopt new technologies, and support policies and changes in energy systems. Furthermore, they can increase our understanding of how organisations such as private and public institutions, and groups and associations of people can play a key role in the sustainable energy transition. We identify key questions to be addressed that have been identified by the Platform for Energy Research in the Socio-economic Nexus (PERSON, see person.eu), including SSH scholars who have been studying energy issues for many years. We identify three main research themes. The first research theme involves understanding which factors encourage different actors to engage in sustainable energy behaviour. The second research theme focuses on understanding which interventions can be effective in encouraging sustainable energy behaviour of different actors, and which factors enhance their effects. The third research theme concerns understanding which factors affect public and policy support for energy policy and changes in energy systems, and how important public concerns can best be addressed as to reduce or prevent resistance.