• Energy Research
• 2021-2025close
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This research presents a 100% renewable energy (RE) scenario by 2050 with a high share of electric vehicles on the grid (V2G) developed in Ecuador with the support of the EnergyPLAN analysis tool. Hour-by-hour data iterations were performed to determine solutions among various features, including energy storage, V2G connections that spanned the distribution system, and long-term evaluation. The high participation in V2G connections keeps the electrical system available; meanwhile, the high proportions of variable renewable energy are the pillar of the joint electrical system. The layout of the sustainable mobility scenario and the high V2G participation maintain the balance of the electrical system during most of the day, simplifying the storage equipment requirements. Consequently, the influence of V2G systems on storage is a significant result that must be considered in the energy transition that Ecuador is developing in the long term. The stored electricity will not only serve as storage for future grid use. Additionally, the V2G batteries serve as a buffer between generation from diversified renewable sources and the end-use stage.

The injection of apparent power to self-consumption buses generates voltage variations during network operation, which, when properly monitored, could support voltage regulation and control. In this paper, we propose a linear sensitivity modelling, quite useful for studies of voltage regulation with distributed energy resources (DER). This modelling consists of two analytical improvement steps: first, a full formulation for the voltage deviations, and second, the influence of line capacitance as Q-injections at the points of common couplings (PCCs). Our proposal is based on the linear topological sensitivity of an existing network (as a function of the line parameters X, R, and Bc), branch power flow (active–reactive power (P-Q)), and power injections at the PCCs. Here, the linear sensitivity algorithm is applied to a modified IEEE 33-bus distribution system to demonstrate its extended effectiveness to voltage monitoring and control scenarios. Its application estimates and compensates in a better way the voltage deviations with regard to the operating desired voltage (|V|op) constraints, using distributed power injections at the PCCs. Numerical results always showed a curtailment of the relative error against common simplifications of the electrical modelling in steady-state, thus simulating two critical scenarios of operation production–consumption for the existing system response. The proposed algorithm was validated considering as reference the voltage profile outputs of the load flow analysis, using the Newton–Raphson method via DIgSILENT, in terms of its accuracy, silhouette shape along the feeder and with regard to the application of reactive compensation as an analytical case study for voltage improvement in active distribution networks.

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

In recent years, solar price drops and regulations have helped residential users to invest in grid-connected photovoltaic (PV) facilities. In Spain, a novel law promotes self-consumption by discounting electricity fed into the grid from the utility bill. However, the performance of PV-based facilities depends on diverse factors. The contribution of this paper is to evaluate the techno-economic performance of such installations for different considerations linked to the Spanish law. A simulation model is used to examine different representative cities, load profiles and alternative objectives: maximising profitability and self-sufficiency. For profit maximisation, results show that load profile variations entail PV size changes up to 5 kWp for the same location, together with huge economic and self-sufficiency differences. In contrast, the solar radiation and compensation rate have a more limited influence. For self-sufficiency maximisation, the economic performance drops close to EUR 0, as benefits are used to double the PV size, buy batteries and reach close to 70% self-sufficiency. Finally, a sensitivity analysis shows a limited impact of the utility tariff and the technology cost on the PV size, but a relevant influence on the benefits. These results can help investors and families to quantify the risks and benefits of domestic self-consumption facilities.

This paper presents a design study focusing on the thermal safety of an induction motor integrated with a pump unit, which operates submerged in liquefied natural gas (LNG) in the LNG tanks of LNG carrier ships ranging from 150 K to 200 K cubic meters (CBM). In this study, we carried out the electromagnetic design of the induction motor and verified the thermal safety against a temperature increase due to losses during the motor operation through thermal fluid analysis, taking into account the discharge flow of the emergency pump and the air gap of the motor. In the electromagnetic design, the resistivity of the stator winding copper conductors and the rotor aluminum bars, which act as important design constants for the rated operating and starting characteristics of the induction motor in cryogenic temperature environments, reflects the characteristic of linearly changing with the temperature. In cryogenic environments, the reduction in the resistance of the rotor bars of the induction motor leads to a decrease in the starting torque characteristics. Therefore, the shape optimization design of the rotor bar was performed to improve the starting torque characteristics, and 2D electromagnetic analysis was performed on the magnetic flux density distribution and magnetic saturation using Ansys Electromagnetics 16.0. After the electromagnetic design, a 3D thermal flow analysis was conducted using Ansys Fluent 17.0, considering the stator iron losses, rotor bar losses, stator and rotor iron losses, and stray load losses as heat sources. The flow analysis aimed to analytically verify the thermal safety concerning the vaporization of the LNG flowing through the emergency pump’s discharge flow path and the motor’s internal air gap. The motor was manufactured, and the rated and starting operating characteristics of the motor were measured under LN2 submerged conditions according to the IEEE 112 F1 method, to validate whether the performance characteristics met the specifications’ requirements. Subsequently, the thermal safety of the motor was finally verified through a temperature increase test under LNG submerged conditions after assembling it with the emergency pump.

The behaviours of individual flow structures have become a relevant matter of study in turbulent flows as the computational power to allow their study feasible has become available. Especially, high instantaneous Reynolds Stress events have been found to dominate the behaviour of the logarithmic layer. In this work, we present a viability study where two machine learning solutions are proposed to reduce the computational cost of tracking such structures in large domains. The first one is a Multi-Layer Perceptron. The second one uses Long Short-Term Memory (LSTM). Both of the methods are developed with the objective of taking the the structures’ geometrical features as inputs from which to predict the structures’ geometrical features in future time steps. Some of the tested Multi-Layer Perceptron architectures proved to perform better and achieve higher accuracy than the LSTM architectures tested, providing lower errors on the predictions and achieving higher accuracy in relating the structures in the consecutive time steps.