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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (24 March 2022) | Viewed by 27864

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Special Issue Editors

Prof. Dr. Ettore Bompard

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Guest Editor

Department of Energy, Politecnico di Torino, 10129 Torino, Italy
Interests: electricity market analysis and simulation; smart grid design and modelling; power system vulnerability assessment and security management; energy security; “science-based” support to policy decision-making in energy and data analytics applications for power systems

Prof. Dr. Francesco Profumo

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Guest Editor

Special Issue Information

Dear Colleagues,

The energy transition from fossil fuels is crucial to building a sustainable future. Climate change mitigation and air pollution reduction have been targeted as major priorities elsewhere. In this transition, electricity will play a key role. The way out from fossil fuels though electricity implies the implementation of a new paradigm of the “electricity triangle” in which electricity is generated from renewables (solar, wind, and others), electricity is widely used as a commodity for energy transmission and electricity is the main commodity in the final use of energy (buildings, industry and transport).

The electricity triangle can be realized according to two different reference scales: small-scale “micro-grids” (low-rated power distributed generation from renewables, local smart distribution grids) or large-scale “global interconnections” (high-rated power concentrated generation from renewables, large scale transmission network). Between these two, some kind of balance, not yet defined, will be achieved in the future. This Special Issue is aimed to provide an overview of this emerging scenario, with reference to the general modelling of the increased penetration of electricity from an energy system and policy perspective, and, as well, from the point of view of the technological developments and implementation, which can make electrification a viable means for the energy transition towards a sustainable word.

Authors are encouraged to send their manuscripts, with reference to the above topics. Novelty and the potential contribution to the advancement of knowledge in the field will be the main criteria for evaluating the acceptance for publication.

Prof. Dr. Ettore Bompard
Prof. Dr. Francesco Profumo
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

Decarbonization
Energy transition
Electrification
Electric technologies
Large-scale interconnections
Smart grids
Micro-grids
Renewable sources
Concentrated and distributed power generation
Storage
Energy systems
Energy forecasting scenarios

Published Papers (7 papers)

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Research

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19 pages, 5447 KiB

Open AccessArticle

Extended Flow-Based Security Assessment for Real-Sized Transmission Network Planning

by Maria Dicorato, Michele Trovato, Chiara Vergine, Corrado Gadaleta, Benedetto Aluisio and Giuseppe Forte

Energies 2020, 13(13), 3363; https://doi.org/10.3390/en13133363 - 01 Jul 2020

Cited by 1 | Viewed by 1498

Abstract

The evolution of electric power systems involves several aspects, dealing with policy and economics as well as security issues. Moreover, due to the high variability of operating conditions, evolution scenarios have to be carefully defined. The aim of this paper is to propose a flow-based procedure for the preliminary security analysis of yearly network evolution scenarios at the real scale level. This procedure is based on hourly load and generation conditions given by market solutions, and exploits Power Transfer Distribution Factors and Line Outage Distribution Factors to determine N and N−1 conditions, properly accounting for possible islanding in the latter case. The analysis of overloads is carried out by dealing with big data analysis through statistic indicators, based on power system background, to draw out critical operating conditions and outages. The procedure is applied to a provisional model of a European high voltage network. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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17 pages, 5158 KiB

Open AccessArticle

Improvement of Short-Term BIPV Power Predictions Using Feature Engineering and a Recurrent Neural Network

by Dongkyu Lee, Jinhwa Jeong, Sung Hoon Yoon and Young Tae Chae

Energies 2019, 12(17), 3247; https://doi.org/10.3390/en12173247 - 23 Aug 2019

Cited by 9 | Viewed by 3168

Abstract

The time resolution and prediction accuracy of the power generated by building-integrated photovoltaics are important for managing electricity demand and formulating a strategy to trade power with the grid. This study presents a novel approach to improve short-term hourly photovoltaic power output predictions using feature engineering and machine learning. Feature selection measured the importance score of input features by using a model-based variable importance. It verified that the normative sky index in the weather forecasted data had the least importance as a predictor for hourly prediction of photovoltaic power output. Six different machine-learning algorithms were assessed to select an appropriate model for the hourly power output prediction with onsite weather forecast data. The recurrent neural network outperformed five other models, including artificial neural networks, support vector machines, classification and regression trees, chi-square automatic interaction detection, and random forests, in terms of its ability to predict photovoltaic power output at an hourly and daily resolution for 64 tested days. Feature engineering was then used to apply dropout observation to the normative sky index from the training and prediction process, which improved the hourly prediction performance. In particular, the prediction accuracy for overcast days improved by 20% compared to the original weather dataset used without dropout observation. The results show that feature engineering effectively improves the short-term predictions of photovoltaic power output in buildings with a simple weather forecasting service. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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23 pages, 6657 KiB

Open AccessArticle

Long-Term Demand Forecasting in a Scenario of Energy Transition

by Rafael Sánchez-Durán, Joaquín Luque and Julio Barbancho

Energies 2019, 12(16), 3095; https://doi.org/10.3390/en12163095 - 12 Aug 2019

Cited by 17 | Viewed by 4288

Abstract

The energy transition from fossil fuels to carbon-free sources will be a big challenge in the coming decades. In this context, the long-term prediction of energy demand plays a key role in planning energy infrastructures and in adopting economic and energy policies. In this article, we aimed to forecast energy demand for Spain, mainly employing econometrics techniques. From information obtained from institutional databases, energy demand was decomposed into many factors and economy-related activity sectors, obtaining a set of disaggregated sequences of time-dependent values. Using time-series techniques, a long-term prediction was then obtained for each component. Finally, every element was aggregated to obtain the final long-term energy demand forecast. For the year 2030, an energy demand equivalent to 82 million tons of oil was forecast. Due to improvements in energy efficiency in the post-crisis period, a decoupling of economy and energy demand was obtained, with a 30% decrease in energy intensity for the period 2005–2030. World future scenarios show a significant increase in energy demand due to human development of less developed economies. For Spain, our research concluded that energy demand will remain stable in the next decade, despite the foreseen 2% annual growth of the nation’s economy. Despite the enormous energy concentration and density of fossil fuels, it will not be affordable to use them to supply energy demand in the future. The consolidation of renewable energies and increasing energy efficiency is the only way to satisfy the planet’s energy needs. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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24 pages, 548 KiB

Open AccessArticle

A Hierarchical Optimisation of a Compressed Natural Gas Station for Energy and Fuelling Efficiency under a Demand Response Program

by Charles Kagiri, Lijun Zhang and Xiaohua Xia

Energies 2019, 12(11), 2165; https://doi.org/10.3390/en12112165 - 06 Jun 2019

Cited by 7 | Viewed by 3153

Abstract

Compressed natural gas stations serve customers who have chosen compressed natural gas powered vehicles as an alternative to diesel and petrol based ones, for cost or environmental reasons. The interaction between the compressed natural gas station and electricity grid requires an energy management strategy to minimise a significant component of the operating costs of the station where demand response programs exist. Such a strategy when enhanced through integration with a control strategy for optimising gas delivery can raise the appeal of the compressed natural gas, which is associated with reduced criteria air pollutants. A hierarchical operation optimisation approach adopted in this study seeks to achieve energy cost reduction for a compressed natural gas station in a time-of-use electricity tariff environment as well as increase the vehicle fuelling efficiency. This is achieved by optimally controlling the gas dispenser and priority panel valve function under an optimised schedule of compressor operation. The results show that electricity cost savings of up to 60.08% are achieved in the upper layer optimisation while meeting vehicle gas demand over the control horizon. Further, a reduction in filling times by an average of 16.92 s is achieved through a lower layer model predictive control of the pressure-ratio-dependent fuelling process. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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14 pages, 4620 KiB

Open AccessArticle

Accurate Expressions of Mutual Inductance and Their Calculation of Archimedean Spiral Coils

by Shuo Liu, Jianhui Su and Jidong Lai

Energies 2019, 12(10), 2017; https://doi.org/10.3390/en12102017 - 26 May 2019

Cited by 35 | Viewed by 6454

Abstract

Considering the helicity of Archimedean spiral coils, this paper proposes accurate expressions of mutual inductance and their numerical calculation methods, which can be applied in the wireless power transmission field, etc. Accurate expressions of mutual inductance are deduced respectively for two coils that are coaxial, laterally misaligned, or non-parallel, and numerical calculations are performed using Gaussian integration as well. In the case of coaxial coils, the calculation results are verified by the 3D finite element method (3D FEM) and compared with the results gained by the traditional method that approximates two spiral coils to two clusters of series-connected circular coils ignoring helicity. The comparison of the three methods shows that results achieved by the proposed expression are close to that of 3D FEM, while there is increasing error with the screw pitches of the coils when using the traditional circular coil approximation method. The influence of relative position on the mutual inductance of the two coils is also studied and it is further explained through magnetic field distribution. Finally, the validity of the proposed expressions of mutual inductance is verified by experimental results. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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16 pages, 248 KiB

Open AccessArticle

The Paradox of Energy Consumption Decrease in the Transition Period towards a Digital Society

by Corina Pelau and Carmen Acatrinei

Energies 2019, 12(8), 1428; https://doi.org/10.3390/en12081428 - 13 Apr 2019

Cited by 19 | Viewed by 3247

Abstract

The digital transformation era is in full motion, steadily making its way into common households, triggering changes in behavior as well as consumption patterns. While some changes can occur only within the context of the household mean income, such as the upgrade of appliances or devices, correlated with a personal preference in adopting such tools and technologies, there is one area that must keep with the pace of change, regardless of the household’s subjective criteria: energy consumption. The objective of this paper is to analyze the impact of digitalization on the household energy consumption, with the intent to understand trends, anticipate future changes as well as impact energy consumption efficiency. The results of the panel regressions based on the quantity of consumed energy and the popularity of several internet activities have revealed an inverse relation. The increased number of consumers doing certain internet activities such as: internet calling, reading online newspapers, activities on social media networks and uploading content online determine a lower energy consumption for that economy. There was no significant evidence for the relation between the energy consumption and internet activities such as: reading e-mails, searching for, doing internet banking and online purchases. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

Review

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18 pages, 4332 KiB

Open AccessReview

The Role of Off-Grid Houses in the Energy Transition with a Case Study in the Netherlands

by Diego F. Quintero Pulido, Marnix V. Ten Kortenaar, Johann L. Hurink and Gerard J.M. Smit

Energies 2019, 12(10), 2033; https://doi.org/10.3390/en12102033 - 27 May 2019

Cited by 13 | Viewed by 5043

Abstract

Off-grid houses can be considered an important concept to increase the access to electricity throughout the world. Although there are quite some initiatives in place to improve the access to electricity, the implementation rate of practical solutions is far below the UN Sustainable Development Goal 7: Energy (SDG 7) + for 2030. This situation is most apparent in Sub-Saharan Africa, where the current trends of electricity access calculated by the World Bank indicate that this region will not be able to achieve the SDG 7 target. Another worldwide trend which may help to increase electricity access is that currently, a lot of renewable energy generation is realized locally in houses (especially Solar Photovoltaics (PV)). This paper reviews the recent developments to increase the access to electricity in the world and the implementation of off-grid houses in different scenarios. The focus here is on the different efforts to create off-grid houses considering their challenges on a macro and micro level. Moreover, potential research directions for technologies in off-grid houses are presented in more detail. For this, a case description of a possible off-grid house in the Netherlands is presented together with some initial simulations results for this case using solar PV, the Sea-Salt battery, and a Glycerol Fuel Cell. The simulations use the DEMkit software and the analysis is performed using measured house load data for a period in winter and in summer. Full article

(This article belongs to the Special Issue Electricity for Energy Transition)

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