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The application of fractional calculus to obtain dynamic models for supercapacitors represents an alternative approach to obtaining simpler and more accurate models. This paper presents a model for the supercapacitor in the time domain, based on the use of the fractional or non-integer order integral. This fractional model is compared with the conventional simple model, which is typically used in industrial applications. This fractional integral-based model provides satisfactory fits in relation to the number of parameters used in the model. Furthermore, an interpretation of the effect of the application of fractional integration is presented for constant current charging and discharging processes at constant current, using the Riemann–Liouville definition for the non-integer order integral. Supercapacitors are devices that exhibit non-linear behavior, with a distinct charging and discharging operation. There are several methods of dynamic analysis for the characterization of supercapacitors. The information extracted from these methods is essential for understanding the behavior of supercapacitors and, thus, ensuring that processes involving supercapacitors are as efficient as possible. This paper presents a dynamic analysis based on charge and discharge operations with constant currents. The conclusion is that the fractional model provides fairly accurate fits.

This paper investigates hydrogen’s potential to accelerate the energy transition in hard-to-abate sectors, such as steel, petrochemicals, glass, cement, and paper. The goal is to assess how hydrogen, produced from renewable sources, can foster both industrial decarbonization and the expansion of renewable energy installations, especially solar and wind. Hydrogen’s dual role as a fuel and a chemical agent for process innovation is explored, with a focus on its ability to enhance energy efficiency and reduce CO2 emissions. Integrating hydrogen with continuous industrial processes minimizes the need for energy storage, making it a more efficient solution. Advances in electrolysis, achieving efficiencies up to 60%, and storage methods, consuming about 10% of stored energy for compression, are discussed. Specifically, in the steel sector, hydrogen can replace carbon as a reductant in the direct reduced iron (DRI) process, which accounts for around 7% of global steel production. A next-generation DRI plant producing one million tons of steel annually would require approximately 3200 MW of photovoltaic capacity to integrate hydrogen effectively. This study also discusses hydrogen’s role as a co-fuel in steel furnaces. Quantitative analyses show that to support typical industrial plants, hydrogen facilities of several hundred to a few thousand MW are necessary. “Virtual” power plants integrating with both the electrical grid and energy-intensive systems are proposed highlighting hydrogen’s critical role in industrial decarbonization and renewable energy growth.

This paper presents an investigation into the virtualization of substation protection IED functions using a sophisticated co-simulation environment that integrates virtual intelligent electronic devices (vIEDs) with a real-time power grid simulation. Anchored by the IEC 61850 protocol, this study constructs a virtualized IED framework, emphasizing the encapsulation of protection schemes using the example of different types of overcurrent protection within a containerized vIED. Using open-source software, this study aims to replicate the communication and functional aspects of physical IEDs. This study uses a co-simulation environment that couples virtualized network components with a real-time power grid simulation to validate the vIEDs against real substation hardware. Simulation results from induced short-circuit events confirm the operational congruence of the vIEDs with their physical counterparts, demonstrating their potential to serve as cost-effective and adaptable testbeds for substation automation. This paper concludes that virtualized IEDs represent a cost-effective, flexible alternative for substation automation testing, with future research directed towards increasing the functional complexity and real-world applicability of these virtual systems.

In young Maxwell’s eyes, electricity, magnetism and fluid mechanics present analogies that let the first be mathematically grasped in a unitary way similarly to the latter. This entry sketches the first steps of James Clerk Maxwell’s unitary view of electromagnetism and fluid mechanics, with long-lasting effects on understanding the physical world. In his very first paper on the subject, Maxwell interpreted Faraday’s concept of lines of force of both electricity and magnetism as filaments of a flowing fluid. That is, Maxwell suggested to unify the previously distinct fields of electricity and magnetism, considering them as different aspects of the same entity, the ‘electromagnetic field’, which is mathematically described by four partial differential equations. In the literature there are several comprehensive works on Maxwell’s mature exposition of his theory; however, the aim of this entry contribution is rather more limited. Indeed, it is restricted to examining the contributions of Maxwell’s first paper towards developing the idea of electric current as the motion of an incompressible fluid. Thus, this entry highlights the strong connections of Maxwell’s epistemological view with the ‘mechanistic’ approach of the time to every aspect of physical phenomenology. For this purpose, this entry mentions some historical context surrounding the emergence of Maxwell’s innovative concepts.

A reduction in greenhouse gases has become an inescapable requirement. An effective scenario for achieving carbon neutrality is to develop a hydrogen economy. Its success, however, requires strict control of the different processes involved in planned hydrogen chains. The energy chain considered in this paper is a stationary application which involves the production of hydrogen by electrolysis (a power-to gas process) and its combustion in gas turbine combined cycles to generate electricity (a gas-to-power process). In such applications, the need is twofold: (i) to control the risk of explosive atmospheres by performing safe gas detection in the presence of hydrogen and (ii) to secure the reliability of all chain processes using hydrogen-rich gases by achieving reliable analyses of these gases. This paper is dedicated to the development of hydrogen energy to decarbonize the thermal production of electricity. We will first describe the hydrogen chain that would best suit the power generation sector. Then, we will highlight the properties of hydrogen that are critical for its reliable operation. Finally, we will review the sensing technologies suitable for hydrogen-containing fuels. This review paper was published as part of a Joint Industrial Project (JIP) aimed at enabling the safe and reliable deployment of hydrogen energy.

This paper presents a live field experience of creating an isolated microgrid for the Expoelectric fair during 2018 and 2019. The islanded microgrid comprises a Master Inverter with grid-forming capabilities and fault management. The Master Inverter and stationary batteries, and EVs with V2G capabilities provide storage. A PV generation system supplies the microgrid. The loads are the fair booths, mainly lighting and chargers for personal mobility vehicles. All the equipment used in the experimental microgrid is from different manufacturers. The operation and control of the islanded microgrid are based on the VDE-AR-N-4105 standard. The paper also presents the operation of the Master Inverter during faults. The live field experience shows that the proposed operation method is valid for operating different converters from different manufacturers without needing any communication layer between them. The experimental results also show that faults can be handled correctly by the Master Inverter to operate the entire microgrid safely. In conclusion, islanded microgrids based on power electronics are feasible to replace diesel generators in faires, conventions or temporary events.

This paper presents a stochastic approach to assessing the hosting capacity for solar PV. The method is part of the optimal techniques for the integration of renewables. There are two types of uncertainties, namely aleatory and epistemic uncertainties. The epistemic and aleatory uncertainties influence distribution networks’ hosting capacity differently. The combination of the two uncertainties influences the planning of distribution networks. The study introduces and considers the epistemic probability distribution function (PDF). DSO does take levels of risk for a parameter violation when planning. Epistemic PDF is a range of values of the planning risk margin for quantifying the hosting capacity. The planning risk acknowledges that overvoltages may occur at weaker conceivable locations in a distribution network. In the paper, it has been shown that the number of customers who will be able to connect solar PV in future is influenced by the DSO’s planning risk margin. The DSO can be stricter or less strict in planning risk margin. It has been concluded that fewer customers can connect solar PV to a distribution network when a DSO takes a stricter planning risk. Alternatively, more customers can connect solar PV units for a less strict planning risk. How stricter or less strict the DSO is with the planning risk margin determines the investment needed for mitigation measures. The mitigation measures in the future will lead to not exceeding the overvoltage limit when solar PV is connected to the weaker conceivable points of the distribution network.

Electric vehicles (EVs) are important elements in the global strategy to tackle climate change; however, research often fails to sufficiently identify the range of barriers which affect their adoption. Taking Saudi Arabia as a case study, this paper analyses responses from 698 potential drivers in order to identify and rank the infrastructure, performance, financial, social, and policy barriers to EV adoption in a major oil-producing nation with a hot climate and a desert terrain. According to this study’s findings, the most important barriers in this context are the lack of charging infrastructure and the additional load placed on the national grid, while others include the safety and effectiveness of batteries at high temperatures, and the ability of EVs to perform in desert conditions. Common themes also include concerns that EVs may damage Saudi’s oil-based economy, cost of purchase and maintenance, low resale value, and the absence of awareness about EVs. The study concludes that EV manufacturers must demonstrate that their vehicles are suitable for the Saudi climate. Governments should also provide subsidies, or other incentives, to promote adoption of EVs as the study also found that variations in the cost of different EV models in Saudi Arabia, for example, the Tesla Model 3, is up to 40% more expensive to own than a Toyota Camry, mean that owning EVs can cost significantly more than small sized internal combustion engine-based vehicles (ICEVs). This paper identifies and ranks the barriers to EV ownership in a desert nation which is a leading petroleum producer and compares the relative costs of EVs and ICEVs in the country. As such, it has immediate relevance in countries with similar economic, geographic, and climatic conditions.

The method of symmetrical components is an important mathematical tool for electrical engineering, as it simplifies the analysis of unbalanced electrical circuits. The method is used almost exclusively for three-phase networks, but with the advancement of multiphase electrical systems, it could be convenient to utilize it for such systems as well. In this paper, the method of symmetrical components is used to analyze a generic five-phase electrical system for various short-circuit faults and to determine the sequence networks connections for these faults. The analysis performed covers the derivation of the symmetrical components for voltage/current and of fault currents. The analytical results and the inferred sequence networks connections are validated by computer simulations. This paper therefore extends the literature on short-circuit analysis of multiphase electrical systems using the method of symmetrical components.

Cables are the largest assets by volume on power distribution networks and the assets with the least health information routinely gathered. Projections over the next 8 years suggest increased penetration of low-carbon technology (LCT) at the distribution level with higher loads resulting from electric vehicle (EV) and heat pump uptake. Over this period, increased cable loading will directly influence their lifetimes and may mean that existing asset management practices need to be revised to understand the specific impact on end-of-life assessment. Accordingly, this paper uses a physics-based thermal lifetime model based on projected uptake trends for LCTs to evaluate the impact on distribution cable lifetime. Two case studies are presented considering portions of network and the ultimate impact on asset life over the next decade. Two commonly used cables are considered to quantify the lifetime reduction caused by LCT for asset fleets. The paper shows that the projected uptake of EVs and heat pumps will have a detrimental effect on cable life with a 30% reduction in cable lifetime possible.

This paper explores the role of electricity in the transition to renewable energy to mitigate climate change. A systematic literature review with the Scopus database identified 92 papers relevant to the renewable electricity transition. A PESTLE (Political, Economic, Sociological, Technological, Legal, and Environmental) review of the papers provided a multidisciplinary analysis. The Paris Agreement created a global movement for carbon neutrality to address the threats of climate change, calling for a transition to renewable electricity to lead the way and expand into new sectors and regions. Although smaller renewable technologies are ramping up, complexities thwarting the transition include locked-in assets, high upfront costs, variability of solar and wind energy, infrastructure, difficulty in decarbonizing transportation and industry, material resource constraints, and fossil fuel support. This research found that renewables are not replacing fossil fuels to date but adding further energy demands, so that greenhouse gas emissions rose in 2021 despite an increased renewable electricity share. Without a major shift in the trillions of dollars of subsidies and investment away from fossil fuels to renewables, catastrophic climate change is predicted. This paper found that the Paris Agreement’s commitment to net-zero carbon and the transition to renewable electricity are undermined by record-high levels of subsidies and financing for fossil fuel industry expansion. Transitioning to a climate-neutral economy requires an investment away from fossil fuels into renewable energy ecosystems. Renewable electricity provides possibilities to realize sustainable development goals, climate stabilization, job creation, a green economy, and energy security with careful planning.

This paper compares concentrated and distributed reactive power compensation to improve the power factor at the point of common connection (PCC) of an industrial electrical system (IES) with harmonics. The electrical system under study has a low power factor, voltage variation, and harmonics caused by motors operating at low loads and powered by variable-speed drives. The designed compensation system mitigates harmonics and reduces electrical losses with the shortest payback period. Four solutions were compared, considering concentrated and distributed compensation with capacitor banks and harmonic filters. Although the cost of investment in concentrated compensation is lower than that of distributed compensation, a higher reduction in electrical losses and a lower payback period are obtained with distributed compensation. Although the lowest payback period was obtained with distributed compensation with capacitor banks (0.4 years), it is not recommended in the presence of harmonics because the effects of current harmonics significantly reduce the useful life of these elements. For this reason, distributed compensation with harmonic filters obtained a payback period of 0.6 years, and it was proposed as the best solution. These results should be considered in projects aimed at power factor compensation in IESs with harmonics. The concentrated compensation of the capacitor bank at the PCC is proposed because of the lower investment cost and ease of installation. However, the advantages of distributed compensation with harmonic filters have not been evaluated. An energy efficiency approach is used to analyze the impact of the location methods of the power factor compensation equipment on the electrical losses of the IES.

This paper presents the design of a predictive controller for a boost converter and validation through real-time simulation. First, the boost converter was mathematically modeled, and then the electronic components were designed to meet the operation requirements. Subsequently, a model-based predictive controller (MBPC) and a digital PI (Proportional–Integral) controller were designed, and their performance was compared using MATLAB/SIMULINK®. The controls were further verified by implementing test benches based on an FPGA (Field-Programmable Gate Array) with an OPAL-RT real-time simulator, which included the RT-LAB and RT-eFPGAsim simulation packages. These tests were successfully carried out, and the methodology used for this design was validated. The results showed a better response obtained with MBPC, both in terms of stabilization time and lower overvoltage.

This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region.

Recent advancements in residential solar electricity have revolutionized sustainable development. This paper introduces a methodology leveraging machine learning to forecast solar panels’ power output based on weather and air pollution parameters, along with an automated model for fault detection. Innovations in high-efficiency solar panels and advanced energy storage systems ensure reliable electricity supply. Smart inverters and grid-tied systems enhance energy management. Government incentives and decreasing installation costs have increased solar power accessibility. The proposed methodology, utilizing machine learning techniques, achieved an R-squared value of 0.95 and a Mean Squared Error of 0.02 in forecasting solar panel power output, demonstrating high accuracy in predicting energy production under varying environmental conditions. By improving operational efficiency and anticipating power output, this approach not only reduces carbon footprints but also promotes energy independence, contributing to the global transition towards sustainability.

Electricity plays a significant role in daily life and is the main component of countless applications. Thus, ongoing research is necessary to improve the existing approaches, or find new approaches, to enhancing power generation. The thermoelectric generator (TEG) is among the notable and widespread technologies used to produce electricity, and converts waste energy into electrical energy using the Seebeck effect. Due to the Seebeck effect, temperature change can be turned into electrical energy; hence, a TEG can be applied whenever there is a temperature difference. The present paper presents the theoretical background of the TEG, in addition to a comprehensive review of the TEG and its implementation in various fields. This paper also sheds light on the new technologies of the TEG and their related challenges. Notably, it was found that the TEG is efficient in hybrid heat recovery systems, such as the phase change material (PCM), heat pipe (HP), and proton exchange membrane (PEM), and the efficiency of the TEG has increased due to a set of improvements in the TEG’s materials. Moreover, results show that the TEG technology has been frequently applied in recent years, and all of the investigated papers agree that the TEG is a promising technology in power generation and heat recovery systems.

This paper presents a study and proposes a new methodology to analyze, evaluate and reduce the overall uncertainty of instrumentations for EMC measurements. For the scope of this work, the front end of a commercial EMI receiver is chosen and variations due to tolerances, temperature and frequency response of the system are evaluated. This paper illustrates in detail how to treat each block composing the model by analyzing each discrete component, and how to evaluate their influence on the measurand. Since a model can have hundreds or even thousands of parameters, the probability distribution functions (PDFs) of some variable might be unknown. So, a method that allows to obtain in a fast and easy way the uncertainty of the measurement despite having so many variables, to then being able to evaluate the influence of each component on the measurand, is necessary for a correct design. In this way, it will be possible to indicate which discrete components have the most influence on the measurand and thus set the maximum tolerances allowed and being able to design a cost-effective solution. Furthermore, this works presents a methodology which can easily be extended and applied to estimate and compute the uncertainty for electromagnetic interferences, energy storage systems (ESS), energy production, electric machines, electric transports and power plants in general.

In this paper, a systematic literature review is presented, through a survey of the main digital databases, regarding modelling methods for Short-Term Load Forecasting (STLF) for hourly electricity demand for residential electricity and to realize the performance evolution and impact of Artificial Intelligence (AI) in STLF. With these specific objectives, a conceptual framework on the subject was developed, along with a systematic review of the literature based on scientific publications with high impact and a bibliometric study directed towards the scientific production of AI and STLF. The review of research articles over a 10-year period, which took place between 2012 and 2022, used the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) method. This research resulted in more than 300 articles, available in four databases: Web of Science, IEEE Xplore, Scopus, and Science Direct. The research was organized around three central themes, which were defined through the following keywords: STLF, Electricity, and Residential, along with their corresponding synonyms. In total, 334 research articles were analyzed, and the year of publication, journal, author, geography by continent and country, and the area of application were identified. Of the 335 documents found in the initial research and after applying the inclusion/exclusion criteria, which allowed delimiting the subject addressed in the topics of interest for analysis, 38 (thirty-eight) documents were in English (26 journal articles and 12 conference papers). The results point to a diversity of modelling techniques and associated algorithms. The corresponding performance was measured with different metrics and, therefore, cannot be compared directly. Hence, it is desirable to have a unified dataset, together with a set of benchmarks with well-defined metrics for a clear comparison of all the modelling techniques and the corresponding algorithms.

Reverse bandgaps generate PVT-independent reference voltages by means of the sums of pairs of currents over individual matched resistors: one (CTAT) current is proportional to VEB; the other one (PTAT) is proportional to VT (Thermal voltage). Design guidelines and techniques for a CMOS low-power reverse bandgap reference are presented and discussed in this paper. The paper explains firstly how to design the components of the bandgap branches to minimize circuit current. Secondly, error amplifier topologies are studied in order to reveal the best one, depending on the operation conditions. Finally, a low-voltage bandgap in 65 nm CMOS with 5 ppm/°C, with a DC PSR of −91 dB, with power consumption of 5.2 μW and with an area of 0.0352 mm2 developed with these techniques is presented.

This paper introduces a dynamic consensus-based economic dispatch (ED) algorithm utilizing the Alternating Direction Method of Multipliers (ADMM) to optimize real-time pricing and generation/demand decisions within a decentralized energy management framework. The increasing complexity of modern energy markets, driven by the proliferation of Distributed Energy Resources (DER) and variable demands from hybrid electric vehicles, necessitates a departure from traditional centralized dispatch methods. This research proposes a novel ADMM-based solution tailored for non-responsive and responsive demand units that integrates demand response mechanisms to adaptively manage real-time fluctuations while enhancing security and privacy through distributed data management. The testing of the algorithm on the IEEE 39 bus system under various load conditions over 24 h demonstrated the algorithm’s effectiveness in handling traditional and renewable energy sources, particularly highlighting the economic benefits of shifting controllable loads to periods of low-cost renewable availability. The findings underscore the algorithm’s potential to reduce energy costs, enhance energy efficiency, and offer a scalable solution across diverse grid systems, contributing significantly to advancing global energy policy and sustainable management practices.

Electricity theft comes with various disadvantages for power utilities, governments, businesses, and the general public. This continues despite the various solutions employed to detect and prevent it. Some of the disadvantages of electricity theft include revenue loss and load shedding, leading to a disruption in business operations. This study aimed to conduct a systematic literature review to identify what technology solutions have been offered to solve electricity theft and the effectiveness of those solutions by considering peer-reviewed empirical studies. The systematic literature review was undertaken following the guidelines for conducting a literature review in computer science to assess potential bias. A total of 11 journal articles published from 2012 to 2022 in SCOPUS, Science Direct, and Web of Science were analysed to reveal solutions, the type of theft addressed, and the success and limitations of the solutions. The findings show that the focus in research is channelled towards solving electricity theft in Smart Grids (SGs) and Advanced Metering Infrastructure (AMI); moreover, there is a neglect in the recent literature on finding solutions that can prevent electricity theft in countries that do not have SG and AMI installed. Although the results reported in this study are confined to the analysed research papers, the leading limitation in the selected studies, lack of real-life data for dishonest users. This study’s contribution is to show what technology solutions are prevalent in solving electricity theft in recent years and the effectiveness of such solutions.

The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used.

The current transition towards renewable energies has led to an increased utilization of Photovoltaic (PV) sources and battery energy storage systems to complement the PV panels. To facilitate energy transfer among PVs, batteries, and loads, multiple converters are required. Thus, this transformation in the energy system has resulted in an increase in converter-interfaced elements. Within this context, three-port converters allow for replacing multiple converters with a single one. These three-port converters use a high-frequency AC resonant link for the bidirectional transfer of energy across the different ports. This architecture uses multiple switches and has a variable operating frequency. These characteristics make the simulation of these converters computationally heavy. Thus, averaged models are required, especially for simulating multiple converters connected in parallel or composing a microgrid. In this paper, an averaged model for this type of converter is developed. The methodology is first demonstrated and applied to a two-port DC/DC converter, and subsequently extended to the three-port DC/DC/DC version. Afterwards, control strategies for three-port DC/DC/DC converters are proposed based on the elements connected to their ports. The developed model for three-port DC/DC/DC converters is then implemented in an islanded DC microgrid to demonstrate their parallel operation. The proposed developed averaged models and the test DC microgrid are implemented in MATLAB/Simulink.

Three LED drivers which can be used for illumination, but whose main task is the transmission of information (data) via the light of the LEDs, are explored in this paper. The converter circuits need no capacitors for the energy transformation and avoid an inrush current. The lack of necessity of electrolytic capacitors reduces cost and space. Dimming the illumination is also easy to achieve. The control concept of the converters and the generation of pulsing of the LEDs for transmitting the information (data) are explained. The converters can also be expanded to more stages to drive more LEDs with different types of information. All three converters are explained in detail; all presented circuits are built up and simulated with LTSpice. Several data transmission concepts are applied and demonstrated through simulations.

In this paper an efficient, compact, and cheap power source design for an off-grid PV water pumping system is investigated. The proposed system consists of a PV array, battery, three-port converter (TPC), three-phase voltage source inverter, and induction motor pump. Power is extracted from PV sources during the daytime and used to charge batteries through the three-port converter, then used later to supply load during the nighttime. An intelligent MPPT method is used to obtain PV maximum power; a jellyfish optimization technique with different control algorithms is used to optimize and tune controllers’ parameters among the system. Different modes for the TPC are discussed depending on PV power availability. The proposed system is simulated to assess system performance under different conditions; also the system is efficient with reduced number of components than conventional converters. A complete unified power management over PV input port, battery port, and load port has occurred for all operation modes. At all operation modes, the system has been feeding load without any unmet loads. A real case study in Al-Kharijah oasis is studied and simulation results are listed; for the Dom case DC bus ripple factor voltage percentage equals 0.8%, in the Dim case equals 3%, and in the Siso mode equals 9%.

The problem of White Etching Cracks (WEC) leading to failures in the life cycle of industrial and automotive drive trains has existed for more than 30 years. Many parameters leading to WEC, such as the presence of electricity, unfavorable lubricants, and other factors, have been identified by the use of test rigs. However, since (a) within lifecycle operation these impacts appear incidentally, and (b) the identified impacts stimulate each other as stated in WEC research, the appearance of WEC in a drive train is impossible to predict for any given application. This difficulty causes WEC to be a serious problem. Obtaining reliable failure prediction rates using construction guidelines is still impossible, resulting in warranty claims. The aim of this paper is, first, to establish a routine to determine if and how lubricants could be described numerically with respect to their susceptibility toward electrical fields and to see how this factor could be added in a later stage to construction guidelines. Second, this paper aims to give advice to the applicant in terms of countermeasures. Currently, as predictors are missing, extensive and time-consuming testing is required. Contradictory test results in the field of application, indicate the need for fundamental parameters to determine in which circumstances the application is exposed to WEC risk and to suggest countermeasures. The current study presents a simulation method based solely on the chemical structure of lubricant components, investigating the appearance of WEC and their response to increasing electrical fields. The results show a clear pattern in WEC criticality with respect to lubricants: if two or more components present in the lubricant create clusters through their dipolar interaction, an apparent WEC risk could be accurately predicted apart from test rig results. These clusters are charged like one big particle in an early stage of electrical field exposure. As a result, the surface area increases, facilitating a higher uptake of charge. The incidental breakdown of this charge is assumed. As the charge of a cluster is higher than that of single molecules, WEC critical lubricants are subjected to this pattern. The study validates these results by comparing them using lubricants known to be critical with respect to WEC, suggesting further tests in the near future. Despite the fact that some lubricants seem more critical than others related to WEC, each lubricant clearly might lead to WEC under given conditions. Thus, constructing guidelines for a prediction routine is essential.

Due to high electricity prices and possible shortages of gas and other energy commodities, various fluctuations in electricity generation will need to be regulated. Given the increasing expansion of wind power plants in Europe and worldwide. It is necessary and essential to put power regulation into practice, as mandated by regulation 2016/631 EU. A significant power balance problem may arise on the grid, which may lead to cyclical and recurring blackouts in the future. The motivation for this paper is to raise awareness of the controllability of wind turbines and to highlight the gentle pace of research in this area for pitch angle control. Therefore, the chief idea of the paper is to develop a proposal for wind power plant power control by changing the rotor blade rotation, following previous research in this area, and determining the shortcomings and possibilities. The paper provides a numerical method for controlling the power output of a wind power plant, for which an algorithm has been proposed. This control is intended to provide a framework for the design and implementation of a wind power plant control program. Coordination between the multiple sources will fulfil a leading role in smooth power management.

This paper proposes a single-stage direct AC to high-frequency (HF) AC resonant converter based on LLC configuration for induction heating (IH) systems or HF applications. Unlike conventional converters for IH systems, the proposed topology converts the utility frequency to HF AC in a single stage without using a DC link inductor and capacitors and takes the advantages of LLC configuration. Additionally, it improves the power factor to 0.9–1, lowers the THD (3.2% experimentally), and protects against the high-frequency components. An embedded control scheme was designed to keep the HF current oscillating at a resonant frequency, ensuring zero-voltage switching. The operating principle of the proposed topology was investigated using mathematical equations and equivalent circuits. Finally, it was verified using computer simulation, and an experimental prototype of 1.1 kW was developed to demonstrate the proposed topology’s uniqueness.

The global capacity for renewable electricity generation has surged, with distributed photovoltaic generation being the primary driver. The increasing penetration of non-programmable renewable Distributed Energy Resources (DERs) presents challenges for properly managing distribution networks, requiring advanced voltage regulation techniques. This paper proposes an innovative decentralised voltage strategy that considers DERs, particularly inverter-based ones, as autonomous regulators in compliance with the state-of-the-art European technical standards and grid codes. The proposed method uses an optimal reactive power flow that minimises voltage deviations along all the medium voltage nodes; to check the algorithm’s performance, it has been applied to a small-scale test network and on a real Italian medium-voltage distribution network, and compared with a fully centralised ORPF. The results show that the proposed decentralised autonomous strategy effectively improves voltage profiles in both case studies, reducing voltage deviation by a few percentage points; these results are further confirmed through an analysis conducted over several days to observe how seasons affect the results.

Over the years, a rapid evolution of smart grids has been witnessed across the world due to their intelligent operations and control, smart characteristics, and benefits, which can overcome several difficulties of traditional electric grids. However, due to multifaceted technological advancements, the development of smart grids is evolving day by day. Thus, smart grid researchers need to understand and adapt to new concepts and research trends. Understanding these new trends in smart grids is essential for several reasons, as the energy sector undergoes a major transformation towards becoming energy efficient and resilient. Moreover, it is imperative to realize the complete potential of modernizing the energy infrastructure. In this regard, this paper presents a comprehensive bibliometric analysis of smart grid concepts and research trends. In the initial search, the bibliometric data extracted from the Scopus and Web of Science databases totaled 11,600 and 2846 records, respectively. After thorough scrutiny, 2529 unique records were considered for the bibliometric analysis. Bibliometric analysis is a systematic method used to analyze and evaluate the scholarly literature on a particular topic and provides valuable insights to researchers. The proposed analysis provides key information on emerging research areas, high-impact sources, authors and their collaboration, affiliations, annual production of various countries and their collaboration in smart grids, and topic-wise title count. The information extracted from this bibliometric analysis will help researchers and other stakeholders to thoroughly understand the above-mentioned aspects related to smart grids. This analysis was carried out on smart grid literature by using the bibliometric package in R.

The purpose of the following article is to present the situation of the energy market from a household perspective between 2010 and 2020 in selected EU countries (the group of member states which joined EU after 2004). The selected countries when joining the EU had similar economic indicators and to some extent were similar in other macro-economic situations (personal income, unemployment rate, GDP level and annual growth). This article analyzes the past and current situation of the household ability expenditure on electricity and energy resources (petrol—eurosuper 95 and diesel and natural gas), taking into account price, tax conditions and the real possibility to purchase the analyzed energy sources (based on annual net salaries). The paper includes the conclusions and prospects for the future. The main objective of the study is to determine the ability amount of expenditure on electricity, natural gas and liquid fuels by household in the countries that joined the European Union after 2004. The specific objectives of the work include: the evolution of retail prices of energy sources in those countries and prices of electricity, natural gas and liquid fuels—petrol and diesel oil—in the research period from 2010 to 2020. The element that influences the final price, as assessed in this paper, is the share of taxes and compulsory charges imposed by the EU countries covered in this study. The result of the study presented inter alia that energy consumption structure did not change significantly, electricity prices were steadily growing in the countries under assessment, the use of liquid fuels—petrol and diesel oil—in the countries under study, grew over the study period. Furthermore, prices of fuel fluctuated over the period from 2010 to 2020 and during the COVID-19 pandemic, which broke out in March 2020, but did not cause any significant changes in the prices of energy carriers in the analyzed period, apart from the declines in the prices of eurosuper 95 and diesel.

This paper discusses the authors’ experience gained with the selection of Projects of Common Interest (PCIs) in the thematic area of smart grids deployment, in the context of the TEN-E Regulation. It presents the framework for assessing candidate electricity smart grids for inclusion in the European Union list of PCIs, in view of the TEN-E Regulation and the existing literature on assessment methodologies for energy infrastructure projects. It also provides an overview of smart grid projects included in the PCI lists, with the aim to shed light on the types of projects and their contribution to accelerating the development of European cross-border energy infrastructure projects to respond to EU energy and climate targets. The paper concludes with discussion of recent regulatory initiatives and their potential implications on the presented methodology.

The current formal common denominator of the electricity supply system in Europe has been the Harmonized Electricity Market Role Model (HEMRM) set up by ENTSO-E, ebIX, and EFET at the turn of the millennium; it introduced the concept of de-coupling and the vertical structuring of the system into the previously vertically integrated system. Since then, within demonstration projects, the system has been undergoing further changes in a controlled environment, generating bottom-up energy, caused by new technologies, business models, and new players, and extending the concept of the system to the level of energy communities and prosumers. Therefore, this paper proposes a coherent approach to the extension of HEMRM to the lowest levels in both the grid and market segments—full harmonization. This entails further structuring of both segments downwards and applying the principles of vertically nested subsystems—a system of systems approach—to a unit functional level of the electricity system, which can be the prosumer itself. At the lowest levels, the de-coupled system becomes coupled; additionally, it cross-sects with other energy vectors. Complete harmonization reduces the number of system and market segments and represents system standardization, leading to both subsystem and system-wide optimization. Prerequisites for it include the automated trading of flexibilities by the prosumers and implicit trading of energy transfer capacities along the distribution grids. The energy reservoirs, implicit and explicit, short-term, and long-term, play a vital role in techno-economic balancing.

Magnetostrictive alloys hold great promise for Energy Harvesting applications due to their inherent durability. However, their implementation often results in usable voltage ranges that fall significantly below common electronic standards like 1.6, 3.3, and 5 volts. Consequently, the utilization of electronic circuits becomes essential to amplify the voltage and enhance energy conversion efficiency. Over the past few decades, numerous conversion techniques have been devised for other intelligent materials, such as piezoelectrics, some of which have even made their way into commercial products. Surprisingly, there is a dearth of specialized techniques, if not a complete absence, tailored to magnetostrictive devices. Among potential solutions, a suitable AC–DC Boost converter stands out as a highly promising candidate for addressing this challenge, but this solution has never been fully characterized. Then, this paper presents thorough experimental validations of such a converter, driven by a real-time Arduino board equipped to measure source time periods and operate under various conditions. We present several cases demonstrating the circuit’s substantial potential for enhancing energy harvesting from magnetostrictive materials.

This paper presents the techno-economic feasibility of using grid-connected PV hybrid systems to supply power in large grid-dependent academic institutions. The study was conducted using the administration building of Moi University in Kenya. The power consumption profile of the building was collected using a PCE-360 power analyzer. The peak load demand was found to be 60 kW. Using random variability constants of 4% for day-to-day and 4% time-step load variability, a peak demand of 70.58 kW was obtained, which was used in our simulation. The solar radiation and temperature data for this site were collected from the weather station of the university. The hybrid system was simulated using HOMER Pro software. It was found from the simulation results that the optimal system was the solar PV/grid without battery storage, which had a levelized cost of energy (LCOE) of KSH 8.78/kWh (USD 0.072), net present cost (NPC) of KSH 27,974,492 (USD 230,813), capital expenditure (CAPEX) of KSH 26,300,000 (USD 216,997), and a simple payback period (SPBP) of 5.08 years for a 25-year life span. This system, when compared to the existing grid, showed an 83.94% reduction in the annual electricity bill of the administration building. These results demonstrate a reduction in energy cost by a renewable energy fraction of 67.1%.

The dynamics of electrical systems have changed significantly with the increasing penetration of non-conventional loads such as hydrogen electrolysers. As a result, detailed investigations are required to quantify and characterize these loads’ effects on the dynamic response of interconnected synchronous machines after being subjected to a disturbance. Many studies have focused on the effects of conventional static and dynamic loads. However, the impact of hydrogen electrolysers on the stability of power systems’ rotor angles is rarely studied. This paper assesses the effect of proton exchange membrane (PEM) electrolysers on small-disturbance rotor-angle stability. Dynamic modelling and the control of a PEM electrolyser as a load are first studied to achieve this. Then, the proposed electrolyser model is tested in the Amercoeur plant, which is part of the Belgian power system, to study its effect on the small-signal rotor-angle stability. Two approaches are considered to examine this impact: an analytical approach and time-domain simulations. The analytical approach consists of establishing a state-space model of the Belgian test system through linearisation around an operating point of the non-linear differential and the algebraic equations of the synchronous generators, the PEM electrolyser, the loads, and the network. The obtained state-space model allows for the determination of the eigenvalues, which are useful to evaluate the effect of the PEM electrolyser on the small-signal rotor-angle stability. This impact is investigated by examining the movement of the eigenvalues in the left complex half-plane. The obtained results show that the PEM electrolyser affects the electromechanical modes of synchronous machines by increasing their oscillation frequencies. The results also show that the effect of the electrolyser on these modes can be improved by adjusting the inertial constant and the damping coefficient of the synchronous machines. These results are consolidated through time-domain simulations using the software Matlab/Simscape from the version MatlabR2022a-academic use from Mathworks.

In this paper, a long short-term memory (LSTM)-based method with a multi-input tensor approach is used for the classification of events that affect the power quality (PQ) in power systems with distributed generation sources. The considered events are line faults (one line, two lines, and three lines faulted), islanding events, sudden load variations, and generation tripping. The proposed LSTM-based method was trained and tested using the signals produced by the events simulated in a study system with distributed generation sources via PSCAD®. Then, noise with different levels was added to the testing set for a thorough assessment, and the results were compared with other well-known methods such as convolutional and simple recurrent neuronal networks. The LSTM-based method with multi-input proved to be effective for event classification, achieving remarkable classification performance even in noisy conditions.

A significant electromotive force is induced in the rotor circuit of a doubly fed induction generator (DFIG) due to its high vulnerability to grid faults. Therefore, the system performance must be increased with appropriate control actions that can successfully offset such abnormalities in order to provide consistent and stable operations during grid disturbances. In this regard, this paper presents a solution based on a combination of an energy storage-based crowbar and a rotor-side crowbar that makes the effective transient current and voltage suppression for wind-driven DFIG possible. The core of the solution is its ability to restrict the transient rotor and stator overcurrents and DC-link overvoltages within their prescribed limits, thereby protecting the DFIG and power converters and improving the system’s ability to ride through faults. Further, the capacity of an energy storage device for transient suppression is estimated. The results confirmed that the proposed approach not only kept the transient rotor and stator currents within ±50% of their respective rated values in severe system faults but also limited the DC-link voltage variations under ±15% of its rated value, achieving transient control objectives precisely and maintaining a stable grid connection during the faults.

Research on White Etching Cracks (WEC) in multiple bearing applications has identified various drivers that cause them. Lubricants and electricity combined with contact mechanics have been proven to catalyze WEC significantly. However, none of these factors solely cause WEC on its own; instead, combinations of factors discretize whether WEC appears or not. Hence, the WEC phenomenon appears to be multidimensional, making WEC still unpredictable. The current paper is about a systematic study using a Deep Grove Ball Bearing test rig to investigate how lubricant chemicals, combined with electricity and variations in oil flow and pressure, lead to WEC formation. It becomes evident that even under critical conditions for WEC formation, increasing oil flow and decreasing contact pressure can prevent WEC.

The wholesale electricity and capacity market constitute the backbone of the Russian power industry. It is in this market that large suppliers and buyers operate, and its entire turnover is consequently transmitted to the retail market. Our paper presents a theoretical overview of the main tools for forming the cost of electricity and capacity in the wholesale market in Russia (depending on the regional affiliation), the type of end users, and the degree of state participation. We consider the specifics of the formation of the cost of electricity and capacity in the price and non-price wholesale markets of Russia, which differ in territorial, climatic, and economic characteristics, as well as the established structure of generation. In the empirical part of the paper, we carry out a structural analysis of the volumes of trade in electricity and capacity in the price and non-price zones of the market. Furthermore, we explain the reasons for the current dynamics of prices in the wholesale market. Using the obtained results, we calculate the maximum annual effect of the solar power plant operation in various zones of the Russian wholesale market, as well as in the retail market. In addition, we estimate the economic incentive for the transition of the functioning of power facilities from the wholesale to the retail market. Our results can be of considerable practical importance and might be used for improving the strategy for the development of the electric power industry at the regional level both in Russia and in the other countries.

This Editorial provides an overview of the 13 papers published in the Special Issue Environmental and Energetic Valorization of RenewableResources belonging to Section B: Sustainable Energy of the Energies journal, five being review papers and the remaining being scientific articles.