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Photovoltaic technology has become one of the major renewable ways to generate electric power. However, the mismatch between the incident solar spectrum and photo-electric response efficiency of solar cells severely constrains their performance. Hence, spectral modification technologies, e.g., up-conversion (UC), down-conversion (DC), and luminescent down-shifting (LDS) technologies have been applied widely in the photovoltaic field to reform the incident spectrum to match the best response band possible. In this paper, we review the latest developments of the three technologies above in terms of material selection, optical characteristics, and photovoltaic performance. It is found that the three most popular materials for conversion are NaYF4: Er3+, Yb3+, and Yb3+. The excitation bands for the three technologies are 800–1550 nm, 250–488 nm, and 250–488 nm, respectively, while the emission bands are 523–669 nm, 520–1031 nm, and 490–1010 nm, respectively. Furthermore, issues hindering the development of spectral modification technologies are pointed out, e.g., low absorption efficiency, poor quantum conversion efficiency, and hurdles in commercialization. Finally, suggestions and solutions to address the above-mentioned issues are provided. [ABSTRACT FROM AUTHOR]

Nowadays, the microgrid system is characterized by a diversification of power factors and a complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting mostly focus on the fault detection and operation optimization of a single power device. However, for increasingly complex microgrid systems, it becomes increasingly challenging to effectively contain faults within a specific spatiotemporal range. This can lead to the spread of power faults, posing great harm to the safety of the microgrid. The topology optimization of the microgrid based on deep reinforcement learning proposed in this paper starts from the overall power grid and aims to minimize the overall failure rate of the microgrid by optimizing the topology of the power grid. This approach can limit internal faults within a small range, greatly improving the safety and reliability of microgrid operation. The method proposed in this paper can optimize the network topology for the single node fault and multi-node fault, reducing the influence range of the node fault by 21% and 58%, respectively. [ABSTRACT FROM AUTHOR]

Electrical vehicles are finding wide acceptance in the Jordanian transportation market; this has caused an accelerating shift in the emissions of greenhouse gases from the direct burning of fossil fuels consumed by the transportation sector towards the power generation sector. On the other hand, as electric vehicles gain more popularity, an extra load is added to the electrical power generation systems, raising essential concerns such as the capability of the power network to support this massive extra load and the increased emission of greenhouse gases caused by power plants. Studies show that Jordan's weather is known for being bright, sunny, and very suitable for the generation of electric power from solar energy sources. Therefore, with an infrastructure that can support convenient off-grid charging, a huge burden will be taken off the national grid and the environment. Therefore, this work proposes a basic design for an off-grid PV-covered carport and presents a study of the economics and effectiveness of using such a system to charge electric vehicles owned by the students and employees of the Applied Science Private University. The study is based on actual solar irradiance data collected on-site during university working hours (8 a.m.–5 p.m.) to allow students and employees to charge their electric vehicles from an off-grid carport system while on campus. Space limitations for carport design, initial design cost, return on investment, and annual electricity consumption are discussed to demonstrate the benefits of such a system for both the consumer (convenience and low charging cost) and the power company provider (less load to maintain). [ABSTRACT FROM AUTHOR]

In a conventional automotive manufacturing plant, the paint shop alone can represent 36% of the total energy consumption, making it the most demanding area in terms of electricity and fossil fuel energy consumption. This study explores the possibility of decentralizing the production of electrical power and heat simultaneously, using an Organic Rankine Cycle (ORC) system integrated with a Parabolic Trough Collector (PTC) in a paint shop. To date, no similar system has been explored or implemented by the automotive industry. To increase the efficiency of the integrated system, wasted heat generated during the paint manufacturing process is recovered and used to pre-heat the organic fluid in the ORC system. A 4E analysis (Energy, Exergy, Economic, and Environmental) is conducted to determine the practical viability of the proposed system. When applied to the southern region of the USA, this system's installed capacity is projected to be 11 times higher than the two unique SORC pieces of equipment currently running in Louisiana and Florida. The goals are to reduce the reliance on external primary energy sources and decrease the carbon emission footprint from production activity. The system is evaluated for a location in Alabama, USA. The designed SORC, using toluene, can produce 712.2 kWel net and 13,132 kg/h of hot water, with an overall energy efficiency of 31.02%; exergy efficiency of 34.23; and ORC efficiency of 27.70%. This leads to an electrical energy saving of 5.9% for the manufacturing plant. The regenerative thermal oxidizer (RTO) heat exchanger, the secondary heat source of the system, has the highest exergy destruction—3583 kW. The system avoids the emission of 4521 tCO2 per year. A payback period of 10.16 years for the proposed system is estimated. Considering a planning horizon of 10 years, the investment in the system is also justified by a benefit–cost analysis. [ABSTRACT FROM AUTHOR]

High temperatures in photovoltaic (PV) modules lead to the degradation of electrical efficiency. To address the challenge of reducing the temperature of photovoltaic modules and enhancing their electrical power output efficiency, a simple but efficient photovoltaic cooling system based on heat pipes (PV-HP) is introduced in this study. Through experimental and numerical investigations, this study delves into the temperature characteristics and power output performance of the PV-HP system. Orthogonal tests are conducted to discern the influence of different factors on the PV-HP system. The experimental findings indicate that the performance of the PV-HP system is superior to that of the single system without heat pipes. The numerical simulation shows the effects of system structural parameters (number of heat pipes, angle of heat pipe condensation section) on system temperature and power output performance. The numerical simulation results show that increasing the angle of the heat pipe condensation section and the number of heat pipes leads to a significant drop in system temperature and an increase in the efficiency of the photovoltaic cells. [ABSTRACT FROM AUTHOR]

This research proposes the utilization of Peltier modules to convert electrical energy from thermal energy to show its potential as a renewable energy source for residential and commercial application. The study, whose results are presented in this manuscript, was conducted in the city of Monterrey, located in the northeast of Mexico. The energy source was tested and analyzed utilizing a set of statistical metrics and further comparison against experimental test results. The Distrito Tec area in Monterrey city is an academic complex and it was chosen for this study, which consisted of the indirect measurement of the average annual heat energy stored within the buildings' cement structure. The aim was to obtain the annual accumulated electrical power in Wh per year that Peltier modules could provide in Distrito Tec, which is located in a city with solar irradiation levels above the world average. The proposal in this paper could encourage further investigation regarding this energy that is currently waste heat. More specifically, the results of this research highlight the importance of thermoelectric modules and seek to motivate research to improve their properties and make them more efficient and more viable as well. Thermoelectric modules have the potential to be part of the solution to sustainable development as presented in the United Nations SDG-7—ensure access to affordable, reliable, sustainable and modern energy for all. [ABSTRACT FROM AUTHOR]

It is essential to protect control, regulation and data storage units used in automated robotic manufacturing from the consequences of harmful electrical grid harmonics. In this paper, the effectiveness of active/passive harmonic filters built into LED lamps, test benches, and industrial robots was investigated (in the latter two cases, light and heavy load states were applied). Based on network analysis, it was found that the built-in passive harmonic filters of the luminaries were ineffective because the THD of the current was approximately two or three times the permissible value according to the IEEE 519-2022 standard. It was proved that the built-in active harmonic filter of the test bench at a heavy load worked properly, but at a light load it was not effective, while the magnitude of harmonic distortion of the industrial robot exceeded the allowed level (three times the limit at a light load, seven times the limit at a heavy load). Further measurements were also performed at three locations: an engineering room, a gearbox house machine tool, and an office room (where there were no built-in filters). The results proved that in each case, there was a significant exceedance of the limit value. Therefore, protection against harmonics needs to be installed, and then the measurements must be repeated. [ABSTRACT FROM AUTHOR]

The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, the skin effect occurs, and the current carrying capacity of cables is reduced. This results in the increase in and uneven distribution of the temperature inside the conductor. This paper presents a comparison of the temperature distribution inside a power cable for an ideal 50 Hz sine wave and highly distorted current (T H D I = 41 %) . The calculated active power losses for the IEC 60287-1-1:2006+A1:2014 standard and the method described in the literature were used as a basis for further calculations. The obtained results revealed the problem of the uneven distribution of the conductor temperature. Considering the skin effect, increasing the temperature in the outer layers leads to severe damage and faster insulation aging. The abovementioned phenomenon is a decrease in the permissible load capacity of the conductor. The table given in the IEC 60364-5-52 standard summarizes the percentage contribution of the third harmonic to the current waveform. For percentages between 15% and 33%, the current carrying capacity is reduced by up to 86% of the full-load current rating. In addition, consideration of thermal conditions forces the use of cables with larger cross-sections. This leads to their non-optimal use and makes the investment more expensive from an economic point of view. [ABSTRACT FROM AUTHOR]

The widespread use of static converters for controlling electrical machines and the concern for electrical power quality in industrial environments provide an opportunity for utilizing these devices to enhance the power quality. In this context, this work presents a back-to-back converter model for driving induction machines. The converter is designed to correct the power factor of the point common coupling (PCC), compensate for harmonic currents (acting as an active filter), and withstand voltage sags. The necessary control system models were developed, and an alternative implementation for these functions in the converter was proposed. The results demonstrate the technical feasibility of this solution, as the converter operated within its nominal limits by compensating for harmonics and reactive power. Moreover, the equipment showed resilience to severe voltage sags. The contribution of this paper focuses on the multifunctionality of the frequency converter for driving induction machines. It emphasizes the advantage of the inverter in improving power quality in industrial environments through reactive power compensation and harmonic current compensation, thus functioning as an active power filter. Additionally, it is worth highlighting its ability to handle voltage dips. In this regard, this paper contributes by providing an operational strategy for driving the induction machine during such transients. [ABSTRACT FROM AUTHOR]

With the higher penetration of intermittent renewable energy sources in the electric power grid, more flexibility is needed to cope with challenges related to stability and reliability. Consumers can be part of the solution through demand response, for example, by investing in residential batteries that can charge and discharge based on price signals (implicit flexibility) or externally controlled based on grid-related needs (explicit flexibility). In this study, we investigate the feasibility of deploying residential batteries through a case study consisting of 20 households located in south-eastern Norway. The potential annual savings from implicit flexibility are optimized based on the retail electricity price, a power-based tariff, and potential revenues by selling electricity to the grid. Real historical price and consumption data with hourly resolutions from the entire year of 2022 are used as input for the optimization, yielding a theoretical profit potential. Based on this, profitability analyses are performed. The results show that the battery investments will not reach an economic break-even point during their lifetime under today's electricity price conditions. However, future developments in profit increase from implicit flexibility, substantial investment support, or additional revenues from emerging flexibility markets could make the investment economically attractive for a regular consumer. [ABSTRACT FROM AUTHOR]

The paper addresses rare issue in cable ampacity calculations, namely the presence of discontinuities along the routes. One which occurs in almost all cable installations is the presence of joints. In a standard cable rating analysis, the joints are ignored, mostly because of difficulties in building analytical models that represent the heat transfer phenomena within them. However, they can be a limiting part of the cable rating and, therefore, there is a need to model them correctly. This paper introduces an analytical algorithm for cable rating calculations in the presence of discontinuities with an emphasis on cable joints. New developments are illustrated by several numerical examples. [ABSTRACT FROM AUTHOR]

The growing demand for high-power DC fast-charging (DCFC) stations for electric vehicles (EVs) is expected to lead to increased peak power demand and a reduction in grid power quality. To maximize the economic benefits and station utilization under practical constraints set by regulatory authorities, utilities and DCFC station operators, this study explores and provides methods for connecting DCFC stations to the grid, employing low-power interconnection rules and distributed energy resources (DERs). The system uses automotive second-life batteries (SLBs) and photovoltaic (PV) systems as energy buffer and local energy resources to support EV charging and improve the station techno-economic feasibility through load shifting and charge sustaining. The optimal sizing of the DERs and the selection of the grid interconnection topology is achieved by means of a design space exploration (DSE) and exhaustive search approach to maximize the economic benefits of the charging station and to mitigate high-power demand to the grid. Without losing generality, this study considers a 150 kW DCFC station with a range of DER sizes, grid interconnection specifications and related electricity tariffs of American Electric Power (AEP) Ohio and the Public Utility Commission of Ohio (PUCO). Various realistic scenarios and strategies are defined to account for the interconnection requirements of the grid to the DCFC with DERs. The system's techno-economic performance over a ten-year period for different scenarios is analyzed and compared using a multitude of metrics. The results of the analysis show that the the integration of DERs in DCFC stations has a positive impact on the economic value of the investment when compared to traditional installations. [ABSTRACT FROM AUTHOR]

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller's effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources. [ABSTRACT FROM AUTHOR]

Ecofuels and their feedstock come in three main product classes: electrofuels (e-Fuels), biofuels, and non-biowaste-derived fuels. Ecofuels originate from non-fossil sources, derived from circular raw materials such as non-food organic waste, renewable hydrogen, and captured CO2 through a rapid process of carbon fixation. Proposed regulation drafts under discussion indicate that new fuels would need to reach a substantial degree of climate neutrality. The manufacture of all ecofuels, however, requires energy input to accomplish the conversion of the initial feedstock; their climate neutrality claims stem from the use of renewable electric energy and/or biomasses in the production process, but fossil fuels are still the main primary sources of global (and the EU's) electric power, and most biofuels consumed in the EU transport mix are still crop-based, with potential conflicts with food and land use. Furthermore, entirely neglecting GHG emissions from renewable energy generation is scientifically debatable, as the impact of the energy (and the related GHG emissions) embedded in the materials used to build renewable energy facilities is small, but not nil. The paper reports ecofuel trends according to the above-mentioned originating technologies and discusses the issues related to their development. [ABSTRACT FROM AUTHOR]

Automatic distribution master stations (ADMSs) are software platforms that can be used to monitor energy supply and consumption of power demand-side resources as well as to guarantee grid security. They play a vital role in maintaining the optimal performance and stability of electrical power systems. However, the stability of ADMSs is usually determined by the performance of the information interaction, which includes various challenges and complexities. Therefore, an efficient multiple-indicator filtering-based information interaction evaluation method for the ADMS is proposed in this paper. The proposed method first utilizes the principal component analysis (PCA) to filter the indicators of the ADMS. Then, the data envelopment method and the analytic network process (ANP) are employed to remove the invalid indicators and to determine the indicator weights. In this regard, the secondary screening of the indicators is completed, the effective indicators are obtained, and the accuracy of the evaluation system is improved. Results of the simulation show that the proposed method works well when evaluating information interaction performance, and it offers satisfactory performance evaluation of ADMSs. [ABSTRACT FROM AUTHOR]

Hydraulic turbines have become indispensable for harnessing renewable energy sources, particularly in-pipe hydraulic turbine technology, which leverages excess energy within pipeline systems like drinking water distribution pipes to produce electrical power. Among these turbines, the propeller-type axial turbine with circular blades stands out for its efficiency. However, there is a notable lack of literature on fluid dynamics and structural behavior under various operational conditions. This study introduces a comprehensive methodology to numerically investigate the hydraulic and structural responses of turbines designed for in-pipe installation. The methodology encompasses the design of circular blades, followed by parametric studies on fluid dynamics and structural analysis. The circular blade's performance was evaluated across different materials, incorporating static, modal, and harmonic response analyses. Results showed that the circular blade achieved a peak hydraulic efficiency of 75.5% at a flow rate of 10 l/s, generating 1.86 m of head pressure drop and 138 W of mechanical power. Structurally, it demonstrated a safety factor exceeding 1 across the entire hydraulic range without encountering resonance or fatigue issues. This research and its methodology significantly contribute to advancing the understanding of designing and assessing the fluid dynamic behavior and structural integrity of circular blades in axial propeller-type turbines for in-pipe installations, serving as a valuable resource for future studies in similar domains. [ABSTRACT FROM AUTHOR]

This study primarily investigates the adaptability and performance of hydraulic–electric regenerative dampers for high-speed trains by substituting conventional primary dampers with hydraulic–electric regenerative dampers. The primary objectives are to develop a detailed model of primary suspension regenerative damper (PSRD) energy conversion that incorporates factors such as oil pressure loss, motor efficiency, and overall system efficiency, and to perform a comprehensive comparative analysis of vibration responses, wheel wear, comfort indices, and power generation using an integrated MATLAB and SIMPACK co-simulation platform. The results reveal that at an operational speed of 350 km/h, the dynamic responses of the carbody, bogie, wheelset, and dampers equipped with the proposed PSRD systems closely align with those of conventional primary vertical damper systems. The detailed PSRDs' hydraulic–mechanical–electrical model effectively captures the subtleties of oil pressure fluctuations and their impacts. The wear distribution and magnitude across the vehicle remain consistent during acceleration, constant, and deceleration speeds, ensuring uniform wear characteristics. Under real-world railway operational conditions, the ride comfort metrics of vehicles fitted with regenerative dampers are comparable to those with conventional primary vertical dampers. Furthermore, each regenerative damper can generate up to 21.72 W of electrical power, achieving a generation efficiency of 45.28%. Finally, a test rig was designed and fabricated to validate the primary suspension regenerative damper (PSRD) model, showing good agreement between predicted and actual damping force and power regeneration, with results indicating a peak damping force of 12.5 kN and approximately 230 W of regenerated power. This research provides a theoretical foundation and experimental validation for implementing power regeneration mechanisms in railway transportation, demonstrating that the hydraulic–mechanical–electrical PSRD model can fulfil the performance criteria of conventional dampers while offering substantial energy harvesting capabilities. This advancement not only enhances energy efficiency but also contributes to the sustainable development of high-speed rail systems. [ABSTRACT FROM AUTHOR]

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to forecast electrical demand for the Chilean Electrical Power System considering a national, regional, district and bus spatial disaggregation. The methodology developed was based on different kinds of econometric models and end-use models to represent the massification of low carbon emission technologies such as electromobility, electric heating, electric water heating, and distributed generation. In addition, the methodology developed allows for the projection of the electric demand considering different kinds of clients as regulated and non-regulated clients, and different economic sectors. The model was applied to forecast the long-term electricity demand in Chile for the period 2022–2042 for 207 districts and 474 buses. The results include projections under the base case and low carbon scenarios, highlighting the significant influence of new technologies on future demand. [ABSTRACT FROM AUTHOR]

This paper proposes a new technique for a single-direction solar tracker. The proposed design is based on a sun sensor system that controls the position of the solar panel. The sun sensors of the proposed design contain four photodiodes that are placed on the solar panel in specific angles and directions. The proposed system has several advantages such as the simplicity of implementing the system. This system combines the real-time tracking of sunlight and the low cost of applying a single-direction tracker. The prototyping experiment and Simulink MATLAB were applied to show the advantages of applying a single-direction tracker by following the angle of sunlight during the day. Real-time sun position and irradiation data were applied. The experimental results show that the proposed single-axis sun sensor PV tracker system generates around 20 more electric power than a fixed-structure PV system. [ABSTRACT FROM AUTHOR]

Early detection of threats to electrical energy distribution systems helps professionals make decisions and mitigate interruptions in supply and improper activation of the protection system. Biologically inspired methods, e.g., artificial neural networks, genetic algorithms, and ant colonies, solve optimization problems and facilitate pattern recognition and decision-making. The present work presents a tool for detecting and classifying voltage disturbances based on the negative selection algorithm, which identifies and eliminates self-reactive cells, associated with multiresolution analysis, which analyzes the signal at different scales of detail, allowing a more complete understanding and detailed description of the phenomenon in question. The negative wavelet selection algorithm demonstrates robustness to detect and classify disturbances. [ABSTRACT FROM AUTHOR]

The broad acceptance of sustainable and renewable energy sources as a means of integrating them into electrical power networks is essential to promote sustainable development. Microgrids using direct currents (DCs) are becoming more and more popular because of their great energy efficiency and straightforward design. In this work, we discuss the control of a PV-based renewable energy system and a battery- and supercapacitor-based energy storage system in a DC microgrid. We describe a hierarchical control approach based on sliding-mode controllers and the Lyapunov stability theory. To balance the load and generation, a fuzzy logic-based energy management system has been created. Using a neural network, maximum power defects for the PV system were determined. The global asymptotic stability of the framework has been verified using Lyapunov stability analysis. In order to simulate the proposed DC microgrid and controllers, MATLAB/SimulinkR (2019a) was utilized. The outcomes show that the system operates effectively with changing production and consumption. [ABSTRACT FROM AUTHOR]

This paper reviews alarm processing methods in electrical power systems, focusing on evolving strategies beyond traditional fault analysis to accommodate modern grid complexities. Historically, alarm processing has predominantly aimed at fault analysis, increasingly merging with technological advances in communication and computing. However, it still needs to fully meet the challenges posed by the dynamic characteristics of modern power systems. This review points out certain inadequacies in current practices, notably their limited adaptation to new grid conditions. The authors propose a novel generation of alarm processing methodologies designed for future grids, emphasizing managing rare events and enhancing operator decision-making through advanced anomaly detection and explainable artificial intelligence. This synthesis presents a prospective direction for future research and applications in alarm processing, advocating for methodologies better suited to supporting system operators amidst technological advancements. [ABSTRACT FROM AUTHOR]

This study investigates the crucial role of Carbon Capture and Storage (CCS) technology in mitigating CO2 emissions from Poland's power systems, which is essential not only for meeting climate targets but also for maintaining energy security in the country. Acknowledging natural gas as a transitional fuel, the focus is on evaluating the decarbonization potential of the natural gas combined cycle (NGCC) power plant. The NGCC with and without an amine-based carbon capture unit was modeled using IPSEpro (SimTech, version 7.0). It was found that the annual CO2 emission from 435.68 MWe (net) NGCC can be reduced from 1,365,501 tons (357.8 kgCO2/MWh) to 136,556 tons (42.9 kgCO2/MWh). On the other hand, the CCS reduced the net electric power of the NGCC from 435.68 MW to 363.47 MW and the net energy efficiency from 55.60% to 46.39%. Nonetheless, these results demonstrate the potential of using the amine-based CO2 capture technology in NGCC systems. This is especially important in the context of the decarbonization of the Polish power system. [ABSTRACT FROM AUTHOR]

The coupling between modern electric power physical and cyber systems is deepening. An increasing number of users are gradually participating in power operation and control, engaging in bidirectional interactions with the grid. The evolving new power system is transforming into a highly intelligent socio–cyber–physical system, featuring increasingly intricate and expansive architectures. Demands for stable system operation are becoming more specific and rigorous. The new power system confronts significant challenges in areas like planning, dispatching, and operational maintenance. Hence, this paper aims to comprehensively explore potential synergies among various power system components from multiple viewpoints. It analyzes numerous core elements and key technologies to fully unlock the efficiency of this coupling. Our objective is to establish a solid theoretical foundation and practical strategies for the precise implementation of integrated planning and operation dispatching of source–grid–load–storage systems. Based on this, the paper first delves into the theoretical concepts of source, grid, load, and storage, comprehensively exploring new developments and emerging changes in each domain within the new power system context. Secondly, it summarizes pivotal technologies such as data acquisition, collaborative planning, and security measures, while presenting reasonable prospects for their future advancement. Finally, the paper extensively discusses the immense value and potential applications of the integrated planning and operation dispatching concept in source–grid–load–storage systems. This includes its assistance in regards to large-scale engineering projects such as extreme disaster management, facilitating green energy development in desertification regions, and promoting the construction of zero-carbon parks. [ABSTRACT FROM AUTHOR]

Hybrid PVT solar systems offer an innovative approach that allows solar energy to be used to simultaneously generate thermal and electrical energy. It is still a challenge to develop an energy-efficient hybrid PVT system. The aim of this work is to develop a mathematical model, investigate the system's performance based on parameters, include sensitivity analysis in the upper layer mainly photovoltaic part, and provide an efficient and innovative system. Performance analysis of the hybrid system is obtained by establishing a mathematical model and efficiency analysis. The electrical model and thermal model of the hybrid system is also obtained by appropriate and complete mathematical modeling. It establishes a good connection of the system in the context of electrical analysis and power generation. The parameters variation impact and sensitivity analysis of the most important parameters, namely, irradiance, ambient temperature, panel temperature, wind speed, and humidity in the PV panel section, are also obtained using a MATLAB model. The results show the effective increase or decrease in the electrical power and sensitiveness in the output of the system due to this modification. Related MPP values as a result of these parameters variation and their impact on the overall output of the hybrid PVT system are also analyzed. [ABSTRACT FROM AUTHOR]

The research work explores the impact of temperature on Silicon photovoltaic (PV) panels, considering Nigeria as a case study. It is found that high solar radiation in Nigeria increases the surface temperature of PV panels above 25 °C of the optimal operating temperature. The redundant energy gain from solar irradiance creates heat at the rear of solar panels and reduces their efficiency. Cooling mechanisms are therefore needed to increase efficiency. In this study, we demonstrated a unique hybrid system design employing a heat exchanger at the back of the panel, with water circulated through the back of the PV panel to cool the system. The system was simulated using TRNSYS at three locations in Nigeria—Maiduguri, Makurdi, and Port Harcourt. The results of the peak annual electrical power output in Maiduguri give a power yield of 1907 kWh/kWp, which is the highest, due to a high solar radiation average of 727 W/m2 across the year. For Makurdi, the peak annual electrical power output is 1542 kWh/kWp, while for Port Harcourt the peak power output is 1355 kWh/kWp. It was observed that the surface temperature of Polycrystalline Si-PV was decreased from 49.25 °C to 38.38 °C. The electrical power was increased from 1526.83 W to 1566.82 W in a day, and efficiency increased from 13.99% to 15.01%. [ABSTRACT FROM AUTHOR]

Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade. [ABSTRACT FROM AUTHOR]

In the increasingly complex and dynamic electrical power system, forecasting harmonics is key to developing and ensuring a clean power supply. The traditional methods have achieved some degree of success. However, they often fail to forecast complex and dynamic harmonics, highlighting the serious need to improve the forecasting performance. Precise forecasting of electrical power system harmonics is challenging and demanding, owing to the increased frequency with harmonic noise. The occurrence of harmonics is stochastic in nature; it has taken a long time for the development of dependable and efficient models. Several machine learning and statistical methods have produced positive results with minimal errors. To improve the prognostic accuracy of the power supply system, this study proposes an organic hybrid combination of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) with the attention mechanism (AM) method (CNN-BiLSTM-AM) to forecast load harmonics. CNN models intricate non-linear systems with multi-dimensionality aspects. LSTM performs better when dealing with exploding gradients in time series data. Bi-LSTM has two LSTM layers: one layer processes data in the onward direction and the other in the regressive direction. Bi-LSTM uses both preceding and subsequent data, and as a result, it has better performance compared to RNN and LSTM. AM's purpose is to make desired features outstanding. The CNN-BiLSTM-AM method performed better than the other five methods, with a prediction accuracy of 92.366% and a root mean square error (RMSE) of 0.000000222. [ABSTRACT FROM AUTHOR]

System health monitoring (SHM) of a ball screw laboratory system using an embedded real-time platform based on Field-Programmable Gate Array (FPGA) technology was developed. The ball screw condition assessment algorithms based on machine learning approaches implemented on multiple platforms were compared and evaluated. Studies on electric power consumption during the processing of the proposed structure of a neural network, implementing SHM, were carried out for three hardware platforms: computer, Raspberry Pi 4B, and Kria KV260. It was found that the average electrical power consumed during calculations is the lowest for the Kria platform using the FPGA system. However, the best ratio of the average power consumption to the accuracy of the neural network was obtained for the Raspberry Pi 4B. The concept of an efficient and energy-saving hardware platform that enables monitoring and analysis of the operation of the selected dynamic system was proposed. It allows for easy integration of many software environments (e.g., MATLAB and Python) with the System-on-a-Chip (SoC) platform containing an FPGA and a CPU. [ABSTRACT FROM AUTHOR]

In recent times, renewable energy sources have gained considerable vitality due to their inexhaustible resources and the detrimental effects of fossil fuels, such as the impact of greenhouse gases on the planet. This article aims to be a supportive tool for the development of research in the field of artificial intelligence (AI), as it presents a solution for predicting photovoltaic energy production. The basis of the AI models is provided from two data sets, one for generated electrical power and another for meteorological data, related to the year 2017, which are freely available on the Energias de Portugal (EDP) Open Project website. The implemented AI models rely on long short-term memory (LSTM) neural networks, providing a forecast value for electrical energy with a 60-min horizon based on meteorological variables. The performance of the models is evaluated using the performance indicators MAE, RMSE, and R2, for which favorable results were obtained, with particular emphasis on forecasts for the spring and summer seasons. [ABSTRACT FROM AUTHOR]

This paper analyzes the behavior of an electrical power system when N-1 contingencies occur in the transmission stage, which can be produced by incorrect operation of the protection relays, phenomena of natural origin, or increased loadability, which affect the operation and reliability of the electrical system. The operation output of a transmission line results in the variation of the nominal values of the electrical parameters involved because they disturb the stability of the generation, transmission systems, and the supply of electrical energy to the loads, such as voltages and angles of the nodes and the active and reactive power of the system. The proposed methodology was based on analyzing the different electrical parameters of the power system, quantifying the contingency index in a state of regular operation, and comparing it to operation in contingency N-1, with which the most severe contingency was determined and, therefore, achieved; identifying contingencies that can cause system collapses; improving the contingency index from 23.08555 to 22.9276624 for the L16–19 contingency and to 22.9795235 for the L21–22 contingency, which are the most severe contingencies determined with the proposed methodology. To test the proposed methodology, the IEEE 39 bus-bar test system was considered, and the elements that should be implemented to avoid the vulnerability of the power system to N-1 contingencies were determined. [ABSTRACT FROM AUTHOR]

This paper introduces a novel hybrid filter topology that combines passive and active components to enhance harmonic filtering and resonance damping in electrical power systems. The design integrates a three-phase two-level voltage-source converter with a double-tuned passive filter in parallel, significantly reducing the power rating and operational costs while maintaining good harmonic filtering performance and reactive current compensation. Double-tuned passive filters, compared to single-tuned ones, offer improved harmonic attenuation at multiple frequencies, enhancing overall system efficiency. Moreover, when used with the proposed hybrid filter topology, the double-tuned version allows for even lower dimensions of the active part, thereby further reducing system cost. A state-feedback controller is designed to enhance the performance of the hybrid filter, proving particularly effective in environments with complex impedance conditions. This paper also examines the impact of variations in passive component parameters, demonstrating the design's robustness against potential deviations expected over the operational lifespan. The results indicate that the hybrid filter effectively mitigates harmonics and maintains operational stability under various transient conditions, as confirmed by analytical and simulation studies on a real industrial network model. These findings underline the hybrid filter's potential to significantly improve power quality in modern electrical networks. [ABSTRACT FROM AUTHOR]

Since the creation of the first parallel electrical power systems around the world, the rotor angle stability of synchronously operating generators has been one of the most crucial and challenging problems. In modern electricity networks, including in Kazakhstan, where renewable energy technologies are rapidly emerging, the issue of stability takes on even greater importance due to the technical shortcomings of inverter-based generation. In this framework, an analysis of rotor angle transient stability was carried out when replacing existing synchronous generators with doubly fed induction generators under a certain pre-emergency mode. A critical proportion of active power generation by DFIG units was identified at which transient stability can still be maintained due to the sufficient stored kinetic energy of the synchronous machines remaining in operation. In addition, two simple solutions were investigated to improve transient stability, such as an increased time of the automatic reclosure operation and the use of special load-shedding automation. Finally, this paper proposes a novel type of flexible smart-grid automation that is capable of monitoring the main operating parameters and issuing control actions depending on inertia, the availability of wind resources, and the load of the system as a whole. For this analysis, a real power system from the Mangystau region in Kazakhstan was considered, and the PowerWorld software 23 was used. [ABSTRACT FROM AUTHOR]

Human footsteps are a sustainable energy source that is derived from kinetic energy. As a result, in this study, piezoelectric sensors placed beneath floor tiles were excited by human footsteps to provide practical electrical energy. A simple rectifying circuit with a filter was used to capture electrical power. The floor tile is 455 mm in length and 405 mm in width. Two light-emitted diodes were lit up as the actual load by utilising electrical energy obtained from the kinetic energy generated by human footsteps. The greatest attainable power that could be extracted from the suggested floor tile was 249.6 milliwatts, with an approximate cost of $10.2. [ABSTRACT FROM AUTHOR]

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation's effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem's globally optimal solution within ten seconds. [ABSTRACT FROM AUTHOR]

The growing integration of distributed energy resources underscores the critical importance of having precise insights into the dynamics of an electrical power system (EPS). Consequently, an estimator must align with the EPS dynamics to enhance the overall reliability, safety, and system stability. This alignment ensures that operators can make informed decisions during system operations. An initial step in gaining insight into the system's state involves examining its state vector, which is represented by voltage phasors. These results are derived through the application of a distributed state-estimation process in large-scale systems. This study delved into the effectiveness of Bayesian filters, with a particular emphasis on the extended Kalman filter (EKF) algorithm in the context of distributed state estimation. To analyze the outcomes, the nodal partitioning process was incorporated within the distributed state-estimation framework. The synergy between the EKF algorithm and the partitioning method was evaluated using the IEEE118 test system. [ABSTRACT FROM AUTHOR]

With the expansion of the scale of electric power, high-quality electrical energy remains a crucial aspect of power system management and operation. The generation of reactive power is the primary cause of the decline in electrical energy quality. Therefore, optimization of reactive power in the power system becomes particularly important. The primary objective of this article is to create a multi-objective reactive power optimization (MORPO) model for distribution networks. The model aims to minimize reactive power loss, reduce the overall compensation required for reactive power devices, and minimize the total sum of node voltage deviations. To tackle the MORPO problems for distribution networks, the improved sparrow search algorithm–particle swarm optimization (ISSA-PSO) algorithm is proposed. Specifically, two improvements are proposed in this paper. The first is to introduce a chaotic mapping mechanism to enhance the diversity of the population during initialization. The second is to introduce a three-stage differential evolution mechanism to improve the global exploration capability of the algorithm. The proposed algorithm is tested on the IEEE 33-node system and the practical 22-node system. The results indicate a reduction of 32.71% in network losses for the IEEE 33-node system after optimization, and the average voltage of the circuit increases from 0.9485 p.u. to 0.9748 p.u. At the same time, optimization results in a reduction of 44.07% in network losses for the practical 22-node system, and the average voltage of the circuit increases from 0.9838 p.u. to 0.9921 p.u. Therefore, the proposed method exhibits better performance for reducing network losses and enhancing voltage levels. [ABSTRACT FROM AUTHOR]

The maintenance of an uninterrupted electricity supply to meet demand is of paramount importance for maintaining the stable operation of an electrical power system. Machine learning and deep learning play a crucial role in maintaining that stable operation. These algorithms have the ability to acquire knowledge from past data, enabling them to efficiently identify and forecast potential scenarios of instability in the future. This work presents a hybrid convolutional long short-term memory (ConvLSTM) technique for training and predicting nodal voltage stability in an IEEE 14-bus microgrid. Analysis of the findings shows that the suggested ConvLSTM model exhibits the highest level of precision, reaching a value of 97.65%. Furthermore, the ConvLSTM model has been shown to perform better compared to alternative machine learning and deep learning models such as convolutional neural networks, k-nearest neighbors, and support vector machine models, specifically in terms of accurately forecasting voltage stability. The IEEE 14-bus system tests indicate that the suggested method can quickly and accurately determine the stability status of the system. The comparative analysis obtained the results and further justified the efficiency and voltage stability of the proposed model. [ABSTRACT FROM AUTHOR]

Energy sources are crucial for the development and growth of economies and civilizations. Solar energy is an alternative energy to generate electrical power. The challenges of solar photovoltaic panels (PV) are the low output power and efficiency and the huge installation area beside PVs need a tracking system for better efficiency. The motivation of this paper is to design an innovative solar sphere system, which is a new concentrated photovoltaic technology that has better performance (efficiency and output power) than the normal conventional solar panel (PV) with a smaller installation area and without any tracking system. This design consists of an acrylic solar sphere entirely filled with cooking oil (sunflower or corn oil) that captures solar radiation and concentrates it on a focal point. The focal point is adjusted over a multi-junction cell that acts as a collector device (concentrator solar cell). This focused solar energy can generate a massive amount of power, which is used to produce more electricity than normal photovoltaic panels. The experiments were carried out in order to discover the best acrylic models or shape designs, which is the sphere, the best materials or media in the sphere, that is oil, the best sphere's size and volume, and that is larger, the best sphere thickness, which at first is lower, the best fluid oil type, which is cooking oil, and finally the best fluid amount or volume inside the sphere, and this is the entire volume. Then, these factors mentioned above are compared with normal photovoltaics (PV) that have the same section area as these shapes. The results revealed that these factors have significant effects on the output power value and efficiency. It has been demonstrated that our innovative concentrated solar sphere system can produce nearly four times the output power or electricity greater than that of a conventional solar panel PV with the same cross-sectional area. This specific sort of compression is crucial because it shows that less space is required to establish this system than it would to install conventional solar panels. The performance of the system per unit of the square area it occupies was compared to the latest generation of flat panel PV available at the market performance; hence, the installation space will be decreased by 40% to 60%. Our system has about twice as much efficiency as solar PV and does not require a tracking system and maintenance. Our technology also has the benefit of not being impacted by extreme temperatures, clouds, dust, and humidity. [ABSTRACT FROM AUTHOR]

When a medium–low-speed (MLS) maglev train is braking, part of its regenerative braking (RB) power consumption may cause a significant rise in the positive rail (PR) voltage. For RB energy re-utilization, an RB energy feedback system (RBEFS) is a promising application, but there is still no specific research in the field of MLS maglev trains. From this perspective, this article focuses on identifying the PR voltage rise behavior and investigating the application of an RBEFS on the over-voltage inhibition. Some development trends of the MLS maglev train, including the DC 3 kV traction grid system and the speed being raised to 160~200 km/h, are also considered in the analyzed scenarios. At first, a modeling scheme of a detailed vehicle–grid electrical power model with the RBEFS is established. On this basis, the PR voltage rise characteristics are analyzed with consideration of three pivotal influencing factors: RB power, PR impedance and supply voltage level. Subsequently, to stabilize the PR voltage fluctuations, the influence rules of the RBEFS on the voltage rise and the mutual transient voltage influences under the operating status switching for multiple vehicles running on the same power supply section are analyzed. [ABSTRACT FROM AUTHOR]

This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage. [ABSTRACT FROM AUTHOR]

There are two main beneficial characteristics that doubly salient permanent magnet (PM) electrical machines present for aircraft applications: armature windings and PMs excitation sources placed on the stator side (maintenance and thermal management), and having a clear-cut rotor without PMs or excitation windings (vulnerable at high speeds due to associated centripetal mechanical stresses). Within this framework, a doubly salient permanent magnet (DSPM) generator was conceived by optimizing the stator size and rotor structure to minimize the torque ripple and maximize the root-mean-square (RMS) voltage value per turn of each generator phase. Firstly, a comparison between the 2D and 3D finite element method (FEM) models is made considering the results of 3D finite element analysis (FEA) as our benchmark in order to understand the accuracy of the 2D results against our benchmark model, the 3D one. A multi-objective design strategy based on a 2D FEA is made, it is set to have characteristics closest to optimal for a Boeing 767 turbine, that is, the necessary electromotive force for a required power of 90 kW at 3000 rpm, feeding a simplified Boeing 767 electrical power distribution system. The results show that the machine could not deliver the required power at 3000 rpm since the 2D FEA demonstrates that the 2D model gives optimistic results when compared with the 3D FEM model. However, with a 3D FEA of the machine feeding the aircraft load, it was seen that the machine's efficiency is 92%, suggesting that this machine can be a plausible solution. [ABSTRACT FROM AUTHOR]

This document provides an overview of innovations in thermoelectric technology, with a focus on materials and applications. It discusses thermoelectric generators (TEGs), which convert thermal energy into electrical energy, and their versatility in various settings such as space, medical applications, and vehicles. The document also highlights advancements in thermoelectric materials, such as Cu2−xSe and PbTe0.7S0.3, which improve the efficiency of TEGs. The included research papers cover topics such as TEG design, durability under different conditions, and the development of nanostructured materials. The findings emphasize the need for further research and collaboration to enhance the efficiency and practicality of thermoelectric systems. [Extracted from the article]

As the operating speed of electric multiple units (EMUs) in high-speed railways increases, pantograph–catenary (PC) detachment arcing occurs frequently. The resulting vehicular-grounding electromagnetic transients are related to the dynamic characteristics of the arc length. During large detachment, the processes of arc extinction and arc reignition may occur, resulting in more severe train body (TB) over-voltages and adverse effects on some vehicular electronic devices. As an extension of the previous works, this paper aims to establish a suitable PC arc model to examine the TB transient voltages. To begin with, the arc length dynamic characteristics are reasonably analyzed to deduce the relationship between the detachment distance and the arc length via the chain arc model. Then, the dynamic characteristics of the arc length are introduced, and an arc modeling scheme is proposed to elaborate the vehicle-grid electric power model for EMUs encountering various arcing scenarios. Based on this, the transient over-voltages are analyzed, accounting for both the arc extinction and arc reignition, as well as the mutual influences of multiple detachments in a short time. The influential factors, including arc length characteristics, phase angle, excitation inductance, and grounding parameters, are also involved in the performed analyses. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency's (IEA's) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid's frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach. [ABSTRACT FROM AUTHOR]

Efficiency losses resulting from electrical mismatching in densely packed photovoltaic arrays present a significant challenge, particularly exacerbated in nonuniformly illuminated receivers and under varying temperatures. Serial configurations are particularly susceptible to radiation nonuniformities, while parallel systems are negatively affected by temperature variations. Various authors have recommended the incorporation of electrical voltage and current sources to mitigate these losses. This study explores different electrical connection configurations utilizing concentrated photovoltaic (CPV) cells and DC-DC electrical current converters. A self-adaptive microfluidic cell matrix cooling system is employed to mitigate thermal dispersion caused by the highly nonuniform illumination profile. The obtained results for each configuration are compared with the total electrical power produced by individual cells, operating under identical radiation and temperature conditions to those of the entire array. The results reveal a noteworthy increase in production across all studied configurations, with the parallel–series arrangement demonstrating the most promising practical utility. This configuration exhibited a remarkable 50.75% increase in power production compared with the standard series connection. [ABSTRACT FROM AUTHOR]

The growing demand for electricity, driven by factors such as the shift to carbon neutrality and economic growth, is a challenge shared by South Korea and Japan. South Korea, a peninsula nation, and Japan, an island country, which are both heavily dependent on foreign energy sources and have manufacturing-based industrial structures, are actively working to secure stable power supplies for their economic development. This article carries out a quantitative analysis of the roles of the South Korean and Japanese electric power sectors (EPSs) in their respective economies, seeking to identify differences and generate actionable insights for decision making and policy formulation. Utilizing the input–output (IO) technique with the latest available data, the analysis includes a demand-side model, a supply-side model, and a price-side model to examine various effects of the EPSs. The key findings reveal differences in the production-inducing, value-added creation, and job-creation effects between the two countries, highlighting operational disparities in their electricity sectors. Additionally, South Korea exhibits higher wage-inducing, supply shortage, and price-side effects than Japan, because of its public enterprise-oriented high-wage structure and a substantial manufacturing sector. These quantitative results provide valuable reference material for future government decisions and policy development in the EPS and emphasize the significant role and impact of the power sector in both countries. [ABSTRACT FROM AUTHOR]

The increasing interest in the use of renewable energy technologies is directing attention towards the potential contribution of marine energy technologies, especially ocean wave energy, to world energy demand. While open-sea demonstrations of full-scale devices have been carried out to validate several technologies, the focus now is shifting to optimising the components for efficiency and reliability. The efficiency of the electrical generator plays a crucial role in wave-to-wire numerical models for converting wave energy into usable electricity. It provides essential data that enables the industry to reduce technical risks and uncertainties. Wave-to-wire models typically simplify the generator's efficiency through assuming a single curve based on the load. This curve is usually provided by the machine manufacturers for the nominal rotational speed. However, the rotational speed varies in the case of air turbines used in OWC devices. Therefore, to accurately estimate decision variables derived from these models, a comprehensive efficiency map is necessary. This map should demonstrate the performance at different rotational speeds and loads, as it directly influences the estimation of key parameters. The main objective of the present work is to improve the generator behaviour of an OWC for different generator operation regimes. For this purpose, a numerical model of the generator's efficiency will be developed throughout the segregation of losses and validated experimentally. Finally, an optimal control law will be presented to maximise the electrical power output of the wave energy converter, considering the efficiency of both the generator and the turbine. [ABSTRACT FROM AUTHOR]

In the late 1960s, a handful of inspired researchers predicted the great potential of supercritical CO2 ("sCO2") cycles for the production of electricity and highlighted the prospects for dramatic reductions in component sizes and efficiency increases. Since then, considerable development programs have been deployed around the world to "tame" this new technology. Despite these efforts, in-depth engineering studies and extensive testing are still necessary today before viable designs can be released for large-scale industrial applications. This raises questions as to the reasons for this delay, this debate being rarely addressed in the current literature. This situation has motivated the present study. Trying to unravel such an intricate topic requires to understand the distinctive properties of supercritical CO2 and the particular requirements of closed, high-pressure power systems. This article aims then to provide a broad overview of sCO2 power cycles, highlighting their main advantages and limitations and reflecting the challenges associated with the industrialization of that technology which actually requires disruptive and innovative designs. [ABSTRACT FROM AUTHOR]