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21 pages, 1493 KiB

Open AccessArticle

An Assistive System for Thermal Power Plant Management

by Aleksa Stojic, Goran Kvascev and Zeljko Djurovic

Energies 2025, 18(11), 2977; https://doi.org/10.3390/en18112977 - 5 Jun 2025

Viewed by 193

Abstract

The estimation of available active power in coal-fired thermal power plant units involves considerable complexity and remains a critical task for plant operators. To avoid compromising system stability, operators often operate the thermal unit below its full capacity. To address this issue, the [...] Read more.

The estimation of available active power in coal-fired thermal power plant units involves considerable complexity and remains a critical task for plant operators. To avoid compromising system stability, operators often operate the thermal unit below its full capacity. To address this issue, the aim of this paper is to facilitate the process of estimating the maximum active electrical power by applying an assistive system based on ANFIS (Adaptive Neuro-Fuzzy Inference System), a method that combines the strengths of neural networks and fuzzy logic. Since the generated electric energy is directly linked to the amount of thermal energy produced, the analysis is focused on the boiler combustion process. It has been shown that the key factors in this process are the coal mills and their achievable capacity, as well as the calorific value of coal. Therefore, the proposed assistive system is based on the estimation of the available capacity of each active mill, which is then combined with the estimated calorific value of the coal to determine the achievable active electrical power of the unit. The conducted analysis and experiments confirm the validity of this approach. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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21 pages, 5910 KiB

Open AccessArticle

Applying Structure Exchange to Battery Charging to Enhance Light-Load Efficiency

by Kuo-Ing Hwu, Pei-Ching Tseng and Jenn-Jong Shieh

Energies 2025, 18(11), 2699; https://doi.org/10.3390/en18112699 - 23 May 2025

Viewed by 298

Abstract

A full-bridge DC–DC converter with structure exchange is proposed to simulate battery charging based on an electronic load. The full-bridge phase-shift converter (FBPSC) uses an external resonant inductor and phase-shift control on the primary side to realize zero voltage switching (ZVS) above medium [...] Read more.

A full-bridge DC–DC converter with structure exchange is proposed to simulate battery charging based on an electronic load. The full-bridge phase-shift converter (FBPSC) uses an external resonant inductor and phase-shift control on the primary side to realize zero voltage switching (ZVS) above medium load. However, the energy of the resonant inductor is not enough to carry away the energy of the parasitic capacitance on the switch at light load, leading to the inability of ZVS as well as the circulating current problem due to the long duration of the primary-side circulating current. Consequently, in order to conquer such problems mentioned above, the structure exchange, with only the control strategy changed from the phase-shift control to the two-transistor forward control, is presented to increase the light-load efficiency remarkably. Furthermore, the number of inductors is reduced by using the center-tap structure on the secondary side compared to the current-doubler structure. In addition, the synchronous rectifier on the secondary side is used to further improve the overall efficiency of the converter. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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13 pages, 846 KiB

Open AccessArticle

A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System

by Yun Yang, Zichao Meng, Guobing Wu, Zhanxin Yang and Ruipeng Guo

Energies 2025, 18(10), 2658; https://doi.org/10.3390/en18102658 - 21 May 2025

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Abstract

Probabilistic modeling of net load forecast errors is an important approach for reserve decision-making in power systems with a high penetration of renewable energy. However, existing probabilistic modeling methods face issues such as insufficient estimation accuracy in the small probability interval of the [...] Read more.

Probabilistic modeling of net load forecast errors is an important approach for reserve decision-making in power systems with a high penetration of renewable energy. However, existing probabilistic modeling methods face issues such as insufficient estimation accuracy in the small probability interval of the tails or increased complexity in probability decision-making problems. A probabilistic reserve decision-making method based on cumulative probability approximation is proposed. By using key points on the cumulative probability distribution curve of net load forecast error samples, this method enhances the fitting accuracy of the normal distribution model in the small probability interval of the tail, resulting in an optimal reserve outcome with the desired comprehensive expected profit. Using relevant renewable energy output and load data from actual transmission networks in Guangdong Province, China, the proposed method demonstrates good practical value. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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16 pages, 5681 KiB

Open AccessArticle

Reactive Power Compensation for Single-Phase AC Motors Using Integral Power Theory

by Grzegorz Kosobudzki, Daniel Dusza, Marek Pawel Ciurys and Aleksander Leicht

Energies 2025, 18(10), 2641; https://doi.org/10.3390/en18102641 - 20 May 2025

Viewed by 202

Abstract

The paper investigates an alternative approach to measuring and compensating reactive power in electric machines, particularly under non-sinusoidal voltage and current waveforms. Traditional power definitions, such as those introduced by Budeanu and Fryze, as well as the power triangle, are discussed alongside integral [...] Read more.

The paper investigates an alternative approach to measuring and compensating reactive power in electric machines, particularly under non-sinusoidal voltage and current waveforms. Traditional power definitions, such as those introduced by Budeanu and Fryze, as well as the power triangle, are discussed alongside integral definitions of reactive power, which account for waveform distortions. This approach is novel and has not been previously applied in the context of electric machines. A digital algorithm for reactive power calculation, based on the integral definition, is proposed. It requires minimal computational resources and is easy to implement. Experimental measurements conducted on a single-phase induction motor demonstrate the impact of capacitive compensation on current waveforms. The results confirm the validity of the adopted definition of reactive power. With full reactive power compensation, the RMS value of the current drawn by the motor is minimized, which is not always the case with the classical approach to improving the power factor. The findings highlight the importance of accurate reactive power measurement and compensation in enhancing the performance and energy efficiency of electrical machines. The proposed approach is applicable not only to single-phase motors but also more broadly in determining the reactive power drawn by electric machines and in measuring electric energy, particularly in the presence of distorted voltages and currents. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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26 pages, 3971 KiB

Open AccessArticle

Design of a Controller for Supercapacitor’s Bidirectional High-Gain Interleaved Converter

by Jessica C. A. Sousa, Thiago M. Soares, Jonathan M. Tabora and Hugo G. Lott

Energies 2025, 18(10), 2605; https://doi.org/10.3390/en18102605 - 17 May 2025

Viewed by 356

Abstract

This study focuses on the mathematical modeling, control design, and analysis of an interleaved bidirectional high-voltage-gain DC-DC converter for energy management in supercapacitors. The state of the art is reviewed, with an emphasis on research related to DC-DC converters and energy storage systems. [...] Read more.

This study focuses on the mathematical modeling, control design, and analysis of an interleaved bidirectional high-voltage-gain DC-DC converter for energy management in supercapacitors. The state of the art is reviewed, with an emphasis on research related to DC-DC converters and energy storage systems. The characteristics and modeling of the supercapacitors are thoroughly analyzed. The converter’s operation in both buck and boost modes is described, detailing its operating stages, design parameters, and component sizing. The modeling accounts for the dynamics of the converter in both operational modes. PI controllers and compensation techniques were implemented to ensure the desired performance and meet the design criteria. Simulations were conducted using PSIM software, version 2023.1, with a power flow of 1 kW, a 48 V DC bus (buck mode), and a 162 V supercapacitor module (boost mode), operating at 500 kHz. The performance of the controllers was evaluated during both the charging and discharging processes of the supercapacitor, analyzing the dynamic response and behavior in the continuous mode, even in the presence of system disturbances. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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31 pages, 997 KiB

Open AccessArticle

A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios

by Manuel Jaramillo, Diego Carrión, Filippos Perdikos and Luis Tipan

Energies 2025, 18(10), 2466; https://doi.org/10.3390/en18102466 - 11 May 2025

Viewed by 285

Abstract

This research presents a novel methodology based on data analysis for improving voltage stability in transmission systems. The proposal aims to determine a single distributed generator’s optimal location and sizing using the Fast Voltage Stability Index (FVSI) as the primary metric under [...] Read more.

This research presents a novel methodology based on data analysis for improving voltage stability in transmission systems. The proposal aims to determine a single distributed generator’s optimal location and sizing using the Fast Voltage Stability Index (FVSI) as the primary metric under

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contingency conditions. The developed strategy systematically identifies the most critical transmission lines close to instability through a frequency analysis of the FVSI in the base case and across multiple contingency scenarios. Subsequently, the weak buses associated with the most critical line are determined, on which critical load increases are simulated. The Distributed Generator (DG) sizing and location parameters are then optimized through a statistical analysis of the inflection point and the rate of change of the FVSI statistical parameters. The methodology is validated in three case studies: IEEE systems with 14, 30, and 118 buses, demonstrating its scalability and effectiveness. The results show significant reductions in FVSI values and notable improvements in voltage profiles under stress and contingency conditions. For example, in the 30-bus IEEE system, the average FVSI for all contingency scenarios was reduced by 26% after applying the optimal solution. At the same time, the voltage profiles even exceeded those of the base case. This strategy represents a significant contribution, as it is capable of improving the stability of the electrical power system in all

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contingency scenarios with overload at critical nodes. Using a single DG as a low-cost and highly effective corrective measure, the proposed approach outperforms conventional solutions through statistical analysis and a data-centric approach. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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17 pages, 6128 KiB

Open AccessArticle

Beam Shape Control System with Cylindrical Lens Optics for Optical Wireless Power Transmission

by Kenta Moriyama, Kaoru Asaba and Tomoyuki Miyamoto

Energies 2025, 18(9), 2310; https://doi.org/10.3390/en18092310 - 30 Apr 2025

Viewed by 287

Abstract

Due to its narrow divergence, optical wireless power transmission (OWPT) is promising for long-distance transmission systems. In OWPT systems, matching the beam shape with the solar cell geometry is crucial for both efficiency and safety. When the light is incident at an oblique [...] Read more.

Due to its narrow divergence, optical wireless power transmission (OWPT) is promising for long-distance transmission systems. In OWPT systems, matching the beam shape with the solar cell geometry is crucial for both efficiency and safety. When the light is incident at an oblique angle, the beam is distorted in an axial direction, which requires appropriate beam shape control. In this study, a cylindrical lens system was designed to ensure uniform and effective light beam irradiation, even under oblique incidence conditions. A numerical model of the optical system was constructed, and it was experimentally confirmed that the beam shape could be controlled within 5% error over a transmission range of 1 m. The optical system was integrated with solar cell detection for consistent target recognition and beam irradiation, and its functionality was experimentally validated. The results are useful for expanding the application and infrastructure design in OWPT. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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Review

Jump to: Research, Other

16 pages, 3490 KiB

Open AccessReview

GaN Power Transistors in Converter Design Techniques

by Piotr J. Chrzan and Pawel B. Derkacz

Energies 2025, 18(11), 2890; https://doi.org/10.3390/en18112890 - 30 May 2025

Viewed by 269

Abstract

The expected outstanding performance of GaN-based transistors in power applications, characterized by high switching frequency, efficiency, and compactness, requires that the design rules of converter layout optimization, filtering, and shielding need to be reexamined. Addressing the above topics, this paper reviews commercial GaN [...] Read more.

The expected outstanding performance of GaN-based transistors in power applications, characterized by high switching frequency, efficiency, and compactness, requires that the design rules of converter layout optimization, filtering, and shielding need to be reexamined. Addressing the above topics, this paper reviews commercial GaN power transistors and specifies their integration techniques, including printed circuit board (PCB) embedded solutions. Then, referring to the optimization results of a half-bridge inverter leg, design techniques are presented that reduce the harmful effect of inductive and capacitive internal converter couplings, thus mitigating the electromagnetic interference (EMI) conducted emissions. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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Other

Jump to: Research, Review

32 pages, 2390 KiB

Open AccessSystematic Review

A Bibliometric Assessment of AI, IoT, Blockchain, and Big Data in Renewable Energy-Oriented Power Systems

by Manuel Jaramillo, Diego Carrión, Jorge Muñoz and Luis Tipán

Energies 2025, 18(12), 3067; https://doi.org/10.3390/en18123067 - 10 Jun 2025

Abstract

This study presents a systematic bibliometric review of digital innovations in renewable energy-oriented power systems, with a focus on Blockchain, Artificial Intelligence (AI), the Internet of Things (IoT), and Data Analytics. The objective is to evaluate the research landscape, trends, and integration potential [...] Read more.

This study presents a systematic bibliometric review of digital innovations in renewable energy-oriented power systems, with a focus on Blockchain, Artificial Intelligence (AI), the Internet of Things (IoT), and Data Analytics. The objective is to evaluate the research landscape, trends, and integration potential of these technologies within sustainable energy infrastructures. Peer-reviewed journal articles published between 2020 and 2025 were retrieved from Scopus using a structured search strategy. A total of 23,074 records were initially identified and filtered according to inclusion criteria based on relevance, peer-review status, and citation impact. No risk of bias assessment was applicable due to the nature of the study. The analysis employed bibliometric and keyword clustering techniques using VOSviewer and MATLAB to identify publication trends, citation patterns, and technology-specific application areas. AI emerged as the most studied domain, peaking with 1209 papers and 15,667 citations in 2024. IoT and Data Analytics followed in relevance, contributing to real-time system optimization and monitoring. Blockchain, while less frequent, is gaining traction in secure decentralized energy markets. Limitations include possible indexing delays affecting 2025 trends and the exclusion of gray literature. This study offers actionable insights for researchers and policymakers by identifying converging research fronts and recommending areas for regulatory, infrastructural, and collaborative focus. This review was not pre-registered. Funding was provided by the Universidad Politécnica Salesiana under project code 005-01-2025-02-07. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)

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