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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: 30 October 2025 | Viewed by 5593

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Special Issue Editors

Dr. Stelios Ioannou

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Guest Editor

Electrical and Electronic Engineering, School of Sciences, University of Central Lancashire, Cyprus Campus, 7080 Larnaka, Cyprus
Interests: energy and power systems; power quality; energy management; controls and optimization

Prof. Dr. Mohamed Darwish

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Guest Editor

Power Electronics and Systems, Department of Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, London, UK
Interests: power active filtering techniques; UPS systems; electric vehicles; power quality issues
Special Issues, Collections and Topics in MDPI journals

Dr. Nicholas G. Christofides

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Guest Editor

Department of Electrical Engineering, Computer Engineering and Informatics, Frederick University, Nicosia 1036, Cyprus
Interests: power systems; distributed generation; power quality; energy efficiency; wiring regulations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Traditionally, only loads are variable, and an electric grid’s stability is controlled by centralized generators. However, growing environmental concerns have led to the increased integration of Renewable Energy Sources (RESs) such as photovoltaic, wave, and wind technologies. These are considered Variable Energy Sources (VESs) because their generation is inherently influenced by weather conditions, which introduces new complexities in grid management. The problem has been further exacerbated by the worldwide increase in energy demand, putting additional strain on the grid. To address this, Demand Side Management (DSM) techniques, including load forecasting, peak shaving, and load shifting, have played a crucial role in maintaining grid stability without requiring additional generation capacity.

Today, the evolution of the smart grid, which is characterized by its intelligent, responsive, dynamic, flexible, and adaptive nature, is seen as the largest and most complex man-made system. This advanced grid enables better integration of renewable energy and more efficient energy distribution. However, as with any continuously evolving system, there are ongoing challenges and opportunities for improvement. Key challenges include, but are not limited to, the following:

Simultaneously managing technical and economic performance;
Addressing multiple time-scale dynamics within the grid;
Effectively integrating active demand-side resources;
Incorporating Multi-Agent Systems (MASs) and decentralized decision-making;
Managing the active power grid periphery, which requires careful coordination of grid edges where distributed energy resources (DERs) are most prevalent;
Advancements in Power Electronics Converters, Modulation Processes and Mathematical Models;
Energy Storage Systems;
Efficiency Investigation of a Grid Connected Systems with Power Smoothing;
Efficiency Investigation of Protection and Correction Systems;
Load Shedding Methods and Schemes for Blackout Prevention and Islanding Distribution Network Operation in Active Distribution Networks.

Dr. Stelios Ioannou
Prof. Dr. Mohamed Darwish
Dr. Nicholas Christofides
Guest Editors

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Keywords

active power grid periphery
multi-agent systems (MASs)
smart grid
power systems
renewable energy

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Published Papers (6 papers)

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Research

15 pages, 3794 KiB

Open AccessArticle

Sizing the Split DC Link Capacitance in Three-Phase Three-Level Bidirectional AC-DC Converters Operating with Arbitrary Power Factor Under Zero-Sequence Injection Restriction

by Yarden Siton, Vladimir Yuhimenko, Sergei Kolesnik, Asher Yahalom, Moshe Sitbon and Alon Kuperman

Appl. Sci. 2025, 15(6), 3159; https://doi.org/10.3390/app15063159 - 14 Mar 2025

Viewed by 680

Abstract

The paper presents a methodology for determining the minimum split DC link capacitance for a family of three-phase, three-level grid-connected bidirectional AC-DC converters operating under arbitrary power factor under restriction of DC-only zero-sequence injection. The approach is based on the recently revealed generalized behavior of split DC link voltages in the above-mentioned converters family while distinguishing between leading and lagging power factors in order to highlight different impacts on split DC link capacitor voltages pulsating components. The minimum capacitance value is derived from the boundary condition, ensuring the mains voltage remains below or equal to the capacitor voltage at all times. It is revealed that operation with the lowest expected leading power factor should be employed as the design operating point. The accuracy of the proposed methodology is validated by simulations and experiments carried out employing a 10 kVA grid-connected T-type converter prototype. The results demonstrate close agreement between theoretical predictions and experiments, confirming the practical applicability of the proposed method. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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22 pages, 2223 KiB

Open AccessArticle

RMS Modeling and Control of a Grid-Forming E-STATCOM for Power System Stability in Isolated Grids

by José Luis Rodriguez-Amenedo, Miguel E. Montilla-DJesus, Santiago Arnaltes and Francisco Arredondo

Appl. Sci. 2025, 15(6), 3014; https://doi.org/10.3390/app15063014 - 11 Mar 2025

Cited by 1 | Viewed by 1025

Abstract

This paper presents a comprehensive RMS-based phasorial model of an E-STATCOM with grid-forming (GFM) control, designed to improve power system stability in isolated grids. Unlike previous approaches, this model integrates a governor with an internal power system stabilizer (PSS) and an active current limiter (ACL) to enhance frequency regulation and mitigate oscillations. Additionally, an exciter with a nonlinear modulation function is introduced to optimize voltage regulation and reactive power support. A detailed conventional supercapacitor (SC) model is also incorporated, enabling dynamic DC-voltage control based on active power variations, improving frequency stability. The proposed E-STATCOM RMS model includes algebraic equations, dynamic governor and exciter models, supercapacitor-based energy storage control, and an advanced current-limiting strategy. Simulations are conducted on the Fuerteventura–Lanzarote (Canary Islands, Spain) power system, comparing the E-STATCOM with a synchronous condenser (SynCon) in frequency response, voltage regulation, and fault performance. The results show that the E-STATCOM improves frequency stabilization and energy efficiency while complying with grid codes. This study introduces a novel RMS-based modeling approach for GFM E-STATCOMs, bridging the gap between theoretical phasorial analysis and real-world applications. The findings confirm that E-STATCOMs are a viable alternative to SynCons, enhancing grid stability in high-renewable-penetration systems. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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30 pages, 3278 KiB

Open AccessArticle

Centralized MPPT Control Architecture for Photovoltaic Systems Using LoRa Technology

by Pablo Fernández-Bustamante, Eneko Artetxe, Isidro Calvo and Oscar Barambones

Appl. Sci. 2025, 15(5), 2456; https://doi.org/10.3390/app15052456 - 25 Feb 2025

Viewed by 465

Abstract

Maximum power point tracking (MPPT) algorithms are necessary to optimize the power generation in solar photovoltaic (PV) power plants. Typically, MPPT control systems depend on the wired connections among sensors, processing nodes, and DC–DC power converters. However, Low-Power Wide-Area Networks (LPWANs) allow for centralizing the execution of MPPT algorithms wirelessly, achieving more flexibility and reducing costs. In particular, LoRa/LoRaWAN is a low-cost/low-consumption technology with an excellent immunity to interference, which is able to operate over tens of kilometers. This article presents a centralized MPPT control architecture for PV systems based on the LoRa/LoRaWAN technology. This technology provides long-range/low-cost wireless connectivity with PV plants located far away. The presented approach allows for executing in parallel, on a central computing node, different MPPT algorithms for distinct PV subsystems. A proof-of-concept prototype was implemented to experimentally validate the architecture. It involved a rooftop PV system and a DC–DC converter connected to a computer, which executes the MPPT algorithms, by means of a point-to-point LoRa network. For validation purpose, two MPPT control techniques were implemented: Perturb and Observe (P&O) and Sliding Mode Control (SMC). However, the presented approach allows for the implementation of more sophisticated MPPT algorithms for optimizing energy production. The obtained results prove the validity of the concept and suggest that the proposed low-cost approach can be extrapolated to be used with LoRaWAN networks. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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30 pages, 8959 KiB

Open AccessArticle

Forecasts Plus Assessments of Renewable Generation Performance, the Effect of Earth’s Geographic Location on Solar and Wind Generation

by César Berna-Escriche, Lucas Álvarez-Piñeiro and David Blanco

Appl. Sci. 2025, 15(3), 1450; https://doi.org/10.3390/app15031450 - 31 Jan 2025

Cited by 1 | Viewed by 663

Abstract

Solar and wind resources are critical for the global transition to net-zero emission energy systems. However, their variability and unpredictability pose challenges for system reliability, often requiring fossil fuel-based backups or energy storage solutions. The mismatch between renewable energy generation and electricity demand necessitates analytical methods to ensure a reliable transition. Sole reliance on single-year data is insufficient, as it does not account for interannual variability or extreme conditions. This paper explores probabilistic modeling as a solution to more accurately assess renewable energy availability. A 22-year dataset is used to generate synthetic data for solar irradiance, wind speed, and temperature, modeled using statistical probability distributions. Monte Carlo simulations, run 93 times, achieve 95% confidence and confidence levels, providing reliable assessments of renewable energy potential. The analysis finds that during Dunkelflaute periods, in high-solar and high-wind areas, DF events average 20 h in the worst case, while low-resource regions may experience DF periods lasting up to 48 h. Optimal energy mixes for these regions should include 15–20% storage and interconnections to neighboring areas. Therefore, stochastic consideration and geographic differentiation are essential analyses to address these differences and ensure a reliable and resilient renewable energy system. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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25 pages, 17168 KiB

Open AccessArticle

Energy Optimal Configuration Strategy of Distributed Photovoltaic Power System for Multi-Level Distribution Network

by Yanmin Wang, Hanqing Zhang, Weiqi Zhang, Song Han and Yuzhuo Yang

Appl. Sci. 2025, 15(1), 234; https://doi.org/10.3390/app15010234 - 30 Dec 2024

Viewed by 745

Abstract

As the strategic position of distributed photovoltaic (PV) power generation in multi-level distribution networks continues to rise, its impact on the stable operation of the grid is becoming increasingly significant. This study delves into the influence of two key factors, the integration location and penetration rate of PV systems, on the distribution and flow of energy and the steady-state performance of multi-level distribution networks. Based on this, the study proposes a simplified grid analysis framework for analyzing and optimizing the energy allocation strategy of distribution systems and develops a PV configuration strategy aimed at optimizing the energy planning and design process of engineering projects. Taking a typical PV-participating distribution system as an example, the study provides a detailed description of the typical three-layer distribution network structure and deduces the relationship of the PV, node voltage, and node voltage deviation. The study verifies the accuracy and practical value of the proposed simplified framework through real-time monitoring simulation of node voltages and line losses. Finally, to achieve optimal energy allocation, the study proposes a PV segmentation strategy applied to the system and compares it with the traditional reactive power control strategy, demonstrating the advantage of the strategy in improving the system’s clean energy ratio and reducing network losses. This paper’s research on the impact of PV systems and the proposed simplified theory for distribution networks is universally applicable, and it holds significant reference value for practical engineering design. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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27 pages, 6343 KiB

Open AccessArticle

Software Integration of Power System Measurement Devices with AI Capabilities

by Victoria Arenas-Ramos, Federico Cuesta, Victor Pallares-Lopez and Isabel Santiago

Appl. Sci. 2025, 15(1), 170; https://doi.org/10.3390/app15010170 - 28 Dec 2024

Viewed by 1153

Abstract

The latest changes on the distribution network due to the presence of distributed energy resources (DERs) and electric vehicles make it necessary to monitor the grid using a real-time high-precision system. The present work centers on the development of an open-source software platform that allows for the joint management of, at least, power quality monitors (PQMs), phasor measurement units (PMUs), and smart meters (SMs), which are three of the most widespread devices on distribution networks. This framework could work remotely while allowing access to the measurements in a comfortable way for grid analysis, prediction, or control tasks. The platform must meet the requirements of synchronism and scalability needed when working with electrical monitoring devices while considering the large volumes of data that these devices generate. The framework has been experimentally validated in laboratory and field tests in two photovoltaic plants. Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time. Full article

(This article belongs to the Special Issue Energy and Power Systems: Control and Management)

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