Energies

13 pages, 645 KB

Open AccessEditor’s ChoicePerspective

A Perspective on Hydrogen Storage in the Energetic Transition Scenario

by Mattia Bartoli, Candido Fabrizio Pirri and Sergio Bocchini

Energies 2025, 18(24), 6564; https://doi.org/10.3390/en18246564 - 16 Dec 2025

Cited by 1 | Viewed by 992

Hydrogen is key player in the energetic transition towards a more sustainable society as a very versatile energy carrier. Nevertheless, hydrogen storage represents the main limitation to the spread of a hydrogen driven economy on a small and medium scale. Clearly, achieving this [...] Read more.

Hydrogen is key player in the energetic transition towards a more sustainable society as a very versatile energy carrier. Nevertheless, hydrogen storage represents the main limitation to the spread of a hydrogen driven economy on a small and medium scale. Clearly, achieving this requires a balance among material engineering, system optimization, and techno-economic assessments to optimize performance, safety, and scalability. In this work we briefly and critically discuss the progress in hydrogen storage focusing on the necessity to create a bridge to overcome the actual limitations. We explore the most recent advancement in the field drawing a picture of the complex scenario of hydrogen storage in the framework to the transition to a net zero or carbon negative society providing an updated opinion on the challenges addressed and those still to be solved. Full article

(This article belongs to the Section A5: Hydrogen Energy)

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28 pages, 3705 KB

Open AccessEditor’s ChoiceArticle

Transformer Iron Core Temperature Field Calculation Based on Finite Element Analysis

by Ziyang Chen, Zhenggang He and Shuhong Wang

Energies 2025, 18(24), 6537; https://doi.org/10.3390/en18246537 - 13 Dec 2025

Viewed by 652

Abstract

Temperature anomaly is a common fault in power transformers; therefore, achieving a fast and accurate calculation of the transformer temperature field is of great significance. This paper primarily introduces the methodology and self-programmed calculation for realizing the temperature field analysis of a single-phase, [...] Read more.

Temperature anomaly is a common fault in power transformers; therefore, achieving a fast and accurate calculation of the transformer temperature field is of great significance. This paper primarily introduces the methodology and self-programmed calculation for realizing the temperature field analysis of a single-phase, two-limb transformer iron core. First, the finite element equation for the three-dimensional steady-state temperature field is derived to provide the basis for the self-programmed Finite Element Method (FEM) calculation. Subsequently, the Finite Element Method (FEM) calculation of the single-phase, two-limb transformer iron core temperature field was implemented using the self-programmed code, and the results were compared with the COMSOL calculation results. The comparison showed that the error at each node was within 0.5 K. Compared to COMSOL, the computation time was reduced by 46.89%, and the memory usage was reduced by 82.37%. Finally, a temperature rise test was designed for the single-phase, two-limb transformer. Compared with the experimental data, the maximum error is within 3 K, which further confirms the accuracy of the program. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

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15 pages, 1824 KB

Open AccessEditor’s ChoiceArticle

Optimal Determination of Synchronous Condenser Placement and Voltage Setting for Enhancing Power System Stability

by Juseong Lee, Hyeongjun Jo and Soobae Kim

Energies 2025, 18(24), 6474; https://doi.org/10.3390/en18246474 - 10 Dec 2025

Cited by 1 | Viewed by 744

Abstract

With the increasing share of renewable energy in power systems, the instability of the power systems is becoming increasingly significant. Consequently, power system stability has become a critical issue, and non-transmission alternatives have been examined as potential solutions. Among non-transmission alternatives, the synchronous [...] Read more.

With the increasing share of renewable energy in power systems, the instability of the power systems is becoming increasingly significant. Consequently, power system stability has become a critical issue, and non-transmission alternatives have been examined as potential solutions. Among non-transmission alternatives, the synchronous condenser can enhance power system stability by providing inertia support and reactive power compensation, especially in systems with a high share of renewable energy. The placement and voltage settings of synchronous condensers significantly impact system stability. This paper proposes a methodology for determining the optimal placement and optimal voltage setting of synchronous condensers for enhancing their voltage stability and transient stability; the improved voltage stability index and synchronizing torque coefficient are used for enhancing the voltage stability and transient stability, respectively. A case study with a focus on specific stability aspects and involving scenarios where the size and number of synchronous capacitors are varied while maintaining a constant inertia energy is presented. The results of the case study show that strategically optimizing the placement and voltage setting of synchronous condensers can enhance the stability of a power system significantly. Full article

(This article belongs to the Special Issue Advanced Electric Power Systems, 2nd Edition)

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37 pages, 4200 KB

Open AccessEditor’s ChoiceReview

Agrivoltaics Around the World: Potential, Technology, Crops and Policies to Address the Energy–Agriculture Nexus for Sustainable and Climate-Resilient Land Use

by Kedar Mehta, Rushabh Jain and Wilfried Zörner

Energies 2025, 18(24), 6417; https://doi.org/10.3390/en18246417 - 8 Dec 2025

Cited by 2 | Viewed by 2643

Abstract

The urgent pursuit of climate-resilient agriculture and clean energy systems, central to the Energy–Agriculture Nexus and the UN Sustainable Development Goals, has accelerated global interest in agrivoltaic (Agri-PV) technologies. This paper presents a global systematic review and meta-analysis of 160 peer-reviewed studies, structured [...] Read more.

The urgent pursuit of climate-resilient agriculture and clean energy systems, central to the Energy–Agriculture Nexus and the UN Sustainable Development Goals, has accelerated global interest in agrivoltaic (Agri-PV) technologies. This paper presents a global systematic review and meta-analysis of 160 peer-reviewed studies, structured through a five-stage thematic synthesis: (1) mapping global and regional Agri-PV deployment and potential, (2) analyzing system design and modeling methodologies, (3) evaluating crop suitability under partial shading, (4) reviewing enabling policies and regulatory frameworks, and (5) assessing techno-economic feasibility and investment barriers. Results reveal that Europe and Asia lead Agri-PV development, driven by incentive-based policies and national tenders, while limited regulatory clarity and high capital costs constrain wider adoption. Despite technological progress, no integrated model fully captures the coupled energy, water, and crop dynamics essential for holistic assessment. Strengthening economic valuation, policy coherence, and standardized modeling approaches will be critical to scale Agri-PV systems as a cornerstone of sustainable and climate-resilient land use. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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24 pages, 51220 KB

Open AccessEditor’s ChoiceArticle

Estimation of Power-Coefficient Curve from SCADA Data for Digital-Twin Applications

by Minseok Song, Minho Kim, Jeongtaek Lim, Kyung Sun Ham and Taehyoung Kim

Energies 2025, 18(24), 6394; https://doi.org/10.3390/en18246394 - 6 Dec 2025

Cited by 1 | Viewed by 513

Abstract

Digital twins are emerging as a pivotal technology for the performance optimization, predictive maintenance, and real-time monitoring of wind turbines. However, the accuracy of these virtual representations critically depends on the availability of the power coefficient (

C_{p}

) curve, a key [...] Read more.

Digital twins are emerging as a pivotal technology for the performance optimization, predictive maintenance, and real-time monitoring of wind turbines. However, the accuracy of these virtual representations critically depends on the availability of the power coefficient (

C_{p}

) curve, a key descriptor of a turbine’s aerodynamic efficiency. This information is often proprietary and not disclosed by manufacturers, posing a significant barrier to the development of high-fidelity digital twins. This study addresses this critical gap by proposing a novel framework for estimating

C_{p}

curves using operational Supervisory Control and Data Acquisition (SCADA) data. The proposed methodology utilizes a parameterized mathematical formulation to model the

C_{p}

curve and employs the Adam optimizer to robustly tune the model’s parameters against real-world operational data. The framework was evaluated through a two-pronged process. First, the model’s accuracy was assessed using synthetic SCADA data from a high-fidelity simulator under ideal conditions, demonstrating excellent agreement with an

R^{2}

exceeding 0.99 and a normalized Mean Absolute Percentage Error (nMAPE) ranging from 4.38% to 6.03%. Second, its practical performance was evaluated using real SCADA data from a commercial wind turbine, where it maintained high accuracy with an

R^{2}

ranging from 0.89 to 0.98 and an nMAPE of 3.27% to 5.97%. The findings demonstrate that the proposed methodology can effectively reconstruct a turbine’s aerodynamic characteristics without proprietary manufacturer data. This research offers a viable pathway for operators and researchers to create accurate, turbine-specific digital twins, thereby enabling enhanced performance monitoring, advanced control optimization, and predictive maintenance for more efficient and reliable wind energy production. Full article

(This article belongs to the Special Issue Advanced Wind Energy Systems: Comprehensive Insights into Analysis, Design, Control, and Optimization)

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19 pages, 11470 KB

Open AccessEditor’s ChoiceArticle

A Large Eddy Simulation-Based Power Forecast Approach for Offshore Wind Farms

by Yongjie Lu, Tasnim Zaman, Bin Ma, Marina Astitha and Georgios Matheou

Energies 2025, 18(24), 6386; https://doi.org/10.3390/en18246386 - 5 Dec 2025

Cited by 1 | Viewed by 1093

Abstract

Reliable power forecasts are essential for the grid integration of offshore wind. This work presents a physics-based forecasting framework that couples mesoscale numerical weather prediction with large-eddy simulation (LES) and an actuator-disk turbine representation to predict farm-scale flows and power under realistic atmospheric [...] Read more.

Reliable power forecasts are essential for the grid integration of offshore wind. This work presents a physics-based forecasting framework that couples mesoscale numerical weather prediction with large-eddy simulation (LES) and an actuator-disk turbine representation to predict farm-scale flows and power under realistic atmospheric conditions. Mean meteorological profiles from the Weather Research and Forecasting model drive a concurrent–precursor LES generating turbulent inflow consistent with the evolving boundary layer, while a main LES resolves turbulence and wake formation within the wind farm. The LES configuration and turbine-forcing implementation are validated against canonical single- and multi-turbine benchmarks, showing close agreement in wake deficits and recovery trends. The framework is then demonstrated for the South Fork Wind project (12 turbines, ∼132 MW) using a set of time-varying cases over a 24 h period. Simulations reproduce hub-height wind variability, row-to-row power differences associated with wake interactions, and turbine-level power fluctuations (order 1 MW) that converge with appropriate averaging windows. The results illustrate how an LES-augmented hierarchical modeling system can complement conventional forecasting by providing physically interpretable flow fields and power estimates at operational scales. Full article

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20 pages, 6570 KB

Open AccessEditor’s ChoiceArticle

Research into the Energy Potential of Vine Pruning Residues in Western Serbia

by Aleksandar Ašonja, Sunčica Vještica, Aleksandar Bošković, Svetlana Živković Radeta, Mirjana Ćeranić, Zoran Jovanović and Siniša Škrbić

Energies 2025, 18(24), 6384; https://doi.org/10.3390/en18246384 - 5 Dec 2025

Cited by 3 | Viewed by 646

Abstract

Research and practice experience have shown that in the Republic of Serbia, vine pruning residues (VPRs) from vineyard production are mostly partially ploughed or uncontrollably burned in fields. Uncontrolled burning of VPRs in fields can destroy flora and fauna and cause uncontrolled fires. [...] Read more.

Research and practice experience have shown that in the Republic of Serbia, vine pruning residues (VPRs) from vineyard production are mostly partially ploughed or uncontrollably burned in fields. Uncontrolled burning of VPRs in fields can destroy flora and fauna and cause uncontrolled fires. On the other hand, on an annual basis, the resulting VPRs can completely replace the fossil fuels used for thermal energy production on these estates and significantly reduce the emission of pollutants from fossil fuels. The novelty of this study lies in the fact that the research was conducted on a very young vineyard, four years old, and the results show that the agricultural property is fully sustainable in terms of thermal energy needs. The research aimed to investigate the energy potential of VPRs at the vineyard located in the Mrčić settlement in Western Serbia. The research results include the following grape varieties: Tamjanika, Morava, Cabernet Sauvignon, and Cabernet Franc. The average yield of VPR biomass for all tested varieties was 0.387 kg/vine or 1741.50 kg/ha. The lower calorific values for the tested biomass samples at 15% moisture content ranged from 14,668 kJ/kg to 14,258 kJ/kg, while the upper values ranged from 16,099 kJ/kg to 15,721 kJ/kg. The total energy potential of biomass obtained from a vineyard, expressed in final energy, was 41.90 MWh/year. In the observed vineyard, for the same equivalent value, biomass from VPRs was 3.57 times cheaper compared to brown coal and 8.26 times cheaper compared to diesel fuel. Full article

(This article belongs to the Special Issue Renewable Energy Integration into Agricultural and Food Engineering)

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25 pages, 5911 KB

Open AccessEditor’s ChoiceArticle

A Numerical Study of Vertically Graded Gyroid Structures for Enhanced Heat Transfer in Sodium Acetate Trihydrate

by Martin Beer and Radim Rybár

Energies 2025, 18(23), 6373; https://doi.org/10.3390/en18236373 - 4 Dec 2025

Viewed by 643

Abstract

Thermal energy storage using latent heat storage materials represents a promising solution for stabilizing low-temperature energy systems; however, its effectiveness is limited by the low thermal conductivity of phase change materials (PCM), particularly salt hydrates such as sodium acetate trihydrate (SAT). The objective [...] Read more.

Thermal energy storage using latent heat storage materials represents a promising solution for stabilizing low-temperature energy systems; however, its effectiveness is limited by the low thermal conductivity of phase change materials (PCM), particularly salt hydrates such as sodium acetate trihydrate (SAT). The objective of this work is to analyze to what extent vertical gradation of a metallic gyroid structure can enhance heat transfer and temperature homogeneity in the PCM during charging. Time-dependent numerical simulations of conjugate heat transfer were performed for three gyroid variants differing in the orientation of pore gradation, modeling heat transfer between the flowing water, the aluminum gyroid structure, and the solid phase of SAT until the PCM reached a temperature of 58 °C. The results showed that the orientation of the gradation significantly affects both the heating dynamics and the quality of the temperature field. The variant with enlarged pores in the region of contact with the fluid and gradually decreasing pores toward the PCM achieved the shortest time to complete heating, the lowest temperature amplitude, and the highest degree of temperature homogeneity. This variant also exhibited the highest energetic efficiency, expressed as the ratio of transferred heat to pressure drop. The study demonstrates that deliberately designed gyroid gradation can substantially improve the performance of PCM composites without increasing the amount of material and represents a promising pathway for the development of advanced thermal storage systems. Full article

(This article belongs to the Special Issue Advances in Research on Phase Change Materials for Thermal Energy Storage Applications)

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24 pages, 6756 KB

Open AccessEditor’s ChoiceArticle

Integrated Assessment Framework for Rice Yield and Energy Yield in Bifacial Agrivoltaic Systems

by Seokhun Yoo and Kyungsoo Lee

Energies 2025, 18(23), 6359; https://doi.org/10.3390/en18236359 - 4 Dec 2025

Cited by 1 | Viewed by 612

Abstract

Agrivoltaic (APV) systems co-locate agricultural production and photovoltaic (PV) electricity generation on the same land to maximize land use efficiency. This study proposes an integrated assessment framework that jointly evaluates crop yield and electricity generation in APV systems. Unlike many previous APV studies [...] Read more.

Agrivoltaic (APV) systems co-locate agricultural production and photovoltaic (PV) electricity generation on the same land to maximize land use efficiency. This study proposes an integrated assessment framework that jointly evaluates crop yield and electricity generation in APV systems. Unlike many previous APV studies that estimated crop responses from empirical PAR–photosynthesis relationships, this framework explicitly couples a process-based rice growth model (DSSAT-CERES-Rice) with irradiance and PV performance simulations (Honeybee-Radiance and PVlib) in a single workflow. The five-stage framework comprises (i) meteorological data acquisition and processing; (ii) 3D modeling in Rhinoceros; (iii) calculation of module front and rear irradiance and crop height irradiance using Honeybee; (iv) crop yield calculation with DSSAT; and (v) electricity generation calculation with PVlib. Using bifacial PV modules under rice cultivation in Gochang, Jeollabuk-do (Republic of Korea), simulations were performed with ground coverage ratio (GCR) and PV array azimuth as key design variables. As GCR increased from 20% to 50%, crop yield reduction (CYR) rose from 12% to 33%, while land equivalent ratio (LER) increased from 128% to 158%. To keep CYR within the domestic guideline of 20% while maximizing land use, designs with GCR ≤ 30% were found to be appropriate. At GCR 30%, CYR of 17–18% and LER of 139–140% were achieved, securing a balance between agricultural productivity and electricity generation. Although PV array azimuth had a limited impact on crop yield and electricity generation, southeast or southwest orientations showed more uniform irradiance distributions over the field than due south. A simple economic assessment was also conducted for the study site to compare total annual net income from rice and PV across GCR scenarios. The proposed framework can be applied to other crops and sites and supports design-stage decisions that jointly consider crop yield, electricity generation, and economic viability. Full article

(This article belongs to the Special Issue Renewable Energy Integration into Agricultural and Food Engineering)

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22 pages, 2569 KB

Open AccessEditor’s ChoiceReview

Amorphous Transition Metal Sulfide Electrocatalysts for Green Hydrogen Generation from Solar-Driven Electrochemical Water Splitting

by Terence K. S. Wong

Energies 2025, 18(23), 6348; https://doi.org/10.3390/en18236348 - 3 Dec 2025

Viewed by 868

Abstract

The synthesis and electrocatalytic properties of amorphous first- and third-row transition metal sulfides (a-TMS) for green hydrogen generation have been comprehensively reviewed. These electrocatalysts can be prepared by several solution processes, including chemical bath deposition, electrodeposition, sol–gel, hydrothermal reaction and thermolysis. The deposition [...] Read more.

The synthesis and electrocatalytic properties of amorphous first- and third-row transition metal sulfides (a-TMS) for green hydrogen generation have been comprehensively reviewed. These electrocatalysts can be prepared by several solution processes, including chemical bath deposition, electrodeposition, sol–gel, hydrothermal reaction and thermolysis. The deposition method strongly influences the electrochemical properties of the synthesized a-TMS electrocatalyst. Based on overpotential at 10 mA/cm², the electrocatalytic activity of mono-metallic a-TMS for hydrogen evolution is ranked as follows: a-NiS_x > a-CuS_x > a-CoS_x > a-WS_x > a-FeS_x. The best performing a-NiS_x prepared by chemical bath deposition has an overpotential at 10 mA/cm² of 53 mV and Tafel slope of 68 mV/dec in 1 M KOH electrolyte. The integration of Ni into the a-TMS network structure is crucial to achieving high activity in multi-metallic a-TMS electrocatalyst, as demonstrated by the bifunctional (NiFe)S_x/NiFe(OH)_y nanocomposite catalyst. The critical role of Ni in a-TMS catalyst design can be attributed to the lower free energy change for hydrogen adsorption on Ni. Finally, the emerging catalyst design strategy of amorphous–crystalline heterostructures with a three-dimensional morphology will be discussed together with the need to identify hydrogen adsorption sites on a-TMS electrocatalysts in future. Full article

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20 pages, 8891 KB

Open AccessEditor’s ChoiceArticle

Sensorless Field-Oriented Control of a Low-Speed Six-Phase Induction Generator

by Marius Ouédraogo, Amine Yazidi and Franck Betin

Energies 2025, 18(23), 6293; https://doi.org/10.3390/en18236293 - 29 Nov 2025

Viewed by 487

Abstract

This paper presents a sensorless control strategy for a six-phase induction generator (6PIG) operating at low speed (125 rpm). The proposed approach is based on the Model Reference Adaptive System (MRAS), with an initial estimation scheme developed using the reference model as the [...] Read more.

This paper presents a sensorless control strategy for a six-phase induction generator (6PIG) operating at low speed (125 rpm). The proposed approach is based on the Model Reference Adaptive System (MRAS), with an initial estimation scheme developed using the reference model as the rotor flux. Simulation studies were conducted in MATLAB/Simulink 24.2.0.2740171 (R2024b) Update 1 and experimentally validated on a 24 kW–125 rpm 6PIG, to demonstrate the feasibility and performance of this method. A reactive power-based MRAS variant was also proposed to overcome the observed limitations. Comparative analysis showed a significant improvement in estimation accuracy and dynamic response compared with the flux-based MRAS. Robustness tests under fault conditions, such as opening phases, confirmed that the reactive power-based MRAS maintains a stable and accurate rotor speed estimation. These findings demonstrate the potential of reactive-power-based MRAS for the sensorless control of six-phase induction generators (6PIGs) in renewable energy systems. Full article

(This article belongs to the Special Issue Design and Production Process Optimization for High Performance and Energy Efficiency in Electrical Machines—2nd Edition)

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28 pages, 46098 KB

Open AccessEditor’s ChoiceArticle

Assessing Time Series Foundation Models for Probabilistic Electricity Price Forecasting: Toward a Unified Benchmark

by Gabriele Marchesi, Andrea Ballarino and Alessandro Brusaferri

Energies 2025, 18(23), 6269; https://doi.org/10.3390/en18236269 - 28 Nov 2025

Cited by 1 | Viewed by 1574

Abstract

Probabilistic electricity price forecasting (PEPF) is a highly complex task with broad economic and operational impact. Recent advances in time series foundation models (TSFMs) offer promising tools to improve PEPF performance. In contrast, PEPF provides a challenging platform for evaluating and accelerating the [...] Read more.

Probabilistic electricity price forecasting (PEPF) is a highly complex task with broad economic and operational impact. Recent advances in time series foundation models (TSFMs) offer promising tools to improve PEPF performance. In contrast, PEPF provides a challenging platform for evaluating and accelerating the development of general TSFMs. Despite their potential synergies, TSFMs have received limited attention in the PEPF literature, while the PEPF task remains largely unexplored in the TSFM context. This work aims to bridge these currently parallel research streams, fostering convergence and cross-fertilization to advance both fields. Focusing on Moirai, an open-source probabilistic framework with native covariate support and fine-tuning capabilities, we set up a comprehensive benchmark against specialized neural network-based PEPF methods across multiple market regions characterized by high variability and heterogeneous conditions. Additionally, we systematically explore fine-tuning strategies and model configurations, including context lengths and exogenous variable usage, to assess their impact on probabilistic forecasting accuracy. Experimental results indicate that Moirai provides promising zero-shot predictions, though it still underperforms compared to domain-specific neural networks. Fine-tuning improves calibration, while the architecture does not yet fully leverage exogenous features. Taken together, these observations offer valuable insights to foster future developments. We release our code through an open repository to facilitate collaborative progress within the PEPF and TSFM communities. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response: 2nd Edition)

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52 pages, 4973 KB

Open AccessEditor’s ChoiceArticle

TESE-Informed Evolution Pathways for Photovoltaic Systems: Bridging Technology Trajectories and Market Needs

by Jadwiga Gorączkowska, Marta Moczulska and Sergey Yatsunenko

Energies 2025, 18(23), 6216; https://doi.org/10.3390/en18236216 - 27 Nov 2025

Viewed by 1136

Abstract

Challenges related to energy security require support for investments in renewable energy sources. One of the most dynamically developing technologies in this area is photovoltaics. The literature provides numerous publications indicating PV development directions; however, strategic development planning remains fragmented between purely technological [...] Read more.

Challenges related to energy security require support for investments in renewable energy sources. One of the most dynamically developing technologies in this area is photovoltaics. The literature provides numerous publications indicating PV development directions; however, strategic development planning remains fragmented between purely technological solutions and market-economic analyses. Systematic integration of both perspectives with customer needs is lacking. This study fills this gap: applying the Trends of Engineering System Evolution (TESE) methodology enables identification of PV system development trends with particular attention to PV user needs and consideration of market-economic and technological conditions. The TESE framework was used to identify the Main Parameter of Value (MPV), which indicates which technology features are important to consumers. Two key MPVs were identified: “profitability” and “independence.” These reflect the fundamental decision criteria of customers in residential and commercial segments. The analysis revealed that profitability is between stages 2 and 3 of the technology S-curve, while independence is at stage 2. As areas worth developing in terms of the indicated MPVs, the authors proposed: increasing panel efficiency, building integrated platforms containing PV, batteries, and an efficient management system (PV + ESS + EMS), and creating PV microgrids with energy storage. The integration of photovoltaic systems with energy storage solutions proved to be the most important strategic direction, simultaneously addressing both MPVs and enabling advanced energy management capabilities. The study provides manufacturers and technology developers with evidence-based recommendations concerning resource allocation in photovoltaic innovation. It combines the technology development approach and market demand through systematically verified evolutionary patterns. This methodology offers a repeatable framework for strategic technology planning in renewable energy sectors. Full article

(This article belongs to the Special Issue Current Dynamics in Energy, Climate and Environmental Sustainability: Challenges, Prospects and Analysis)

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16 pages, 5681 KB

Open AccessEditor’s ChoiceArticle

Application of IoT in Monitoring Greenhouse Gas Emissions in Anaerobic Reactors

by Angela Li, Aditya Pandey and Pramod Pandey

Energies 2025, 18(23), 6191; https://doi.org/10.3390/en18236191 - 26 Nov 2025

Viewed by 873

Abstract

Anaerobic reactors are often used to control emissions and capture greenhouse gas (GHG) (biogas, a mixture of carbon dioxide and methane) from waste such as dairy manure. However, real-time monitoring of biogas production during in vitro anaerobic experiments is often challenging mainly due [...] Read more.

Anaerobic reactors are often used to control emissions and capture greenhouse gas (GHG) (biogas, a mixture of carbon dioxide and methane) from waste such as dairy manure. However, real-time monitoring of biogas production during in vitro anaerobic experiments is often challenging mainly due to the unpredictable and low levels of biogas production in a lab reactor system. The application of Internet of Things (IoT) technologies can enhance real-time monitoring of biogas production and GHG emissions from livestock waste. Integration of IoT to anaerobic reactors provides transformative solutions for low-cost monitoring. In this study, an IoT based sensor system that included a highly sensitive Renesas mass flow sensor module for biogas monitoring, Adafruit ported pressure sensor for monitoring of reactor pressure, and ultra-small DROK temperature probe for temperature monitoring was built and implemented for determining the biogas production in anaerobic reactors. Further, impacts of anaerobic process on the reduction of pathogenic organisms such as E. coli were determined using the conventional culture-based method. Results showed that the application of the IoT based system was able to monitor biogas production in real-time, and transmit the data to mobile phone using the ThingSpeak IoT platform offered by MathWorks (MATLAB) (Natick, MA, USA). The difference between the sensor’s biogas volume readings and actual observations over a 30-day time interval was 5–6% indicating the high level of accuracy and low error levels of the system. Further, results showed 1.6–4.8 log reductions of E. coli in effluent of anaerobic reactors indicating substantial impacts of the anaerobic process on pathogen indicator reduction. We anticipate that the system we used in this study has a substantial potential to enhance monitoring of anaerobic reactors and GHG emissions from livestock waste. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Economic Growth, Energy Consumption and Carbon Emission)

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29 pages, 2670 KB

Open AccessEditor’s ChoiceArticle

Modelling Solar Intermittency Effects on PEM Electrolyser Performance & Degradation: A Comparison of Oman and UK

by Mohamed Al-Mandhari and Aritra Ghosh

Energies 2025, 18(23), 6131; https://doi.org/10.3390/en18236131 - 23 Nov 2025

Cited by 3 | Viewed by 1146

Abstract

The durability of Proton Exchange Membrane Water Electrolysers (PEMWEs) under intermittent renewable power is a critical challenge for scaling green hydrogen. This study investigates the influence of solar intermittency on PEMWE performance and degradation in direct-coupled photovoltaic (PV) systems by comparing two contrasting [...] Read more.

The durability of Proton Exchange Membrane Water Electrolysers (PEMWEs) under intermittent renewable power is a critical challenge for scaling green hydrogen. This study investigates the influence of solar intermittency on PEMWE performance and degradation in direct-coupled photovoltaic (PV) systems by comparing two contrasting climates: Muscat, Oman (hot-arid, high irradiance) and Brighton, UK (temperate, variable irradiance). A validated physics-based model, incorporating reversible, activation, ohmic, and concentration overpotentials along with empirical degradation laws for catalyst decay, membrane thinning, and interfacial resistance growth, was applied to hourly PV-generation data. The results indicate that Muscat’s high irradiance (985 MWh year⁻¹) produced nearly double Brighton’s hydrogen yield (14,018 kg vs. 7566 kg) and longer operational hours (3269 h vs. 2244 h), but at the cost of accelerated degradation (359.8 μV h⁻¹ vs. 231.4 μV h⁻¹). In contrast, Brighton’s cooler and more humid climate preserved efficiency (65.8% vs. 59.8%) and reduced degradation, although higher daily cycling and seasonal variability constrained total output. The findings reveal a climate-dependent trade-off: hot, stable regions maximise hydrogen productivity at the expense of lifespan, whereas variable, cooler climates extend durability but limit yield. By explicitly linking intermittency to performance and ageing, this work provides a location-specific assessment of PEMWE feasibility, supporting design and operation strategies for renewable hydrogen deployment. Full article

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34 pages, 6640 KB

Open AccessEditor’s ChoiceReview

Hydrogen Storage Systems Supplying Combustion Hydrogen Engines—Review

by Jakub Lach, Kamil Wróbel, Wojciech Tokarz, Justyna Wróbel, Piotr Podsadni and Andrzej Czerwiński

Energies 2025, 18(23), 6093; https://doi.org/10.3390/en18236093 - 21 Nov 2025

Cited by 1 | Viewed by 1120

Abstract

The hydrogen drive is a promising zero-emission solution in transportation that can be realised through hydrogen internal combustion engines or hydrogen fuel cells. The hydrogen combustion engine’s advantage lies in the simplicity and greater maturity of the technology. At the same time, these [...] Read more.

The hydrogen drive is a promising zero-emission solution in transportation that can be realised through hydrogen internal combustion engines or hydrogen fuel cells. The hydrogen combustion engine’s advantage lies in the simplicity and greater maturity of the technology. At the same time, these solutions require appropriate fuel storage systems. The publication presents an overview of the currently used and developed hydrogen storage technologies. The main focus is placed on hydrogen tanks intended for vehicles powered by hydrogen internal combustion engines. The manuscript describes physical storage, including popular pressurised and cryogenic tanks. Additionally, technologies which can lead to improvements in the future, such as metallic and non-metallic hydrides and sorbents, are presented. The characteristics of the storage technologies in connection with the combustion engines are shown, as well as the outlook for the future of these solutions and their recent uses in vehicles. When focusing on vehicular and combustion applications, their specifics make physical storage methods the leading technology for now. Hydrogen storage today is still not competitive with fossil fuels; however, there are promising developments than can lead to achieving the requirements needed for its viable storage and use. Full article

(This article belongs to the Special Issue Internal Combustion Engines: Research and Applications—3rd Edition)

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14 pages, 2760 KB

Open AccessEditor’s ChoiceArticle

Quantification of CO₂ Emission from Liquefied Natural Gas Truck Under Varied Traffic Condition via Portable Measurement Emission System

by Yufei Shi, Hongmei Zhao, Bowen Li, Liangying Luo and Hongdi He

Energies 2025, 18(22), 6002; https://doi.org/10.3390/en18226002 - 16 Nov 2025

Viewed by 583

Abstract

Liquefied natural gas (LNG) container trucks are regarded as clean energy vehicles with the potential to reduce air pollution. However, their CO₂ emissions remain relatively high and are not yet well understood. In this study, the actual CO₂ emissions of LNG [...] Read more.

Liquefied natural gas (LNG) container trucks are regarded as clean energy vehicles with the potential to reduce air pollution. However, their CO₂ emissions remain relatively high and are not yet well understood. In this study, the actual CO₂ emissions of LNG container trucks in Shanghai were measured using a portable emissions measurement system (PEMS). This study quantitatively analyzed the relationship between traffic congestion levels and CO₂ emissions on elevated roadways, providing new insights into the impact of urban traffic conditions. In addition, distinct emission patterns were revealed under different uphill, downhill, and level road conditions, highlighting the substantial effects of roadway geometry on vehicle carbon emissions. Based on these findings, engine-related factors were identified as the dominant contributors, explaining 74% of the emission variance, while road slope analysis showed that uphill driving increased emissions by 13.41% compared with flat roads, whereas downhill driving reduced them by 76.22%. Finally, an efficient carbon emission prediction model for LNG container trucks was developed using machine learning methods. This study enriches the understanding of carbon emissions from LNG container trucks and provides theoretical support for their future applications in sustainable freight transportation. Full article

(This article belongs to the Special Issue Transportation Energy and Emissions Modeling)

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37 pages, 3505 KB

Open AccessEditor’s ChoiceReview

Prospects and Trends in the Development of Small Modular Nuclear Reactors

by Dagmara Chmielewska-Śmietanko, Tomasz Smoliński, Łukasz Bartela and Andrzej G. Chmielewski

Energies 2025, 18(22), 5970; https://doi.org/10.3390/en18225970 - 13 Nov 2025

Cited by 2 | Viewed by 3013

Abstract

Small Modular Reactor (SMR) concepts have developed faster than anyone could have predicted even ten years ago. Over the next decade, it is highly likely that we will see the construction and the operation of multiple SMRs based on both third- and fourth-generation [...] Read more.

Small Modular Reactor (SMR) concepts have developed faster than anyone could have predicted even ten years ago. Over the next decade, it is highly likely that we will see the construction and the operation of multiple SMRs based on both third- and fourth-generation nuclear reactors. This review paper aims to evaluate the development and maturity of Small Modular Reactor technologies using the Technology Readiness Level (TRL) framework, providing both quantitative and qualitative insights into their readiness. Since a key application of SMRs is the decarbonization of the energy sector, an example of data-driven methodology has been given for selecting both the site and type of reactor in Poland. However, TRL assessment and site selection with potential use of existing infrastructure are general in nature. They are based on international standards and recommendations from the IAEA and NEA OECD. The review further examines critical issues shaping SMR deployment, with particular attention to licensing requirements and compliance with the Non-Proliferation Treaty (NPT). Full article

(This article belongs to the Special Issue Renewable and Sustainable Energy in Light of Energy Transition Processes—2nd Edition)

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16 pages, 3989 KB

Open AccessEditor’s ChoiceArticle

Integrating Fish-Friendly Hydropower Solutions with the Nature Restoration Policy Through River Barrier Modification

by Calvin Stephen, Brian Huxley, John A. Byrne, Patrick Morrissey, Mary Kelly-Quinn and Aonghus McNabola

Energies 2025, 18(22), 5931; https://doi.org/10.3390/en18225931 - 11 Nov 2025

Cited by 1 | Viewed by 1300

Abstract

The recently adopted EU Nature Restoration law emphasises the urgent need to address the ecological impacts of river barriers, which fragment habitats and disrupt natural flows. However, efforts to remove barriers are often constrained by prohibitive costs, regulatory hurdles, and public opposition. In [...] Read more.

The recently adopted EU Nature Restoration law emphasises the urgent need to address the ecological impacts of river barriers, which fragment habitats and disrupt natural flows. However, efforts to remove barriers are often constrained by prohibitive costs, regulatory hurdles, and public opposition. In Ireland, barrier removal costs range between EUR 200,000 and EUR 500,000 per structure, representing a substantial financial burden given that more than 73,000 barriers are identified nationwide. Although removal would restore ecological function, it would also eliminate the potential to repurpose these structures for hydropower, thereby reducing opportunities to contribute to the national target of 80% renewable electricity generation by 2030. This study outlines the development of a river barrier modification system to serve the dual purposes of upstream and downstream fish lift over barriers and generation of electricity for local consumption using a fish-friendly pump-as-turbine unit. Under normal flows, the unit generates electricity while during low flows it operates in pumping mode to enable fish passage. A prototype was fabricated and tested at a fish farm using both artificial and live fish. An assessment of the regional potential was also extrapolated from preliminary results suggesting that the BMS offers a cost-effective alternative to full barrier removal, potentially offsetting costs by 50–85% while contributing to both EU restoration targets and national renewable energy goals. Full article

(This article belongs to the Special Issue Climate Change in Power and Energy Systems: Challenges, Innovations, and Solutions)

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38 pages, 3977 KB

Open AccessEditor’s ChoiceReview

Biomass for Residential Heating: A Review of Technologies, Applications, and Sustainability Aspects

by Jakub Katerla and Krzysztof Sornek

Energies 2025, 18(22), 5875; https://doi.org/10.3390/en18225875 - 7 Nov 2025

Cited by 2 | Viewed by 2832

Abstract

Biomass has long been a major source of energy for residential heating and, in recent decades, has regained attention as a renewable alternative to fossil fuels. This review explores the current state and prospects of domestic biomass-based heating technologies, including biomass-fired boilers, local [...] Read more.

Biomass has long been a major source of energy for residential heating and, in recent decades, has regained attention as a renewable alternative to fossil fuels. This review explores the current state and prospects of domestic biomass-based heating technologies, including biomass-fired boilers, local space heaters, and hybrid systems that integrate biomass with complementary renewable energy sources to deliver heat, electricity, and cooling. The review was conducted to identify key trends, performance data, and innovations in conversion technologies, fuel types, and efficiency enhancement strategies. The analysis highlights that biomass is increasingly recognized as a viable energy carrier for energy-efficient, passive, and nearly zero-energy buildings, particularly in cold climates where heating demand remains high. The analysis of the available studies shows that modern biomass-fired systems can achieve high energy performance while reducing environmental impact through advanced combustion control, optimized heat recovery, and integration with low-temperature heating networks. Overall, the findings demonstrate that biomass-based technologies, when designed and sourced efficiently and sustainably, can play a significant role in decarbonizing the residential heating sector and advancing nearly zero-energy building concepts. Full article

(This article belongs to the Special Issue Novel and Emerging Energy Systems)

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27 pages, 1182 KB

Open AccessEditor’s ChoiceArticle

Fairness–Performance Trade-Offs in Active Power Curtailment for Radial Distribution Grids with Battery Energy Storage

by Giorgos Gotzias, Eleni Stai and Symeon Papavassiliou

Energies 2025, 18(22), 5873; https://doi.org/10.3390/en18225873 - 7 Nov 2025

Viewed by 1001

Abstract

The increasing integration of decentralized technologies such as photovoltaic (PV) systems and electric vehicles (EVs) poses significant challenges to the reliable operation of radial distribution grids. In this paper, we study Active Power Curtailment (APC), which is a cost-effective method that maintains grid [...] Read more.

The increasing integration of decentralized technologies such as photovoltaic (PV) systems and electric vehicles (EVs) poses significant challenges to the reliable operation of radial distribution grids. In this paper, we study Active Power Curtailment (APC), which is a cost-effective method that maintains grid safety by temporarily reducing power injections. However, APC can place disproportional curtailment burden on grid buses that may in fact undermine the continuous adoption of PVs and EVs. In this work, we propose different novel APC methods that incorporate fairness properties for radial grids with PVs, EVs, and battery energy storage systems (BESSs). In addition, we integrate BESSs and show their benefits in lowering APC levels and achieving better PV and EV utilization while enhancing fairness. The proposed APC designs allow for fast decision making and can be generalized to unseen grids. To do so, a two-step solution is adopted, where in the first step, a reinforcement learning (RL)-based agent determines uniform per-feeder APC and BESS actions, and in the second step, heuristic controllers disaggregate these actions into tailored per-bus decisions while incorporating fairness features. Through simulations, the controllers are shown to mitigate over

99 %

of constraint violations and significantly enhance fairness in curtailment distribution. BESSs are shown to improve the violations count and APC trade-off, leaning towards reduced APC percentages. Finally, we exemplify how the solution generalizes effectively to unseen grid configurations. Full article

(This article belongs to the Special Issue Techno-Economic Analysis and Optimization for Energy Systems: 3rd Edition on the Way to Green Transition)

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16 pages, 968 KB

Open AccessEditor’s ChoiceArticle

Real-Time Reconfiguration of PV Arrays and Control Strategy Using Minimum Number of Sensors and Switches

by Wing Kong Ng and Nesimi Ertugrul

Energies 2025, 18(22), 5866; https://doi.org/10.3390/en18225866 - 7 Nov 2025

Viewed by 649

Abstract

This paper presents a reconfigurable switching circuit and control methodology for mitigating power losses in photovoltaic (PV) systems under partial shading. The proposed hardware uses a simplified network of power MOSFETs and diodes to enable dynamic reconfiguration between series and parallel connections, improving [...] Read more.

This paper presents a reconfigurable switching circuit and control methodology for mitigating power losses in photovoltaic (PV) systems under partial shading. The proposed hardware uses a simplified network of power MOSFETs and diodes to enable dynamic reconfiguration between series and parallel connections, improving energy yield with minimal conduction losses. Unlike conventional approaches that require irradiance measurements or extensive sensing, the control algorithm uses only per-module voltage and a single-current measurement to detect shading events in real time. A novel switching strategy reduces the number of actively controlled transistors, simplifying the control circuitry and reducing power dissipation. Both simulation and experimental results validate the method. Simulations of a 4-module PV system showed maximum power point (MPP) increases from 900 W to over 1100 W and from 460 W to 900 W, with full recovery to 1500 W after shading removal. Experimental verification on a 3-module setup under controlled shading yielded similar improvements: MPP increased from 38.4 W to 45.6 W and from 38.4 W to 45.8 W. These results demonstrate rapid adaptability, effective mismatch loss reduction, and maximisation of available power, making the proposed design a practical and low-overhead solution for commercial PV systems with non-uniform irradiance. Full article

(This article belongs to the Special Issue Intelligent Control for Electrical Power and Energy System)

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12 pages, 436 KB

Open AccessEditor’s ChoicePerspective

Economic and Environmental Outlook on Agrivoltaics: Review and Perspectives

by Alexandra Jean and Kurt A. Rosentrater

Energies 2025, 18(21), 5836; https://doi.org/10.3390/en18215836 - 5 Nov 2025

Viewed by 1259

Abstract

The growing world population has continued to drive up the demand for food and energy resources, putting substantial strain on the finite land, water, and fossil resources of the earth. Given the current climate crisis, the necessity of implementing renewable energy-generation strategies has [...] Read more.

The growing world population has continued to drive up the demand for food and energy resources, putting substantial strain on the finite land, water, and fossil resources of the earth. Given the current climate crisis, the necessity of implementing renewable energy-generation strategies has become clear. Although solar energy is one of the most abundant and consistent forms of renewable energy available, conventional ground-mounted solar arrays require large amounts of land area, and solar energy generation may come into competition with agriculture with increasing installation capacity. Agrivoltaics has been presented as a solution to integrate agricultural activities with solar energy generation to enhance the land efficiency of both activities. Through this method, agriculture and solar energy become synergistic, generating multiple profit streams from the same land with additional potential environmental benefits. The review presented herein studies the literature pertaining to the triple bottom line for agrivoltaics systems: people, planet, and profit. Despite the early-stage nature of many available studies, researchers have reported that certain agrivoltaics systems could be up to 270% more profitable than standalone cropping systems and reduce the greenhouse gas potential of traditional agriculture and energy generation by up to 99%. By synthesizing the information from multiple techno-economic analyses, life-cycle assessments, and policy recommendations, we hope to provide some insight into the key parameters driving the long-term sustainability of agrivoltaics systems. Full article

(This article belongs to the Section B: Energy and Environment)

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22 pages, 1924 KB

Open AccessEditor’s ChoiceReview

Review of Data-Driven Approaches Applied to Time-Series Solar Irradiance Forecasting for Future Energy Networks

by Xuan Jiao and Weidong Xiao

Energies 2025, 18(21), 5823; https://doi.org/10.3390/en18215823 - 4 Nov 2025

Cited by 2 | Viewed by 1040

Abstract

The fast-increasing penetration of photovoltaic (PV) power raises the issue of grid stability due to its intermittency and lack of inertia in power systems. Solar irradiance forecasting effectively supports advanced control, mitigates power intermittency, and improves grid resilience. Irradiance forecasting based on data-driven [...] Read more.

The fast-increasing penetration of photovoltaic (PV) power raises the issue of grid stability due to its intermittency and lack of inertia in power systems. Solar irradiance forecasting effectively supports advanced control, mitigates power intermittency, and improves grid resilience. Irradiance forecasting based on data-driven methods aims to predict the direction and level of power variation and indicate quick action. This article presents a comprehensive review and comparative analysis of data-driven approaches for time-series solar irradiance forecasting. It systematically evaluates nineteen representative models spanning from traditional statistical methods to state-of-the-art deep learning architectures across multiple performance dimensions that are critical for practical deployment. The analysis aims to provide actionable insights for researchers and practitioners when selecting and implementing suitable forecasting solutions for diverse solar energy applications. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Generation Technologies and Power Demand Response: 2nd Edition)

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23 pages, 2647 KB

Open AccessEditor’s ChoiceReview

Biogas Upgrading into Renewable Natural Gas: Part II—An Assessment of Emerging Technologies

by Blake Foret, José Ramón Laines Canepa, Gabriel Núñez-Nogueira, Stephen Dufreche, Rafael Hernandez, Daniel Gang, Wayne Sharp, Emmanuel Revellame, Dhan Lord B. Fortela, Sarah Simoneaux, Hayden Hulin, William E. Holmes and Mark E. Zappi

Energies 2025, 18(21), 5760; https://doi.org/10.3390/en18215760 - 31 Oct 2025

Viewed by 1548

Abstract

Renewable natural gas is an innovative alternative fuel source that has the potential to integrate seamlessly into the current energy and fuel sector. In addition, growing concerns related to energy security and environmental impact are incentivizing the development of RNG technologies. In conjunction [...] Read more.

Renewable natural gas is an innovative alternative fuel source that has the potential to integrate seamlessly into the current energy and fuel sector. In addition, growing concerns related to energy security and environmental impact are incentivizing the development of RNG technologies. In conjunction with this document, current technologies related to biogas conditioning and biogas upgrading were covered in a separate analysis deemed Part I. With the current technologies, however, issues such as compositional quality, combustion efficiency, and high operational costs still need to be addressed before RNG can reach its true capability in use. Recent innovations have focused on optimizing techniques and introducing new methods to maximize methane yield and purity while minimizing costs and energy consumption. This document, Part II, provides an overview of emerging technologies related to further biogas upgrading, such as cryogenics, methane enrichment, and hybrid treatments, aimed at increasing cleaned biogas purity. Processes in development are also discussed, including industrial lung, supersonic separation, chemical hydrogenation, hydrate formation, and various biological treatments. The benefits of these advancements are increased purity for the ability to pipeline renewable natural gas in existing infrastructure, help industries reach sustainability goals, and contribute to a more resilient energy system. Together, Parts I and II offer a comprehensive understanding of both current and future technological developments. Full article

(This article belongs to the Special Issue Advances in Integration of Renewable Energy Technologies and Distribution Systems: 2nd Edition)

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27 pages, 1473 KB

Open AccessEditor’s ChoiceReview

Biogas Upgrading into Renewable Natural Gas: Part I—An Assessment of Available Technologies

by José Ramón Laines Canepa, Blake Foret, Gabriel Núñez-Nogueira, Stephen Dufreche, Rafael Hernandez, Daniel Gang, Wayne Sharp, Emmanuel Revellame, Dhan Lord B. Fortela, Sarah Simoneaux, Hayden Hulin, William E. Holmes and Mark E. Zappi

Energies 2025, 18(21), 5750; https://doi.org/10.3390/en18215750 - 31 Oct 2025

Viewed by 1536

Abstract

Energy security is a growing societal and industrial concern that leads research and development toward more sustainable options. Biogas, a bio-alternative to conventional fuels, is a product generated from the anaerobic digestion of organic matter. This source of fuel production is more environmentally [...] Read more.

Energy security is a growing societal and industrial concern that leads research and development toward more sustainable options. Biogas, a bio-alternative to conventional fuels, is a product generated from the anaerobic digestion of organic matter. This source of fuel production is more environmentally friendly compared to traditional fossil fuels, leading to a lower carbon footprint, higher air quality, and the promotion of a circular economy. Impurities of raw biogas, such as carbon dioxide, hydrogen sulfide, and other trace contaminants, make biogas conditioning necessary for most applications. In addition, biogas upgrading, technologies furthering biogas purity, is an important factor in the production of biomethane, a sustainable biofuel known more commonly as renewable natural gas (RNG). Diversifying fuel sources and providing energy sustainability while mitigating negative environmental effects makes RNG an attractive alternative to conventional natural gas. This document, Part I, provides an overview of current technologies related to biogas conditioning, such as sorption, oxidation, and biological treatments aimed at the removal of a wide variety of contaminants. Processes developed for biogas upgrading are also discussed, including physical/chemical absorption, pressure swing adsorption, and membrane separation. The focus of upgrading applies approaches in meeting a higher quality biofuel by further carbon dioxide exclusion to ease pipeline transport and increase combustion efficiency. These technologies present the core foundation of processes in the production of RNG; however, all face inherent challenges that deem further research and development a requirement for global adoption. The biggest challenges are either in the cost of reaching higher purities or the inability to do so without other operations. Thus, in conjunction with this document, emerging and developing technologies are provided in a separate analysis deemed Part II. Together, these documents offer a comprehensive understanding of current practices and growing technological developments. Full article

(This article belongs to the Special Issue Advances in Integration of Renewable Energy Technologies and Distribution Systems: 2nd Edition)

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27 pages, 7870 KB

Open AccessEditor’s ChoiceReview

Direct vs. Indirect Charge Transfer: A Paradigm Shift in Phase-Spanning Triboelectric Nanogenerators Focused on Liquid and Gas Interfaces

by Jee Hwan Ahn, Quang Tan Nguyen, Tran Buu Thach Nguyen, Md Fajla Rabbi, Van Hien Nguyen, Yoon Ho Lee and Kyoung Kwan Ahn

Energies 2025, 18(21), 5709; https://doi.org/10.3390/en18215709 - 30 Oct 2025

Viewed by 1137

Abstract

Triboelectric nanogenerators (TENGs) have emerged as a promising technology for harvesting mechanical energy via contact electrification (CE) at diverse interfaces, including solid–liquid, liquid–liquid, and gas–liquid phases. This review systematically explores fluid-based TENGs (Flu-TENGs), introducing a foundational and novel classification framework based on direct [...] Read more.

Triboelectric nanogenerators (TENGs) have emerged as a promising technology for harvesting mechanical energy via contact electrification (CE) at diverse interfaces, including solid–liquid, liquid–liquid, and gas–liquid phases. This review systematically explores fluid-based TENGs (Flu-TENGs), introducing a foundational and novel classification framework based on direct versus indirect charge transfer to the charge-collecting electrode (CCE). This framework addresses a critical gap by providing the first unified analysis of charge transfer mechanisms across all major fluid interfaces, establishing a clear design principle for future device engineering. We comprehensively compare the underlying mechanisms and performance outcomes, revealing that direct charge transfer consistently delivers superior energy conversion—with specific studies achieving up to 11-fold higher current and 8.8-fold higher voltage in solid–liquid TENGs (SL-TENGs), 60-fold current and 3-fold voltage gains in liquid–liquid TENGs (LL-TENGs), and 34-fold current and 10-fold voltage enhancements in gas–liquid TENGs (GL-TENGs). Indirect mechanisms, relying on electrostatic induction, provide stable Alternating Current (AC) output ideal for low-power, long-term applications such as environmental sensors and wearable bioelectronics, while direct mechanisms enable high-efficiency Direct Current (DC) output suitable for energy-intensive systems including soft actuators and biomedical micro-pumps. This review highlights a paradigm shift in Flu-TENG design, where the deliberate selection of charge transfer pathways based on this framework can optimize energy harvesting and device performance across a broad spectrum of next-generation sensing, actuation, and micro-power systems. By bridging fundamental charge dynamics with application-driven engineering, this work provides actionable insights for advancing sustainable energy solutions and expanding the practical impact of TENG technology. Full article

(This article belongs to the Special Issue Advances in Energy Harvesting Systems)

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33 pages, 1062 KB

Open AccessEditor’s ChoiceReview

A Multi-Level Perspective on Transition to Renewable Energy in the Indonesian Transport Sector

by Ferry Fathoni, Jon C. Lovett and Muhammad Mufti Rifansha

Energies 2025, 18(21), 5723; https://doi.org/10.3390/en18215723 - 30 Oct 2025

Cited by 1 | Viewed by 1653

Abstract

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze [...] Read more.

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze how policy formulation, critical junctures, and path dependence shape institutional changes toward sustainable mobility. The evolution of institutional arrangements can be categorized into three phases: the establishment of fuel-oil-based infrastructure and dependency (1970–2003); the diversification of cleaner fuels through compressed natural gas and biofuels (2004–2014); and the development of affordable and clean energy, focusing on biofuels and electrification (2015 to present). In parallel, a quantitative total cost of ownership analysis of vehicles using different fuel types demonstrates how institutional reforms, fiscal incentives, and regulatory support reshape the economic feasibility of low-carbon technologies. Landscape pressures—such as global decarbonization, fuel import dependence, and energy security challenges—interact with niche innovations, including biofuels, electric vehicles, and hybrid systems, to drive systemic transformation. The findings indicate that institutional changes, supported by quantitative economic evidence and technology diffusion, play a pivotal role in realigning Indonesia’s transport energy regime toward a more resilient, inclusive, and sustainable transition. Full article

(This article belongs to the Special Issue Renewable Energy Sources towards a Zero-Emission Economy)

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31 pages, 1382 KB

Open AccessEditor’s ChoiceReview

Towards Sustainable Buildings and Energy Communities: AI-Driven Transactive Energy, Smart Local Microgrids, and Life Cycle Integration

by Andrzej Ożadowicz

Energies 2025, 18(21), 5668; https://doi.org/10.3390/en18215668 - 29 Oct 2025

Cited by 1 | Viewed by 1595

Abstract

The transition towards sustainable and low-carbon energy systems highlights the crucial role of buildings, microgrids, and local communities as key actors in enhancing resilience and achieving decarbonization targets. The application of artificial intelligence (AI) is of paramount importance as it enables accurate prediction, [...] Read more.

The transition towards sustainable and low-carbon energy systems highlights the crucial role of buildings, microgrids, and local communities as key actors in enhancing resilience and achieving decarbonization targets. The application of artificial intelligence (AI) is of paramount importance as it enables accurate prediction, adaptive control, and optimization of distributed resources. This paper reviews recent advances in AI applications for transactive energy (TE) and dynamic energy management (DEM), focusing on their integration with building automation, microgrid coordination, and community energy exchanges. It also considers the emerging role of life cycle-based methods, such as life cycle assessment (LCA) and life cycle cost (LCC), in extending operational intelligence to long-term environmental and economic objectives. The analysis is based on a curated set of 97 publications identified through structured queries and thematic filtering. The findings indicate substantial advancement in methodological approaches, notably reinforcement learning (RL), hybrid model predictive control, federated and edge AI, and digital twin applications. However, this study also uncovers shortcomings in the integration and interoperability of sustainability. This paper contributes by consolidating fragmented research and proposing a multi-layered AI framework that aligns short-term performance with long-term resilience and sustainability. Full article

(This article belongs to the Special Issue Energy Management Systems: Challenges, Techniques and Opportunities: 2nd Edition)

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33 pages, 4008 KB

Open AccessEditor’s ChoiceSystematic Review

Applications of the Digital Twin and the Related Technologies Within the Power Generation Sector: A Systematic Literature Review

by Saeid Shahmoradi, Mahmood Hosseini Imani, Andrea Mazza and Enrico Pons

Energies 2025, 18(21), 5627; https://doi.org/10.3390/en18215627 - 26 Oct 2025

Cited by 3 | Viewed by 2763

Abstract

Digital Twin (DT) technology has emerged as a valuable tool for researchers and engineers, enabling them to optimize performance and enhance system efficiency. This paper presents a comprehensive Systematic Literature Review (SLR) following the PRISMA framework to explore current applications of DT technology [...] Read more.

Digital Twin (DT) technology has emerged as a valuable tool for researchers and engineers, enabling them to optimize performance and enhance system efficiency. This paper presents a comprehensive Systematic Literature Review (SLR) following the PRISMA framework to explore current applications of DT technology in the power generation sector while highlighting key advancements. A new framework is developed to categorize DTs in terms of time-scale horizons and applications, focusing on power plant types (emissive vs. non-emissive), operational behaviors (including condition monitoring, predictive maintenance, fault detection, power generation prediction, and optimization), and specific components (e.g., power transformers). The time-scale is subdivided into a six-level structure to precisely indicate the speed and time range at which it is used. More importantly, each category in the application is further subcategorized into a three-level framework: component-level (i.e., fundamental physical properties and operational characteristics), system-level (i.e., interaction of subsystems and optimization), and service-level (i.e., value-adding service outputs). This classification can be utilized by various parties, such as stakeholders, engineers, scientists, and policymakers, to gain both a general and detailed understanding of potential research and operational gaps. Addressing these gaps could improve asset longevity and reduce energy consumption and emissions. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 3rd Edition)

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17 pages, 3831 KB

Open AccessEditor’s ChoiceArticle

Simulation Analysis of Cu₂O Solar Cells

by Sinuo Chen, Lichun Wang, Chunlan Zhou, Jinli Yang and Xiaojie Jia

Energies 2025, 18(21), 5623; https://doi.org/10.3390/en18215623 - 26 Oct 2025

Viewed by 1017

Abstract

Cu₂O solar cells are regarded as a promising emerging inorganic photovoltaic technology due to their power conversion efficiency (PCE) potential and material sustainability. While previous studies primarily focused on the band offset between n-type buffer layers and Cu₂O optical [...] Read more.

Cu₂O solar cells are regarded as a promising emerging inorganic photovoltaic technology due to their power conversion efficiency (PCE) potential and material sustainability. While previous studies primarily focused on the band offset between n-type buffer layers and Cu₂O optical absorption, this work systematically investigated an ETL/buffer/p-Cu₂O/HTL heterojunction structure using SCAPS-1D simulations. Key design parameters, including bandgap (Eg) and electron affinity (χ) matching across layers, were optimized to minimize carrier transport barriers. Furthermore, the doping concentration and thickness of each functional layer (ETL: transparent conductive oxide; HTL: hole transport layer) were tailored to balance electron conductivity, parasitic absorption, and Auger recombination. Through this approach, a maximum PCE of 14.12% was achieved (V_oc = 1.51V, J_sc = 10.52 mA/cm², FF = 88.9%). The study also identified candidate materials for ETL (e.g., GaN, ZnO:Mg) and HTL (e.g., ZnTe, NiO_x), along with optimal thicknesses and doping ranges for the Cu₂O absorber. These findings provide critical guidance for advancing high-performance Cu₂O solar cells. Full article

(This article belongs to the Special Issue Functional Materials for Advanced Energy Applications)

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61 pages, 13924 KB

Open AccessEditor’s ChoiceReview

Agar-Based Composites in Sustainable Energy Storage: A Comprehensive Review

by Zeenat Akhter, Sultan Ullah, Arvydas Palevicius and Giedrius Janusas

Energies 2025, 18(21), 5618; https://doi.org/10.3390/en18215618 - 25 Oct 2025

Cited by 2 | Viewed by 2312

Abstract

The shift towards renewable resources has positioned agar, a natural seaweed polysaccharide, as a pivotal and sustainable material for developing next-generation energy storage technologies. This review highlights the transformative role of agar-based composites as a game-changing and eco-friendly platform for supercapacitors, batteries, and [...] Read more.

The shift towards renewable resources has positioned agar, a natural seaweed polysaccharide, as a pivotal and sustainable material for developing next-generation energy storage technologies. This review highlights the transformative role of agar-based composites as a game-changing and eco-friendly platform for supercapacitors, batteries, and fuel cells. Moving beyond the traditional synthetic polymers, agar introduces a novel paradigm by leveraging its natural gelation, superior film-forming ability, and inherent ionic conductivity to create advanced electrolytes, binders, and matrices. The novelty of this field lies in the strategic fabrication of synergistic composites with polymers, metal oxides, and carbon materials, engineered through innovative techniques like electrospinning, solvent casting, crosslinking, 3D printing, and freeze-drying. We critically examine how these innovative composites are breaking new ground in enhancing device efficacy, flexibility, and thermal stability. Ultimately, this analysis not only consolidates the current landscape but also charts future pathways, positioning agar-based materials as a pivotal and sustainable solution for powering the future. Full article

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37 pages, 3050 KB

Open AccessEditor’s ChoiceReview

Power-to-Heat and Seasonal Thermal Energy Storage: Pathways Toward a Low-Carbon Future for District Heating

by Krzysztof Sornek, Maksymilian Homa, Flaviu Mihai Frigura-Iliasa, Mihaela Frigura-Iliasa, Marcin Jankowski, Karolina Papis-Frączek, Jakub Katerla and Jakub Janus

Energies 2025, 18(21), 5577; https://doi.org/10.3390/en18215577 - 23 Oct 2025

Cited by 9 | Viewed by 5269

Abstract

Power-to-Heat and Seasonal Thermal Energy Storage are emerging technologies that facilitate the integration of variable renewable energy sources into building and district energy systems. This review synthesizes recent advancements in technologies, integration strategies, and case studies, with a particular focus on nearly zero-energy [...] Read more.

Power-to-Heat and Seasonal Thermal Energy Storage are emerging technologies that facilitate the integration of variable renewable energy sources into building and district energy systems. This review synthesizes recent advancements in technologies, integration strategies, and case studies, with a particular focus on nearly zero-energy buildings and nearly zero-energy districts. A structured literature survey, prioritizing sources from 2020 to 2025, was conducted to map available options. The analysis includes Power-to-Heat systems, primarily electric boilers and heat pumps, as well as various seasonal thermal energy storage configurations, including Aquifer Thermal Energy Storage, Borehole Thermal Energy Storage, Pit Thermal Energy Storage, Tank Thermal Energy Storage, and Packed Bed Thermal Energy Storage. The findings indicate that coupling renewable energy with Power-to-Heat and seasonal thermal energy storage can significantly enhance the flexibility of buildings and district systems, reducing the curtailment of renewable sources by utilizing surplus electricity from renewable generation, particularly during periods of low demand, and lowering the environmental impact of buildings and district heating networks. Full article

(This article belongs to the Special Issue Advanced Energy Systems in Energy Resilient and Flexible Zero/Positive Energy Buildings, Communities and Districts)

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23 pages, 2723 KB

Open AccessEditor’s ChoiceReview

Assessment Methods for DC Stray Current Corrosion Hazards in Underground Gas Pipelines: A Review Focused on Rail Traction Systems

by Krzysztof Żakowski, Michał Szociński and Stefan Krakowiak

Energies 2025, 18(21), 5570; https://doi.org/10.3390/en18215570 - 23 Oct 2025

Cited by 1 | Viewed by 1555

Abstract

Stray currents leaking from electrified DC rail systems cause the greatest corrosion risk to underground metal gas pipelines and can lead to pipeline wall perforation in a very short time. Leakage and gas explosion, and other direct and indirect effects, can even disrupt [...] Read more.

Stray currents leaking from electrified DC rail systems cause the greatest corrosion risk to underground metal gas pipelines and can lead to pipeline wall perforation in a very short time. Leakage and gas explosion, and other direct and indirect effects, can even disrupt the stability of the energy system. Maintaining the reliability of gas pipelines, therefore, requires protecting them against corrosion caused by stray currents. It is therefore necessary to conduct field studies to identify sections of gas pipelines at risk and where protective installations should be installed. The paper discusses the most important field methods for assessing the risk of stray currents to gas pipelines: the potential of rail traction relative to ground, electric field gradients in the ground associated with stray current flow, correlation of gas pipeline potential and voltage of pipeline vs. the rail, and time-frequency analysis of the pipeline and rail potentials. A typical application case for each method is indicated, and the advantages and disadvantages of each research technique are identified. The criterion for selecting methods for this review was a short measurement duration (tens of minutes), after which it is possible to determine the level of the hazard to the gas pipeline caused by stray currents in the examined location. This is why these methods have an advantage over other research techniques that require long-term monitoring or exposure of probes or sensors. The review will be useful for cathodic protection personnel involved in the operation of gas pipelines and may be helpful in developing new methods for assessing the impact of stray currents. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering: 2nd Edition)

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18 pages, 9888 KB

Open AccessEditor’s ChoiceArticle

Measuring and Simulating Wind Farm Wakes in the North Sea for Use in Assessing Other Regions

by Richard J. Foreman, Cristian Birzer and Beatriz Cañadillas

Energies 2025, 18(20), 5538; https://doi.org/10.3390/en18205538 - 21 Oct 2025

Viewed by 1333

Abstract

“Wind theft”, the extraction of upstream wind resources by neighboring wind farms on account of wind farm or cluster wakes, is receiving wider popular attention. Cluster wakes need to be accounted for in wider planning strategies, for which measurements and wake models can [...] Read more.

“Wind theft”, the extraction of upstream wind resources by neighboring wind farms on account of wind farm or cluster wakes, is receiving wider popular attention. Cluster wakes need to be accounted for in wider planning strategies, for which measurements and wake models can be deployed to aid this process. To contribute to such planning measures, a flight campaign for investigating cluster waking and other phenomena in the North Sea was conducted in 2020 and 2021 to contribute extra flight data obtained during the first flight campaign of 2016 and 2017. We report the latest results of the 2020–2021 flight campaign following the work and methodology of Cañadillas et al. (2020), where, using the 2016–2017 flight measurements, wake lengths extending up to approximately 60 km in stable stratification were inferred, consistent with an explicit stability-dependent analytical model. Analysis of the recent 2020–2021 flight data is approximately consistent with the results of Cañadillas et al. (2020) in stable conditions, albeit with greater scatter. This is because Cañadillas et al. (2020) analyzed only flights in which the wind conditions remained nearly constant during the measurement period, whereas the current dataset includes more variable conditions. Comparisons with the analytical-based engineering model show good first-order agreement with the flight data, but higher-order effects, such as flow non-homogeneity, are not accounted for. The application of these results to the stability information for developing offshore wind energy regions such as the East Coast of the USA and Bass Strait, Australia gives an outline of the expected wake lengths there. Simple engineering models, such as that demonstrated here, though primarily designed for commercial applications, need to be further developed into advanced spatial planning frameworks for offshore wind energy areas. Full article

(This article belongs to the Special Issue Advancements in Wind Farm Design and Optimization)

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19 pages, 4673 KB

Open AccessEditor’s ChoiceArticle

Scaling of Automotive Fuel Cells in Terms of Operating Indicators

by Ireneusz Pielecha and Piotr Pielecha

Energies 2025, 18(20), 5513; https://doi.org/10.3390/en18205513 - 19 Oct 2025

Viewed by 1223

Abstract

The search for alternatives to fossil fuels has led to hydrogen becoming an important factor in the powering means of transportation. Its most effective application is in fuel cells. A single fuel cell is not a sufficient source of power, which is why [...] Read more.

The search for alternatives to fossil fuels has led to hydrogen becoming an important factor in the powering means of transportation. Its most effective application is in fuel cells. A single fuel cell is not a sufficient source of power, which is why a stack of fuel cells is the more common solution. Fuel cells are tested using single units, as this allows all cell parameters (the current density, flow rates and efficiency) to be evaluated. Therefore, the scalability of fuel cells is an essential factor. This paper analyses the scalability of fuel cells with a power of approximately 100 kW and 1.2 kW. Road tests of the fuel cells were compared with stationary tests, which allowed the load to be reproduced and scaled. This provided a representation of the scaled current and the scalable power of the fuel cell. The research provided voltage–current characteristics of fuel cell stacks and their individual equivalents. It was concluded that regardless of the power scaling or current values, the characteristics obtain similar patterns. A very important element of the research is the awareness of the properties of these cells (the number of cells and active charge exchange area) in order to compare the unit characteristics of fuel cells. Full article

(This article belongs to the Special Issue Sustainable Development of Fuel Cells and Hydrogen Technologies)

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27 pages, 1246 KB

Open AccessEditor’s ChoiceReview

Hydrogen Safety in Energy Infrastructure: A Review

by Eva Gregorovičová and Jiří Pospíšil

Energies 2025, 18(20), 5470; https://doi.org/10.3390/en18205470 - 17 Oct 2025

Cited by 4 | Viewed by 2183

Abstract

For the transition to emission-free or low-emission energy, hydrogen is a promising energy carrier and fuel of the future with the possibility of long-term storage. Due to its specific properties, it poses certain safety risks; therefore, it is necessary to have a comprehensive [...] Read more.

For the transition to emission-free or low-emission energy, hydrogen is a promising energy carrier and fuel of the future with the possibility of long-term storage. Due to its specific properties, it poses certain safety risks; therefore, it is necessary to have a comprehensive understanding of hydrogen. This review article contains ten main chapters and provides, by synthesizing current findings primarily from standards and scientific studies (predominantly from 2023 to 2024), the theoretical basis for further research directed toward safe hydrogen infrastructure. Full article

(This article belongs to the Special Issue Improving Hydrogen Safety for Energy Applications)

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24 pages, 2699 KB

Open AccessEditor’s ChoiceArticle

Digital Twin Framework for Energy Transition in Gas Networks Based on Open-Source Tools: Methodology and Case Study in Southern Italy

by Filippo Luca Alberto Munafò, Ben Alex Baby, Tancredi Testasecca, Marco Ferraro and Marco Beccali

Energies 2025, 18(20), 5434; https://doi.org/10.3390/en18205434 - 15 Oct 2025

Viewed by 1073

Abstract

The ongoing digitalization of energy infrastructure is a crucial enabler for improving efficiency, reliability, and sustainability in gas distribution networks, especially in the context of decarbonization and the integration of alternative energy carriers (e.g., renewable gases including biogas, green hydrogen). This study presents [...] Read more.

The ongoing digitalization of energy infrastructure is a crucial enabler for improving efficiency, reliability, and sustainability in gas distribution networks, especially in the context of decarbonization and the integration of alternative energy carriers (e.g., renewable gases including biogas, green hydrogen). This study presents the development and application of a Digital Twin framework for a real-world gas distribution network developed using open-source tools. The proposed methodology covers the entire digital lifecycle: from data acquisition through smart meters and GIS mapping, to 3D modelling and simulation using tools such as QGIS, FreeCAD, and GasNetSim. Consumption data are collected, processed, and harmonized via Python-based workflows, hourly simulations of network operation, including pressure, flow rate, and gas quality indicators like the Wobbe Index. Results demonstrate the effectiveness of the Digital Twin in accurately replicating real network behavior and supporting scenario analyses for the introduction of greener energy vectors such as hydrogen or biomethane. The case study highlights the flexibility and transparency of the workflow, as well as the critical importance of data quality and availability. The framework provides a robust basis for advanced network management, optimization, and planning, offering practical tools to support the energy transition in the gas sector. Full article

(This article belongs to the Special Issue Decarbonizing Smart Buildings and Energy Systems: Digital Twins, Advanced Models and Optimization Algorithms)

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31 pages, 1516 KB

Open AccessEditor’s ChoiceArticle

Federated Quantum Machine Learning for Distributed Cybersecurity in Multi-Agent Energy Systems

by Kwabena Addo, Musasa Kabeya and Evans Eshiemogie Ojo

Energies 2025, 18(20), 5418; https://doi.org/10.3390/en18205418 - 14 Oct 2025

Cited by 2 | Viewed by 1263

Abstract

The increasing digitization and decentralization of modern energy systems have heightened their vulnerability to sophisticated cyber threats, necessitating advanced, scalable, and privacy-preserving detection frameworks. This paper introduces a novel Federated Quantum Machine Learning (FQML) framework tailored for anomaly detection in multi-agent energy environments. [...] Read more.

The increasing digitization and decentralization of modern energy systems have heightened their vulnerability to sophisticated cyber threats, necessitating advanced, scalable, and privacy-preserving detection frameworks. This paper introduces a novel Federated Quantum Machine Learning (FQML) framework tailored for anomaly detection in multi-agent energy environments. By integrating parameterized quantum circuits (PQCs) at the local agent level with secure federated learning protocols, the framework enhances detection accuracy while preserving data privacy. A trimmed-mean aggregation scheme and differential privacy mechanisms are embedded to defend against Byzantine behaviors and data-poisoning attacks. The problem is formally modeled as a constrained optimization task, accounting for quantum circuit depth, communication latency, and adversarial resilience. Experimental validation on synthetic smart grid datasets demonstrates that FQML achieves high detection accuracy (≥96.3%), maintains robustness under adversarial perturbations, and reduces communication overhead by 28.6% compared to classical federated baselines. These results substantiate the viability of quantum-enhanced federated learning as a practical, hardware-conscious approach to distributed cybersecurity in next-generation energy infrastructures. Full article

(This article belongs to the Special Issue AI-Driven Sustainable Power Grids: Enhancing Cybersecurity, Operation, and Control of Conventional, Modern, and Renewable-Based Energy Systems)

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16 pages, 2085 KB

Open AccessEditor’s ChoiceReview

Robotics and Automation for Energy Efficiency and Sustainability in the Industry 4.0 Era: A Review

by Zsolt Buri and Judit T. Kiss

Energies 2025, 18(20), 5399; https://doi.org/10.3390/en18205399 - 14 Oct 2025

Viewed by 2278

Abstract

Robotisation is playing an increasingly important role in economic and technological life today. Industrial robotisation has a significant impact on the efficiency and productivity of manufacturing companies, and service robots are becoming more and more common in everyday life. The main objective of [...] Read more.

Robotisation is playing an increasingly important role in economic and technological life today. Industrial robotisation has a significant impact on the efficiency and productivity of manufacturing companies, and service robots are becoming more and more common in everyday life. The main objective of our research is to examine the impact of robotisation on energy consumption and sustainability, as well as the technological and corporate challenges facing the integration of robots. The research is based on a literature review, which we supplemented with a bibliographic analysis. In terms of methods, we relied on the Global Citation Score, Co-Coupling Network Analysis, and Burst Analysis. Our results suggest that research on industrial robotisation can be divided into complementary dimensions, ranging from engineering-level trajectory optimization and subsystem design to system-level modeling, macroeconomic sustainability analysis, and data-driven optimization. The findings highlight that the positive impacts of robotisation on both energy efficiency and carbon reduction can be maximized when these approaches are integrated into a systemic framework that connects micro- and macro-level perspectives. Full article

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35 pages, 12982 KB

Open AccessEditor’s ChoiceArticle

A Data-Driven Decision-Making Tool for Prioritizing Resilience Strategies in Cold-Climate Urban Neighborhoods

by Ahmed Nouby Mohamed Hassan and Caroline Hachem-Vermette

Energies 2025, 18(20), 5421; https://doi.org/10.3390/en18205421 - 14 Oct 2025

Cited by 1 | Viewed by 1041

Abstract

Cold-climate urban neighborhoods face mounting energy and thermal risks from extreme weather and power outages, creating trade-offs between different resilience capacities and objectives. This study develops a scalable, data-driven decision-making tool to support early-stage prioritization of resilience strategies at both the building component [...] Read more.

Cold-climate urban neighborhoods face mounting energy and thermal risks from extreme weather and power outages, creating trade-offs between different resilience capacities and objectives. This study develops a scalable, data-driven decision-making tool to support early-stage prioritization of resilience strategies at both the building component and neighborhood levels. A database of 48 active and passive strategies was systematically linked to 14 resilience objectives, reflecting energy- and thermally oriented capacities. Each strategy–objective pair was qualitatively assessed through a literature review and translated into probability distributions. Monte Carlo simulations (10,000 iterations) were performed to generate possible outcomes and several scores were calculated. Comparative scenario analysis—spanning holistic, short-term, long-term, energy-oriented, and thermally oriented perspectives—highlighted distinct adoption patterns. Active energy strategies, such as ESS, decentralized RES, microgrids, and CHP, consistently achieved the highest adoption (A) scores across levels and scenarios. Several passive measures, including green roofs, natural ventilation with passive heat recovery, and responsive glazing, also demonstrated strong multi-objective performance and outage resilience. A case study application integrated stakeholder-specific objective weightings, revealing convergent strategies suitable for immediate adoption and divergent ones requiring negotiation. This tool provides an adaptable probabilistic foundation for evaluating resilience strategies under uncertainty. Full article

(This article belongs to the Special Issue Climate Change in Power and Energy Systems: Challenges, Innovations, and Solutions)

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29 pages, 1859 KB

Open AccessEditor’s ChoiceReview

Advancements in Food Waste Recycling Technologies in South Africa: Novel Approaches for Biofertilizer and Bioenergy Production—A Review

by Samukelo Zwelokuthula Mngadi, Emmanuel Kweinor Tetteh, Siphesihle Mangena Khumalo and Sudesh Rathilal

Energies 2025, 18(20), 5396; https://doi.org/10.3390/en18205396 - 13 Oct 2025

Cited by 1 | Viewed by 1487

Abstract

Globally, tons of agricultural and food waste are inevitably produced daily due to increasing population demands. As fertilizer prices surge and environmental degradation worsens, sustainable farming practices are gaining attention, especially with circular economic principles. This study explores how food waste can be [...] Read more.

Globally, tons of agricultural and food waste are inevitably produced daily due to increasing population demands. As fertilizer prices surge and environmental degradation worsens, sustainable farming practices are gaining attention, especially with circular economic principles. This study explores how food waste can be repurposed into biofertilizers and bioenergy using advanced technologies like anaerobic digestion, composting, pyrolysis, and heat treatment. These methods are evaluated for their effectiveness in recovering essential nutrients (nitrogen, phosphorus, and potassium) and generating energy, alongside their sustainability and cost-effectiveness. Data trends reveal a significant rise in studies focused on “circular economy” and “food waste valorization.” Early findings highlight anaerobic digestion and composting as the most practical approaches, offering efficient nutrient recovery and minimal greenhouse gas emissions. Overall, the integration of food waste recycling with sustainable agricultural practices presents a powerful path toward mitigating environmental impact, lowering fertilizer costs, and supporting global food security through circular economic solutions. Full article

(This article belongs to the Special Issue Green Additive for Biofuel Energy Production)

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25 pages, 1120 KB

Open AccessEditor’s ChoiceSystematic Review

Systematic Review of Biomass Supercritical Water Gasification for Energy Production

by Filipe Neves, Armando A. Soares and Abel Rouboa

Energies 2025, 18(20), 5374; https://doi.org/10.3390/en18205374 - 12 Oct 2025

Cited by 2 | Viewed by 1861

Abstract

Due to the growing global population, rising energy demands, and the environmental impacts of fossil fuel use, there is an urgent need for sustainable energy sources. Biomass conversion technologies have emerged as a promising solution, particularly supercritical water gasification (SCWG), which enables efficient [...] Read more.

Due to the growing global population, rising energy demands, and the environmental impacts of fossil fuel use, there is an urgent need for sustainable energy sources. Biomass conversion technologies have emerged as a promising solution, particularly supercritical water gasification (SCWG), which enables efficient energy recovery from wet and dry biomass. This systematic review, following PRISMA 2020 guidelines, analyzed 51 peer-reviewed studies published between 2015 and 2025. The number of publications has increased over the decade, reflecting rising interest in SCWG for energy production. Research has focused on six biomass feedstock categories, with lignocellulosic and wet biomasses most widely studied. Reported energy efficiencies ranged from ~20% to >80%, strongly influenced by operating conditions and system integration. Integrating SCWG with solid oxide fuel cells, organic Rankine cycles, carbon capture and storage, or solar input enhanced both energy recovery and environmental performance. While SCWG demonstrates lower greenhouse gas emissions than conventional methods, many studies lacked comprehensive life cycle or economic analyses. Common limitations include high energy demand, modeling simplifications, and scalability challenges. These trends highlight both the potential and the barriers to advancing SCWG as a viable biomass-to-energy technology. Full article

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54 pages, 5812 KB

Open AccessEditor’s ChoiceReview

Advancing Renewable-Dominant Power Systems Through Internet of Things and Artificial Intelligence: A Comprehensive Review

by Temitope Adefarati, Gulshan Sharma, Pitshou N. Bokoro and Rajesh Kumar

Energies 2025, 18(19), 5243; https://doi.org/10.3390/en18195243 - 2 Oct 2025

Cited by 4 | Viewed by 2121

Abstract

The sudden increase in global energy demand has prompted the integration of Artificial Intelligence and the Internet of Things into the utility grid. The synergy of Artificial Intelligence and the Internet of Things in renewable energy sources has emerged as a promising solution [...] Read more.

The sudden increase in global energy demand has prompted the integration of Artificial Intelligence and the Internet of Things into the utility grid. The synergy of Artificial Intelligence and the Internet of Things in renewable energy sources has emerged as a promising solution for the development of smart grids and a transformative catalyst that restructures centralized power systems into resilient and sustainable systems. The state-of-the-art of the Internet of Things and Artificial Intelligence is presented in this paper to support the design, planning, operation, management and optimization of renewable energy-based power systems. This paper outlines the benefits of smart and resilient energy systems and the contributions of the Internet of Things across several applications, devices and networks. Artificial Intelligence can be utilized for predictive maintenance, demand-side management, fault detection, forecasting and scheduling. This paper highlights crucial future research directions aimed at overcoming the challenges that are associated with the adoption of emerging technologies in the power system by focusing on market policy and regulation and the human-centric and ethical aspects of Artificial Intelligence and the Internet of Things. The outcomes of this study can be used by policymakers, researchers and development agencies to improve global access to electricity and accelerate the development of sustainable energy systems. Full article

(This article belongs to the Special Issue AI-Driven Sustainable Power Grids: Enhancing Cybersecurity, Operation, and Control of Conventional, Modern, and Renewable-Based Energy Systems)

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22 pages, 2187 KB

Open AccessEditor’s ChoiceReview

Artificial Intelligence and Digital Twins for Bioclimatic Building Design: Innovations in Sustainability and Efficiency

by Ekaterina Filippova, Sattar Hedayat, Tina Ziarati and Matteo Manganelli

Energies 2025, 18(19), 5230; https://doi.org/10.3390/en18195230 - 1 Oct 2025

Cited by 7 | Viewed by 2470

Abstract

The integration of artificial intelligence (AI) into bioclimatic building design is reshaping the architecture, engineering, and construction (AEC) industry by addressing critical challenges in sustainability and efficiency. By aligning structures with local climates, bioclimatic design addresses global challenges such as energy consumption, urbanization, [...] Read more.

The integration of artificial intelligence (AI) into bioclimatic building design is reshaping the architecture, engineering, and construction (AEC) industry by addressing critical challenges in sustainability and efficiency. By aligning structures with local climates, bioclimatic design addresses global challenges such as energy consumption, urbanization, and climate change. Complementing these principles, AI technologies—including machine learning, digital twins, and generative algorithms—are revolutionizing the sector by optimizing processes across the entire building lifecycle, from design and construction to operation and maintenance. Amid the diverse array of AI-driven innovations, this research highlights digital twin (DT) technologies as a key to AI-driven transformation, enabling real-time monitoring, simulation, and optimization for sustainable design. Applications like façade optimization, energy flow analysis, and predictive maintenance showcase their role in adaptive architecture, while frameworks like Construction 4.0 and 5.0 promote human-centric, data-driven sustainability. By bridging AI with bioclimatic design, the findings contribute to a vision of a built environment that seamlessly aligns environmental sustainability with technological advancement and societal well-being, setting new standards for adaptive and resilient architecture. Despite the immense potential, AI and DTs face challenges like high computational demands, regulatory barriers, interoperability and skill gaps. Overcoming these challenges will be crucial for maximizing the impact on sustainable building, requiring ongoing research to ensure scalability, ethics, and accessibility. Full article

(This article belongs to the Special Issue New Insights into Hybrid Renewable Energy Systems in Buildings)

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37 pages, 3155 KB

Open AccessEditor’s ChoiceReview

Decarbonising the Inland Waterways: A Review of Fuel-Agnostic Energy Provision and the Infrastructure Challenges

by Paul Simavari, Kayvan Pazouki and Rosemary Norman

Energies 2025, 18(19), 5146; https://doi.org/10.3390/en18195146 - 27 Sep 2025

Cited by 1 | Viewed by 1392

Abstract

Inland Waterway Transport (IWT) is widely recognised as an energy-efficient freight mode, yet its decarbonisation is increasingly constrained not by propulsion technology, but by the absence of infrastructure capable of delivering clean energy where and when it is needed. This paper presents a [...] Read more.

Inland Waterway Transport (IWT) is widely recognised as an energy-efficient freight mode, yet its decarbonisation is increasingly constrained not by propulsion technology, but by the absence of infrastructure capable of delivering clean energy where and when it is needed. This paper presents a structured review of over a decade of academic, policy and technical literature, identifying systemic gaps in current decarbonisation strategies. The analysis shows that most pilot projects are vessel-specific, and poorly scalable, with infrastructure planning rarely based on vessel-level energy demand data, leaving energy provision as an afterthought. Current approaches overemphasise technology readiness while neglecting the complexity of aligning supply chains, operational diversity, and infrastructure deployment. This review reframes IWT decarbonisation as a problem of provision, not propulsion. It calls for demand-led, demand driven, fuel agnostic infrastructure models and proposes a roadmap that integrates technical, operational, and policy considerations. Without rethinking energy access as a core design challenge—on par with vessel systems and regulatory standards—the sector risks investing in stranded assets and missing climate and modal shift targets. Aligning vessel operations with dynamic, scalable energy delivery systems is essential to achieve a commercially viable, fully decarbonised IWT sector. Full article

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34 pages, 3251 KB

Open AccessEditor’s ChoiceArticle

Stochastic Markov-Based Modelling of Residential Lighting Demand in Luxembourg: Integrating Occupant Behavior and Energy Efficiency

by Vahid Arabzadeh and Raphael Frank

Energies 2025, 18(19), 5133; https://doi.org/10.3390/en18195133 - 26 Sep 2025

Cited by 3 | Viewed by 997

Abstract

This study presents a stochastic Markov-based modeling framework for occupant behavior and residential lighting demand in Luxembourg. Integrating demographic data, time-use surveys, Markov chains, and dual-layer optimization, the model enhances the accuracy of non-HVAC energy demand simulations. The Harmonized European Time Use Surveys [...] Read more.

This study presents a stochastic Markov-based modeling framework for occupant behavior and residential lighting demand in Luxembourg. Integrating demographic data, time-use surveys, Markov chains, and dual-layer optimization, the model enhances the accuracy of non-HVAC energy demand simulations. The Harmonized European Time Use Surveys (HETUS) provide a detailed activity-based energy modeling approach, while Bayesian and constraint-based optimization improve data calibration and reduce modeling uncertainties. A Luxembourg-specific stochastic load profile generator links occupant activities to energy loads, incorporating occupancy patterns and daylight illuminance calculations. This study quantifies lighting demand variations across household types, validating results against empirical TUS data with a low mean squared error (MSE) and a minor deviation of +3.42% from EU residential lighting demand standards. Findings show that activity-aware dimming can reduce lighting demand by 30%, while price-based dimming achieves a 21.60% reduction in power demand. The proposed approach provides data-driven insights for energy-efficient residential lighting management, supporting sustainable energy policies and household-level optimization. Full article

(This article belongs to the Topic Intelligent and Flexible Energy Management Strategies (EMSs) and Technologies)

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22 pages, 1203 KB

Open AccessEditor’s ChoiceReview

Modelling Syngas Combustion from Biomass Gasification and Engine Applications: A Comprehensive Review

by José Ramón Copa Rey, Andrei Longo, Bruna Rijo, Cecilia Mateos-Pedrero, Paulo Brito and Catarina Nobre

Energies 2025, 18(19), 5112; https://doi.org/10.3390/en18195112 - 25 Sep 2025

Cited by 2 | Viewed by 4149

Abstract

Syngas, a renewable fuel primarily composed of hydrogen and carbon monoxide, is emerging as a viable alternative to conventional fossil fuels in internal combustion engines (ICEs). Obtained mainly through the gasification of biomass and organic waste, syngas offers significant environmental benefits but also [...] Read more.

Syngas, a renewable fuel primarily composed of hydrogen and carbon monoxide, is emerging as a viable alternative to conventional fossil fuels in internal combustion engines (ICEs). Obtained mainly through the gasification of biomass and organic waste, syngas offers significant environmental benefits but also presents challenges due to its lower heating value and variable composition. This review establishes recent advances in understanding syngas combustion, chemical kinetics, and practical applications in spark-ignition (SI) and compression-ignition (CI) engines. Variability in syngas composition, dependent on feedstock and gasification conditions, strongly influences ignition behavior, flame stability, and emissions, demanding detailed kinetic models and adaptive engine control strategies. In SI engines, syngas can replace up to 100% of conventional fuel, typically at 20–30% reduced power output. CI engines generally require a pilot fuel representing 10–20% of total energy to start combustion, favoring dual-fuel (DF) operation for efficiency and emissions control. This work underlines the need to integrate advanced modelling approaches with experimental insights to optimize performance and meet emission targets. By addressing challenges of fuel variability and engine adaptation, syngas reveals promising potential as a clean fuel for future sustainable power generation and transport applications. Full article

(This article belongs to the Section B: Energy and Environment)

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15 pages, 132684 KB

Open AccessEditor’s ChoiceArticle

Overcoming Variable Illumination in Photovoltaic Snow Monitoring: A Real-Time Robust Drone-Based Deep Learning Approach

by Amna Mazen, Ashraf Saleem, Kamyab Yazdipaz and Ana Dyreson

Energies 2025, 18(19), 5092; https://doi.org/10.3390/en18195092 - 25 Sep 2025

Cited by 1 | Viewed by 872

Abstract

Snow accumulation on photovoltaic (PV) panels can cause significant energy losses in cold climates. While drone-based monitoring offers a scalable solution, real-world challenges like varying illumination can hinder accurate snow detection. We previously developed a YOLO-based drone system for snow coverage detection using [...] Read more.

Snow accumulation on photovoltaic (PV) panels can cause significant energy losses in cold climates. While drone-based monitoring offers a scalable solution, real-world challenges like varying illumination can hinder accurate snow detection. We previously developed a YOLO-based drone system for snow coverage detection using a Fixed Thresholding segmentation method to discriminate snow from the solar panel; however, it struggled in challenging lighting conditions. This work addresses those limitations by presenting a reliable drone-based system to accurately estimate the Snow Coverage Percentage (SCP) over PV panels. The system combines a lightweight YOLOv11n-seg deep learning model for panel detection with an adaptive image processing algorithm for snow segmentation. We benchmarked several segmentation models, including MASK R-CNN and the state-of-the-art SAM2 segmentation model. YOLOv11n-seg was selected for its optimal balance of speed and accuracy, achieving 0.99 precision and 0.80 recall. To overcome the unreliability of static thresholding under changing lighting, various dynamic methods were evaluated. Otsu’s algorithm proved most effective, reducing the absolute error of the mean in SCP estimation to just 1.1%, a significant improvement over the 13.78% error from the previous fixed-thresholding approach. The integrated system was successfully validated for real-time performance on live drone video streams, demonstrating a highly accurate and scalable solution for autonomous snow monitoring on PV systems. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 3rd Edition)

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21 pages, 1816 KB

Open AccessEditor’s ChoiceArticle

Progress Towards Affordable and Clean Energy: A Comparative Analysis of SDG7 Implementation

by Beata Bieszk-Stolorz and Joanna Landmesser-Rusek

Energies 2025, 18(19), 5078; https://doi.org/10.3390/en18195078 - 24 Sep 2025

Cited by 3 | Viewed by 1777

Abstract

Progress towards Sustainable Development Goal 7 (SDG7) is currently insufficient to achieve. It is particularly important to ensure that all people have access to sustainable, reliable and affordable energy. As SDG7 is linked to other goals, a lack of progress in its implementation [...] Read more.

Progress towards Sustainable Development Goal 7 (SDG7) is currently insufficient to achieve. It is particularly important to ensure that all people have access to sustainable, reliable and affordable energy. As SDG7 is linked to other goals, a lack of progress in its implementation could disrupt the entire sustainable development process. The aim of our article is to compare selected countries around the world in terms of the degree of SDG7 implementation and its dynamics in the years 2000–2022. We assessed the degree of SDG7 implementation using Hellwig’s method in the dynamic approach, and we compared the dynamics of the degree of implementation using the dynamic time warping (DTW) method and hierarchical clustering. The cluster of countries with the highest degree of SDG7 implementation included the European countries of Norway, Sweden and Iceland. The lowest degree of implementation was observed in Belarus, Uzbekistan and Turkmenistan. The dynamic approach to the problem allowed us to conclude that there was an increase in the synthetic measure in all the countries analysed in the period 2000–2022, with the strongest increase observed in the countries with the lowest initial degree of SDG7 implementation (Belarus, Uzbekistan, Turkmenistan). Full article

(This article belongs to the Special Issue Towards Sustainable Energy Development: Energy Efficiency and Economic Growth)

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