Energies

19 pages, 1575 KB

Open AccessArticle

Comparative Investigation of Hydrogen Production from Polyethylene, Polypropylene, and Garden Residues and Their Blends by Gasification

by Betul Colak Karadag, Ali Atas, Nader Javani and Ozgun Yucel

Energies 2026, 19(17), 4229; https://doi.org/10.3390/en19174229 - 7 Sep 2026

Abstract

The current study investigates hydrogen-rich syngas production from polyethylene (PE), polypropylene (PP), garden waste (GW), and their co-gasification blends using Aspen Plus simulations. A thermodynamic equilibrium model based on Gibbs free-energy minimization was developed and validated using experimental data reported in the literature. [...] Read more.

The current study investigates hydrogen-rich syngas production from polyethylene (PE), polypropylene (PP), garden waste (GW), and their co-gasification blends using Aspen Plus simulations. A thermodynamic equilibrium model based on Gibbs free-energy minimization was developed and validated using experimental data reported in the literature. The developed model can assess how gasification temperature and equivalence ratio (ER) affect syngas composition and H₂ mole fraction. Validation results demonstrated acceptable agreement with experimental data, yielding root mean square error (RMSE) values of 2.25, 4.38, and 4.75 for PE, PP, and GW gasification, respectively. The results showed that increasing temperature enhanced the H₂ and CO mole fractions while reducing the CO₂ and CH₄ mole fractions. Among the individual feedstocks, GW exhibited the highest H₂ mole fraction, reaching 0.250 at 750 °C. Among the co-gasification blends, the maximum H₂ mole fractions were 0.208 for the polypropylene–garden waste (PP + GW) blend, 0.2205 for the polyethylene–garden waste (PE + GW) blend, and 0.222 for the polypropylene–polyethylene–garden waste (PP + PE + GW) blend. The ternary PP + PE + GW blend therefore exhibited the highest H₂ mole fraction among the blended systems under the temperature analysis. The ER analysis showed maximum H₂ mole fractions of 0.218 for PP + GW at an ER of 0.27, 0.212 for PE + GW at an ER of 0.28, and 0.211 for PP + PE + GW at an ER of 0.28. The findings demonstrate that plastic–biomass co-gasification provides favorable syngas characteristics and enables the utilization of mixed waste resources for hydrogen-rich syngas production. Overall, the developed Aspen Plus model provides a reliable tool for evaluating plastic–biomass co-gasification systems and supports the utilization of mixed waste resources for H₂ mole fractions and waste-to-energy applications. Full article

(This article belongs to the Topic Biomass for Energy, Chemicals and Materials)

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32 pages, 8994 KB

Open AccessArticle

Data-Driven Fault Ride-Through Operation of Distributed Grid-Forming Inverters Using Multi-Agent Reinforcement Learning

by Shyamal S. Chand, Arman Ali, Sohail A. Ali, Maurizio Cirrincione and Branislav Hredzak

Energies 2026, 19(17), 4228; https://doi.org/10.3390/en19174228 - 7 Sep 2026

Abstract

Grid-forming inverters (GFMIs) are essential for future low-inertia power systems because they establish voltage and frequency rather than simply following the grid. However, compared with synchronous machines, they have limited overload and fault current capability, so providing reliable fault ride-through (FRT)/low-voltage ride-through (LVRT) [...] Read more.

Grid-forming inverters (GFMIs) are essential for future low-inertia power systems because they establish voltage and frequency rather than simply following the grid. However, compared with synchronous machines, they have limited overload and fault current capability, so providing reliable fault ride-through (FRT)/low-voltage ride-through (LVRT) behavior requires specially designed control strategies. This study proposes a multi-agent reinforcement learning inspired technique for the parameter selection of virtual synchronous generator (VSG)-controlled GFMIs through independent twin delayed deep deterministic policy gradient (TD3PG) agents, considering symmetrical and asymmetrical grid faults on the IEEE 13 bus network. The methodology utilizes power flow errors and voltage unbalance factors as key observational inputs within the MATLAB/Simulink^® 2023b environment. The policies are designed to modify the inertia and damping coefficients of the active power controller, as well as the proportional–integral gains of the reactive power controller to enhance stability in response to grid disturbances. The efficacy of this approach was evaluated against a conventional VSG control approach and VSG with virtual impedance and dynamic current saturation across multiple inverters with different power ratings. The proposed reinforcement learning assisted control embedded with current limiting consistently showed reductions in peak fault current of approximately 10–12% as well as reductions in active and reactive power settling times from around 3.50–5 s to about 1–1.50 s. In addition, it also limits fault currents to below 1.25 p.u. during disturbance intervals, thereby enabling continuous operation of inverters with a wide range of power ratings under both symmetrical and asymmetrical fault conditions. Full article

(This article belongs to the Section F1: Electrical Power System)

24 pages, 21810 KB

Open AccessArticle

A Dual-Stream Network with Dynamic Graph Convolution and Attention-Based BiGRU for IGBT Open-Circuit Fault Diagnosis in T-NPC Three-Level Inverters

by Lin Bai, Bo Guo, Weiye Jing, Feng Li and Wei Luo

Energies 2026, 19(17), 4227; https://doi.org/10.3390/en19174227 - 7 Sep 2026

Abstract

Existing CNN, TCN, residual, and lightweight network methods have achieved good performance in IGBT open-circuit fault diagnosis, but they often overlook the non-Euclidean relationships among signals. To address this limitation, this paper proposes a parallel graph–temporal network for T-NPC three-level inverters. A shared [...] Read more.

Existing CNN, TCN, residual, and lightweight network methods have achieved good performance in IGBT open-circuit fault diagnosis, but they often overlook the non-Euclidean relationships among signals. To address this limitation, this paper proposes a parallel graph–temporal network for T-NPC three-level inverters. A shared CNN extracts compact features from the three-phase currents and voltages, while the Sinkhorn–Wasserstein distance constructs a sample-level weighted dynamic graph for GCN-based relationship extraction. In parallel, BiGRU with global attention captures temporal information. Unlike fixed or equally weighted graphs, the proposed method adapts signal connections to different fault conditions. Furthermore, simulation models are constructed in MATLAB/Simulink, and the T-NPC converter operation is emulated on a real-time simulator Starsim MT6060. The proposed dual-stream model classifies 21 fault states, achieving an average validation accuracy of 99.88%, while maintaining high accuracy under severe noise. Full article

(This article belongs to the Special Issue Condition Monitoring, Reliability Analysis, and Fault Detection of Power Electronics)

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44 pages, 32541 KB

Open AccessReview

Hybrid and All-Electric Civil and Military Ships: From Maritime Decarbonisation Drivers to Integrated Energy System Architectures

by Jorge do Vale, João F. P. Fernandes, Mário Monteiro Marques and P. J. Costa Branco

Energies 2026, 19(17), 4226; https://doi.org/10.3390/en19174226 - 7 Sep 2026

Abstract

The maritime sector is undergoing rapid change due to stricter environmental regulations, shifting policies, and growing concerns about energy security and operational resilience. In this landscape, hybrid and all-electric ships (AES) are gaining recognition as effective solutions for reducing emissions, boosting efficiency, and [...] Read more.

The maritime sector is undergoing rapid change due to stricter environmental regulations, shifting policies, and growing concerns about energy security and operational resilience. In this landscape, hybrid and all-electric ships (AES) are gaining recognition as effective solutions for reducing emissions, boosting efficiency, and harnessing alternative energy sources. Nonetheless, many electrification initiatives mainly target propulsion, while the entire onboard energy infrastructure, including generation, storage, distribution, power conversion, and energy management, is often developed separately. This paper investigates hybrid and AES systems linking maritime decarbonisation goals to the development of integrated onboard energy architectures. It starts with an overview of key international, European, and Portuguese policies that impact maritime decarbonisation, emphasising their influence on both the commercial and military sectors. The literature review then charts the evolution of onboard power systems, showing the shift from mechanical propulsion to integrated power solutions. Finally, it analyses different architectural configurations, energy storage technologies, alternative energy sources, and energy management strategies found in current research. Our analysis shows that adopting hybrid and AES systems requires a comprehensive system-level strategy that links power generation, storage, distribution, operational profiles, and energy management. By combining policy initiatives, technological progress, and current research, our review highlights the crucial role of integrated energy system architectures in the development of future hybrid and AES systems. We also identify key research gaps, such as multi-domain modelling, consistent performance metrics, mission-oriented energy management, and assessments of long-term robustness and operational sustainability. Full article

(This article belongs to the Section F: Electrical Engineering)

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25 pages, 809 KB

Open AccessArticle

Nuclear Energy Development and Energy Security in Slovakia: Current Status and Conditional Prospects up to 2050

by Jacek Dworzecki and Izabela Nowicka

Energies 2026, 19(17), 4225; https://doi.org/10.3390/en19174225 - 7 Sep 2026

Abstract

This article evaluates how nuclear energy development may affect energy security and nuclear energy security in Slovakia up to 2050. It applies a qualitative-dominant mixed-method design combining critical source-position appraisal, a claim-evidence matrix, quantitative reconstruction of the 2021–2024 electricity balance, comparison of three [...] Read more.

This article evaluates how nuclear energy development may affect energy security and nuclear energy security in Slovakia up to 2050. It applies a qualitative-dominant mixed-method design combining critical source-position appraisal, a claim-evidence matrix, quantitative reconstruction of the 2021–2024 electricity balance, comparison of three official 2040 adequacy scenarios, stress tests for a 1200 MW large reactor and a 300 MW small modular reactor (SMR), and negative-case analysis. The results show that Slovakia entered 2024 as a net electricity exporter after Mochovce Unit 3 increased nuclear generation, while electricity consumption remained 3.1 TWh below 2021. The decline from 2021 to 2022 reflected a combination of the energy-price shock, industrial demand curtailment, lower fossil generation and hydrological variability rather than a single structural factor. Official 2040 scenarios project gross generation of 43.9–48.5 TWh, of which nuclear contributes 24.2–26.7 TWh, approximately 55%. Adding a 1200 MW unit would generate about 8.4–10.0 TWh annually at capacity factors of 80–95%, creating a material need for demand growth, exports, storage, nuclear heat, hydrogen or load-following operation. The analysis therefore does not treat the Bohunice project or SMRs as inevitable. Their contribution to energy security is conditional on financing, licensing, fuel diversification, grid flexibility, heat off-takers, climate-resilient cooling, radioactive-waste governance, workforce continuity and transparent public governance. A diversified pathway combining safe long-term operation of existing units, renewables, wind development, storage, demand response and selective nuclear investment is more robust than a single-project strategy. Full article

(This article belongs to the Section B4: Nuclear Energy)

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15 pages, 3871 KB

Open AccessArticle

Ambient Temperature-Dependent Parameterization of the IEC 60076-7 Top-Oil Thermal Model

by João Pedro da Costa Souza, Patrick Picher, Issouf Fofana and Arnaud Zinflou

Energies 2026, 19(17), 4224; https://doi.org/10.3390/en19174224 - 7 Sep 2026

Abstract

Transformer top-oil temperature prediction is essential for reliable thermal assessment and lifetime management. Although the IEC 60076-7 loading guide model is widely adopted for this purpose, its thermal parameters are generally assumed to remain constant regardless of environmental conditions: an assumption that has [...] Read more.

Transformer top-oil temperature prediction is essential for reliable thermal assessment and lifetime management. Although the IEC 60076-7 loading guide model is widely adopted for this purpose, its thermal parameters are generally assumed to remain constant regardless of environmental conditions: an assumption that has received limited attention. This paper investigates the influence of ambient temperature on the IEC top-oil model parameters and proposes an adaptive ambient-dependent parameterization framework. A segmented optimization methodology is applied to field measurements from a 66 MVA, 225/26.4 kV power transformer to identify the optimal rated top-oil temperature rise and thermal exponent x over different ambient temperatures. The results reveal an approximately linear dependence of the optimized parameters on ambient temperature, suggesting that the thermal dynamics represented by the IEC model evolve with environmental conditions. Incorporating this dependency improves prediction accuracy, achieving a mean absolute error (MAE) of 2.03 °C and a root mean squared error (RMSE) of 2.56 °C on the test dataset, outperforming both the conventional IEC model with fixed parameters and a previously published adaptive approach. These findings offer a practical extension of the IEC model with applications in transformer monitoring, dynamic loading, and digital-twin-based asset management. Full article

(This article belongs to the Section F1: Electrical Power System)

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25 pages, 51730 KB

Open AccessArticle

Thermal Storage Characteristics of Honeycomb Phase Change Unit with Different Fluid Parameters

by Mingji Wang, Yangyang Wu, Xinhua Guo and Yinxia Zhuang

Energies 2026, 19(17), 4223; https://doi.org/10.3390/en19174223 - 7 Sep 2026

Abstract

Phase change thermal storage tanks are important components of clean energy heating systems, and their charging performance depends strongly on storage-unit geometry and heat transfer fluid (HTF) conditions. This study develops a two-dimensional numerical model of a hexagonal honeycomb phase change storage unit [...] Read more.

Phase change thermal storage tanks are important components of clean energy heating systems, and their charging performance depends strongly on storage-unit geometry and heat transfer fluid (HTF) conditions. This study develops a two-dimensional numerical model of a hexagonal honeycomb phase change storage unit and investigates the effects of cell number, HTF inlet temperature, inlet velocity, and fluid type under an approximately constant PCM inventory. Compared with the 4-cell configuration, the 9-, 16-, and 25-cell units reduce the times required to reach an average liquid fraction of 0.8 by 58.3%, 73.9%, and 83.5%, respectively. At 9000 s, the total stored heat of the 25-cell unit is 106.0% higher than that of the 4-cell unit. Increasing the inlet temperature from 338 K to 343 K and 348 K reduces the complete melting time by 27.4% and 42.5% and increases the total stored heat by 14.6% and 26.9%, respectively. An inlet velocity of 0.01 m/s provides the best thermal charging performance, while further increases cause slight deterioration. Water performs best, although differences among the three HTFs remain small. These results provide a quantitative basis for honeycomb PCM storage-unit design. Full article

(This article belongs to the Special Issue Energy Storage Systems: Modeling, State Estimation and Optimal Dispatch)

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9 pages, 162 KB

Open AccessEditorial

Key Technologies of Novel Power Systems: From Optimal Scheduling to Intelligent Operation and Maintenance Review

by Bo Yang, Guo Zhou and Lin Jiang

Energies 2026, 19(17), 4222; https://doi.org/10.3390/en19174222 - 7 Sep 2026

Abstract

As the goals of peak carbon emissions and carbon neutrality continue to progress, the power system is rapidly evolving toward a cleaner, low-carbon, and more efficient structure with increasing integration of renewable generation, which brings new research concerns regarding low-inertia operational characteristics and [...] Read more.

As the goals of peak carbon emissions and carbon neutrality continue to progress, the power system is rapidly evolving toward a cleaner, low-carbon, and more efficient structure with increasing integration of renewable generation, which brings new research concerns regarding low-inertia operational characteristics and relay protection adaptation for renewable dominated power grids [...] Full article

(This article belongs to the Topic Advances in Power Science and Technology, 2nd Edition)

31 pages, 3487 KB

Open AccessArticle

Thermal Stabilization as a Key to Sustainable Operation of Combustion Engines and Power Plants—Part 2: Thermal Stabilization of IES Due to Advanced Intake Air Cooling and Heat Recovery Assessed by Appropriate Criteria

by Yue Liu, Andrii Radchenko, Feng Zheng, Roman Radchenko, Mykola Radchenko, Anatolii Zubarev and Serhiy Forduy

Energies 2026, 19(17), 4221; https://doi.org/10.3390/en19174221 - 7 Sep 2026

Abstract

The sustainable performance of combustion engines in integrated energy systems (IESs) at a safe thermal level and with high fuel effectiveness is possible if intake air is cooled and the released heat is fully utilized by a heat recovery chiller (HRCh). Herein, the [...] Read more.

The sustainable performance of combustion engines in integrated energy systems (IESs) at a safe thermal level and with high fuel effectiveness is possible if intake air is cooled and the released heat is fully utilized by a heat recovery chiller (HRCh). Herein, the temperature of return hot water, used as a coolant, at the engine inlet is not to be higher than 70 °C to ensure safe, thermally stabilized engine performance. This cannot be ensured by only an absorption lithium-bromide chiller (LBCh) as the most efficient HRCh, which has a COP of about 0.7 and provides a return hot-water temperature of about 75 °C against the required 70 °C, which reduces the engine lifetime by about 10%. To ensure the thermally stabilized performance of the engine in conventional IESs, the residual heat left from the LBCh is ejected into the atmosphere by an emergency radiator with a heat loss of about 25% as the “cost” for safe engine performance. The concept of IES thermal stabilization in terms of both aspects—intake air cooling and the full utilization of the released heat by a combined LBCh boosted by an ejector chiller (ECh), easily implemented into an existing IES—was developed. The appropriate new unified criterion indicators for estimating the rate of thermal stabilization (RS) were adopted to ensure sustainable performance and increased the lifetime of the engine by about 10%, providing an innovative heat recovery intake air cooling system and boosting the conventional IES as a prosperous trend. Thus, for the first time in the practices of IES design and operation, the aggregated effect on engine thermal stabilization, followed by maximizing its efficiency, has been gained due to intake air cooling and full utilization of the heat released as mutually affecting aspects. Full article

(This article belongs to the Special Issue Advancements in Sustainable Energy Technologies: Innovations, Integration, and Impact—2nd Edition)

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15 pages, 2469 KB

Open AccessArticle

Neural Network-Based Real-Time Wind Energy Estimation

by Fara Sene, Mamadou Lamine Doumbia and Simon Pierre Betoka-Onyama

Energies 2026, 19(17), 4220; https://doi.org/10.3390/en19174220 - 7 Sep 2026

Abstract

This work proposes a real-time wind power estimation approach for a direct-current (DC) wind energy conversion system based on an artificial neural network (ANN). The proposed ANN uses the Levenberg–Marquardt (LM) algorithm and is trained using experimental data collected from a LabVolt wind [...] Read more.

This work proposes a real-time wind power estimation approach for a direct-current (DC) wind energy conversion system based on an artificial neural network (ANN). The proposed ANN uses the Levenberg–Marquardt (LM) algorithm and is trained using experimental data collected from a LabVolt wind energy test bench. The objective is to accurately estimate the instantaneous electrical power generated from the measured wind speed under different operating conditions. The proposed methodology comprises experimental data acquisition, ANN training, algorithm comparison, and model validation. The training performance of the LM algorithm was compared with that of the Resilient Backpropagation algorithm using the same dataset and network architecture. The results demonstrate that the LM algorithm provides superior convergence and prediction accuracy for the considered dataset. The selected ANN model achieved an MSE of 0.240601, an RMSE of 0.490511, an MAE of 0.207092, and a coefficient of determination of (R² = 0.999964). These results demonstrate an excellent agreement between the measured and predicted power values. The proposed ANN-based approach provides an accurate and computationally efficient solution for real-time wind power estimation and shows strong potential for integration into intelligent energy management systems and digital twin frameworks for wind energy conversion systems. Full article

(This article belongs to the Topic AI-Enabled Operation and Control of Modern Power and Energy Systems)

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14 pages, 2546 KB

Open AccessArticle

Series-Connected Grid-Following and Grid-Forming Hybrid Control Strategy for VSC-HVDC Converters to Enhance Transient Voltage Stability in Receiving-End Power Grids

by Bo Bao, Zhen Gong, Cong Fu, Shun Li and Xiaorong Xie

Energies 2026, 19(17), 4219; https://doi.org/10.3390/en19174219 - 7 Sep 2026

Abstract

With an increase in the High-Voltage Direct Current (HVDC) infeed, the strength of the receiving-end AC grid decreases, leading to transient voltage instability. Voltage source converter (VSC)-HVDC stations have a large unit capacity and high controllability, offering great potential for voltage support of [...] Read more.

With an increase in the High-Voltage Direct Current (HVDC) infeed, the strength of the receiving-end AC grid decreases, leading to transient voltage instability. Voltage source converter (VSC)-HVDC stations have a large unit capacity and high controllability, offering great potential for voltage support of the receiving-end grid. A grid-following/grid-forming (GFL–GFM) hybrid control can improve the oscillation stability of VSC stations under both strong and weak grid conditions; however, most relevant studies have focused on oscillation stability, while little attention has been paid to transient voltage regulation performance. Moreover, a quantitative analysis method for the transient active- and reactive-power characteristics of the hybrid control is lacking. This paper proposes a series-connected GFL/GFM hybrid control strategy along with a quantitative dynamic power analysis method. By establishing the closed-loop transfer function model, the steady-state power control performance and transient reactive-power response of the proposed control are quantitatively analyzed. Electro-Magnetic Transient (EMT) simulation results verify that, compared with the existing hybrid synchronization-type control, the proposed series-connected scheme exhibits superior performance in mitigating transient low-voltage and overvoltage issues, with the minimum voltage dip improved from 0.3 p. u. to 0.8 p. u. and the maximum overvoltage after fault clearance decreasing from 1.38 p. u. to 1 p. u. Full article

(This article belongs to the Section F1: Electrical Power System)

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33 pages, 7615 KB

Open AccessArticle

Phase-Selective Volt/VAR Placement and Sizing of Distributed Generation in Unbalanced Medium-Voltage Feeders: A Constructive Method Under Local-Demand Constraints

by Anthony Buezo, Jared Murillo, Osly Rodas, Jonathan Muñoz Tabora and Rafael A. Garcia

Energies 2026, 19(17), 4218; https://doi.org/10.3390/en19174218 - 6 Sep 2026

Abstract

Inverter-interfaced distributed generation (DG) can provide voltage support in unbalanced distribution feeders; however, sequential, phase-selective siting and sizing under local interconnection constraints have received limited attention. This study proposes a constructive Volt/VAR planning method that allocates DG according to the apparent demand and [...] Read more.

Inverter-interfaced distributed generation (DG) can provide voltage support in unbalanced distribution feeders; however, sequential, phase-selective siting and sizing under local interconnection constraints have received limited attention. This study proposes a constructive Volt/VAR planning method that allocates DG according to the apparent demand and voltage-deficient phases at each candidate bus. A descending reactive power feasibility test rejects solutions that cause non-convergence, overvoltage, or deterioration of the minimum system voltage. The method was implemented through automated unbalanced three-phase power-flow simulations and tested on the IEEE 13-node feeder and the real 3849-bus CHIRIPA medium-voltage network in Honduras, using active power allocation factors of 0.7 and 0.9. The selected configurations were evaluated over 24 h profiles for representative sunny and rainy days, annualized, and assessed economically over a 25-year horizon. Annual energy losses decreased by 25.8% and 26.4% in the IEEE feeder, although local capacity constraints prevented all phase voltages from reaching the 0.95–1.05 p.u. range. In CHIRIPA, all medium-voltage bus-phase voltages satisfied this range at maximum demand, although this improvement persisted only during solar hours; annual losses fell by 15.1% and 18.7%. The economic feasibility threshold in CHIRIPA depended primarily on installed capacity (approximately 6.5–6.6 MW), rather than unit count. These results provide a reproducible framework for prioritizing phase-specific DG investments under technical and economic constraints. Full article

(This article belongs to the Special Issue Planning and Operation of Integrated Renewable Energy Distribution System: 2nd Edition)

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19 pages, 17170 KB

Open AccessArticle

Experimental Investigation of Water-in-Oil Emulsions on Viscosity and Gas Exsolution Behavior of Heavy Oil Under CCEC Conditions

by Jingwei Jiang, Xue Bai, Shixuan Lu, Na Jia and Amin Badamchi-Zadeh

Energies 2026, 19(17), 4217; https://doi.org/10.3390/en19174217 - 6 Sep 2026

Abstract

Water-in-oil (W/O) emulsions are commonly encountered during heavy oil production, yet their effects on fluid rheology and gas exsolution behavior remain poorly characterized. This study systematically investigates how the water content of W/O emulsions (10%, 20%, and 30 vol.%) influences the viscosity, interfacial [...] Read more.

Water-in-oil (W/O) emulsions are commonly encountered during heavy oil production, yet their effects on fluid rheology and gas exsolution behavior remain poorly characterized. This study systematically investigates how the water content of W/O emulsions (10%, 20%, and 30 vol.%) influences the viscosity, interfacial tension (IFT), and pressure–volume behavior of heavy oils under conditions relevant to cyclic solvent injection. Viscosity measurements show that water content is the dominant rheological factor, with the 30% emulsion exhibiting approximately three times the viscosity of the 10% emulsion at 25 °C. In contrast, IFT between emulsified oils and methane is insensitive to water content, indicating that rheological differences across emulsions are structurally rather than thermodynamically driven. Constant-composition expansion and compression (CCEC) experiments reveal that pseudo-bubble point pressures decrease with increasing water content during fast depressurization, consistent with enhanced foamy-oil stabilization by the more viscous emulsion network. A hysteresis inversion phenomenon is identified, in which the compression path falls below the expansion path at higher water contents. Quantitative analysis using an integrated hysteresis index confirms a monotonic transition from positive to negative hysteresis with increasing water content at 15 °C, which is suppressed at elevated temperature and during slow depressurization. These findings demonstrate that conventional PVT data obtained with clean oil will systematically mischaracterize foamy-oil behavior in emulsified systems. Full article

(This article belongs to the Special Issue Advanced Research in Geoenergy Storage and Conversion)

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22 pages, 3457 KB

Open AccessArticle

Reducing Air Pollution in Rural Areas with Hybrid Heat Pump Supported by Biomass Boiler

by Jaka Bizjak, Jure Čižman, Boris Sučić and Marko Matkovič

Energies 2026, 19(17), 4216; https://doi.org/10.3390/en19174216 - 6 Sep 2026

Abstract

The widespread deployment of low-carbon technologies in households is increasing the need to reduce peak electricity demand on distribution grids. Air-source heat pumps (ASHPs) are efficient heating units, but their performance declines at low ambient temperatures, increasing winter peak demand. In rural areas, [...] Read more.

The widespread deployment of low-carbon technologies in households is increasing the need to reduce peak electricity demand on distribution grids. Air-source heat pumps (ASHPs) are efficient heating units, but their performance declines at low ambient temperatures, increasing winter peak demand. In rural areas, limited grid capacity can constrain their use as a sole heating source, while biomass remains widely used for space heating and contributes to fine particulate matter (PM₁₀) emissions. Unfavourable winter conditions can further increase local pollutant concentrations. This study investigates the potential operating cost savings and PM₁₀ emission reductions when using a biomass-assisted hybrid heat pump (HHP) operating in bivalent mode, while also evaluating GHG emissions relative to a monovalent ASHP, providing a combined assessment not previously applied to biomass-assisted hybrid heat pumps. A validated simulation model was developed to determine the optimal switching temperature using hourly temperature data from 23 locations across Slovenia. The results were interpolated nationally and visualised using GIS tools. The findings indicate that annual cost savings can reach up to 10% and PM₁₀ emission reductions can reach up to 20 kg for a single-family building in colder, mountainous regions. Full article

(This article belongs to the Special Issue Sustainable Buildings and Green Design)

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44 pages, 1125 KB

Open AccessArticle

Energy Consumption Management of Intelligent Production Buildings Within the Supply Chain Ecosystem of Smart City Manufacturing and Service Clusters: A Knowledge-Driven Coordination Approach

by Robert Ulewicz, Karina Dzhuguryan, Liudmyla Davydenko and Tygran Dzhuguryan

Energies 2026, 19(17), 4215; https://doi.org/10.3390/en19174215 - 6 Sep 2026

Abstract

The supply chain ecosystem (SCE) operating within an urban environment is characterised by continuous interactions among manufacturing, logistics, service, information, and energy flows across multiple smart city manufacturing-service clusters (SCMSCs). Within the SCE, intelligent production buildings (IPBs) emerge as multifunctional multistorey production-service infrastructures [...] Read more.

The supply chain ecosystem (SCE) operating within an urban environment is characterised by continuous interactions among manufacturing, logistics, service, information, and energy flows across multiple smart city manufacturing-service clusters (SCMSCs). Within the SCE, intelligent production buildings (IPBs) emerge as multifunctional multistorey production-service infrastructures developed under conditions of limited urban land availability and increasing demand for localised manufacturing and service integration. These buildings operate under heterogeneous and dynamically changing energy-demand conditions, substantially complicating energy consumption management. This study develops a knowledge-driven coordination approach for the energy consumption management of IPBs operating within SCMSCs from the perspective of the urban SCE. IPBs are conceptualised as distributed environments with finite building-level power supply system capacity, where manufacturing, logistics, service, and digital processes dynamically compete for shared energy resources. A hierarchical representation of the SCMSC energy environment is proposed, capturing distributed interactions and heterogeneous electricity-demand profiles across interconnected clusters. An information-analytical system integrating monitoring, data acquisition, analysis, ML-based demand prediction, planning, and decision-support functions is developed to support predictive electricity-demand coordination. The proposed framework combines IoT-enabled monitoring with digital-twin-supported synchronisation of energy states for distributed coordination among IPBs. The proposed approach is evaluated through scenario-based analysis of an IPB operating within an urban manufacturing-service environment. The results indicate the potential of knowledge-driven coordination to improve energy-capacity utilisation, mitigate peak-load formation, and enhance operational stability within SCMSCs. Full article

22 pages, 1495 KB

Open AccessReview

Energy-Efficiency Actions in Food Cold Chains: A Systematic Review of Refrigeration, Logistics, Digital Monitoring and Collaborative Implementation

by Ivan Ferretti, Beatrice Marchi and Simone Zanoni

Energies 2026, 19(17), 4214; https://doi.org/10.3390/en19174214 - 6 Sep 2026

Abstract

Food cold chains rely on refrigeration, cold storage, refrigerated transport, packaging and monitoring systems that consume electricity and fuel while preserving food safety, quality and shelf life. Although many studies propose energy-saving technologies or optimization models for individual cold-chain operations, less is known [...] Read more.

Food cold chains rely on refrigeration, cold storage, refrigerated transport, packaging and monitoring systems that consume electricity and fuel while preserving food safety, quality and shelf life. Although many studies propose energy-saving technologies or optimization models for individual cold-chain operations, less is known about how energy-efficiency actions are distributed across refrigeration, logistics and digital monitoring domains, which actors must collaborate to implement them, and which benefits and barriers shape adoption. This paper presents a systematic literature review supported by bibliometric and structured content analysis. Searches in Scopus and Web of Science identified 3930 records before deduplication. After removing out-of-year records and duplicates, 2368 unique records were screened; 896 reports were sought for full-text assessment; 751 reports were retrieved and assessed; 466 studies were included in the final review corpus; and 408 were coded as an applied/action corpus. The synthesis identifies ten energy-efficiency action families, seven cold-chain stage classes, multi-actor configurations, evidence types, collaboration-intensity levels, energy benefits, non-energy benefits and implementation barriers. Transport, routing and distribution is the largest action family (134 records), followed by cold storage and refrigeration technology (66), digital monitoring and information sharing (58), life-cycle assessment, energy assessment and decision support (36), energy systems and renewable cooling (34), packaging and thermal insulation (33), and inventory, and planning and coordination (27). The findings show that food cold-chain energy efficiency is not only a technical refrigeration problem but also a collaborative implementation challenge: many actions require information sharing, coordinated operating decisions, joint investment, data governance or cost/benefit-sharing mechanisms. The review contributes an action-oriented framework that links energy-saving actions to stages, actors, collaboration requirements, benefits and barriers, and it identifies future research priorities on comparable energy metrics, measured savings, renewable cooling, digital twins, demand-side flexibility and governance of collaborative energy-efficiency investments. Full article

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27 pages, 17489 KB

Open AccessArticle

A Time-Decoupled PWM Implementation Architecture Based on Predictive Duty-Cycle Sequences for High-Switching-Frequency Three-Phase Buck Rectifiers

by Li Ding, Dehong Zhou, Siping Feng and Jianxiao Zou

Energies 2026, 19(17), 4213; https://doi.org/10.3390/en19174213 - 6 Sep 2026

Abstract

High-switching-frequency operation substantially reduces the available time for sampling, control computation, modulation mapping, PWM-register updating, and auxiliary interrupt operations in digitally controlled three-phase buck rectifiers. Given this, this paper presents a time-decoupled PWM implementation architecture (TD-PWM) based on predictive duty-cycle sequences that enables [...] Read more.

High-switching-frequency operation substantially reduces the available time for sampling, control computation, modulation mapping, PWM-register updating, and auxiliary interrupt operations in digitally controlled three-phase buck rectifiers. Given this, this paper presents a time-decoupled PWM implementation architecture (TD-PWM) based on predictive duty-cycle sequences that enables sufficient computational redundancy. In the proposed architecture, the sampled information is used to generate an N-element duty-cycle sequence for the following control period. The generated sequence is stored in a buffer and subsequently loaded into the PWM registers one element per switching period. Consequently, prediction, control calculation, and SVPWM mapping are performed at the control frequency, whereas the duty-cycle values are updated at the switching frequency. A two-timescale execution structure is implemented in which the control-period task performs sampling and sequence generation, while the high-priority switching-period task performs sequence indexing and PWM-register loading. Experimental validation is conducted on a 400 W three-phase buck-rectifier prototype with a switching frequency of 100 kHz, a control frequency of 20 kHz, and N = 5. Under the investigated operating conditions, the proposed architecture achieves an input-current THD of 2.06% and shorter measured settling times than the two reference implementations. The results demonstrate the feasibility of the proposed implementation architecture. Full article

20 pages, 1747 KB

Open AccessArticle

Failure Mode, Effects, and Criticality Analysis (FMECA)-Based Fault Diagnosis of a High-Voltage Disconnect Switch

by Arafat Fousseni, Ali Awada, Mounia Achouch and Khaled Ziane

Energies 2026, 19(17), 4212; https://doi.org/10.3390/en19174212 - 6 Sep 2026

Abstract

High-voltage disconnect switches (HVDSs) are crucial for ensuring visible electrical isolation but often operate under challenging environmental conditions. While current monitoring methods can detect faults, simply identifying them is not enough for effective maintenance planning or efficient resource management. Electric utilities need tools [...] Read more.

High-voltage disconnect switches (HVDSs) are crucial for ensuring visible electrical isolation but often operate under challenging environmental conditions. While current monitoring methods can detect faults, simply identifying them is not enough for effective maintenance planning or efficient resource management. Electric utilities need tools or platforms that enable them to identify various failure modes and their impact on the safety and reliability of the system. This paper presents a failure mode and effects analysis of a HVDS and an assessment of its criticality (FMECA). For each failure mode identified by the FMECA, a cause-and-effect analysis is used to further investigate their root causes. Next, the criticality of each failure mode is evaluated using the Risk Priority Number (RPN). Finally, each failure mode is subjected to an analysis to prioritize the sensor used to measure the physical quantity associated with the failure. This sensor prioritization is performed by considering not only the RPN but also the sensor’s utility in terms of failure detection efficiency and ease of installation. The results provide a robust foundation for the development of predictive maintenance strategies customized for HVDS equipment, thereby contributing to enhanced reliability and resilience of electrical power systems. Full article

(This article belongs to the Section F1: Electrical Power System)

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35 pages, 18382 KB

Open AccessArticle

Preliminary Technical and Pumping-Energy Assessment of an Underground Pumped-Storage Hydropower System Using a Post-Mining Shaft as the Lower Reservoir

by Piotr Matusiak, Daniel Kowol, Rafał Baron, Paweł Friebe, Marcin Lutyński, Konrad Kołodziej, Agata Czardybon and Karina Ignasiak

Energies 2026, 19(17), 4211; https://doi.org/10.3390/en19174211 - 6 Sep 2026

Abstract

The reuse of post-mining infrastructure for pumped-storage hydropower may reduce new underground construction while supporting the repurposing of decommissioned mines. This study presents a site-specific preliminary technical and pumping-energy assessment of an underground pumped-storage system using Budryk Shaft II as the lower reservoir. [...] Read more.

The reuse of post-mining infrastructure for pumped-storage hydropower may reduce new underground construction while supporting the repurposing of decommissioned mines. This study presents a site-specific preliminary technical and pumping-energy assessment of an underground pumped-storage system using Budryk Shaft II as the lower reservoir. The assessment integrated shaft geometry, hydraulic conditions, turbine–generator selection, pressure-pipeline configuration, structural adaptation, hydraulic isolation, and staged water return. A working water volume of 12,000 m³ was adopted. The proposed generation unit comprises a vertical Pelton turbine operating at a gross design head of 900 m, a rated net head of 837.81 m, and a discharge of 0.71 m³/s. The rated turbine output is 5287 kW, and the turbine is coupled to a 6.3 kV synchronous generator. The three-stage pumping calculation yielded energy demands of 7.037, 19.600, and 37.371 MWh, giving a total of 64.008 MWh. These values are calculation-based estimates derived from the listed nominal pump capacities and powers using a simplified proportional power–flow assumption. At the rated turbine output, the calculated generation time of 4.695 h corresponds to 24.822 MWh of mechanical energy at the turbine shaft. Because verified generator-efficiency data are unavailable, the generated electrical energy and electrical round-trip efficiency cannot be determined exactly. The ratio of turbine-shaft energy to the calculated pumping-energy demand gives an upper-bound energy-return indicator of approximately 38.8%. Further work must verify pump operating points, generator performance, hydraulic transients, structural integrity, shaft sealing, auxiliary-energy demand, and the complete hydraulic connection to the upper reservoir. Full article

(This article belongs to the Special Issue Advances in Hydropower and Pumped Storage: Technologies and Applications)

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