Energies

23 pages, 4790 KB

Open AccessArticle

Data-Driven Probabilistic Power Flow for Energy-Storage Planning Considering Interconnected Grids

by Tingting Cheng, Xirui Jiang, Zheng Fan, Yanan Wu, Ying Mu, Dashun Guan, Dongliang Zhang and Ying Bai

Energies 2025, 18(24), 6633; https://doi.org/10.3390/en18246633 - 18 Dec 2025

Viewed by 355

Abstract

As renewable energy penetration increases, the volatility and uncertainty of photovoltaic generation and load demand pose significant challenges to power-system stability. This paper proposes a data-driven probabilistic load-flow method that employs a Gaussian mixture model (GMM) to model uncertainties in photovoltaic generation and [...] Read more.

As renewable energy penetration increases, the volatility and uncertainty of photovoltaic generation and load demand pose significant challenges to power-system stability. This paper proposes a data-driven probabilistic load-flow method that employs a Gaussian mixture model (GMM) to model uncertainties in photovoltaic generation and load demand. Cumulative quantity analysis is then applied to conduct probabilistic load-flow studies, quantifying the impact of these uncertainties on the power system. Building upon this foundation, a two-layer optimization model is constructed to optimize the siting, capacity, and operational strategies of energy storage systems. Experimental results demonstrate that this method effectively reduces the probability of voltage-limit violations, ensures the reliability of supply–demand balance, and enhances system stability and reliability even under fluctuating PV generation and load-demand conditions. Full article

(This article belongs to the Special Issue Advances in Power System and Renewable Energy)

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47 pages, 6936 KB

Open AccessReview

Research on Direct Air Capture: A Review

by Yiqing Zhao, Bowen Zheng, Jin Zhang and Hongyang Xu

Energies 2025, 18(24), 6632; https://doi.org/10.3390/en18246632 - 18 Dec 2025

Viewed by 1416

Abstract

Direct Air Capture (DAC) technology plays a crucial role in reducing atmospheric CO₂, but large-scale deployment faces challenges such as high energy consumption, operational costs, and slow material development. This study provides a comprehensive review of DAC principles, including chemical and [...] Read more.

Direct Air Capture (DAC) technology plays a crucial role in reducing atmospheric CO₂, but large-scale deployment faces challenges such as high energy consumption, operational costs, and slow material development. This study provides a comprehensive review of DAC principles, including chemical and solid adsorption methods, with a focus on emerging technologies like Metal–Organic Frameworks (MOFs) and graphene aerogels. MOFs have achieved adsorption capacities up to 1.5 mmol/g, while modified graphene aerogels reach 1.3 mmol/g. Other advancing approaches include DAC with Methanation (DACM), variable-humidity adsorption, photo-induced swing adsorption, and biosorption. The study also examines global industrialization trends, noting a significant rise in DAC projects since 2020, particularly in the U.S., China, and Europe. The integration of DAC with renewable energy sources, such as photovoltaic/electrochemical regeneration, offers significant cost-reduction potential and can cut reliance on conventional heat by 30%. This study focuses on the integration of Artificial Intelligence (AI) for accelerating material design and system optimization. AI and Machine Learning (ML) are accelerating DAC R&D: high-throughput screening shortens material design cycles by 60%, while AI-driven control systems optimize temperature, humidity, and adsorption dynamics in real time, improving CO₂ capture efficiency by 15–20%. The study emphasizes DAC’s future role in achieving carbon neutrality through enhanced material efficiency, integration with renewable energy, and expanded CO₂ utilization pathways, providing a roadmap for scaling DAC technology in the coming years. Full article

(This article belongs to the Special Issue Carbon Capture, Storage and Utilization Technologies: Advances and Challenges)

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24 pages, 13011 KB

Open AccessArticle

Assessment of Potential for Green Hydrogen Production in a Power-to-Gas Pilot Plant Under Real Conditions in La Guajira, Colombia

by Marlon Cordoba-Ramirez, Marlon Bastidas-Barranco, Dario Serrano-Florez, Leonel Alfredo Noriega De la Cruz and Andres Adolfo Amell Arrieta

Energies 2025, 18(24), 6631; https://doi.org/10.3390/en18246631 - 18 Dec 2025

Viewed by 298

Abstract

This study presents the operational assessment of a pilot-scale power-to-gas (PtG) facility located in La Guajira, Colombia, which integrates a 10 kW photovoltaic array and a 5 kW wind turbine to power a system with two anion exchange membrane (AEM) electrolyzer of 4.8 [...] Read more.

This study presents the operational assessment of a pilot-scale power-to-gas (PtG) facility located in La Guajira, Colombia, which integrates a 10 kW photovoltaic array and a 5 kW wind turbine to power a system with two anion exchange membrane (AEM) electrolyzer of 4.8 kW in total for green hydrogen production. Unlike most studies that rely on simulations or short-term evaluations, this study analyzes nine months of real operating data to quantify renewable energy availability, system capacity factors, and effective hydrogen output under tropical conditions. The results show that the hybrid system generated 7111 kWh during the monitoring period. The comparison of theoretical models with real-time energy production shows a low correlation between the data. The MBE ranged from 1253 to 2988 for the solar system, from −814 to 1013 for the wind system, and from 338 to 2714 for the hybrid system. The RMSE values obtained for each evaluated month ranged from 3179 to 3811 for the solar system, from 928 to 1910 for the wind system, and from 2310 to 4327 for the hybrid system, suggesting that the theoretical models tend to overestimate the energy production of the hybrid system in general terms. From the renewable energy produced in real conditions, 92 kg of hydrogen was produced at an average rate of 9 kg/month, considering the availability of wind and solar resources. However, approximately 300 kWh/month of renewable electricity remained unused because the removable generation did not meet the operating conditions of the electrolyzers, highlighting the importance of improved energy management and storage strategies. These findings provide a real scenario of power-to-gas system performance under Caribbean climatic conditions in Colombia, demonstrate the challenges of resource intermittency and system underutilization, and underline the importance of design systems that allow these intermittencies to be managed for the more optimal production of hydrogen from renewable sources. The outcomes contribute to the understanding of small-scale PtG systems in developing regions and support decision making for future scaling and replication of hybrid renewable–hydrogen infrastructures. Full article

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

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24 pages, 3887 KB

Open AccessArticle

Numerical Simulation Study on Synergistic Influencing Factors of CO₂ Flooding and Geological Storage in Low-Permeability and High-Water-Cut Reservoirs

by Qi Wang, Jihong Zhang, Guantong Huo, Peng Wang, Fei Li, Xinjian Tan and Qiang Xie

Energies 2025, 18(24), 6630; https://doi.org/10.3390/en18246630 - 18 Dec 2025

Viewed by 255

Abstract

How to economically and effectively mobilize remaining oil and achieve carbon sequestration after water flooding in low-permeability, high-water-cut reservoirs is an urgent challenge. This study, focusing on Block Y of the Daqing Oilfield, employs numerical simulation to systematically reveal the synergistic influencing mechanisms [...] Read more.

How to economically and effectively mobilize remaining oil and achieve carbon sequestration after water flooding in low-permeability, high-water-cut reservoirs is an urgent challenge. This study, focusing on Block Y of the Daqing Oilfield, employs numerical simulation to systematically reveal the synergistic influencing mechanisms of CO₂ flooding and geological storage. A three-dimensional compositional model characterizing this reservoir was constructed, with a focus on analyzing the controlling effects of key geological (depth, heterogeneity, physical properties) and engineering (gas injection rate, gas injection volume, bottom-hole flowing pressure) parameters on the displacement and storage processes. Simulation results indicate that the low-permeability characteristics of Block Y effectively suppress gas channeling, enabling a CO₂ flooding enhanced oil recovery (EOR) increment of 15.65%. Increasing reservoir depth significantly improves both oil recovery and storage efficiency by improving the mobility ratio and enhancing gravity segregation. Parameter optimization is key to achieving synergistic benefits: the optimal gas injection rate is 700–900 m³/d, the economically reasonable gas injection volume is 0.4–0.5 PV, and the optimal bottom-hole flowing pressure is 9–10 MPa. This study confirms that for Block Y and similar high-water-cut, low-permeability reservoirs, CO₂ flooding is a highly promising replacement technology; through optimized design, it can simultaneously achieve significant crude oil production increase and efficient CO₂ storage. Full article

(This article belongs to the Special Issue Advances in Carbon Dioxide (CO₂) Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS))

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18 pages, 3223 KB

Open AccessArticle

Voltage Stabilization in Shipboard Diesel-PMSG Autonomous Set Using a Parallel-Connected Converter

by Arkadiusz Nerc, Dariusz Tarnapowicz and Zenon Zwierzewicz

Energies 2025, 18(24), 6629; https://doi.org/10.3390/en18246629 - 18 Dec 2025

Viewed by 257

Abstract

The paper presents an innovative method of voltage stabilization in a ship’s power supply system, which involves controlling a converter connected in parallel with a permanent magnet synchronous generator (PMSG) as the main part of an autonomous power generation unit. The proposed solution [...] Read more.

The paper presents an innovative method of voltage stabilization in a ship’s power supply system, which involves controlling a converter connected in parallel with a permanent magnet synchronous generator (PMSG) as the main part of an autonomous power generation unit. The proposed solution addresses the critical challenges of maintaining a stable voltage level under varying load conditions typical of marine power plants, which often face unpredictable operational demands. The novel system topology and the proposed converter control strategy enable precise regulation of the output voltage supplied to the ship’s loads, ensuring high power quality, enhanced system reliability, and improved operational efficiency. The results of simulations and experiments presented in the article, which are confirmed by analytical studies, demonstrate the effectiveness and reliability of the developed voltage stabilization method. This concept holds significant potential for application in modern maritime power systems, contributing to the advancement of autonomous, energy-efficient, and environmentally friendly shipboard electrical technologies. Full article

(This article belongs to the Special Issue Grid-Forming Converters in Power Systems)

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15 pages, 1607 KB

Open AccessArticle

Identification of Important Lines in Power Grids Based on Improved ProfitLeader Algorithm

by Xinghua Liu, Guangyang Han, Dongfei Lv and Guowei Sun

Energies 2025, 18(24), 6628; https://doi.org/10.3390/en18246628 - 18 Dec 2025

Viewed by 284

Abstract

Rapid and accurate identification of important lines in power grids is crucial for enhancing grid reliability and preventing large-scale blackouts. This paper proposes a method for identifying important lines in power systems using an improved ProfitLeader (IPL) algorithm. First, a correlation network integrating [...] Read more.

Rapid and accurate identification of important lines in power grids is crucial for enhancing grid reliability and preventing large-scale blackouts. This paper proposes a method for identifying important lines in power systems using an improved ProfitLeader (IPL) algorithm. First, a correlation network integrating power flow dynamics and topological structure is constructed. Then, by incorporating line weights and directionality, the method overcomes the limitation of traditional ProfitLeader algorithms that only consider node out-degree. Finally, the constructed correlation network and improved algorithm are applied to identify important lines. Comparative studies with other common identification methods on the IEEE 39-bus system show that after attacking the top seven important lines identified by the proposed algorithm, the number of electrical islands in the system increases significantly, and the remaining load rate drops to 43.7%. These results verify the accuracy and effectiveness of the proposed method. Full article

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

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26 pages, 10588 KB

Open AccessArticle

Mechanical Response of Supporting Unit with Continuous Mining and Continuous Backfilling Method in Close Distance Coal Seams

by Guozhen Zhao, Hao Wu and Jiaqi Zhang

Energies 2025, 18(24), 6627; https://doi.org/10.3390/en18246627 - 18 Dec 2025

Viewed by 223

Abstract

In the process of continuous mining and continuous backfilling (CMCB) in close-distance coal seams, the supporting unit (CMCBSU), composed of coal pillar and filling body, is affected by mining-induced disturbances from adjacent coal seams. This study establishes a mechanical model for the CMCBSU, [...] Read more.

In the process of continuous mining and continuous backfilling (CMCB) in close-distance coal seams, the supporting unit (CMCBSU), composed of coal pillar and filling body, is affected by mining-induced disturbances from adjacent coal seams. This study establishes a mechanical model for the CMCBSU, revealing that the coordination of the CMCBSU depends on the similarity degree of elastic modulus of the components. Subsequently, numerical simulations were conducted to analyze the stress conditions. The results showed that the

σ_{1}

and

σ_{3}

exhibited cyclic loading and unloading characteristics. Based on the stress paths, conventional triaxial compression tests were performed on coal (CTC-coal), filling body, and the CMCBSU, as well as triaxial cyclic loading and unloading tests on coal (TCLU-coal). The results indicated that coal exhibited significant brittleness, the filling body demonstrated strain-softening characteristics, and the CMCBSU showed strain-softening behavior. Hysteresis loops were observed in the elastic region of the TCLU-coal. The failure characteristics of the specimens indicated that the shear stress was the primary cause of specimen failure. After testing, the filling body exhibited radial fish-scale-like wrinkles on the specimen surface, the coal and the CMCBSU showed primary shear cracks. In the CMCBSU, the primary shear crack generated on the filling body side relates to that on the coal side. In contrast, secondary cracks on the filling body side rarely penetrate the coal side. Excluding the influence of internal weak planes on specimen failure, cyclic loading and unloading within the elastic region of the coal reduced its internal friction angle. Mechanical parameters indicate that the weaker load-bearing medium determined the load-bearing capacity of the CMCBSU, the medium with a higher elastic modulus primarily determined the CMCBSU’s resistance to elastic deformation, and the cyclic loading and unloading caused by CMCBSU in close-distance coal seams had minimal impact on the coal’s resistance to elastic deformation. Full article

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22 pages, 3995 KB

Open AccessArticle

The Role of Demand Flexibility in Addressing Inc-Dec Gaming in Electricity Markets

by Luciano Pozzi, Dimitrios Papadaskalopoulos, Vincenzo Trovato, Dawei Qiu and Goran Strbac

Energies 2025, 18(24), 6626; https://doi.org/10.3390/en18246626 - 18 Dec 2025

Viewed by 250

Abstract

Zonal day-ahead (DA) electricity markets followed by redispatch (RD) markets for congestion management are vulnerable to the strategic bidding behavior known as Inc-Dec gaming. Although previous literature has demonstrated the effects of Inc-Dec gaming, it has neglected the participation of flexible demand in [...] Read more.

Zonal day-ahead (DA) electricity markets followed by redispatch (RD) markets for congestion management are vulnerable to the strategic bidding behavior known as Inc-Dec gaming. Although previous literature has demonstrated the effects of Inc-Dec gaming, it has neglected the participation of flexible demand in RD markets. This paper addresses this gap by developing a novel multi-period bi-level optimization model of a strategic producer participating in DA and RD markets, accounting for the inherent time-coupling operating characteristics of demand flexibility (DF) in the RD market. This model includes an upper level problem determining the optimal bidding decisions of the strategic producer in the DA and RD markets, and two lower level problems representing the clearing process of the two markets. The role of DF in addressing Inc-Dec gaming is demonstrated through a small-scale case study involving a 2-node system and a 2-period market horizon (showing peak/off-peak dynamics), as well as a large-scale case study involving a modified IEEE RTS 24-node system and a daily (24-h) market horizon. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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31 pages, 3254 KB

Open AccessArticle

An Electric Vehicle Conversion for Rural Mobility in Sub-Saharan Africa

by Daneel Wasserfall, Stefan Botha and Marthinus Johannes Booysen

Energies 2025, 18(24), 6625; https://doi.org/10.3390/en18246625 - 18 Dec 2025

Viewed by 504

Abstract

Rural Sub-Saharan Africa (SSA) faces limited transport options, with many dispersed settlements dependent on poorly maintained roads. Light delivery vehicles (LDVs) can improve mobility, but conventional internal combustion engine vehicles are costly to operate and contribute to emissions. Electric vehicle (EV) conversions offer [...] Read more.

Rural Sub-Saharan Africa (SSA) faces limited transport options, with many dispersed settlements dependent on poorly maintained roads. Light delivery vehicles (LDVs) can improve mobility, but conventional internal combustion engine vehicles are costly to operate and contribute to emissions. Electric vehicle (EV) conversions offer a practical alternative by extending vehicle life and reducing energy, maintenance, and environmental costs. This study presents a simulation-based framework to guide LDV conversion design for rural SSA. The framework includes component sizing, subsystem modeling, and full-vehicle benchmarking under representative conditions. Scenario-based simulations include trips ranging from shorter local access routes to longer remote trips on both paved and dirt roads, allowing the conversion’s performance to be quantified under representative conditions. A sensitivity analysis indicates that road grade, aerodynamic drag, and rolling resistance are the primary factors driving energy use variation. Using the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) drive cycle, the conversion energy consumption (∼217 Wh/km) comparable to that of commercial electric vans, though the range is reduced relative to its battery capacity. The framework establishes a benchmark for EV conversion performance in SSA and supports broader adoption of sustainable rural mobility solutions. Full article

(This article belongs to the Section E: Electric Vehicles)

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22 pages, 2892 KB

Open AccessArticle

Technical Benchmarking of Site Acceptance Testing Methods of Offshore Wind Farm HVAC Power Cables

by Edward Gulski, George J. Anders, Jaroslaw Parciak, Laurens Pots and Robert Parciak

Energies 2025, 18(24), 6624; https://doi.org/10.3390/en18246624 - 18 Dec 2025

Viewed by 302

Abstract

The reliability of an offshore wind farm (OWF) depends strongly on the export and inter-array cable installations. AC export cables (EXCs) are typically up to 120 km long and operate at voltages ranging from 220 to 275 kV. The newest inter-array cables (IACs) [...] Read more.

The reliability of an offshore wind farm (OWF) depends strongly on the export and inter-array cable installations. AC export cables (EXCs) are typically up to 120 km long and operate at voltages ranging from 220 to 275 kV. The newest inter-array cables (IACs) operate at 66 kV and can be up to 20 km long. They connect individual wind turbines to the offshore substation. This paper discusses current failure statistics and costs, as well as the technical challenges associated with different site acceptance testing (SAT) methods for offshore wind farm export and inter-array cables. The technical benchmark analysis for both EXCs and IACs shows the most reliable solutions for SAT. Moreover, practical applications based on 13 international OWF installations show that damped AC (DAC) supports quality control of newly installed EXC and IAC cable systems and provides a solid basis for in-service condition-based maintenance. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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22 pages, 3019 KB

Open AccessArticle

Total CO₂ Release from Combustion, Electric, and Hybrid Vehicles—A Case Study for Latin America’s Countries

by Robert E. Rockwood, Ana Vassileva Borissova and Klaus Lieutenant

Energies 2025, 18(24), 6623; https://doi.org/10.3390/en18246623 - 18 Dec 2025

Viewed by 435

Abstract

This study investigates the total carbon dioxide (CO₂) emissions from various types of passenger vehicles in five Latin American countries: Argentina, Brazil, Ecuador, Mexico, and Paraguay. The aim was to analyze to which degree CO₂ output can be reduced in [...] Read more.

This study investigates the total carbon dioxide (CO₂) emissions from various types of passenger vehicles in five Latin American countries: Argentina, Brazil, Ecuador, Mexico, and Paraguay. The aim was to analyze to which degree CO₂ output can be reduced in Latin America by switching from petrol cars to electric cars. The vehicles analyzed include petrol-driven cars, short-, mid-, and long-range battery electric vehicles, fuel cell electric vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. The study examines the total CO₂ emissions including battery production, vehicle manufacturing, and their operation, considering the energy grid mix of the selected countries for the year 2023. Using experimental data and considering production conditions yields more reliable results than previous studies. The results indicate that battery cars with the shortest cruising range using batteries produced in Europe and/or America generate the lowest levels of CO₂ emissions, regardless of the energy mix. However, the emission values vary across different countries. In countries with a predominant share of renewable energy for the electricity generation, such as Paraguay, Brazil, and Ecuador, battery cars are the most effective in reducing overall CO₂ emissions. Conversely, in countries like Argentina and Mexico, where renewable energy sources constitute a smaller share of the energy mix, the use of electric vehicles yields only a minor reduction in CO₂ output, while emissions of long-range vehicles with batteries produced in Asia even exceed those of internal combustion engine vehicles. Therefore, eco-friendly electricity generation is a prerequisite for eco-friendly use of electric cars and should therefore be the goal of every country. Full article

(This article belongs to the Special Issue Analysis of Energy Consumption and Energy Efficiency of Electric Vehicles)

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16 pages, 2187 KB

Open AccessArticle

Combined Mild Thermal Pretreatment and Bioaugmentation of Ammonia-Acclimatised Inoculum to Enhance Biomethanation of Poultry Manure

by Christos A. Tzenos, Antonios A. Lithourgidis, Dimitra S. Pitsikoglou, Maria-Athina Tsitsimpikou, Sotirios D. Kalamaras, Vasileios K. Firfiris, Ioannis A. Fotidis and Thomas A. Kotsopoulos

Energies 2025, 18(24), 6622; https://doi.org/10.3390/en18246622 - 18 Dec 2025

Viewed by 279

Abstract

Anaerobic digestion (AD) of poultry manure often faces ammonia inhibition due to its high nitrogen content. This study investigated a combined strategy involving mild thermal hydrolysis pretreatment and bioaugmentation with ammonia-acclimatised inoculum to enhance methane production and process stability under ammonia-stressed conditions. Batch [...] Read more.

Anaerobic digestion (AD) of poultry manure often faces ammonia inhibition due to its high nitrogen content. This study investigated a combined strategy involving mild thermal hydrolysis pretreatment and bioaugmentation with ammonia-acclimatised inoculum to enhance methane production and process stability under ammonia-stressed conditions. Batch biomethanation efficiency assays were first conducted to evaluate the effect of different hydrolysis conditions (55–70 °C, 30–60 min) on substrate methane yields and biodegradability. The optimal condition (70 °C for 60 min) increased methane potential by 8.7% compared to the untreated substrate. In addition, a mesophilic continuous stirred-tank reactor (CSTR) experiment was conducted using both non-hydrolysed and thermally hydrolysed poultry manure under hydraulic retention times of 25 and 30 days, across four operational phases: steady-state, ammonia toxicity, bioaugmentation recovery, and increased organic loading rate. CSTRs were subjected to ammonia stress (6500 mg NH₄⁺-N L⁻¹) to assess the effectiveness of an acclimatised bioaugmentation inoculum. Methane yields recovered up to 93% and 100% of pre-inhibition and ammonia-toxicity levels, respectively, accompanied by process stability while reaching 7280 mg NH₄⁺-N L⁻¹. The synergistic application of hydrolysis and bioaugmentation significantly improved substrate conversion and overall AD robustness. This integrated approach provides a viable and scalable strategy for optimising AD performance of nitrogen-rich feedstocks, enabling its future application in AD plants. Full article

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

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23 pages, 3492 KB

Open AccessArticle

Multi-Objective Reinforcement Learning for Virtual Impedance Scheduling in Grid-Forming Power Converters Under Nonlinear and Transient Loads

by Jianli Ma, Kaixiang Peng, Xin Qin and Zheng Xu

Energies 2025, 18(24), 6621; https://doi.org/10.3390/en18246621 - 18 Dec 2025

Viewed by 354

Abstract

Grid-forming power converters play a foundational role in modern microgrids and inverter-dominated distribution systems by establishing voltage and frequency references during islanded or low-inertia operation. However, when subjected to nonlinear or impulsive impact-type loads, these converters often suffer from severe harmonic distortion and [...] Read more.

Grid-forming power converters play a foundational role in modern microgrids and inverter-dominated distribution systems by establishing voltage and frequency references during islanded or low-inertia operation. However, when subjected to nonlinear or impulsive impact-type loads, these converters often suffer from severe harmonic distortion and transient current overshoot, leading to waveform degradation and protection-triggered failures. While virtual impedance control has been widely adopted to mitigate these issues, conventional implementations rely on fixed or rule-based tuning heuristics that lack adaptivity and robustness under dynamic, uncertain conditions. This paper proposes a novel reinforcement learning-based framework for real-time virtual impedance scheduling in grid-forming converters, enabling simultaneous optimization of harmonic suppression and impact load resilience. The core of the methodology is a Soft Actor-Critic (SAC) agent that continuously adjusts the converter’s virtual impedance tensor—comprising dynamically tunable resistive, inductive, and capacitive elements—based on real-time observations of voltage harmonics, current derivatives, and historical impedance states. A physics-informed simulation environment is constructed, including nonlinear load models with dominant low-order harmonics and stochastic impact events emulating asynchronous motor startups. The system dynamics are modeled through a high-order nonlinear framework with embedded constraints on impedance smoothness, stability margins, and THD compliance. Extensive training and evaluation demonstrate that the learned impedance policy effectively reduces output voltage total harmonic distortion from over 8% to below 3.5%, while simultaneously limiting current overshoot during impact events by more than 60% compared to baseline methods. The learned controller adapts continuously without requiring explicit load classification or mode switching, and achieves strong generalization across unseen operating conditions. Pareto analysis further reveals the multi-objective trade-offs learned by the agent between waveform quality and transient mitigation. Full article

(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)

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14 pages, 2354 KB

Open AccessArticle

Analysis of the Feasibility of Using Hybrid DC Circuit Breakers with Forced Switching for Parallel Connections

by Łukasz Nowak, Michał Rodak and Piotr Borkowski

Energies 2025, 18(24), 6620; https://doi.org/10.3390/en18246620 - 18 Dec 2025

Viewed by 372

Abstract

The use of advanced switching technologies, including hybrid and fully semiconductor-based circuit breakers, enables a significant reduction in the prospective short-circuit current. This enhances the level of circuit protection by minimizing thermal and electrodynamic stresses. One of the available solutions is a hybrid [...] Read more.

The use of advanced switching technologies, including hybrid and fully semiconductor-based circuit breakers, enables a significant reduction in the prospective short-circuit current. This enhances the level of circuit protection by minimizing thermal and electrodynamic stresses. One of the available solutions is a hybrid DC circuit breaker employing the forced commutation method, in which a counter-current generator is incorporated into the auxiliary branch. Increasing requirements not only for short-circuit protection reliability but also for operational flexibility impose the need to configure DC breakers for parallel operation. This paper presents an analysis of the performance of forced-commutation circuit breakers connected in parallel with another identical device, as well as with a conventional fast magnetic blow-out breaker. To prevent unintended and undesired tripping, the influence of counter-current generator parameters on the overcurrent protection response was investigated. In the analyzed configuration, the applied hybrid DC breaker limits the expected short-circuit current from approximately 45 kA to 5 kA within about 2 ms. Full article

(This article belongs to the Section F6: High Voltage)

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22 pages, 8029 KB

Open AccessArticle

Early-Stage Fault Diagnosis for Batteries Based on Expansion Force Prediction

by Liye Wang, Yong Li, Yuxin Tian, Jinlong Wu, Chunxiao Ma, Lifang Wang and Chenglin Liao

Energies 2025, 18(24), 6619; https://doi.org/10.3390/en18246619 - 18 Dec 2025

Viewed by 303

Abstract

With the continuous expansion of the electric vehicle market, lithium-ion batteries have also been rapidly developed, but this has brought about concerns over the safety of lithium-ion batteries. Research on the correlation mechanism between the expansion and safety of lithium-ion batteries is a [...] Read more.

With the continuous expansion of the electric vehicle market, lithium-ion batteries have also been rapidly developed, but this has brought about concerns over the safety of lithium-ion batteries. Research on the correlation mechanism between the expansion and safety of lithium-ion batteries is a key step in the construction of a battery life cycle safety evaluation system. In this paper, the physicochemical mechanism of early safety faults in batteries was analyzed from three dimensions of electricity, heat, and force. The interactions of electrochemical side reactions, thermal runaway chain reactions, and mechanical fault mechanisms were analyzed, and the core induction of early safety risk was explored. A battery coupling model based on electrical, thermal, and mechanical dimensions was built, and the accuracy of the coupling model was verified by a variety of test conditions. Based on the coupling model, the stress distribution of the battery under different safety boundary conditions was simulated, and then the average expansion force of the battery surface was calculated through the stress distribution results. Through this process, a multi-parameter database based on the test and simulation data was obtained. According to the data of battery parameters at different times, an early safety classification method based on the battery expansion force was proposed, and a classification model between battery dimension data and safety level was proposed based on the nonlinear dynamic sparse regression method, and the classification accuracy was validated. From the perspective of fault warning, by establishing a multi-physical coupling model of electrical, thermal, and mechanical fields, the space-time evolution law of battery expansion under different working conditions can be dynamically monitored, and the fault criterion based on the expansion force can be established accordingly to provide quantitative indicators for safety risk classification warnings, and improve the battery’s reliability and durability. Full article

(This article belongs to the Special Issue Renewable Energy Development in Distribution Networks: Optimization, Assessment and Design of Renewable Plants)

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32 pages, 3717 KB

Open AccessArticle

Governance Quality and the Green Transition: Integrating Econometric and Machine Learning Evidence on Renewable Energy Efficiency in Sub-Saharan Africa

by Joseph Nyabvudzi, Hongyi Xu and Francis Atta Sarpong

Energies 2025, 18(24), 6618; https://doi.org/10.3390/en18246618 - 18 Dec 2025

Viewed by 427

Abstract

Renewable energy efficiency (REE) remains critically low across many Sub-Saharan African (SSA) countries, yet the existing literature provides limited empirical clarity on how governance quality shapes efficiency outcomes and through which mechanisms these effects operate. This study addresses this gap by examining the [...] Read more.

Renewable energy efficiency (REE) remains critically low across many Sub-Saharan African (SSA) countries, yet the existing literature provides limited empirical clarity on how governance quality shapes efficiency outcomes and through which mechanisms these effects operate. This study addresses this gap by examining the influence of governance quality on REE in 23 SSA countries from 2005 to 2023, drawing on institutional theory and innovation diffusion theory. The analysis investigates three mediating channels, renewable investment, green policy, and green technology, using a multidimensional empirical framework that integrates the Malmquist Productivity Index (MPI), Two-Step System GMM, Generalized Estimating Equations (GEE), Generalized Least Squares (GLS), and Panel-Corrected Standard Errors (PCSE). Results consistently show that governance quality significantly enhances REE through investment, policy, and technological pathways. To capture nonlinearities and heterogeneous responses often overlooked in traditional models, we complement the econometric estimations with causal machine-learning simulations (Double Machine Learning and Causal Forests). These counterfactual analyses reveal that governance improvements and renewable-policy adoption produce the highest efficiency gains in mid-governance countries with stronger absorptive capacity. While the study offers policy-relevant insights, limitations remain, due to data constraints, unobserved institutional dynamics, and the uneven maturity of green-technology systems across the region. Nevertheless, the findings underscore that strengthening governance and fostering innovation are fundamental to accelerating a sustainable and inclusive green-energy transition in Sub-Saharan Africa. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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22 pages, 2280 KB

Open AccessArticle

Control Analysis of Renewable Energy System with Hydrogen Storage to Match Energy Community Demand: A Whole-System Perspective

by Adriano Valle, Gabriele G. Gagliardi, Domenico Borello and Paolo Venturini

Energies 2025, 18(24), 6617; https://doi.org/10.3390/en18246617 - 18 Dec 2025

Viewed by 398

Abstract

This paper proposes an analysis of different logics (heuristic and linear) of managing renewables scenarios including two different operating conditions and their relative degradation: fixed and variable point. The synergy between two storage technologies, such as Li-ion batteries and the hydrogen power-to-power solution [...] Read more.

This paper proposes an analysis of different logics (heuristic and linear) of managing renewables scenarios including two different operating conditions and their relative degradation: fixed and variable point. The synergy between two storage technologies, such as Li-ion batteries and the hydrogen power-to-power solution (electrolyzer, H₂ tank, and fuel cells), is evaluated to ensure the balance of the power grid. This paper presents a numerical model of the smart grid developed in MATLAB/Simulink. A detailed performance evaluation of each component was performed to meet an electrical load (30 kW-peak) of a smart renewable energy community. From the optimization process, a fuel cell of 6 kW, an electrolyzer of 18 kW, a tank of 40 m³ at 200 bars, as well as a battery of 75 kWh were selected. The fuel cell operates during autumn and winter due to the lack of photovoltaic power generation, while its contribution is reduced during the summer period. In the heuristic logic, the minimum and maximum hydrogen levels are 18% and 60% of the tank volume (40 m³), respectively, while in the linear logic, they are 33% and 65%. The average value of the state of charge (SOC) of the battery is similar in both logics (0.51 vs. 0.53). Regarding hydrogen produced from the electrolyzer, the linear logic allows it to produce a quantity 7% higher than the heuristic one; therefore, the linear logic allows it to properly manage the electrochemical systems. The dynamic operation results in more significant degradation of hydrogen systems, making them less suitable; thus, to preserve the devices (up to 25% of lifetime more), a fixed-point operation is recommended. The cost comparison does not show relevant differences between the two scenarios, while a steep increase in the costs is shown when the fuel cell is operated in dynamic mode. Finally, the total emissions associated with renewable microgrids are 30 times lower than the traditional grid scenario, demonstrating the potential of renewable energy communities. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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34 pages, 418 KB

Open AccessArticle

The Role of Climate-Oriented Funding in Advancing Renewable Energy Transition Across the EU

by Gheorghița Dincă, Ioana-Cătălina Netcu and Camelia Ungureanu

Energies 2025, 18(24), 6616; https://doi.org/10.3390/en18246616 - 18 Dec 2025

Viewed by 308

Abstract

The shift to renewable energy is a key goal for the European Union as it aims for climate neutrality; however, the effectiveness of climate-focused funding instruments varies significantly across member states. This research investigates the influences of mitigation investments, R&D spending, environmental tax [...] Read more.

The shift to renewable energy is a key goal for the European Union as it aims for climate neutrality; however, the effectiveness of climate-focused funding instruments varies significantly across member states. This research investigates the influences of mitigation investments, R&D spending, environmental tax revenues, subsidies, GDP growth, and capital formation on renewable energy expansion within the EU-27, placing particular emphasis on the structural differences between Old Member States (OMS) and New Member States (NMS). The study utilizes robust long-run estimation techniques alongside causality analysis over a span of 13 years, from 2010–2023. The findings highlight notable distinctions among the EU-27, OMS, and NMS regions. While the EU-27 and OMS show that funds designated for climate mitigation and R&D are critical drivers of the clean energy transition, in the NMS, environmental taxes, subsidies, innovation, and gross fixed capital formation play vital roles in advancing this transition. Furthermore, economic development shows mixed results in achieving sustainable objectives, underscoring the necessity for climate-oriented funding and initiatives. Therefore, policy measures should focus on mitigation finance and innovation across the EU, while the design of subsidies and environmental tax structures must be tailored to each region to ensure a fair and expedited transition. Full article

(This article belongs to the Special Issue Energy Economics, Finance and Policy Towards Sustainable Energy: 2nd Edition)

26 pages, 2485 KB

Open AccessArticle

Beyond Subsidies: Economic Performance of Optimized PV-BESS Configurations in Polish Residential Sector

by Tomasz Wiśniewski and Marcin Pawlak

Energies 2025, 18(24), 6615; https://doi.org/10.3390/en18246615 - 18 Dec 2025

Viewed by 477

Abstract

This study examines the economic performance of residential photovoltaic systems combined with battery storage (PV-BESS) under Poland’s net-billing regime for a single-family household without subsidy support in 10-year operational horizon. These insights extend existing European evidence by demonstrating how net-billing fundamentally alters investment [...] Read more.

This study examines the economic performance of residential photovoltaic systems combined with battery storage (PV-BESS) under Poland’s net-billing regime for a single-family household without subsidy support in 10-year operational horizon. These insights extend existing European evidence by demonstrating how net-billing fundamentally alters investment incentives. The analysis incorporates real production data from selected locations and realistic household consumption profiles. Results demonstrate that optimal system configuration (6 kWp PV with 15 kWh storage) achieves 64.3% reduction in grid electricity consumption and positive economic performance with NPV of EUR 599, IRR of 5.32%, B/C ratio of 1.124 and discounted payback period of 9.0 years. The optimized system can cover electricity demand in the summer half-year by over 90% and reduce local network stress by shifting surplus solar generation away from midday peaks. Residential PV-BESS systems can achieve economic efficiency in Polish conditions when properly optimized, though marginal profitability requires careful risk assessment regarding component costs, durability and electricity market conditions. For Polish energy policy, the findings indicate that net-billing creates strong incentives for regulatory instruments that promote higher self-consumption, which would enhance the economic role of residential storage. Full article

(This article belongs to the Topic Energy Policy, Regulation and Sustainable Development—2nd Edition)

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25 pages, 3260 KB

Open AccessArticle

Signal-Guided Cooperative Optimization Method for Active Distribution Networks Oriented to Microgrid Clusters

by Zihao Wang, Shuoyu Li, Kai Yu, Wenjing Wei, Guo Lin, Xiqiu Zhou, Yilin Huang and Yuping Huang

Energies 2025, 18(24), 6614; https://doi.org/10.3390/en18246614 - 18 Dec 2025

Viewed by 278

Abstract

To achieve low-carbon collaborative operation of active distribution networks (ADNs) and microgrid clusters, this paper proposes a signal-guided collaborative optimization method. Firstly, a spatiotemporal carbon intensity equilibrium model (STCIEM) is constructed, overcoming the limitations of centralized carbon emission flow models in terms of [...] Read more.

To achieve low-carbon collaborative operation of active distribution networks (ADNs) and microgrid clusters, this paper proposes a signal-guided collaborative optimization method. Firstly, a spatiotemporal carbon intensity equilibrium model (STCIEM) is constructed, overcoming the limitations of centralized carbon emission flow models in terms of data privacy and equitable distribution, and enabling distributed and precise carbon emission measurement. Secondly, a dual-market mechanism for carbon and electricity is designed to support peer-to-peer (P2P) carbon quota trading between microgrids and ADN-backed clearing, enhancing market liquidity and flexibility. In terms of scheduling strategy optimization, the multi-agent deep deterministic policy gradient (MADDPG) algorithm is incorporated into the carbon-electricity cooperative game framework, enabling differentiated energy scheduling under constraints. Simulation results demonstrate that the proposed method can effectively coordinate the operation of energy storage, gas turbines, and demand response, reduce system carbon intensity, improve market fairness, and enhance overall economic performance and robustness. The study shows that this framework provides theoretical support and practical reference for future distributed energy consumption and carbon neutrality paths. Full article

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26 pages, 3837 KB

Open AccessArticle

Design and Performance Analysis of MPPT Algorithms Applied to Multistring Thermoelectric Generator Arrays Under Multiple Thermal Gradients

by Emerson Rodrigues de Lira, Eder Andrade da Silva, Sergio Vladimir Barreiro Degiorgi, João Paulo Pereira do Carmo and Oswaldo Hideo Ando Junior

Energies 2025, 18(24), 6613; https://doi.org/10.3390/en18246613 - 18 Dec 2025

Viewed by 317

Abstract

Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This [...] Read more.

Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This study presents a comprehensive performance evaluation of four maximum power point tracking (MPPT) algorithms, Perturb and Observe (P&O), Incremental Conductance (InC), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), applied to multistring thermoelectric generator (TEG) arrays under multiple and asymmetric thermal gradients. The simulated systems, modeled in MATLAB/Simulink, replicate real-world thermoelectric configurations by employing series-parallel topologies and eleven distinct thermal scenarios, including uniform, localized, and sinusoidal temperature distributions. The key contribution of this work lies in demonstrating the superior capability of metaheuristic algorithms (PSO and GA) to locate the global maximum power point (GMPP) in complex thermal environments, outperforming classical methods (P&O and InC), which consistently converged to local maxima under multi-peak conditions. Notably, PSO achieved the best average convergence time (0.23 s), while the GA recorded the fastest response (0.05 s) in the most challenging multi-peak scenarios. Both maintained high tracking accuracy (error ≈ 0.01%) and minimized power ripple, resulting in conversion efficiencies exceeding 97%. The study emphasizes the crucial role of algorithm selection in maximizing energy harvesting performance in practical TEG applications such as embedded systems, waste heat recovery, and autonomous sensor networks. Future directions include physical validation through prototypes, incorporation of dynamic thermal modeling, and development of hybrid or AI-enhanced MPPT strategies. Full article

(This article belongs to the Special Issue Advanced Research on Heat Exchanger Networks and Heat Recovery: 2nd Edition)

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20 pages, 2583 KB

Open AccessArticle

Enhancing Reliability Indices in Power Distribution Grids Through the Optimal Placement of Redundant Lines Using a Teaching–Learning-Based Optimization Approach

by Johao Jiménez, Diego Carrión and Manuel Jaramillo

Energies 2025, 18(24), 6612; https://doi.org/10.3390/en18246612 - 18 Dec 2025

Viewed by 327

Abstract

Given the pressing need to strengthen operational reliability in electrical distribution networks, this study proposes an optimization methodology based on the Teaching–Learning-Based Optimization (TLBO) algorithm for the strategic location of redundant lines. The model is validated on the “MV Distribution Network—Base Model” test [...] Read more.

Given the pressing need to strengthen operational reliability in electrical distribution networks, this study proposes an optimization methodology based on the Teaching–Learning-Based Optimization (TLBO) algorithm for the strategic location of redundant lines. The model is validated on the “MV Distribution Network—Base Model” test system, considering the combination of the MTBF (Mean Time Between Failures) and MTTR (Mean Time To Repair) indicators as the objective function. After 500 independent runs, it is determined that the configuration with three redundant lines identified as LN_1011, LN_1058, and LN_0871 offers the most stable solution. Specifically, this topology increases the MTBF from 403.64 h to 409.42 h and reduces the MTTR from 2.351 h to 2.306 h. In addition, significant improvements are observed in the voltage profile and angle, along with a more balanced redistribution of active and reactive power, more efficient use of existing lines, and an overall reduction in energy losses. Full article

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24 pages, 3697 KB

Open AccessArticle

Study of the Energy Consumption of Buses with Different Power Plants in Urban Traffic Conditions

by Miroslaw Smieszek, Vasyl Mateichyk, Jakub Mosciszewski and Nataliia Kostian

Energies 2025, 18(24), 6611; https://doi.org/10.3390/en18246611 - 18 Dec 2025

Viewed by 237

Abstract

Public transport still uses vehicles powered by fossil fuels. Replacing the fleet with zero-emission vehicles will take many years. During this period, it is still necessary to carry out work aimed at reducing energy consumption and thus the emission of toxic substances into [...] Read more.

Public transport still uses vehicles powered by fossil fuels. Replacing the fleet with zero-emission vehicles will take many years. During this period, it is still necessary to carry out work aimed at reducing energy consumption and thus the emission of toxic substances into the atmosphere. An important part of this work is the study of the relationship between energy demand of buses with different power plants and urban traffic conditions. These conditions include traffic intensity, average and maximum speeds, and number of stops. The VSP (Vehicle-Specific Power) model is useful in research on this relationship. In this article, such research was carried out using data from public bus monitoring and data provided by the city authorities of Rzeszów. In the first stage, a VSP model was created and tuned for three buses with different power plants operating on selected routes. Then, as a result of a large number of simulation processes, the impact of the average speed on the energy demand was determined. The results of the conducted research can be used in the modernization or planning of public transport networks and the modification of road infrastructure. All these activities should contribute to reducing energy consumption and environmental pollution. Full article

(This article belongs to the Section A: Sustainable Energy)

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33 pages, 1956 KB

Open AccessReview

Renewable Energy Integration in Sustainable Transport: A Review of Emerging Propulsion Technologies and Energy Transition Mechanisms

by Anna Kochanek, Tomasz Zacłona, Iga Pietrucha, Agnieszka Petryk, Urszula Ziemiańczyk, Zuzanna Basak, Paweł Guzdek, Leyla Akbulut, Atılgan Atılgan and Agnieszka Dorota Woźniak

Energies 2025, 18(24), 6610; https://doi.org/10.3390/en18246610 - 18 Dec 2025

Cited by 1 | Viewed by 659

Abstract

Decarbonization of transport is a key element of the energy transition and of achieving the Sustainable Development Goals. Integration of renewable energy into transport systems is assessed together with the potential of electric, hybrid, hydrogen, and biofuel-based propulsion to enable low emission mobility. [...] Read more.

Decarbonization of transport is a key element of the energy transition and of achieving the Sustainable Development Goals. Integration of renewable energy into transport systems is assessed together with the potential of electric, hybrid, hydrogen, and biofuel-based propulsion to enable low emission mobility. Literature published from 2019 to 2025 is synthesized using structured searches in Scopus, Web of Science, and Elsevier and evidence is integrated through a thematic comparative approach focused on energy efficiency, life cycle greenhouse gas emissions, and technology readiness. Quantitative findings indicate that battery electric vehicles typically require about 18 to 20 kWh per 100 km, compared with about 60 to 70 kWh per 100 km in energy equivalent terms for internal combustion cars. With higher renewable shares in electricity generation, life cycle CO₂ equivalent emissions are reduced by about 60 to 70 percent under average European grid conditions and up to about 80 percent when renewables exceed 50 percent. Energy storage and smart grid management, including vehicle to grid operation, are identified as enabling measures and are associated with peak demand reductions of about 5 to 10 percent. Hydrogen and advanced biofuels remain important for heavy duty, maritime, and aviation segments where full electrification is constrained. Full article

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25 pages, 3649 KB

Open AccessArticle

Comparative Analysis of CFD Simulations and Empirical Studies for a Heat Exchanger in a Dishwasher

by Wojciech Skarka, Maciej Mazur, Damian Kądzielawa and Robert Kubica

Energies 2025, 18(24), 6609; https://doi.org/10.3390/en18246609 - 18 Dec 2025

Viewed by 378

Abstract

This paper presents a side-by-side study of CFD predictions and experimental measurements for a novel counter-flow heat exchanger installed in the sidewall of a dishwasher (HEBS). The work aims to improve appliance efficiency by transferring heat from discharged hot wastewater to the incoming [...] Read more.

This paper presents a side-by-side study of CFD predictions and experimental measurements for a novel counter-flow heat exchanger installed in the sidewall of a dishwasher (HEBS). The work aims to improve appliance efficiency by transferring heat from discharged hot wastewater to the incoming cold supply. Motivated by sustainability goals and tightening EU energy rules, the research targets the high losses typical of conventional machines. This approach combines detailed ANSYS Fluent 2022R2 simulations with controlled laboratory tests on a bespoke test rig. The measured data show a repeatable rise in the cold-water temperature of roughly 8 K, corresponding to an approximate 15% gain in thermal performance for the heat-recovery stage. While the simulations and experiments efficiently agree based on trends and qualitative behavior, there are noticeable quantitative differences in the total energy transfer, indicating the models need further refinement. The validation carried out here forms a solid basis for design optimization and for reducing energy consumption in household dishwashers. This work overcomes the limitations of previous studies which typically rely on external storage tanks or static heat recovery analysis. The primary novelty of this paper lies in the empirical validation of a high-efficiency heat exchanger integrated into the extremely constrained sidewall volume of the appliance, tested under transient, on-the-fly flow conditions, providing a verified methodology for constrained industrial applications. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics (CFD) Study for Heat Transfer)

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16 pages, 4550 KB

Open AccessArticle

Multi-Step Artificial Neural Networks for Predicting Thermal Prosumer Energy Feed-In into District Heating Networks

by Mattia Ricci, Federico Gianaroli, Marcello Artioli, Simone Beozzo and Paolo Sdringola

Energies 2025, 18(24), 6608; https://doi.org/10.3390/en18246608 - 18 Dec 2025

Viewed by 242

Abstract

The heating and cooling sector accounts for nearly half of Europe’s energy consumption and remains heavily dependent on fossil fuels, emphasizing the urgent need for decarbonization. Simultaneously, the global shift toward renewable energy is accelerating, alongside growing interest in decentralized energy systems where [...] Read more.

The heating and cooling sector accounts for nearly half of Europe’s energy consumption and remains heavily dependent on fossil fuels, emphasizing the urgent need for decarbonization. Simultaneously, the global shift toward renewable energy is accelerating, alongside growing interest in decentralized energy systems where prosumers play a significant role. In this context, district heating and cooling networks, serving nearly 100 million people, are strategically important. In next-generation systems, thermal prosumers can feed-in locally produced or industrial waste heat into the network via bidirectional substations, allowing energy flows in both directions and enhancing system efficiency. The complexity of these networks, with numerous users and interacting heat flows, requires advanced predictive models to manage large volumes of data and multiple variables. This work presents the development of a predictive model based on artificial neural networks (ANNs) for forecasting excess thermal renewable energy from a bidirectional substation. The numerical model of a substation prototype designed by ENEA provided the physical data for the ANN training. Thirteen years of simulation results, combined with extensive meteorological data from ECMWF, were used to train and to test a multi-step ANN capable of forecasting the six-hour thermal power feed-in horizon using data from the preceding 24 h, improving operational planning and control strategies. The ANN model demonstrates high predictive capability and robustness in replicating thermal power dynamics. Accuracy remains high for horizons up to six hours, with MAE ranging from 279 W to 1196 W, RMSE from 662 W to 3096 W, and R² from 0.992 to 0.823. Overall, the ANN satisfactorily reproduces the behavior of the bidirectional substation even over extended forecasting horizons. Full article

(This article belongs to the Special Issue Advances in District Heating and Cooling)

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18 pages, 8729 KB

Open AccessArticle

Experimental and Modelling Study on the Performance of an SI Methanol Marine Engine Under Lean Conditions

by Shishuo Gong, Weijie Liu, Junbo Luo, Zhou Fang and Xiang Gao

Energies 2025, 18(24), 6607; https://doi.org/10.3390/en18246607 - 18 Dec 2025

Viewed by 264

Abstract

This study presents the experimental and modelling investigation of the performance of an SI methanol marine engine operating under lean conditions. The effects of spark timing and excess air ratio on combustion characteristics, engine performance, and emissions are explored. Multiple machine learning models, [...] Read more.

This study presents the experimental and modelling investigation of the performance of an SI methanol marine engine operating under lean conditions. The effects of spark timing and excess air ratio on combustion characteristics, engine performance, and emissions are explored. Multiple machine learning models, including Support Vector Machines (SVM), Artificial Neural Network (ANN), LightGBM, and Random Forest (RF), are employed to predict the engine performance and emission characteristics. Experimental results show that as spark timing advances, the combustion phase advances, with the burn duration being extended. When the excess air ratio is less than 1.35, there exists an optimal spark timing, corresponding to a maximum brake thermal efficiency. The optimal spark timing exhibits an advancing tendency along with increasing excess air ratio. HC emission is primarily determined by the excess air ratio and shows no significant variation under the different spark timings. NO_x emission is initially increased and then decreased with advancing spark timing. Compared with ANN, LightGBM, and RF, SVM demonstrates a superior predictive accuracy, with R² values for engine performance exceeding 0.98 and R² values for emissions above 0.92. Full article

(This article belongs to the Special Issue Performance and Emissions of Advanced Fuels in Combustion Engines)

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18 pages, 6899 KB

Open AccessArticle

A Novel Thermo-Thickening Oil-Based Drilling Fluid Based on Composite Thickener Under High Temperature and Pressure

by Weijie Chen, Xiaoming Tang, Leilei Wang, Hong Ma, Anliang Chen, Jian Zhang, Weian Huang, Guanzheng Zhuang, Hanyi Zhong and Xianbin Zhang

Energies 2025, 18(24), 6606; https://doi.org/10.3390/en18246606 - 18 Dec 2025

Viewed by 328

Abstract

Under high-temperature conditions in deep well formations, oil-based drilling fluids tend to show degraded rheological properties and reduced suspension capacity, which may impair wellbore cleanliness and circulation pump pressure and hinder drilling. To address this issue, a three-component composite thickener including fatty acid [...] Read more.

Under high-temperature conditions in deep well formations, oil-based drilling fluids tend to show degraded rheological properties and reduced suspension capacity, which may impair wellbore cleanliness and circulation pump pressure and hinder drilling. To address this issue, a three-component composite thickener including fatty acid polymers and clay activator was developed, and then the composite agents were used as the core component in formulating a thermo-thickening oil-based drilling fluid. Experimental results demonstrated that at up to 200 °C and 153 MPa, the fluid’s low-shear-rate viscosity and yield point increased steadily, while high-shear-rate viscosity and plastic viscosity remained nearly unchanged. The composite thickener largely enhanced the fluid’s storage modulus and inner structural force, thus improving its rheological properties and suspension capacity under high-temperature and high-pressure conditions. Based on these findings, the thermo-thickening oil-based drilling fluid was supposed to address the critical diminished rheological stability and suspension capacity of conventional oil-based drilling fluids in complex formations with promising application prospects. Full article

(This article belongs to the Section H: Geo-Energy)

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21 pages, 8444 KB

Open AccessArticle

A Novel Standalone TRNSYS Type for a Patented Shallow Ground Heat Exchanger: Development and Implementation in a DSHP System

by Silvia Cesari, Yujie Su and Michele Bottarelli

Energies 2025, 18(24), 6605; https://doi.org/10.3390/en18246605 - 17 Dec 2025

Viewed by 285

Abstract

Decarbonizing building energy use requires efficient heat pumps and low-impact geothermal exchangers. A novel standalone TRNSYS Type was developed for a patented shallow horizontal ground heat exchanger (HGHE), called flat-panel (FP), designed at the University of Ferrara. Beyond simulating the FP in isolation, [...] Read more.

Decarbonizing building energy use requires efficient heat pumps and low-impact geothermal exchangers. A novel standalone TRNSYS Type was developed for a patented shallow horizontal ground heat exchanger (HGHE), called flat-panel (FP), designed at the University of Ferrara. Beyond simulating the FP in isolation, the Type enables coupling with other components within heat-pump configurations, allowing performance assessments that reflect realistic operating conditions. The Type was implemented in TRNSYS models of a ground-source heat pump (GSHP) and of a dual air and ground source heat pump (DSHP) to verify Type reliability and evaluate potential DSHP advantages over GSHP in terms of efficiency and ground-loop downsizing. The performance of the system was analyzed under varying HGHE lengths and DSHP control strategies, which were based on onset temperature differential

D T

. The results highlighted that shorter HGHE lines yielded higher specific HGHE performance, while higher

D T

reduced HGHE operating time. Concurrently, the total energy extracted from the ground decreased with increasing

D T

and reduced length, thus supporting long-term thermal preservation and allowing HGHE to operate under more favorable conditions. Exploiting air as an alternative or supplemental source to the ground allows significant reduction of the HGHE length and the related installation costs, without compromising the system performance. Full article

(This article belongs to the Special Issue Ground-Source Heat Pumps and Thermal Energy Storage Systems—Energy for the Future)

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19 pages, 3543 KB

Open AccessArticle

Scheme Design and Performance Optimization for a 660 MW Ultra-Supercritical Coal Fired Unit Coupled with a Molten Salt Energy Storage System

by Bin Zhang, Wei Su, Junbo Yang, Congyu Wang, Cuiping Ma, Luyun Wang and Xiaohan Ren

Energies 2025, 18(24), 6604; https://doi.org/10.3390/en18246604 - 17 Dec 2025

Viewed by 326

Abstract

With the continuous increase in the proportion of renewable energy in the power grid, enhanced operational flexibility of the power system is required. As baseload generators, combined heat and power (CHP) units are prime candidates for flexibility retrofits that guarantee grid stability. Among [...] Read more.

With the continuous increase in the proportion of renewable energy in the power grid, enhanced operational flexibility of the power system is required. As baseload generators, combined heat and power (CHP) units are prime candidates for flexibility retrofits that guarantee grid stability. Among the available options, molten-salt thermal energy storage (TES) offers an energetically efficient route to decouple heat and electricity production in CHP plants. In this study, a 660 MW ultra-supercritical coal-fired unit is taken as the object of investigation. Sixteen technical routes incorporating steam extraction and electric heating for thermal energy storage and discharging are systematically designed. Results demonstrate that all the combined schemes significantly improve the operational flexibility of the unit. Among them, the C1-S1 configuration exhibits the most outstanding overall economic performance, with a six-hour thermal storage capacity of 294.34 MWh. The system exergy destruction is measured at 6258 kW, while the round-trip efficiency and thermal efficiency are determined to be 81.11% and 45.48%, respectively. Full article

(This article belongs to the Special Issue Advances and Applications in Hybrid Simulation for Future Power and Energy Systems)

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