Energies

21 pages, 2703 KiB

Open AccessArticle

Efficiency and Energy Consumption of Partial Carbonation Process for CO₂ Capture from Natural Gas Combustion

by Rubens Coutinho Toledo, Caio Leandro de Moraes, Vinoth Thangarasu, João Andrade de Carvalho, Jr. and Ivonete Avila

Energies 2025, 18(9), 2285; https://doi.org/10.3390/en18092285 (registering DOI) - 29 Apr 2025

Abstract

Brazil has set a goal to reduce greenhouse gas (GHG) emissions, which is a significant opportunity to leverage calcium looping (CaL) technology for energy generation in natural gas power plants. CaL is a promising technology, due to sorbent low cost and availability, but [...] Read more.

Brazil has set a goal to reduce greenhouse gas (GHG) emissions, which is a significant opportunity to leverage calcium looping (CaL) technology for energy generation in natural gas power plants. CaL is a promising technology, due to sorbent low cost and availability, but its industrial implementation performance decay is a major challenge to face. While evaluating carbon-capture technologies, net emissions perspective is essential, and optimizing CaL capture through a partial carbonation cycle is a promising approach, both to reduce net emissions and improve the number of cycles before deactivation. In this context, a Brazilian dolomite was characterized and evaluated, to be used as sorbent in a CaL process employed in natural gas power plants. For such a purpose, a novel methodology has been proposed to evaluate the mass ratio of CO₂ captured, to assess the energy consumed in the process. A rotatable central composite design (RCCD) model was used to identify the optimal temperature and residence time conditions in the carbonation stage of the CaL process, focusing on achieving energy efficiency. The five most promising conditions were then tested across 10 calcination–carbonation cycles, to examine the impact of partial carbonation in capture efficiency over extended cycles. The results indicate that temperature plays a critical role in the process, particularly in terms of capture efficiency, while residence time significantly affects energy consumption. The conditions that demonstrated optimal performance for both the single and the multi-cycle tests were 580 °C for 7.5 min and 550 °C for 10 min, given that index of capture efficiency (

{IEC}_{10, c}

) values of 1.34 and 1.20 were found, respectively—up to 40% higher than at 475 °C. There was lower energy expenditure at 580 °C (

E_{s p}

) (33.48 kJ), 550 °C (

E_{s p}

= 37.97 kJ),

{CO}_{2}

mass captured (

{CO}_{2} c a p

= 9.80 mg), and the samples exhibited a more preserved surface, thus making it the most suitable option for scale-up applications. Full article

(This article belongs to the Section B3: Carbon Emission and Utilization)

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24 pages, 4775 KiB

Open AccessArticle

Analysis of the Pelletability of Vegetable Crop Foliage Using a Commercial Flat Die Pellet Mill

by Omid Gholami Banadkoki, Shahab Sokhansanj and Anthony Lau

Energies 2025, 18(9), 2284; https://doi.org/10.3390/en18092284 (registering DOI) - 29 Apr 2025

Abstract

Agricultural residues serve as a vast yet underutilized biomass resource with significant potential for bioenergy and biomaterial applications. Converting these residues into densified biomass pellets enhances energy density, handling efficiency, and transportability, offering a sustainable alternative to conventional feedstocks. While extensive research has [...] Read more.

Agricultural residues serve as a vast yet underutilized biomass resource with significant potential for bioenergy and biomaterial applications. Converting these residues into densified biomass pellets enhances energy density, handling efficiency, and transportability, offering a sustainable alternative to conventional feedstocks. While extensive research has focused on woody biomass, studies on the pelletization of vegetable crop foliage remain limited. This study examines the pelletability of foliage from corn, soybean, tomato, eggplant, cucumber, and summer squash, assessing their physical properties, bulk durability, bulk density, and energy consumption during pelletization. Results demonstrated that variation in biomass composition significantly influences pellet quality, with lignin content improving durability and ash content affecting moisture uptake and combustion properties. Cucumber had the highest pellet density (691.2 kg/m³) and durability (97.9%), making it suitable for long-term storage and transport. Sawdust exhibited the lowest moisture absorption (16–18% db), which is attributed to its highest lignin content. Pelletization energy requirements varied significantly, with cucumber (21.8 kWh/t) and summer squash (18.7 kWh/t) requiring the lowest energy input, whereas soybean (49.6 kWh/t) and sawdust (47.3 kWh/t) exhibited the highest energy demands due to greater resistance to densification. A predictive model was developed to correlate single pellet density and durability with bulk pellet properties—yielding high predictive accuracy, with R² = 0.936 for bulk density (𝐵𝐷ₑ) and R² = 0.861 for bulk durability (𝐵𝐷ᵤ)—thereby facilitating process optimization for large-scale pellet production. This study demonstrated that foliage residues from greenhouse crops, such as cucumber and summer squash, can be effectively pelletized with low energy input and high physical integrity. These outcomes suggest that such underutilized agricultural residues hold promise as a densified intermediate feedstock, supporting future applications in bioenergy systems and advancing circular resource use in controlled-environment agriculture. Full article

(This article belongs to the Special Issue Biomass and Bio-Energy—2nd Edition)

20 pages, 3991 KiB

Open AccessArticle

Multi-Objective Optimization for the Low-Carbon Operation of Integrated Energy Systems Based on an Improved Genetic Algorithm

by Yao Duan, Chong Gao, Zhiheng Xu, Songyan Ren and Donghong Wu

Energies 2025, 18(9), 2283; https://doi.org/10.3390/en18092283 (registering DOI) - 29 Apr 2025

Abstract

As global climate change and energy crises intensify, the pursuit of low-carbon integrated energy systems (IESs) has become increasingly important. This paper proposes an improved genetic algorithm (IGA) designed to optimize the multi-objective low-carbon operations of IESs, aiming to minimize both operating costs [...] Read more.

As global climate change and energy crises intensify, the pursuit of low-carbon integrated energy systems (IESs) has become increasingly important. This paper proposes an improved genetic algorithm (IGA) designed to optimize the multi-objective low-carbon operations of IESs, aiming to minimize both operating costs and carbon emissions. The IGA incorporates circular crossover and polynomial mutation techniques, which not only preserve advantageous traits from the parent population but also enhance genetic diversity, enabling comprehensive exploration of potential solutions. Additionally, the algorithm selects parent populations based on individual fitness and dominance, retaining successful chromosomes and eliminating those that violate constraints. This process ensures that subsequent generations inherit superior genetic traits while minimizing constraint violations, thereby enhancing the feasibility of the solutions. To evaluate the effectiveness of the proposed algorithm, we tested it on three different IES scenarios. The results demonstrate that the IGA successfully reduces equality constraint violations to below 0.3 kW, representing less than 0.2% deviation from the IES’s power demand in each time slot. We compared its performance against a multi-objective genetic algorithm, a multi-objective particle swarm algorithm, and a single-objective genetic algorithm. Compared to conventional genetic algorithms, the IGA achieved maximum 5% improvement in both operational cost reduction and carbon emission minimization objectives compared to the unimproved single-objective genetic algorithm, demonstrating its superior performance in multi-objective optimization for low-carbon IESs. These outcomes underscore the algorithm’s reliability and practical applicability. Full article

(This article belongs to the Special Issue Advances in Simulations and Analysis of Electrical Power Systems: Enhancing Efficiency, Reliability and Sustainability)

22 pages, 3809 KiB

Open AccessArticle

Optimized Feedback Type Flux Weakening Control of Non-Salient Permanent Magnet Synchronous Machines in MTPV Region with Improved Stability

by Chao Wang, Ziqiang Zhu, Lei Xu, Ximeng Wu and Kejin Lu

Energies 2025, 18(9), 2282; https://doi.org/10.3390/en18092282 (registering DOI) - 29 Apr 2025

Abstract

This paper introduces an enhanced approach for optimizing the flux-weakening performance of a non-salient permanent magnet synchronous machine (PMSM), by incorporating the maximum torque per voltage (MTPV) region into a conventional voltage magnitude feedback control strategy. The MTPV control strategy is initially optimized [...] Read more.

This paper introduces an enhanced approach for optimizing the flux-weakening performance of a non-salient permanent magnet synchronous machine (PMSM), by incorporating the maximum torque per voltage (MTPV) region into a conventional voltage magnitude feedback control strategy. The MTPV control strategy is initially optimized for steady-state performance by incorporating the effect of resistance, which plays a crucial role in small power motors. To maintain stability and good dynamics in the flux-weakening region, a current command feedback MTPV controller is utilized, as opposed to a voltage command feedback approach. Additionally, to address stability concerns in the MTPV region, a feedback type proportional-integral (PI) MTPV controller is designed and implemented. The stability in both the over-modulation and various flux-weakening regions is further enhanced using a voltage vector modifier (VVM). Therefore, the proposed feedback-based flux-weakening control enhances system steady-state performance, dynamic response, and stability across both linear and over modulation regions under various flux-weakening conditions, making it suitable for general-purpose applications. The effectiveness of the proposed method is validated through experimental results. Full article

(This article belongs to the Special Issue Emerging Trends in Closed-Loop Control Systems for Electric Machines and Drives: From Classical Techniques to Smart Solutions)

18 pages, 2153 KiB

Open AccessArticle

The Impacts of Water Policies and Hydrological Uncertainty on the Future Energy Transition of the Power Sector in Shanxi Province, China

by Xingtong Chen, Jijian Lian and Qizhong Guo

Energies 2025, 18(9), 2281; https://doi.org/10.3390/en18092281 (registering DOI) - 29 Apr 2025

Abstract

Water scarcity under climate change and increasingly stringent water conservation policies may trigger energy security concerns. The current study develops an optimization model to investigate the impacts of water conservation policies and hydrological uncertainties on the regional energy transition process in Shanxi Province, [...] Read more.

Water scarcity under climate change and increasingly stringent water conservation policies may trigger energy security concerns. The current study develops an optimization model to investigate the impacts of water conservation policies and hydrological uncertainties on the regional energy transition process in Shanxi Province, China. The dual-control policies on total water consumption and water intensity are systematically examined for their differential constraints and stimulative effects on various power generation types. Hydrological time series analysis methods are employed to project future water resource variations in Shanxi Province and evaluate their implications for power system optimization. The results indicate that (1) total water constraint policies are more stringent than water intensity constraint policies; (2) changes in water resource availability impose greater restrictions on coal power development than those imposed by current water conservation policies; and (3) when total water resources decrease by approximately 43.5% compared with 2020 levels, Shanxi Province may face electricity shortages. These findings suggest that water conservation policy formulation should be coordinated with regional power sector development planning, while also considering potential energy security risks posed by potential future reductions in water resources. Full article

32 pages, 5315 KiB

Open AccessArticle

Correlating Indoor Environmental Quality Parameters with Human Physiological Responses for Adaptive Comfort Control in Commercial Buildings

by Haoyue Dai, Saba Imani and Joon-Ho Choi

Energies 2025, 18(9), 2280; https://doi.org/10.3390/en18092280 (registering DOI) - 29 Apr 2025

Abstract

This study investigates the critical role of indoor environmental quality (IEQ) adaptations in influencing human physiological responses within commercial building settings. By integrating environmental engineering and human physiology, this research offers empirical insights into the relationship between IEQ modifications and occupant well-being, particularly [...] Read more.

This study investigates the critical role of indoor environmental quality (IEQ) adaptations in influencing human physiological responses within commercial building settings. By integrating environmental engineering and human physiology, this research offers empirical insights into the relationship between IEQ modifications and occupant well-being, particularly in the context of energy performance and efficiency. This study examines correlations between human physiological responses and key IEQ components, including indoor air quality (IAQ), thermal comfort, lighting, and acoustics, using data collected from two office areas with 14 participants. Sensors tracked environmental parameters, while wearable devices monitored physiological responses. Cross-correlation analysis revealed significant relationships between physiological indicators and environmental factors, with indoor temperature, PM_2.5, and relative humidity showing the strongest impacts on electrodermal activity, skin temperature, and stress levels, respectively (p < 0.05). Furthermore, supervised machine learning techniques were employed to develop predictive models that evaluate IAQ and thermal comfort at both personal and general levels. Individual models achieved 84.76% accuracy for IAQ evaluation and 70.5% for thermal comfort prediction, outperforming the general model (69.7% and 64.3%, respectively). Males showed greater overall sensitivity to IEQ indicators, while females demonstrated higher sensitivity specifically to air quality and thermal comfort conditions. The findings underscore the potential of physiological signals to predict environmental satisfaction, providing a foundation for designing energy-efficient buildings that prioritize occupant health and comfort. This research bridges a critical gap in the literature by offering data-driven approaches to align sustainable building practices with human-centric needs. Future studies should expand participant diversity and explore broader demographics to enhance the robustness and applicability of predictive models. Full article

(This article belongs to the Special Issue Human-Centered Energy Optimization in Built Environment)

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15 pages, 3536 KiB

Open AccessArticle

A Low-Cost Wireless Monitoring System for Photovoltaic Systems: Performance Analysis and Potential Application in Direct-Current Nanogrids

by Norman J. Beltrán Castañón, Fredy Chura Acero, José Ramos Cutipa, Omar Chayña Velásquez, Henry Shuta Lloclla and Edisson Cruz Ticona

Energies 2025, 18(9), 2279; https://doi.org/10.3390/en18092279 (registering DOI) - 29 Apr 2025

Abstract

The unique challenges posed by the high altitude and extreme-irradiance variability in the Peruvian Altiplano necessitate innovative and cost-effective monitoring solutions for photovoltaic (PV) systems. This study presents a low-cost wireless monitoring system for PV systems, designed for performance analysis and with potential [...] Read more.

The unique challenges posed by the high altitude and extreme-irradiance variability in the Peruvian Altiplano necessitate innovative and cost-effective monitoring solutions for photovoltaic (PV) systems. This study presents a low-cost wireless monitoring system for PV systems, designed for performance analysis and with potential application in DC nanogrids. The system, based on an Arduino Nano and Raspberry Pi architecture, captures real-time data on key electrical parameters such as voltage, current, and power, as well as environmental conditions like temperature and irradiance, which are critical factors influencing PV system performance. Deployed on a 3 kW grid-connected PV system in the Peruvian Altiplano, the system reveals significant irradiance variability, with fluctuations exceeding 20% within a single day and extreme events surpassing 1500 W/m². This variability resulted in an average daily energy generation fluctuation of 15%, underscoring the importance of continuous monitoring for optimizing PV system operation. This variability impacts energy generation and underscores the importance of continuous monitoring for optimizing PV system operation. The study analyzes the system’s performance under different irradiance conditions and discusses its adaptability for use in DC nanogrids, which offer enhanced efficiency and accessibility in remote areas like the Altiplano. This research contributes a practical and versatile tool for advancing sustainable energy solutions, with implications for improving the efficiency and reliability of both grid-connected PV systems and the emerging field of DC nanogrids in remote areas. Full article

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

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21 pages, 831 KiB

Open AccessArticle

Scenarios of Carbon Capture and Storage Importance in the Process of Energy System Transformation in Poland

by Aurelia Rybak and Jarosław Joostberens

Energies 2025, 18(9), 2278; https://doi.org/10.3390/en18092278 (registering DOI) - 29 Apr 2025

Abstract

One of the most important issues in the coming years will be the decarbonisation of the European Union member states’ energy systems. The majority of the abstract requires modification. I propose that the first sentence of the abstract in the manuscript should better [...] Read more.

One of the most important issues in the coming years will be the decarbonisation of the European Union member states’ energy systems. The majority of the abstract requires modification. I propose that the first sentence of the abstract in the manuscript should better emphasize the formulation of the problem. The remaining part and any corrections were made by the author.Scenarios of the importance of CCS in the process of transformation of energy systems in Poland. One of the most important issues in the coming years will be the transformation of the energy systems of the European Union’s member states, which will require the development of appropriate technological solutions. The research presented here analyses the importance of CCS in energy transformation. This article proposes adapting the energy transformation method to the structure of the energy mix and conditions prevailing in a specific country. Poland was adopted as an example for analysis due to its exceptionally complicated situation, taking into account the structure of energy production. For this purpose, an expert opinion survey was conducted. Both measurable variables, such as the volume of CO₂ emissions and EU ETS prices, and a qualitative variable, i.e., the impact of the political environment on the development of CCS, were introduced to the constructed model. The model allowed us to construct three scenarios describing alternative visions for the future development of CCS: optimistic, pessimistic, and neutral, taking into account different conditions in which CCS can develop. The use of fuzzy sets allowed us to eliminate the most serious drawback of planning scenarios based on expert knowledge, which is the subjectivity of their judgments. This research showed that stable conditions of the political environment and predictable legal regulations will be crucial for the application of CCS in the Polish energy sector. The prepared scenarios will enable a quick response and accurate decisions under various conditions of the turbulent environment. This will facilitate the preparation of energy strategies. The scenarios indicate what combinations of variables, under given environmental conditions, of CCS will be of great importance in the energy transformation, and when it may give way to other technologies. In addition, the scenarios, and especially their visualisation, are extremely valuable for stakeholders, because they will allow them to observe the potential development of the situation under known conditions of the political environment, prices, and CO₂ emissions. They enable understanding the dependence of the importance of CCS in the changing environment. They also enable the detection of critical points for the development of CCS, which, as a result of recent geopolitical events, may be of key importance in the near future for ensuring the energy and military security of Poland and the EU. Full article

(This article belongs to the Special Issue Carbon Capture, Energy Consumption and Storage Technologies in Energy Systems for Green Energy Transition)

15 pages, 930 KiB

Open AccessArticle

Impact of Ethanol–Diesel Blend on CI Engine Performance and Emissions

by Mieczysław Sikora, Piotr Orliński and Mateusz Bednarski

Energies 2025, 18(9), 2277; https://doi.org/10.3390/en18092277 (registering DOI) - 29 Apr 2025

Abstract

The aim of this study was to assess the impact of adding ethanol to diesel fuel on particulate matter (PM) and nitrogen oxides (NOx) emissions in the Perkins 854E compression-ignition engine. Tests were carried out under European Stationary Cycle (ESC) conditions using the [...] Read more.

The aim of this study was to assess the impact of adding ethanol to diesel fuel on particulate matter (PM) and nitrogen oxides (NOx) emissions in the Perkins 854E compression-ignition engine. Tests were carried out under European Stationary Cycle (ESC) conditions using the Horiba Mexa 1230 PM analyzer (HORIBA, Ltd., Kyoto, Japan) for particulate measurement and the AVL CEB II analyzer (AVL, Graz, Austria) for NO_x concentration. The engine under investigation featured direct injection, turbocharging, a common-rail fuel supply system, and complied with the Stage IIIB/Tier 4 emission standard. Two types of fuel were used: conventional diesel fuel (DF) and diesel with a 10% ethanol additive by volume (DFE10). In addition to emissions measurements, key engine performance parameters, such as torque, effective power, and fuel consumption, were analyzed. The ESC test was specifically chosen to isolate the influence of the fuel’s properties by avoiding the effects of changes in combustion control strategies. Due to the lower calorific value of DFE10 compared to DF, a slight increase in fuel consumption was observed under certain operating conditions. Nevertheless, overall engine performance remained largely unchanged. The test results showed that the use of DFE10 led to a significant 44% reduction in particulate matter emissions and a moderate 2.2% decrease in NO_x emissions compared to conventional diesel fuel. These findings highlight the potential of ethanol as a diesel fuel additive to reduce harmful exhaust emissions without negatively affecting the performance of modern diesel engines. Full article

(This article belongs to the Special Issue Numerical and Experimental Study of Alternative Fuel Combustion in Internal Combustion Engines)

18 pages, 2299 KiB

Open AccessArticle

Study on Direct-Contact Prelithiation of Soft Carbon Anodes Using Lithium Foil for Lithium-Ion Capacitors

by Minji Kang, Sanghyeock Jeong, Gabjin Hwang and Cheolhwi Ryu

Energies 2025, 18(9), 2276; https://doi.org/10.3390/en18092276 (registering DOI) - 29 Apr 2025

Abstract

As the global energy demand continues to rise, the utilization of lithium-ion capacitors (LICs), which combine the advantages of lithium-ion batteries (LIBs) and electrochemical capacitors (ECs), is also increasing. LICs offer high energy density, high power density, and a long life cycle. However, [...] Read more.

As the global energy demand continues to rise, the utilization of lithium-ion capacitors (LICs), which combine the advantages of lithium-ion batteries (LIBs) and electrochemical capacitors (ECs), is also increasing. LICs offer high energy density, high power density, and a long life cycle. However, a prelithiation process is required for graphite-based anode materials. In LICs, the formation of the solid electrolyte interphase (SEI) layer inevitably causes an initial irreversible capacity loss, often resulting in the excessive consumption of lithium ions. Considering the limited lithium resources, prelithiation is essential to achieve a satisfactory electrochemical performance in LICs. Various anode prelithiation techniques have been reported to enhance the capacity of LIBs and LICs. Among these, the direct-contact prelithiation method involves physically contacting lithium metal with the electrode or active material. In this study, direct-contact prelithiation was performed on soft carbon-based anode materials, and LICs were fabricated using activated carbon-based cathode materials. The electrochemical properties of the fabricated LICs were evaluated to demonstrate the feasibility of applying the direct-contact prelithiation technique. Full article

(This article belongs to the Section D: Energy Storage and Application)

24 pages, 2770 KiB

Open AccessArticle

Research on the Root Cause Tracing Method of the Change in Access to Electricity Index Based on Data Mining

by Hongshan Luo, Xu Zhou, Weiqi Zheng and Yuling He

Energies 2025, 18(9), 2275; https://doi.org/10.3390/en18092275 (registering DOI) - 29 Apr 2025

Abstract

Superior electricity-optimized business ecosystems (EOBEs) have evolved into pivotal determinants in catalyzing industrial–commercial prosperity. The access to electricity index (AEI) constitutes a valid instrument for assessing the EOBE. To realize the accurate evaluation of EOBE and the root cause tracing of its changes, [...] Read more.

Superior electricity-optimized business ecosystems (EOBEs) have evolved into pivotal determinants in catalyzing industrial–commercial prosperity. The access to electricity index (AEI) constitutes a valid instrument for assessing the EOBE. To realize the accurate evaluation of EOBE and the root cause tracing of its changes, this paper constructs a new analytical model for evaluating and monitoring changes in EOBE. First, this paper constructs a new evaluation model of EOBE based on the Business Ready (B-READY) evaluation system, considering three factors: the power regulatory quality, the public service level, and the enterprises’ gain power efficiency. Then, the model uses the raw data collected to calculate a score for AEI to enable an accurate assessment of EOBE. Next, this paper uses a priori assessment to extract the coupling features of indicators and combines the time series features and policy features to construct the feature matrix. Finally, the characteristic contribution was analyzed using support vector regression (SVR) and Shapley’s additive interpretation (SHAP) value. The experiment shows that the factors affecting the change in AEI are time series features, policy features, and coupling features in decreasing order of importance. This study provides reference cases and improvement ideas for the assessment and optimization of EOBE. Full article

35 pages, 43716 KiB

Open AccessReview

Reducing Rare-Earth Magnet Reliance in Modern Traction Electric Machines

by Oliver Mitchell Lee and Mohammadali Abbasian

Energies 2025, 18(9), 2274; https://doi.org/10.3390/en18092274 (registering DOI) - 29 Apr 2025

Abstract

Currently, electric machines predominantly rely on costly rare-earth NdFeB magnets, which pose both economic and environmental challenges due to rising demand. This research explores recent advancements in machine topologies and magnetic materials to identify and assess promising solutions to this issue. The study [...] Read more.

Currently, electric machines predominantly rely on costly rare-earth NdFeB magnets, which pose both economic and environmental challenges due to rising demand. This research explores recent advancements in machine topologies and magnetic materials to identify and assess promising solutions to this issue. The study investigates two alternative machine topologies to the conventional permanent magnet synchronous machine (PMSM): the permanent magnet-assisted synchronous reluctance machine (PMaSynRM), which reduces magnet usage, and the wound-field synchronous machine (WFSM), which eliminates magnets entirely. Additionally, the potential of ferrite and recycled NdFeB magnets as substitutes for primary NdFeB magnets is evaluated. Through detailed simulations, the study compares the performance and cost-effectiveness of these solutions against a reference permanent magnet synchronous machine (PMSM). Given their promising performance characteristics and potential to reduce or eliminate the use of rare-earth materials in next-generation electric machines, it is recommended that future research should focus on novel topologies like hybrid-excitation, axial-flux, and switched reluctance machines with an emphasis on manufacturability and also novel magnetic materials such as FeN and MnBi that are currently seeing synthesis challenges. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Multiphase Induction Generators: Design, Optimization, and Application 2024)

31 pages, 1146 KiB

Open AccessArticle

The Development and Evaluation of a Low-Emission, Fuel-Flexible, Modular, and Interchangeable Solid Oxide Fuel Cell System Architecture for Combined Heat and Power Production: The SO-FREE Project

by Enrico Bocci, Alessandro Dell’Era, Carlo Tregambe, Giacomo Tamburrano, Vera Marcantonio and Francesca Santoni

Energies 2025, 18(9), 2273; https://doi.org/10.3390/en18092273 - 29 Apr 2025

Abstract

Within the framework of the SOCIETAL CHALLENGES—Secure, Clean, and Efficient Energy objective under the European Horizon 2020 research and innovation funding program, the SO-FREE project has developed a future-ready solid oxide fuel cell (SOFC) system with high-efficiency heat recovery. The system concept prioritizes [...] Read more.

Within the framework of the SOCIETAL CHALLENGES—Secure, Clean, and Efficient Energy objective under the European Horizon 2020 research and innovation funding program, the SO-FREE project has developed a future-ready solid oxide fuel cell (SOFC) system with high-efficiency heat recovery. The system concept prioritizes low emissions, fuel flexibility, modular power production, and efficient thermal management. A key design feature is the interchangeability of two different SOFC stack types, allowing for operation under different temperature conditions. The system was developed with a strong emphasis on simplicity, minimizing the number of components to reduce overall plant costs while maintaining high performance. This paper presents the simulation results of the proposed flexible SOFC system, conducted using Aspen Plus^® software version 11 to establish a baseline architecture for real plant development. The simulated layout consists of an autothermal reformer (ATR), a high-temperature blower, an SOFC stack, a burner, and a heat recovery system incorporating four heat exchangers. Simulations were performed for two different anodic inlet temperatures (600 °C and 700 °C) and three fuel compositions (100% CH₄, 100% H₂, and 50% H₂ + 50% CH₄), resulting in six distinct operating scenarios. The results demonstrate a system utilization factor (UF_F) exceeding 90%, electrical efficiency ranging from 60% to 77%, and an effective heat recovery rate above 60%. These findings were instrumental in the development of the Piping and Instrumentation Diagram (P&ID) required for the design and implementation of the real system. The proposed SOFC system represents a cost-effective and adaptable energy conversion solution, contributing to the advancement of high-efficiency and low-emission power generation technologies. Full article

38 pages, 910 KiB

Open AccessReview

Impact of Agriculture on Greenhouse Gas Emissions—A Review

by Karolina Sokal and Magdalena Kachel

Energies 2025, 18(9), 2272; https://doi.org/10.3390/en18092272 - 29 Apr 2025

Abstract

The restrictions imposed by the European Green Deal on Europe are expected to make Europe climate-neutral by 2050. In this context, this article examines the current efforts to reduce emission levels, focusing on available international scientific papers concerning European territory, particularly Poland. The [...] Read more.

The restrictions imposed by the European Green Deal on Europe are expected to make Europe climate-neutral by 2050. In this context, this article examines the current efforts to reduce emission levels, focusing on available international scientific papers concerning European territory, particularly Poland. The study paid special attention to the sector of agriculture, which is considered a key contributor to greenhouse gas generation. It also analysed the impact of various tillage techniques and the application of organic and inorganic fertilisers, e.g., nitrogen fertilisers, digestate, or compost, on the emissions of greenhouse gases and other environmentally harmful substances. Although there are few scientific articles available that comprehensively describe the problem of greenhouse gas emissions from agriculture, it is still possible to observe the growing awareness of farmers and their daily impact on the environment. The current study demonstrated that agricultural activities significantly contribute to the emissions of three main greenhouse gases: carbon dioxide, nitrous oxide, and methane. The tillage and soil fertilisation methods used play a crucial role in their emissions into the atmosphere. The use of no-tillage (or reduced-tillage) techniques contributes to the sustainable development of agriculture while reducing greenhouse gas emissions. The machinery and fuels used, along with innovative systems and sensors for precise fertilisation, play a significant role in lowering emission levels in agriculture. The authors intend to identify potential opportunities to improve crop productivity and contribute to sustainable reductions in gas emissions. Full article

(This article belongs to the Section B1: Energy and Climate Change)

26 pages, 3022 KiB

Open AccessArticle

Common Rail Injector Operation Model and Its Validation

by Karol Dębowski and Mirosław Karczewski

Energies 2025, 18(9), 2271; https://doi.org/10.3390/en18092271 - 29 Apr 2025

Abstract

The aim of this study was to develop and subsequently validate a simulation model of a Common Rail (CR) system injector. The study includes a description of simulation and experimental tests conducted under various injector operating conditions. Experimental tests were performed using the [...] Read more.

The aim of this study was to develop and subsequently validate a simulation model of a Common Rail (CR) system injector. The study includes a description of simulation and experimental tests conducted under various injector operating conditions. Experimental tests were performed using the STPiW-2 test bench. The operating conditions of the injector were varied in terms of injection pressure and injector opening time. The injector model was developed using the Amesim software, where simulation studies were also conducted. The simulations focused on generating injection characteristics, specifically the volume of fuel injected per injection at pressures ranging from 20 MPa to 140 MPa in 10 MPa increments. Four such injection characteristics were obtained during both experimental and simulation studies, corresponding to injector opening times of 500 µs, 1000 µs, 1500 µs, and 2000 µs. Additionally, volume characteristics were generated under the same conditions. The validation demonstrated a high level of accuracy for the developed model. The obtained injection characteristics exhibited a correlation coefficient exceeding 90% in all four cases. The most accurately replicated injection characteristic was for the 500 µs injector opening time, achieving a correlation coefficient of 99%. Meanwhile, the simulation-derived overflow volume characteristic matched the experimental results with a correlation of 98%. For longer injector opening times, the correlation coefficients were slightly lower but remained satisfactory. The study concluded that for short injector opening times, the assumed model simplifications had minimal impact on the injected fuel volume at a given pressure. However, for longer opening times, discrepancies between simulation and experimental results became more pronounced. This divergence could be attributed to pressure variability within the injector during operation and associated hydraulic phenomena. Full article

(This article belongs to the Topic Energy Systems: Design, Management, Control and Monitoring)

17 pages, 6082 KiB

Open AccessArticle

Thermal Management in 500 kV Oil-Immersed Converter Transformers: Synergistic Investigation of Critical Parameters Through Simulation and Experiment

by Zhengqin Zhou, Chuanxian Luo, Fengda Zhang, Jing Zhang, Xu Yang, Peng Yu and Minfu Liao

Energies 2025, 18(9), 2270; https://doi.org/10.3390/en18092270 - 29 Apr 2025

Abstract

Aimed at solving the problem of insulation failure caused by the local overheating of the oil-immersed converter transformer, this paper investigates the heat transfer characteristics of the 500 kV converter transformer based on the electromagnetic-flow-heat coupling model. Firstly, this paper used the finite [...] Read more.

Aimed at solving the problem of insulation failure caused by the local overheating of the oil-immersed converter transformer, this paper investigates the heat transfer characteristics of the 500 kV converter transformer based on the electromagnetic-flow-heat coupling model. Firstly, this paper used the finite element method to calculate the core and winding loss. Then, a two-dimensional fluid-heat coupling model was used to investigate the effects of the inlet flow rate and the radius of the oil pipe on the heat transfer characteristics. The results show that the larger the inlet flow rate, the smaller the specific gravity of high-temperature transformer oil at the upper end of the tank. Increasing the pipe radius can reduce the temperature of the heat dissipation of the transformer in relative equilibrium. Still, the pipe radius is too large to lead to the reflux of the transformer oil in the oil outlet. Increasing the central and sub-winding turn distance, the oil flow diffusion area and flow velocity increase. Thus, the temperature near the winding is reduced by about 9%, and the upper and lower wall temperature is also reduced by about 4%. Based on the analysis of the sensitivity weight indicators of the above indicators, it is found that the oil flow rate has the largest share of influence on the hot spot temperature of the transformer. Finally, the surface temperature of the oil tank when the converter transformer is at full load is measured. In the paper, the heat transfer characteristics of the converter transformer are investigated through simulation and measurement, which can provide a certain reference value for the study of the insulation performance of the converter transformer. Full article

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

19 pages, 1891 KiB

Open AccessArticle

Detection of Cross-Line Successive Faults in Non-Effective Neutral Grounding Distribution Networks

by Yuxuan Jin, Bin Wang, Mingming Xu, Ruirui Xie, Zhi Li and Xuan Dong

Energies 2025, 18(9), 2269; https://doi.org/10.3390/en18092269 (registering DOI) - 29 Apr 2025

Abstract

In a non-effectively grounded neutral point distribution network, prolonged feeder operation reduces the insulation level, thereby increasing the likelihood of single-phase grounding faults that can generate over-voltages and eventually lead to successive two-point grounding faults. Existing detection methods for single-phase grounding faults fail [...] Read more.

In a non-effectively grounded neutral point distribution network, prolonged feeder operation reduces the insulation level, thereby increasing the likelihood of single-phase grounding faults that can generate over-voltages and eventually lead to successive two-point grounding faults. Existing detection methods for single-phase grounding faults fail to identify the second grounding fault in such scenarios. This paper derives the steady-state analytical expressions for the electrical quantities during faults and examines the characteristic differences at various stages of successive grounding faults under different fault phase sequences. Based on these distinctive features, the paper proposes a detection method for successive cross-line grounding faults with varying fault phases. The effectiveness of the proposed algorithm is verified through both simulation and field data. Full article

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

23 pages, 1233 KiB

Open AccessArticle

Comparative Sensitivity Analyses of Energy Consumption in Response to Average Speed Between Electric Vehicles and Conventional Vehicles: Case Study in Beijing, China

by Xue Lei, Hongyu Lu, Pengfei Fan, Rui Liu, Songsong Li, Yizheng Wu and Guohua Song

Energies 2025, 18(9), 2268; https://doi.org/10.3390/en18092268 - 29 Apr 2025

Abstract

Understanding the sensitivity of vehicle energy consumption to average speed variations is critical for accurately assessing the environmental impacts of urban transportation systems. While the energy consumption patterns of conventional vehicles (CVs) have been extensively studied, the response characteristics of electric vehicles (EVs) [...] Read more.

Understanding the sensitivity of vehicle energy consumption to average speed variations is critical for accurately assessing the environmental impacts of urban transportation systems. While the energy consumption patterns of conventional vehicles (CVs) have been extensively studied, the response characteristics of electric vehicles (EVs) and their fundamental differences from CVs remain insufficiently explored. This knowledge gap may lead to misguided policy interventions—for instance, implementing congestion mitigation strategies that may paradoxically increase EV energy demand. To address this research gap, we developed an energy consumption model based on vehicle-specific power (VSP) distribution analysis, calibrated with over 25 million second-by-second driving records from Beijing. The proposed comparative framework systematically evaluates the sensitivity of EV and CV energy consumption across different speed regimes. The results indicated that EV energy use exhibits a distinctive parabolic trend, with high energy use at both low and high speeds, and a notable increase beyond approximately 70 km/h. A case study indicates that, during the pandemic lockdown, which led to a significant increase in average speed, CV energy use generally decreased, whereas EV energy consumption increased. This discrepancy is primarily attributed to differences in energy consumption rates rather than variations in driving behavior, as reflected in VSP distributions. Full article

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

20 pages, 958 KiB

Open AccessReview

Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects

by Uchenna Emmanuel Edeh, Tek Tjing Lie and Md Apel Mahmud

Energies 2025, 18(9), 2267; https://doi.org/10.3390/en18092267 - 29 Apr 2025

Abstract

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation [...] Read more.

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation fluctuations, and network dynamics. The traditional deterministic TRM methods often fail to capture the stochastic nature of modern grids, leading to inaccurate estimations. This paper reviews the TRM assessment methodologies, emphasizing probabilistic approaches that enhance accuracy in high-RES environments. It explores adaptive statistical techniques, such as rolling window analysis, for dynamic TRM computation. Key challenges, emerging trends, and potential solutions are discussed to support the development of robust ATC modeling frameworks for secure and efficient renewable energy integration. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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18 pages, 7905 KiB

Open AccessCommunication

Analytical Diagnostic and Control System of Energy and Mechanical Efficiency of Electric Drives

by Nikolay Korolev

Energies 2025, 18(9), 2266; https://doi.org/10.3390/en18092266 - 29 Apr 2025

Abstract

The electric drive is strategically placed in the power industry. It is exposed to wear and tear, defects, and constructional damage, as is any technical device. An information–analytical system is presented in this work. It performs the tasks of monitoring, diagnostics, general assessment [...] Read more.

The electric drive is strategically placed in the power industry. It is exposed to wear and tear, defects, and constructional damage, as is any technical device. An information–analytical system is presented in this work. It performs the tasks of monitoring, diagnostics, general assessment of technical condition, and continuous assessment of energy and mechanical efficiency of the electric drive based on the analysis of immediate values of currents and voltages. The system modules are finished products with practical application, which are supported by experimental validation. This article contains a detailed description of the methods implemented in the system development, as well as a description of the laboratory bench and equipment used in our experiments. The information–analytical system is shown and proved on the basis of a fault reconstruction example with electric drive misalignment. According to the obtained results, recommendations for preventive control and proposals for development in this direction are formulated. Full article

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18 pages, 3912 KiB

Open AccessArticle

Numerical Investigation of Sheet-Gyroid Structure Modifications for Mixing Application in Renewable Energy Technologies

by Martin Beer and Radim Rybár

Energies 2025, 18(9), 2265; https://doi.org/10.3390/en18092265 - 29 Apr 2025

Abstract

The presented study focuses on evaluating the mixing properties of structures derived from the so-called sheet-gyroid geometry and their modifications as advanced mixing elements in renewable energy technologies. Using numerical simulations based on computational fluid dynamics (CFD), the hydrodynamic characteristics of the basic [...] Read more.

The presented study focuses on evaluating the mixing properties of structures derived from the so-called sheet-gyroid geometry and their modifications as advanced mixing elements in renewable energy technologies. Using numerical simulations based on computational fluid dynamics (CFD), the hydrodynamic characteristics of the basic sheet-gyroid structure and five geometric modifications were analyzed under laminar flow conditions simulating the mixing of water and ethylene glycol. The evaluation was conducted using the parameters mixing index and performance index, which express the efficiency of fluid homogenization and its associated energy demands. The results show that all tested geometries significantly improve the degree of mixing compared to an empty channel. The highest concentration homogeneity and best energy efficiency were achieved by the twisted sheet-gyroid structure. This geometric modification exhibits the highest value of the performance index, confirming its ability to achieve excellent mixing with minimal pressure losses. The results of the study demonstrated that, despite similar hydraulic losses among some of the structures, their fluid mixing performance differs, which highlights the importance of targeted geometric design of sheet-gyroid structures. These findings are essential for the design of efficient mixers in technological applications where intensive mixing combined with minimal energy consumption is a critical factor. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics: Technologies and Applications for Renewable Energy Systems, 2nd Edition)

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17 pages, 1815 KiB

Open AccessArticle

Dynamic Optical Wireless Power Transmission Infrastructure Configuration for EVs

by Mahiro Kawakami and Tomoyuki Miyamoto

Energies 2025, 18(9), 2264; https://doi.org/10.3390/en18092264 - 29 Apr 2025

Abstract

Electric vehicles (EVs) are becoming more widespread as we move toward a carbon-free society. However, challenges remain, such as the need for large batteries, the inconvenience of charging, and limited driving range. Dynamic optical wireless power transmission (D-OWPT) is considered a promising solution [...] Read more.

Electric vehicles (EVs) are becoming more widespread as we move toward a carbon-free society. However, challenges remain, such as the need for large batteries, the inconvenience of charging, and limited driving range. Dynamic optical wireless power transmission (D-OWPT) is considered a promising solution to these problems. This paper investigates the infrastructure configuration and feasibility of D-OWPT. To this end, a model of EV power consumption was created, and a simulator for D-OWPT was developed. Using this simulator, it was shown that placing light sources in low-speed sections is an effective method, and that continuous driving can be achieved by providing a light source with an output of about 20 kW, assuming a 50% of light irradiation section ratio. Since many of the conditions used in the analysis are achievable with existing technologies, these results demonstrate the high feasibility of D-OWPT. While the analysis presented in this study is based on simulation, the modeling parameters, including EV power consumption and OWPT system characteristics, are derived from actual vehicle specifications and experimental data reported in OWPT research. Although this study does not include physical implementation, the results present numerically validated conditions that are directly applicable to practical system design. This work is intended to serve as a theoretical foundation for the future development and prototyping of D-OWPT infrastructure. Full article

(This article belongs to the Special Issue Future Smart Energy for Electric Vehicle Charging)

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19 pages, 3253 KiB

Open AccessArticle

Research on the Modelling and Analysis of the Penetration of Renewable Sources and Storage into Electrical Networks

by Eva Simonič, Sebastijan Seme and Klemen Sredenšek

Energies 2025, 18(9), 2263; https://doi.org/10.3390/en18092263 - 29 Apr 2025

Abstract

To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. This paper investigates the impact of integrating residential rooftop photovoltaic [...] Read more.

To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. This paper investigates the impact of integrating residential rooftop photovoltaic (PV) systems and battery energy storage systems (BESSs) into low-voltage (LV) distribution networks. A stochastic approach, using the Monte Carlo method, is applied to randomly place PV systems across the network, generating multiple scenarios for power flow simulations in MATLAB Simulink R2024b. The method incorporates real-world consumer load data and grid topology, representing a novel approach in simulating distribution network behaviour accurately. The novelty of this paper lies in its ability to combine stochastic PV placement with real-world load data, providing a more realistic representation of network conditions. The simulation results revealed that widespread PV deployment can lead to overvoltage issues, but the integration of BESSs alongside PV systems mitigates these problems significantly. The findings of this paper offer valuable insights for Distribution Network Operators, aiding in the development of strategies for optimal PV and BESS integration to enhance grid performance. Full article

(This article belongs to the Special Issue Renewable Sources and Storage: Grid Impact, Modeling, and Integration Strategies)

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20 pages, 923 KiB

Open AccessArticle

Cybersecurity Challenges in PV-Hydrogen Transport Networks: Leveraging Recursive Neural Networks for Resilient Operation

by Lei Yang, Saddam Aziz and Zhenyang Yu

Energies 2025, 18(9), 2262; https://doi.org/10.3390/en18092262 - 29 Apr 2025

Abstract

In the rapidly evolving landscape of transportation technologies, hydrogen vehicle networks integrated with photovoltaic (PV) systems represent a significant advancement toward sustainable mobility. However, the integration of such technologies also introduces complex cybersecurity challenges that must be meticulously managed to ensure operational integrity [...] Read more.

In the rapidly evolving landscape of transportation technologies, hydrogen vehicle networks integrated with photovoltaic (PV) systems represent a significant advancement toward sustainable mobility. However, the integration of such technologies also introduces complex cybersecurity challenges that must be meticulously managed to ensure operational integrity and system resilience. This paper explores the intricate dynamics of cybersecurity in PV-powered hydrogen vehicle networks, focusing on the real-time challenges posed by cyber threats such as False Data Injection Attacks (FDIAs) and their impact on network operations. Our research utilizes a novel hierarchical robust optimization model enhanced by Recursive Neural Networks (RNNs) to improve detection rates and response times to cyber incidents across various severity levels. The initial findings reveal that as the severity of incidents escalates from level 1 to 10, the response time significantly increases from an average of 7 min for low-severity incidents to over 20 min for high-severity scenarios, demonstrating the escalating complexity and resource demands of more severe incidents. Additionally, the study introduces an in-depth examination of the detection dynamics, illustrating that while detection rates generally decrease as incident frequency increases—due to system overload—the employment of advanced RNNs effectively mitigates this trend, sustaining high detection rates of up to 95% even under high-frequency scenarios. Furthermore, we analyze the cybersecurity risks specifically associated with the intermittency of PV-based hydrogen production, demonstrating how fluctuations in solar energy availability can create vulnerabilities that cyberattackers may exploit. We also explore the relationship between incident frequency, detection sensitivity, and the resulting false positive rates, revealing that the optimal adjustment of detection thresholds can reduce false positives by as much as 30%, even under peak load conditions. This paper not only provides a detailed empirical analysis of the cybersecurity landscape in PV-integrated hydrogen vehicle networks but also offers strategic insights into the deployment of AI-enhanced cybersecurity frameworks. The findings underscore the critical need for scalable, responsive cybersecurity solutions that can adapt to the dynamic threat environment of modern transport infrastructures, ensuring the sustainability and safety of solar-powered hydrogen mobility solutions. 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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18 pages, 4527 KiB

Open AccessArticle

An Improved PSO-Based DC Discharge Heating Strategy for Lithium-Ion Batteries at Low Temperatures

by Shaojian Han, Chengwei Li, Jifeng Ding, Xinhua Gao, Xiaojie Li and Zhiwen Zhang

Energies 2025, 18(9), 2261; https://doi.org/10.3390/en18092261 - 29 Apr 2025

Abstract

In low-temperature environments, both the electrochemical and thermodynamic performances of lithium-ion batteries are significantly affected, leading to a substantial decline in overall performance. This deterioration is primarily manifested in the inability of the battery to release its actual capacity effectively, a marked reduction [...] Read more.

In low-temperature environments, both the electrochemical and thermodynamic performances of lithium-ion batteries are significantly affected, leading to a substantial decline in overall performance. This deterioration is primarily manifested in the inability of the battery to release its actual capacity effectively, a marked reduction in charge–discharge efficiency, and accelerated capacity degradation, directly undermining its power output capability under low-temperature conditions. This performance degradation severely restricts the application of lithium-ion batteries in scenarios requiring high power and extended range, such as EVs. This paper proposes an intelligent low-temperature DC discharge heating optimization strategy based on the PSO algorithm. The strategy aims to simultaneously optimize heating time and minimize capacity loss by employing the PSO algorithm to dynamically optimize discharge currents under varying ambient temperatures. This approach achieves the simultaneous optimization of battery heating efficiency and capacity loss. It effectively overcomes the limitation of traditional constant-current discharge methods, which struggle to dynamically adjust current intensity based on real operating conditions. By balancing heating efficiency and capacity degradation, the model significantly enhances energy utilization. Taking the weighting factor λ = 0.5 as an example, the battery is heated from −30 °C to 0 °C at a 90% initial SOC. Compared to preheating methods that directly use the minimum optimized dynamic current threshold, it reduces heating time by 48.71 s and increases the heating rate by more than twofold. In contrast to preheating methods using the maximum optimized dynamic current threshold, it decreases capacity degradation by 0.10 Ah after 1000 heating cycles. This strategy addresses the limitations of traditional heating methods, providing a novel solution for the efficient application of lithium-ion batteries in low-temperature environments. Full article

(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)

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25 pages, 7617 KiB

Open AccessArticle

Optimization of Hydronic Heating System in a Commercial Building: Application of Predictive Control with Limited Data

by Rana Loubani, Didier Defer, Ola Alhaj-Hasan and Julien Chamoin

Energies 2025, 18(9), 2260; https://doi.org/10.3390/en18092260 - 29 Apr 2025

Abstract

Optimizing building equipment control is crucial for enhancing energy efficiency. This article presents a predictive control applied to a commercial building heated by a hydronic system, comparing its performance to a traditional heating curve-based strategy. The approach is developed and validated using TRNSYS18 [...] Read more.

Optimizing building equipment control is crucial for enhancing energy efficiency. This article presents a predictive control applied to a commercial building heated by a hydronic system, comparing its performance to a traditional heating curve-based strategy. The approach is developed and validated using TRNSYS18 modeling, which allows for comparison of the control methods under the same weather boundary conditions. The proposed strategy balances energy consumption and indoor thermal comfort. It aims to optimize the control of the secondary heating circuit’s water setpoint temperature, so it is not the boiler supply water temperature that is optimized, but rather the temperature of the water that feeds the radiators. Limited data poses challenges for capturing system dynamics, addressed through a black-box approach combining two machine learning models: an artificial neural network predicts indoor temperature, while a support vector machine estimates gas consumption. Incorporating weather forecasts, occupancy scenarios, and comfort requirements, a genetic algorithm identifies optimal hourly setpoints. This work demonstrates the possibility of creating sufficiently accurate models for this type of application using limited data. It offers a simplified and efficient optimization approach to heat control in such buildings. The case study results show energy savings up to 30% compared to a traditional control method. Full article

(This article belongs to the Special Issue Optimizing Energy Efficiency and Thermal Comfort in Building)

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22 pages, 7900 KiB

Open AccessArticle

Research on a Quantitative Evaluation Method for Reservoir Damage Induced by Waterflooding Rate Sensitivity in Tight Oil Reservoirs

by Zhaoyu Duan, Yongchao Xue, Ziyao Zhang, Lan Yang and Yongji Cai

Energies 2025, 18(9), 2259; https://doi.org/10.3390/en18092259 - 29 Apr 2025

Abstract

This study was conducted to quantitatively evaluate the reservoir damage caused by waterflood-induced velocity sensitivity in the tight oil reservoirs of Block L in the Ordos Basin. This research investigated changes in reservoir pore–throat structure before and after waterflooding through laboratory experiments. A [...] Read more.

This study was conducted to quantitatively evaluate the reservoir damage caused by waterflood-induced velocity sensitivity in the tight oil reservoirs of Block L in the Ordos Basin. This research investigated changes in reservoir pore–throat structure before and after waterflooding through laboratory experiments. A velocity sensitivity characterization model was established as

R_{c} (Q) = \frac{Qexp (- β {[v_{c 0} (1 + λ Q^{η})]}^{δ})}{2 π ϕ h v_{c 0} (1 + λ Q^{η})}

, and the injection volume as Q, and its reliability was validated using both experimental and field data. The results indicate that excessive water injection can lead to permeability damage in the reservoir. Based on this model, the optimal injection rate for Block L was determined to be 16.8 m³/day. Field application of this optimized rate reduced velocity sensitivity-induced particle damage by 21% and improved oil recovery by 1.4%. Full article

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26 pages, 9842 KiB

Open AccessArticle

Compressed Air Energy Storage in Salt Caverns Optimization in Southern Ontario, Canada

by Jingyu Huang and Shunde Yin

Energies 2025, 18(9), 2258; https://doi.org/10.3390/en18092258 - 29 Apr 2025

Abstract

Energy storage systems are gaining increasing attention as a solution to the inherent intermittency of renewable energy sources such as solar and wind power. Among large-scale energy storage technologies, compressed air energy storage (CAES) stands out for its natural sealing properties and cost-efficiency. [...] Read more.

Energy storage systems are gaining increasing attention as a solution to the inherent intermittency of renewable energy sources such as solar and wind power. Among large-scale energy storage technologies, compressed air energy storage (CAES) stands out for its natural sealing properties and cost-efficiency. Having abundant salt resources, the thick and regionally extensive salt deposits in Unit B of Southern Ontario, Canada, demonstrate significant potential for CAES development. In this study, optimization for essential CAES salt cavern parameters are conducted using geological data from Unit B salt deposit. Cylinder-shaped and ellipsoid-shaped caverns with varying diameters are first simulated to determine the optimal geometry. To optimize the best operating pressure range, stationary simulations are first conducted, followed by tightness evaluation and long-term stability simulation that assess plastic and creep deformation. The results indicate that a cylinder-shaped cavern with a diameter 1.5 times its height provides the best balance between storage capacity and structural stability. While ellipsoid shape reduces stress concentration significantly, it also leads to increased deformation in the shale interlayers, making them more susceptible to failure. Additionally, the findings suggest that the optimal operating pressure lies between 0.4 and 0.7 times the vertical stress, maintaining large capacity and minor gas leakage, and developing the least creep deformation. Full article

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27 pages, 7725 KiB

Open AccessArticle

Towards a Generalized Tidal Turbine Wake Analytical Model for Turbine Placement in Array Accounting for Added Turbulence

by Kabir Bashir Shariff and Sylvain S. Guillou

Energies 2025, 18(9), 2257; https://doi.org/10.3390/en18092257 - 29 Apr 2025

Abstract

This study seeks to establish a comprehensive model for estimating both the velocity deficit and turbulence intensity within a tidal turbine farm across various layout configurations. The model incorporates a spectrum of ambient turbulence intensity ranging from 5% to 20%, a rotor diameter-to-depth [...] Read more.

This study seeks to establish a comprehensive model for estimating both the velocity deficit and turbulence intensity within a tidal turbine farm across various layout configurations. The model incorporates a spectrum of ambient turbulence intensity ranging from 5% to 20%, a rotor diameter-to-depth ratio between 20% and 60%, and a rotor thrust coefficient that varies from 0.64 to 0.98. The influence of added turbulence is factored into the evaluation of the velocity deficit within the farm. Consistent with findings from prior research, the results indicate that in a tidal farm consisting of 16 turbines, a staggered array configuration yields 21% more power compared to a rectilinear array. This staggered setup benefits from enhanced flow acceleration and greater spacing between turbines, which facilitates improved wake recovery. The findings suggest that the farm’s dimensions can be optimized by reducing lateral spacing in the rectilinear array and longitudinal spacing in the staggered array without compromising efficiency. Such reductions in farm size can lead to decreased cable expenses and create opportunities for future expansion. For the tidal turbines in shallow water regions, the ratio of rotor diameter to depth is shown to affect the power generated by the turbines. The power produced in the farm decreases with an increase in the rotor diameter-to-depth ratio due to the limited wake expansion along the vertical plane. The efficiency of a tidal farm can be increased by high ambient turbulent intensity, sufficient turbine spacing, and low rotor diameter-to-depth ratio. These factors improve the wake recovery to allow more energy to be extracted by a downstream turbine. This low-computational model can be useful in studying the wake interaction of tidal turbine parks in different configurations. Full article

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

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18 pages, 1084 KiB

Open AccessArticle

Quantile Analysis of Economic Growth, Foreign Direct Investment, and Renewable Energy on CO₂ Emissions in Brazil: Insights for Sustainable Development

by Fatema Fauze Moh Ben Abd Alah and Opeoluwa Seun Ojekemi

Energies 2025, 18(9), 2256; https://doi.org/10.3390/en18092256 - 29 Apr 2025

Abstract

Brazil, as an emerging and newly industrialized nation, presents a complex dynamic between economic advancement and environmental sustainability. This study investigates the influence of coal consumption (COAL), gross domestic product (GDP), renewable energy (REN), and foreign direct investment (FDI) on CO₂ emissions [...] Read more.

Brazil, as an emerging and newly industrialized nation, presents a complex dynamic between economic advancement and environmental sustainability. This study investigates the influence of coal consumption (COAL), gross domestic product (GDP), renewable energy (REN), and foreign direct investment (FDI) on CO₂ emissions in Brazil using quarterly data from 1990Q1 to 2020Q4. Employing the Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) method and the Quantile-on-Quantile Granger Causality (QQGC) test, we uncover significant nonlinear and distributional heterogeneities in these relationships. Results show that COAL, GDP, and FDI consistently exert a positive impact on CO₂ emissions across most quantiles, whereas REN significantly reduces emissions, particularly at the upper emission quantiles. Causality analysis confirms that all four variables are significant predictors of CO₂ emissions. The study contributes methodologically by applying QQKRLS and QQGC to reveal nuanced interactions across the emissions distribution—an advancement over traditional linear approaches. Empirically, it provides Brazil-specific evidence of the dual role of FDI and economic growth in both driving emissions and offering potential for sustainable transition. Based on these findings, we recommend policies that prioritize sector-specific FDI screening to promote green technologies, accelerate investment in renewable energy infrastructure, and impose adaptive carbon pricing mechanisms that reflect the heterogeneous impact of coal and economic growth on emissions. These insights support Brazil’s climate targets and guide a balanced path toward inclusive and sustainable development. Full article

(This article belongs to the Special Issue Energy Transition and Environmental Sustainability: 3rd Edition)

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