Energies

23 pages, 7410 KiB

Open AccessArticle

Techno-Economic Analysis of Geospatial Green Hydrogen Potential Using Solar Photovoltaic in Niger: Application of PEM and Alkaline Water Electrolyzers

by Bachirou Djibo Boubé, Ramchandra Bhandari, Moussa Mounkaila Saley, Abdou Latif Bonkaney and Rabani Adamou

Energies 2025, 18(7), 1872; https://doi.org/10.3390/en18071872 - 7 Apr 2025

Viewed by 219

Abstract

This study evaluates the techno-economic feasibility of solar-based green hydrogen potential for off-grid and utility-scale systems in Niger. The geospatial approach is first employed to identify the area available for green hydrogen production based on environmental and socio-technical constraints. Second, we evaluate the [...] Read more.

This study evaluates the techno-economic feasibility of solar-based green hydrogen potential for off-grid and utility-scale systems in Niger. The geospatial approach is first employed to identify the area available for green hydrogen production based on environmental and socio-technical constraints. Second, we evaluate the potential of green hydrogen production using a geographic information system (GIS) tool, followed by an economic analysis of the levelized cost of hydrogen (LCOH) for alkaline and proton exchange membrane (PEM) water electrolyzers using fresh and desalinated water. The results show that the electricity generation potential is 311,617 TWh/year and 353,166 TWh/year for off-grid and utility-scale systems. The hydrogen potential using PEM (alkaline) water electrolyzers is calculated to be 5932 Mt/year and 6723 Mt/year (5694 Mt/year and 6454 Mt/year) for off-grid and utility-scale systems, respectively. The LCOH production potential decreases for PEM and alkaline water electrolyzers by 2030, ranging between 4.72–5.99 EUR/kgH₂ and 5.05–6.37 EUR/kgH₂ for off-grid and 4.09–5.21 EUR/kgH₂ and 4.22–5.4 EUR/kgH₂ for utility-scale systems. Full article

(This article belongs to the Topic Advances in Green Energy and Energy Derivatives)

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16 pages, 2399 KiB

Open AccessArticle

Evaluating the Balancing Properties of Wind and Solar Photovoltaic System Production

by Riho Meister, Wahiba Yaïci, Reza Moezzi, Mohammad Gheibi, Külli Hovi and Andres Annuk

Energies 2025, 18(7), 1871; https://doi.org/10.3390/en18071871 - 7 Apr 2025

Viewed by 255

Abstract

This research evaluates how wind and solar PV systems balance together. Increasing the share of stochastic renewable energy production in electricity and hot turning reserve deficit are welcome compensation issues. This research used weather station data from an open seashore from the last [...] Read more.

This research evaluates how wind and solar PV systems balance together. Increasing the share of stochastic renewable energy production in electricity and hot turning reserve deficit are welcome compensation issues. This research used weather station data from an open seashore from the last 10 years, 2014–2023, on the Estonian island Saaremaa’s west coast to evaluate yearly fluctuations. We used the indicator demand cover factor to estimate the coincidence of wind generation and solar PV system electricity. For clarity, the initial data were prepared by assuming the equality of production and consumption annual data by scaling the obtained data. This study demonstrates that the best compensating possibilities are the share of wind generation and solar PV electricity mix, respectively, equal to 0.7/0.3 and 0.8/0.2, reaching a demand cover factor of 0.62. This study evaluated the demand cover factor’s dependence on increased production compared to consumption. This study used different batteries to research the influence of these demand cover factors. Furthermore, this research makes a significant contribution by showcasing how to turn weather station data into real wind generator and PV panel production data. Full article

(This article belongs to the Special Issue Integration of Renewable Energy Systems in Power Grid)

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15 pages, 5838 KiB

Open AccessArticle

Study on the Wake Characterization of a Horizontal-Axis Tidal Stream Turbine Utilizing a PIV System in a Large Circulating Water Tunnel

by Sejin Jung, Heebum Lee, Dasom Jeong, Jihoon Kim and Jin Hwan Ko

Energies 2025, 18(7), 1870; https://doi.org/10.3390/en18071870 - 7 Apr 2025

Viewed by 221

Abstract

In this study, a particle image velocimetry (PIV) system was used in a large circulating water tank to investigate the wake of a horizontal-axis tidal turbine model, focusing on minor blockage effects and scale influence. A wake map of the turbine was constructed [...] Read more.

In this study, a particle image velocimetry (PIV) system was used in a large circulating water tank to investigate the wake of a horizontal-axis tidal turbine model, focusing on minor blockage effects and scale influence. A wake map of the turbine was constructed based on PIV measurements, using velocity deficit, turbulence intensity (TI), and turbulence kinetic energy (TKE) as key indicators. The results showed that TKE developed later than TI, forming a plateau-like shape. This plateau was considered the decay region, with the transition and far-wake regions located before and after it, respectively. Additionally, the power law exponent of TI decreased from −0.731 in the decay region to −0.765 in the far wake, indicating a steeper decay further downstream. Overall, the wake map of the tidal stream turbine model exhibited similarities to that of a previously reported wind turbine model. Full article

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

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20 pages, 5100 KiB

Open AccessArticle

Leveraging Seawater Thermal Energy Storage and Heat Pumps for Coupling Electricity and Urban Heating: A Techno-Economic Analysis

by Timur Abbiasov, Aldo Bischi, Manfredi Gangi, Andrea Baccioli, Paolo Santi and Carlo Ratti

Energies 2025, 18(7), 1869; https://doi.org/10.3390/en18071869 - 7 Apr 2025

Viewed by 200

Abstract

This paper presents an economic assessment of seawater thermal energy storage (TES) integrated with industrial heat pumps to couple renewable electricity generation with urban district heating networks. Using Amsterdam as a case study, we develop a techno-economic model leveraging real-world data on electricity [...] Read more.

This paper presents an economic assessment of seawater thermal energy storage (TES) integrated with industrial heat pumps to couple renewable electricity generation with urban district heating networks. Using Amsterdam as a case study, we develop a techno-economic model leveraging real-world data on electricity prices, heat demand, and system costs. Our findings show that large-scale TES using seawater as a storage medium significantly enhances district heating economics through energy arbitrage and operational flexibility. The optimal configuration yields a net present value (NPV) of EUR 466 million over 30 years and a payback period under 6 years. Thermal storage increases NPV by 17% compared to systems without storage, while within-day load shifting further boosts economic value by 23%. Accurate demand and price forecasting is critical, as forecasting errors can reduce NPV by 13.7%. The proposed system is scalable and well suited for coastal cities, offering a sustainable, space-efficient solution for urban decarbonization and addressing renewable energy overproduction. Full article

(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources)

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14 pages, 20066 KiB

Open AccessArticle

Enhanced Harmonic Reduction and Voltage Utilization Ratio Improvement in ANPC Inverters Using an Advanced Hybrid SVPWM Technique

by Gipyo Kim, Hyunjae Lee and Jingeun Shon

Energies 2025, 18(7), 1868; https://doi.org/10.3390/en18071868 - 7 Apr 2025

Viewed by 207

Abstract

This paper proposes an Advanced Hybrid SVPWM (Space Vector Pulse Width Modulation) technique that integrates the benefits of RPS-PWM (Reference Point Saturation-Based PWM) and SVPWM to enhance the performance of three-level ANPC (Active Neutral Point Clamped) inverters. While RPS-PWM effectively reduces switching harmonics, [...] Read more.

This paper proposes an Advanced Hybrid SVPWM (Space Vector Pulse Width Modulation) technique that integrates the benefits of RPS-PWM (Reference Point Saturation-Based PWM) and SVPWM to enhance the performance of three-level ANPC (Active Neutral Point Clamped) inverters. While RPS-PWM effectively reduces switching harmonics, it suffers from lower voltage utilization. In contrast, SVPWM achieves higher voltage utilization but struggles with harmonic suppression. The proposed Advanced Hybrid SVPWM technique addresses these limitations by maintaining the voltage utilization level of RPS-PWM while significantly reducing harmonic distortion and increasing the output

V_{r m s}

. To validate the effectiveness of the proposed method, comprehensive PSIM simulations and DSP-based hardware experiments were conducted. Experimental results confirm that the Advanced Hybrid SVPWM achieves superior harmonic suppression compared to conventional RPS-PWM and SVPWM, while also delivering improved output voltage characteristics. These findings highlight the potential of the proposed technique for enhancing the performance of power electronic systems requiring high efficiency and low harmonic distortion. Full article

(This article belongs to the Section F3: Power Electronics)

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29 pages, 21754 KiB

Open AccessArticle

Multi-Objective Optimization-Driven Research on Rural Residential Building Design in Inner Mongolia Region

by Dezhi Zou, Cheng Sun and Denghui Gao

Energies 2025, 18(7), 1867; https://doi.org/10.3390/en18071867 - 7 Apr 2025

Viewed by 256

Abstract

According to the China Building Energy Consumption and Carbon Emissions Research Report (2023), the construction industry accounts for 36.3% of total societal energy consumption, with residential buildings contributing significantly due to their extensive coverage and high operational frequency. Addressing energy efficiency and carbon [...] Read more.

According to the China Building Energy Consumption and Carbon Emissions Research Report (2023), the construction industry accounts for 36.3% of total societal energy consumption, with residential buildings contributing significantly due to their extensive coverage and high operational frequency. Addressing energy efficiency and carbon reduction in this sector is critical for achieving national sustainability goals. This study proposes an optimization methodology for rural dwellings in Inner Mongolia, focusing on reducing energy demand while enhancing indoor thermal comfort and daylight performance. A parametric model was developed using Grasshopper, with energy consumption, thermal comfort (PPD), and Useful Daylight Illuminance (UDI) simulated through Ladybug and Honeybee tools. Key parameters analyzed include building morphology, envelope structures, and indoor thermal environments, followed by systematic optimization of building components. To refine multi-objective inputs, a specialized wall database was established, enabling categorization and dynamic visualization of material properties and construction methods. Comparative analysis demonstrated a 22.56% reduction in energy consumption, 19.26% decrease in occupant thermal dissatisfaction (PPD), and 25.44% improvement in UDI values post-optimization. The proposed framework provides a scientifically validated approach for improving energy efficiency and environmental adaptability in cold-climate rural architecture. Full article

(This article belongs to the Section G: Energy and Buildings)

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19 pages, 3176 KiB

Open AccessArticle

Real-Time Estimation of the State of Charge of Lithium Batteries Under a Wide Temperature Range

by Da Li, Lu Liu, Chuanxu Yue, Xiaojin Gao and Yunhai Zhu

Energies 2025, 18(7), 1866; https://doi.org/10.3390/en18071866 - 7 Apr 2025

Viewed by 218

Abstract

The state of charge (SOC) of lithium-ion batteries is essential for their proper functioning and serves as the basis for estimating other parameters within the battery management system. To enhance the accuracy of SOC estimation in lithium-ion batteries, we propose a [...] Read more.

The state of charge (SOC) of lithium-ion batteries is essential for their proper functioning and serves as the basis for estimating other parameters within the battery management system. To enhance the accuracy of SOC estimation in lithium-ion batteries, we propose a joint estimation method that integrates lithium-ion battery parameter identification and SOC assessment using cat swarm optimization dual Kalman filtering (CSO–DKF), which accounts for variable-temperature conditions. We adopt a second-order equivalent circuit model, utilizing the Kalman filtering (KF) algorithm as a parameter filter for dynamic parameter identification, while the extended Kalman filtering (EKF) algorithm acts as a state filter for real-time SOC estimation. These two filters operate alternately throughout the iterative process. Additionally, the cat swarm optimization (CSO) algorithm optimizes the noise covariance matrices of both filters, thereby enhancing the precision of parameter identification and SOC estimation. To support this algorithm, we establish an environmental temperature battery database and incorporate temperature variables to achieve accurate SOC estimation under variable-temperature conditions. The results indicate that creating a database that accommodates temperature variations and optimizing dual Kalman filtering through the cat swarm optimization algorithm significantly improves SOC estimation accuracy. Full article

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

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33 pages, 1340 KiB

Open AccessArticle

A Model Predictive Control to Improve Grid Resilience

by Joseph Young, David G. Wilson, Wayne Weaver and Rush D. Robinett III

Energies 2025, 18(7), 1865; https://doi.org/10.3390/en18071865 - 7 Apr 2025

Viewed by 179

Abstract

The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. This topic is of significant interest to utility power systems where distributed intermittent energy sources will increase significantly and be relied on for electric [...] Read more.

The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. This topic is of significant interest to utility power systems where distributed intermittent energy sources will increase significantly and be relied on for electric grid ancillary services. Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. In contrast, this article develops a comprehensive treatment of the construction of an MPC tailored to electric grids and then applies it integration of intermittent energy resources. To accomplish this, the following article includes a description of a reduced order model (ROM) of an electric power grid based on a circuit model, an optimization formulation that describes the MPC, a collocation method for solving linear time-dependent differential algebraic equations (DAEs) that result from the ROM, and an overall strategy for iteratively refining the behavior of the MPC. Next, the algorithm is validated using two separate numerical experiments. First, the algorithm is compared to an existing MPC code and the results are verified by a numerically precise simulation. It is shown that this algorithm produces a control comparable to existing algorithms and the behavior of the control carefully respects the bounds specified. Second, the MPC is applied to a small nine bus system that contains a mix of turbine-spinning-machine-based and intermittent generation in order to demonstrate the algorithm’s utility for resource planning and control of intermittent resources. This study demonstrates how the MPC can be tuned to change the behavior of the control, which can then assist with the integration of intermittent resources into the grid. The emphasis throughout the paper is to provide systematic treatment of the topic and produce a novel nonlinear control compatible design framework applicable to electric grids and the control of variable resources. This differs from the more targeted application-based focus in most presentations. Full article

(This article belongs to the Special Issue Model Predictive Control-Based Approach for Microgrids)

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19 pages, 7329 KiB

Open AccessArticle

An Investigative Study on Mixed Waste Feedstock-Derived Biochar as Active Electrode Material for Supercapacitor Applications

by Sudhakar Pabba, Rajkamal Balu, Arun Krishna Vuppaladadiyam, Ganesh Veluswamy, Manoj Kumar Jena, Ibrahim Gbolahan Hakeem, Namita Roy Choudhury, Abhishek Sharma, Michael Thomas, Aravind Surapaneni, Savankumar Patel and Kalpit Shah

Energies 2025, 18(7), 1864; https://doi.org/10.3390/en18071864 - 7 Apr 2025

Viewed by 289

Abstract

This work demonstrates the feasibility of using biochars derived from a variety of waste feedstocks, such as food organics and garden organics (FOGOs), garden organics (GOs), and biosolids (BSs), provided by Barwon Water (BW) and South East Water (SEW), as active electrode material [...] Read more.

This work demonstrates the feasibility of using biochars derived from a variety of waste feedstocks, such as food organics and garden organics (FOGOs), garden organics (GOs), and biosolids (BSs), provided by Barwon Water (BW) and South East Water (SEW), as active electrode material for supercapacitor application. Four different biochars were produced by the co-pyrolysis of pre-treated mixed waste feedstocks, which were fabricated into a two-electrode symmetric supercapacitor set-up to evaluate their energy storage potential. Two different approaches, (i) carbon nanoparticle coating/modification and (ii) thermochemical activation, were employed to improve the electrochemical properties of the biochars. Potassium hydroxide-activated biochar derived from BW’s triple waste feedstock mixture (comprising 70% GOs, 20% FOGOs, and 10% BSs) demonstrated the highest specific capacitance (30.33 F/g at 0.1 A/g), energy density (4.21 Wh/kg), and power density (2.15 kW/kg) among the tested samples. Such waste-derived biochar offers several benefits for energy storage, including cost-efficiency and sustainable alternatives to traditional electrode materials. The biochar’s electrochemical performance can be further improved by improving the feedstock quality by different pre-treatments. Full article

(This article belongs to the Collection Feature Papers in Energy, Environment and Well-Being)

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23 pages, 5106 KiB

Open AccessArticle

Simulation of Molten Carbonate Fuel Cell with Dry Reforming of Methane (DR-MCFC)

by Kyu-Seok Jung, Young-Bae Jun, Jung-Sik Yoon, Sung-Pil Yoon and Chang-Whan Lee

Energies 2025, 18(7), 1863; https://doi.org/10.3390/en18071863 - 7 Apr 2025

Viewed by 148

Abstract

This study proposes a novel system integrating a molten carbonate fuel cell (MCFC) with a dry reforming process (DR-MCFC) and develops a corresponding simulation model. In a DR-MCFC, the reacting gases from the dry reforming of methane (DRM) process are fed into a [...] Read more.

This study proposes a novel system integrating a molten carbonate fuel cell (MCFC) with a dry reforming process (DR-MCFC) and develops a corresponding simulation model. In a DR-MCFC, the reacting gases from the dry reforming of methane (DRM) process are fed into a molten carbonate fuel cell. CH₄ and CO₂ were used as the reaction gases, while N₂ was employed as the carrier gas and introduced into the DRM. Following the DRM, the reformed gases were humidified and injected into the anode of the MCFC. A simulation model combining the dry reforming process and the MCFC was developed using COMSOL Multiphysics to evaluate the system’s performance and feasibility. The mole fraction of H₂ after the DRM ranged from 0.181 to 0.214 under five different gas conditions. The average current density of the fuel cell varied between 1321.5 and 1444.9 A·m⁻² at a cell voltage of 0.8 V, which was up to 27.07% lower than that of a conventional MCFC operating at 923 K due to the lower hydrogen concentration in the anode. Based on these results, the integration of dry reforming with the MCFC’s operation did not cause any operational issues, demonstrating the feasibility of the proposed DR-MCFC system. Full article

(This article belongs to the Special Issue Recent Advances in New Materials and Technologies for Hydrogen Production)

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23 pages, 1620 KiB

Open AccessReview

Technical Review and Status of Small Modular Reactor Technologies: Prospects of Nuclear Infrastructure Development in the Philippines

by Unico A. Bautista and Rinlee Butch M. Cervera

Energies 2025, 18(7), 1862; https://doi.org/10.3390/en18071862 - 7 Apr 2025

Viewed by 405

Abstract

Small Modular Reactors (SMRs) are gaining significant attention as nuclear power sources due to their advantages, such as compact design, enhanced safety features compared to large nuclear plants, and scalability for varying power output needs. To successfully consider this emerging technology, understanding SMR [...] Read more.

Small Modular Reactors (SMRs) are gaining significant attention as nuclear power sources due to their advantages, such as compact design, enhanced safety features compared to large nuclear plants, and scalability for varying power output needs. To successfully consider this emerging technology, understanding SMR designs and their readiness levels is essential for informed decision making and effective planning. This technical review provides insights into the potential, development, and application of SMR technology. Various SMR designs were investigated to identify those in deployment, commercial operation, or nearing deployment stages. Key technical parameters of advanced-stage SMRs, with some local insights, were analyzed to establish a comprehensive set of criteria for future technical and economic assessments in the context of local applications. Additionally, this study outlines potential phases for SMR project implementation in the Philippines, referencing the IAEA Milestone Approach for nuclear power infrastructure development. Relevant policies, issues, and activities are also discussed, highlighting the status of the country’s nuclear power infrastructure, as well as its legislative and regulatory framework for supporting nuclear energy. While certain SMR technologies show technical readiness, it is important to consider that many are still under development, requiring a careful evaluation of factors such as the 19 Infrastructure Issues to ensure a successful SMR deployment in the Philippines. Full article

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

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16 pages, 6188 KiB

Open AccessArticle

A Semi-Analytical Model for Pressure Transient Analysis of Multiple Fractured Horizontal Wells in Irregular Heterogeneous Reservoirs

by Cheng Chang, Xuefeng Yang, Weiyang Xie, Dan Dai, Yizhao Chen, Xiaojing Ji, Yanzhong Liang and Bailu Teng

Energies 2025, 18(7), 1861; https://doi.org/10.3390/en18071861 - 7 Apr 2025

Viewed by 167

Abstract

The irregular outer boundaries of reservoirs and the associated heterogeneous high-permeability zones formed by complex geological environment pose significant challenges in reservoir characterization and performance prediction. These irregular geometries, which are commonly encountered in field applications but often oversimplified in conventional models, can [...] Read more.

The irregular outer boundaries of reservoirs and the associated heterogeneous high-permeability zones formed by complex geological environment pose significant challenges in reservoir characterization and performance prediction. These irregular geometries, which are commonly encountered in field applications but often oversimplified in conventional models, can substantially influence fluid flow dynamics and transient pressure behavior. To solve this critical issue, this paper presents a semi-analytical model for studying the transient pressure behavior of irregular heterogeneous reservoirs, focusing on the dynamic interactions between hydraulic fractures and the surrounding matrix. The model integrates Green’s function solutions for matrix flow with finite difference methods to simulate fluid flow within complex fracture networks, capturing the heterogeneity of the reservoir and the irregularity of its boundaries. Specifically, the reservoir is divided into locally homogeneous blocks, and the flow within each block is solved using bounded Green’s functions, while the fracture networks are discretized and solved using finite difference methods. This proposed model significantly reduces computational complexity compared to traditional numerical simulations, while maintaining high accuracy. Subsequently, we conducted comprehensive parameter sensitivity analyses. The calculational results show that a multi-fractured horizontal well in an irregular heterogeneous reservoir can observe the following flow regimes: bilinear flow, elliptical flow, and boundary-dominated flow. Longer fractures and higher conductivity enhance fracture flux by increasing the contact area and reducing flow resistance, respectively. However, these positive impacts are constrained by drainage area limitations as production progresses. Full article

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

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27 pages, 1437 KiB

Open AccessReview

Phytoremediation and Environmental Law: Harnessing Biomass and Microbes to Restore Soils and Advance Biofuel Innovation

by Aneta Kowalska and Robert Biczak

Energies 2025, 18(7), 1860; https://doi.org/10.3390/en18071860 - 7 Apr 2025

Viewed by 330

Abstract

Progressing soil degradation worldwide is a complex socio-environmental threat. Implementing environmental policies and actions such as the Sustainable Development Goals, the European Green Deal, and the Renewable Energy Directive III regarding environmental protection aims to protect, conserve, and enhance the EU’s natural capital, [...] Read more.

Progressing soil degradation worldwide is a complex socio-environmental threat. Implementing environmental policies and actions such as the Sustainable Development Goals, the European Green Deal, and the Renewable Energy Directive III regarding environmental protection aims to protect, conserve, and enhance the EU’s natural capital, focusing on soil protection. As assumed in the Green Deal, the European economy has to be turned into a resource-efficient and green economy with zero net emission of greenhouse gases. Since soil quality strongly influences all ecosystem elements, soil remediation is increasingly promoted as a sustainable option to enhance soil quality and, at the same time, help achieve overarching goals set out in European climate law. Biomass in phytoremediation is particularly important in regenerative agriculture, as it emphasizes improving soil quality, increasing biodiversity, and sequestering carbon. Selected plants and microbes can clean degraded agricultural areas, removing heavy metals and pesticides, thus lowering soil toxicity and improving food and feed security. Moreover, the post-phytoremediation biomass can be processed into biofuels or bioproducts, supporting the circular economy. This article summarizes the role of plants and microbial biomass in the struggle to achieve EU environmental goals, enabling the regeneration of degraded ecosystems while supporting sustainable development in agriculture. Full article

(This article belongs to the Special Issue Energy from Waste: Towards Sustainable Development and Clean Future)

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16 pages, 3692 KiB

Open AccessArticle

Research on the Magnetic Integration of Inductors for High-Power DC Transformers—A Case Study on Electric Roadways

by Biyu Li, Hu Wang, Fenglin Cai, Wei Xie and Yang Zeng

Energies 2025, 18(7), 1859; https://doi.org/10.3390/en18071859 - 7 Apr 2025

Viewed by 186

Abstract

With the growth of renewable energy, electrified highways can efficiently utilize green energy such as solar and wind for EVs, promoting sustainable transportation and carbon reduction, and accelerating the transition to a greener future. For high-power DC/DC converters in electrified roadways, a lightweight [...] Read more.

With the growth of renewable energy, electrified highways can efficiently utilize green energy such as solar and wind for EVs, promoting sustainable transportation and carbon reduction, and accelerating the transition to a greener future. For high-power DC/DC converters in electrified roadways, a lightweight and compact design is crucial, but inductors limit progress. Therefore, this study focuses on the magnetic integration of DC/DC chopping inductors. It first selected and optimized the decoupled magnetic integration form, initial electromagnetic parameters, and core sizes based on circuit topology and device specifications, using core loss and thermal rise models. Then, it determined the optimal winding turns ratio according to the air gap and magnetic resistance ratio, obtaining the final design with insulation considered. The design was verified through finite-element simulation, prototype manufacturing, and testing, and an improved optimization with interleaved parallel control was proposed. Results indicate that magnetic integration reduces the inductor’s volume by 7.93% and footprint by 38.62%, facilitating the lightweight and compact design of relevant magnetic components. With interleaved parallel control, the integrated inductor’s volume can be reduced by 19.74%, significantly decreasing the volume and mass of the chopping inductor. Full article

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

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19 pages, 5993 KiB

Open AccessArticle

A Modularity-Enhanced Echo State Network for Nonlinear Wind Energy Predicting

by Sixian Yue, Zhili Zhao, Tianyou Lai and Jin Zhang

Energies 2025, 18(7), 1858; https://doi.org/10.3390/en18071858 - 7 Apr 2025

Viewed by 214

Abstract

With the rapid growth of wind power generation, accurate wind energy prediction has emerged as a critical challenge, particularly due to the highly nonlinear nature of wind speed data. This paper proposes a modularized Echo State Network (MESN) model to improve wind energy [...] Read more.

With the rapid growth of wind power generation, accurate wind energy prediction has emerged as a critical challenge, particularly due to the highly nonlinear nature of wind speed data. This paper proposes a modularized Echo State Network (MESN) model to improve wind energy forecasting. To enhance generalization, the wind speed data is first decomposed into time series components, and Modes-cluster is employed to extract trend patterns and pre-train the ESN output layer. Furthermore, Turbines-cluster groups wind turbines based on their wind speed and energy characteristics, enabling turbines within the same category to share the ESN output matrix for prediction. An output integration module is then introduced to aggregate the predicted results, while the modular design ensures efficient task allocation across different modules. Comparative experiments with other neural network models demonstrate the effectiveness of the proposed approach, showing that the statistical RMSE of parameter error is reduced by an average factor of 2.08 compared to traditional neural network models. Full article

(This article belongs to the Special Issue Recent Advances and Applications of Fluid Flow in Aerodynamics and Energy System)

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21 pages, 303 KiB

Open AccessArticle

Balancing Environmental Regulation and Marketization: A Quantile Analysis of Energy Efficiency in China’s Provinces

by Junguo Shi, Wenyi Yan, Yan Li, Qian Wang and Shanshan Dou

Energies 2025, 18(7), 1857; https://doi.org/10.3390/en18071857 - 7 Apr 2025

Viewed by 215

Abstract

This study investigates the impact of environmental regulations and marketization on energy efficiency in China using panel data from 30 provinces covering the period from 2008 to 2016. The analysis employs fixed effects regression, quantile regression, and heterogeneity analysis methods to provide comprehensive [...] Read more.

This study investigates the impact of environmental regulations and marketization on energy efficiency in China using panel data from 30 provinces covering the period from 2008 to 2016. The analysis employs fixed effects regression, quantile regression, and heterogeneity analysis methods to provide comprehensive insights. The fixed effects regression results reveal that both command-and-control (CAC) regulations and market-based (MBR) regulations exert a negative impact on energy efficiency. Notably, marketization significantly mitigated the adverse effects of CAC regulations. Quantile regression analysis indicates that both negative impacts are more pronounced at lower energy efficiency levels, whereas marketization (MR) significantly mitigates these effects. Heterogeneity analysis further identified regional disparities, with CAC regulations yielding more significant negative impacts in the Western and Central regions and MBR showing stronger effects in the Western region. The results advocate for regionally differentiated policies that account for local economic, infrastructural, and institutional contexts to enhance energy efficiency outcomes rather than relying on one-size-fits-all approaches. Full article

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

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20 pages, 6644 KiB

Open AccessArticle

Safe Path for the Transformation of the Polish Energy System Leading to Its Decarbonization and Reliable Operation

by Andrzej Rusin and Adam Wojaczek

Energies 2025, 18(7), 1856; https://doi.org/10.3390/en18071856 - 7 Apr 2025

Viewed by 226

Abstract

The European Union’s energy policy, which aims to achieve climate neutrality by 2050, requires substantial changes in the structure of the energy sources used for power generation. The paper considers the possibilities of increasing the pace of the Polish energy system transformation by [...] Read more.

The European Union’s energy policy, which aims to achieve climate neutrality by 2050, requires substantial changes in the structure of the energy sources used for power generation. The paper considers the possibilities of increasing the pace of the Polish energy system transformation by replacing coal sources with renewable energy sources using energy storage. It is demonstrated that in the analyzed period until 2040 it will be possible to ensure the required level of the system’s energy supply reliability by supporting the system with energy storage. The assessment of the system reliability was carried out based on the LOLE and LOLP indicators, selecting the system structure in such a way that for the hourly energy demand characteristic adopted in the analyzed year, the LOLE was less than 3 h. The required capacity and power of the storage systems depend on the level of the demand for energy and power. The results of the analyses indicate that for the linear trend in the growth in the demand for energy, nuclear power plants with the total power of 8.8 GW have to be installed in the energy system. However, with a significant rise in the power demand and the decommissioning of coal units, balancing the system using other sources with a dominant share of renewable sources will be insufficient. It will therefore be necessary to use the energy storage with a capacity above 11 GWh and a total power above 2 GW. Full article

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

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17 pages, 6330 KiB

Open AccessArticle

A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM

by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun and Shenghu Li

Energies 2025, 18(7), 1855; https://doi.org/10.3390/en18071855 - 7 Apr 2025

Viewed by 191

Abstract

Short-term load is influenced by multiple external factors and shows strong nonlinearity and volatility, which increases the forecasting difficulty. However, most of existing short-term load forecasting methods rely solely on the original load data or take into account a single external factor, which [...] Read more.

Short-term load is influenced by multiple external factors and shows strong nonlinearity and volatility, which increases the forecasting difficulty. However, most of existing short-term load forecasting methods rely solely on the original load data or take into account a single external factor, which results in significant forecasting errors. To improve the forecasting accuracy, this paper proposes a short-term load forecasting method considering multiple contributing factors based on VAR and CEEMDAN-CNN- BILSTM. Firstly, multiple contributing factors strongly correlated with the short-term load are selected based on the Spearman correlation analysis, the vector autoregressive (VAR) model with multivariate input is derived, and the Levenberg–Marquardt algorithm is introduced to estimate the model parameters. Secondly, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm and permutation entropy (PE) criterion are combined to decompose and reconstruct the original load data into multiple relatively stationary mode components, which are respectively input into the CNN-BILTSM network for forecasting. Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. The actual simulation results utilizing the Australian data validate the forecasting accuracy of the proposed model, achieving reduction in the root mean square error by 31.21% and 18.04% compared to the VAR and CEEMDAN-CNN-BILSTM, respectively. Full article

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

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19 pages, 2475 KiB

Open AccessArticle

Impact of EU Decarbonization Policy on Polish International Road Freight Competitiveness

by Maciej Matczak and Andrzej S. Grzelakowski

Energies 2025, 18(7), 1854; https://doi.org/10.3390/en18071854 - 7 Apr 2025

Viewed by 231

Abstract

Road freight transport is the key driver of the European economy and society; thus, distortion of its operation would have negative influence on growth and well-being. For that reason, implementation of European policies, including transport decarbonization, should be comprehensively evaluated from an environmental, [...] Read more.

Road freight transport is the key driver of the European economy and society; thus, distortion of its operation would have negative influence on growth and well-being. For that reason, implementation of European policies, including transport decarbonization, should be comprehensively evaluated from an environmental, social and economic perspective. In that case, introduction of electric trucks will create a mutual impact on the market and on haulage companies. The main research problem is to assess the future impact of decarbonization on the international road freight transport market structure on the supply side and the competitiveness of companies operating there. Today, a number of small and medium companies, to a great extent from Eastern Europe, render transportation services, creating a competitive structure with high flexibility, accessibility and low prices. Shifting towards electric trucks, with significantly higher upfront costs, will redefine the market structure, eliminating the small carriers and activating horizontal integration. The key objective of this research is to identify the main factors and challenges related to electric truck implementation and define crucial areas of its impact on future market structure. The research shows that the improvement of environmental performance requires low- or zero-emission trucks, where the battery technology is a leading solution. Thus, fleet renewal needs additional financial support from the public side. Different measures are available in European countries, so the level of support is not equal from a competitiveness perspective. Battery truck selling, as well as sustainable strategies, refer mostly to huge transport companies. On the other hand, the case of Polish truckers shows that the economic viability of SMEs is poor; thus, the introduction of BET would be beyond its reach. The research findings could be treated as recommendations for market regulators (EC), where the tempo of implementation, as well as availability of public support programs, should be rethinking. As a result, the costs of the transition will be covered by citizens, as customers, in the prices of products and transport service, or as taxpayers, in public support programs, mainly consumed by large market stakeholders. Full article

(This article belongs to the Special Issue Economic Strategies for Integrating Energy and Sustainability: Challenges and Opportunities)

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23 pages, 4948 KiB

Open AccessArticle

An Analysis of Structural Integrity and Durability in Determining the Optimal Compaction Parameters for Hemp and Pine

by Kamil Roman, Witold Jan Wardal and Gabriela Maksymiuk

Energies 2025, 18(7), 1853; https://doi.org/10.3390/en18071853 - 7 Apr 2025

Viewed by 273

Abstract

Research on seed hemp and pine was carried out to improve sustainability and energy efficiency. The mechanical properties of different species of lignocellulosic biomass are still undocumented in the context of granulation processes, even though lignocellulosic biomass is widely studied for biofuel production. [...] Read more.

Research on seed hemp and pine was carried out to improve sustainability and energy efficiency. The mechanical properties of different species of lignocellulosic biomass are still undocumented in the context of granulation processes, even though lignocellulosic biomass is widely studied for biofuel production. Hemp and pine have not been thoroughly compared in the granulation process. Under compressive forces pertinent to pelletizing, the study investigated the mechanical properties of lignocellulosic materials, such as hemp and Scots pine. Based on their mechanical properties, microscopic analysis and strength tests were conducted to compare hemp pellets and pine briquettes. In recent years, a significant trend has been towards eco-friendly and innovative biofuel production, motivating research on compaction technologies and material strength enhancement. The study compared hemp (Cannabis sativa L.) with Scots pine (Pinus sylvestris) during compaction. Compared with pine briquettes, hemp pellets exhibit superior mechanical durability (durability factor = 0.98) and compressive strength (average 2.5 kN), demonstrating hemp’s potential as a renewable fuel source. The study results contribute to the development of sustainable biofuel production processes. Full article

(This article belongs to the Section A4: Bio-Energy)

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27 pages, 9311 KiB

Open AccessArticle

Learning and Characterizing Chaotic Attractors of a Lean Premixed Combustor

by Sara Navarro-Arredondo and Jim B. W. Kok

Energies 2025, 18(7), 1852; https://doi.org/10.3390/en18071852 - 7 Apr 2025

Viewed by 186

Abstract

This paper is about the characteristics of and a method to recognize the onset of limit cycle thermoacoustic oscillations in a gas turbine-like combustor with a premixed turbulent methane/air flame. Information on the measured time series data of the pressure and the OH* [...] Read more.

This paper is about the characteristics of and a method to recognize the onset of limit cycle thermoacoustic oscillations in a gas turbine-like combustor with a premixed turbulent methane/air flame. Information on the measured time series data of the pressure and the OH* chemiluminescence is acquired and postprocessed. This is performed for a combustor with variation in two parameters: fuel/air equivalence ratio and combustor length. It is of prime importance to acknowledge the nonlinear dynamic nature of these instabilities. A method is studied to interpret thermoacoustic instability phenomena and assess quantitatively the transition of the combustor from a stable to an unstable regime. In this method, three-phase portraits are created on the basis of data retrieved from the measured acoustics and flame intensity in the laboratory-scale test combustor. In the path to limit cycle oscillation, the random distribution in the three-phase portrait contracts to an attractor. The phase portraits obtained when changing operating conditions, moving from the stable to the unstable regime and back, are analyzed. Subsequently, the attractor dimension is determined for quantitative analysis. On the basis of the trajectories from the stable to unstable and back in one run, a study is performed of the hysteresis dynamics in bifurcation diagrams. Finally, the onset of the instability is demonstrated to be recognized by the 0-1 criterion for chaos. The method was developed and demonstrated on a low-power atmospheric methane combustor with the aim to apply it subsequently on a high-power pressurized diesel combustor. Full article

(This article belongs to the Section I2: Energy and Combustion Science)

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25 pages, 2247 KiB

Open AccessArticle

Renewable Energy Consumption and Green Growth in Sub-Saharan Africa

by Brian Tavonga Mazorodze

Energies 2025, 18(7), 1851; https://doi.org/10.3390/en18071851 - 7 Apr 2025

Viewed by 259

Abstract

The debate on renewable energy consumption and green growth is yet to be empirically settled. Motivated by the dearth of literature in sub-Saharan Africa on this subject, this study examines the impact of renewable energy consumption on green growth using a panel of [...] Read more.

The debate on renewable energy consumption and green growth is yet to be empirically settled. Motivated by the dearth of literature in sub-Saharan Africa on this subject, this study examines the impact of renewable energy consumption on green growth using a panel of 22 sub-Saharan countries observed between 1990 and 2019. It criticizes the existing literature for inadequately addressing cross-sectional dependence and inappropriately assuming homogeneity in the way renewable energy consumption affects green growth across countries. A comparison of the commonly applied estimator in the literature which ignores the above two violations, and the preferred estimator suggests that the current state of knowledge could be fundamentally flawed. While the estimator commonly applied in the literature replicates the largely reported positive and direct impact of renewable energy on green growth, the preferred estimator finds the impact insignificant. It instead finds that green growth is primarily driven by gross capital formation, rather than renewable energy consumption. This study additionally examines the effect of renewable energy on several types of environmental damage. Renewable energy is found to significantly reduce CO₂ emissions only. The conclusion is therefore that renewable energy does not have a direct impact on green growth, although it helps reduce CO₂ emissions. Full article

(This article belongs to the Section I2: Energy and Combustion Science)

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18 pages, 4086 KiB

Open AccessArticle

Piezoelectric Energy Harvesting System to Charge Batteries with the Use of a Portable Musical Organ

by Josué Esaú Vega-Ávila, Guillermo Adolfo Anaya-Ruiz, José Joel Román-Godínez, Gabriela Guadalupe Esquivel-Barajas, Jorge Ortiz-Marín, Rogelio Gudiño-Valdez and Hilda Aguilar-Rodríguez

Energies 2025, 18(7), 1850; https://doi.org/10.3390/en18071850 - 6 Apr 2025

Viewed by 269

Abstract

In recent years, the increase in energy demand has been an incentive to search for new ways to generate energy. An alternative is producing this energy from daily human activities. To do this, piezoelectric devices have been used in different human activities to [...] Read more.

In recent years, the increase in energy demand has been an incentive to search for new ways to generate energy. An alternative is producing this energy from daily human activities. To do this, piezoelectric devices have been used in different human activities to collect energy. Some of these potential activities are transportation, biomedicine, and electronic devices. Harvesting energy from the mechanical force applied by a pianist during their performance is one of these activities that can be used. The implementation of piezoelectric devices under the keys of an electric organ was carried out. A theoretical model was developed to estimate the amount of energy we could recover. The system was characterized by controlled forces. The volume generated by the forces was measured via a Musical Instrument Digital Interface (MIDI) using the open-source music production software “LMMS (Linux MultiMedia Studio) 1.2.2 version”. The electric potential difference was measured as a function of the volume generated by the pianist. The voltages generated for different frequencies of the pianist’s rhythm were studied. The efficiency calculated in the mathematical model agreed with that obtained in the implemented system. The study results indicate that the batteries were recharged, which resulted in 53 s of organ operation. Full article

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

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23 pages, 18453 KiB

Open AccessArticle

Efficient Short-Term Wind Power Prediction Using a Novel Hybrid Machine Learning Model: LOFVT-OVMD-INGO-LSSVR

by Zhouning Wei and Duo Zhao

Energies 2025, 18(7), 1849; https://doi.org/10.3390/en18071849 - 6 Apr 2025

Viewed by 275

Abstract

Accurate wind power forecasting (WPF) is crucial to enhance availability and reap the benefits of integration into power grids. The time lag of wind power generation lags the time of wind speed changes, especially in ultra-short-term forecasting. The prediction model is sensitive to [...] Read more.

Accurate wind power forecasting (WPF) is crucial to enhance availability and reap the benefits of integration into power grids. The time lag of wind power generation lags the time of wind speed changes, especially in ultra-short-term forecasting. The prediction model is sensitive to outliers and sudden changes in input historical meteorological data, which may significantly affect the robustness of the WPF model. To address this issue, this paper proposes a novel hybrid machine learning model for highly accurate forecasting of wind power generation in ultra-short-term forecasting. The raw wind power data were filtered and classified with the local outlier factor (LOF) and the voting tree (VT) model to obtain a subset of inputs with the best relevance. The time-varying properties of the fluctuating sub-signals of the wind power sequences were analyzed with the optimized variational mode decomposition (OVMD) algorithm. The Northern Goshawk optimization (NGO) algorithm was improved by incorporating a logical chaotic initialization strategy and chaotic adaptive inertia weights. The improved NGO algorithm was used to optimize the least squares support vector regression (LSSVR) prediction model to improve the computational speed and prediction results. The proposed model was compared with traditional machine learning models, deep learning models, and other hybrid models. The experimental results show that the proposed model has an average R² of 0.9998. The average MSE, average MAE, and average MAPE are as low as 0.0244, 0.1073, and 0.3587, which displayed the best results in ultra-short-term WPF. Full article

(This article belongs to the Special Issue Intelligent Energy Technical Studies About Automobiles, New Energy Vehicles and Key Systems in the Energy Field)

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37 pages, 8933 KiB

Open AccessReview

Integrated Energy Storage Systems for Enhanced Grid Efficiency: A Comprehensive Review of Technologies and Applications

by Raphael I. Areola, Abayomi A. Adebiyi and Katleho Moloi

Energies 2025, 18(7), 1848; https://doi.org/10.3390/en18071848 - 6 Apr 2025

Viewed by 496

Abstract

The rapid global shift toward renewable energy necessitates innovative solutions to address the intermittency and variability of solar and wind power. This study presents a comprehensive review and framework for deploying Integrated Energy Storage Systems (IESSs) to enhance grid efficiency and stability. By [...] Read more.

The rapid global shift toward renewable energy necessitates innovative solutions to address the intermittency and variability of solar and wind power. This study presents a comprehensive review and framework for deploying Integrated Energy Storage Systems (IESSs) to enhance grid efficiency and stability. By leveraging a Multi-Criteria Decision Analysis (MCDA) framework, this study synthesizes techno-economic optimization, lifecycle emissions, and policy frameworks to evaluate storage technologies such as lithium-ion batteries, pumped hydro storage, and vanadium flow batteries. The framework prioritizes hybrid storage systems (e.g., battery–supercapacitor configurations), demonstrating 15% higher grid stability in high-renewable penetration scenarios, and validates findings through global case studies, including the Hornsdale Power Reserve (90–95% round-trip efficiency) and Kauai Island Utility Cooperative (15,000+ cycles for flow batteries). Regionally tailored strategies, such as Kenya’s fast-track licensing and Germany’s H2Global auctions, reduce deployment timelines by 30–40%, while equity-focused policies like India’s SAUBHAGYA scheme cut energy poverty by 25%. This study emphasizes circular economy principles, advocating for mandates like the EU’s 70% lithium recovery target to reduce raw material costs by 40%. Despite reliance on static cost projections and evolving regulatory landscapes, the MCDA framework’s dynamic adaptation mechanisms, including sensitivity analysis for carbon taxes (USD 100/ton CO₂-eq boosts hydrogen viability by 25%), ensure scalability across diverse grids. This work bridges critical gaps in renewable energy integration, offering actionable insights for policymakers and grid operators to achieve resilient, low-carbon energy systems. Full article

(This article belongs to the Special Issue Advancements in Smart Energy Systems, Energy Storage, and Renewables Integration)

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20 pages, 1665 KiB

Open AccessReview

Enhancing Resiliency in Distribution Power Grids with Distributed Generation Through Application of Visualisation Techniques

by Yasmin Nigar Abdul Rasheed, Ashish P. Agalgaonkar and Kashem Muttaqi

Energies 2025, 18(7), 1847; https://doi.org/10.3390/en18071847 - 6 Apr 2025

Viewed by 283

Abstract

With recent technological advancements, advanced communication technology, sensors and distributed generation (DG), it is an undeniable fact that modern power systems are flooded with massive amounts of data. These vast amount of generated data are difficult to interpret and comprehend, and are slow [...] Read more.

With recent technological advancements, advanced communication technology, sensors and distributed generation (DG), it is an undeniable fact that modern power systems are flooded with massive amounts of data. These vast amount of generated data are difficult to interpret and comprehend, and are slow to sort through and explain. With ever increasing renewable power generation, grid operators should gain insights on identifying the vulnerabilities, behaviour and interactions of various power system components and anticipate challenges to enhance power system resiliency. Visualisation offers a means to reveal patterns, trends and connections in data that speed up and present information to a power system operator in a way that can be well understood topographically and provide an ability to accommodate increasing DG resources. Hence, this paper presents a comprehensive literature review of several visualisation techniques that can be embedded for improving operational efficiency and resiliency in modern power grids embedded with distributed and renewable energy resources. Full article

(This article belongs to the Section F2: Distributed Energy System)

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22 pages, 13573 KiB

Open AccessArticle

Carbon Capture Adsorbents Based on Ash Residues from the Combustion of Coal with Biomass Blended Fuels

by Silviya Boycheva, Boian Mladenov, Ana Borissova, Momtchil Dimitrov, Ivalina Trendafilova, Daniela Kovacheva and Margarita Popova

Energies 2025, 18(7), 1846; https://doi.org/10.3390/en18071846 - 6 Apr 2025

Viewed by 298

Abstract

One of the approaches to limit the negative impact on the environment from the burning of coal in the production of heat and electricity is to limit their use by blending them with biomass. Blended fuel combustion leads to the generation of a [...] Read more.

One of the approaches to limit the negative impact on the environment from the burning of coal in the production of heat and electricity is to limit their use by blending them with biomass. Blended fuel combustion leads to the generation of a solid ash residue differing in composition from coal ash, and opportunities for its utilization have not yet been studied. The present paper provides results on the carbon capture potential of adsorbents developed through the alkaline conversion of ash mixtures from the combustion of lignite and biomass from agricultural plants and wood. The raw materials and the obtained adsorbents were studied with respect to the following: their chemical and phase composition based on Atomic Absorption Spectroscopy with Inductively Coupled Plasma (AAS-ICP) and X-ray powder diffraction (XRD), respectively, morphology based on scanning electron spectroscopy (SEM), thermal properties based on thermal analysis (TG and DTG), surface parameters based on N₂ physisorption, and the type of metal oxides within the adsorbents based on temperature-programmed reduction (TPR) and UV-VIS spectroscopy. The adsorption capacity toward CO₂ was studied in dynamic conditions and the obtained results were compared to those of zeolite-like CO₂ adsorbents developed through the utilization of the raw coal ash. It was observed that the adsorbents based on ash of blended fuel have a comparable carbon capture potential with coal fly ash zeolites despite their lower specific surface areas due to their compositional specifics and that they could be successfully applied as adsorbents in post-combustion carbon capture systems. Full article

(This article belongs to the Special Issue Renewable Fuels and Chemicals)

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23 pages, 5386 KiB

Open AccessArticle

Research Trends in Underground Hydrogen Storage: A Bibliometric Approach

by Barbara Uliasz-Misiak, Jacek Misiak and Radosław Tarkowski

Energies 2025, 18(7), 1845; https://doi.org/10.3390/en18071845 - 5 Apr 2025

Viewed by 347

Abstract

This article presents the findings of a bibliometric analysis of scientific publications in journals and materials indexed in the SCOPUS and Web of Science databases, covering the broad topic of underground hydrogen storage (UHS). The use of VOSviewer software for keyword analysis enabled [...] Read more.

This article presents the findings of a bibliometric analysis of scientific publications in journals and materials indexed in the SCOPUS and Web of Science databases, covering the broad topic of underground hydrogen storage (UHS). The use of VOSviewer software for keyword analysis enabled the identification of four key research areas related to UHS. These areas include hydrogen and hydrocarbon reservoir engineering; hydrogen economy and energy transformation; processes in hydrogen storage sites, including lessons from CO₂ sequestration; and the geology, engineering, and geomechanics of underground gas storage. The interdisciplinary nature of UHS research emphasises the synergy of research across diverse fields. A bibliographic analysis allowed for the identification of areas of intensive research and new directions of work related to UHS, key research centres, and the dynamics of the development of research topics related to UHS. This study revealed the chronological dispersion of the research results, their geographical and institutional variability, and the varying contributions of major publishing journals. The research methodology used can serve as an inspiration for the work of other researchers. Full article

(This article belongs to the Special Issue Advanced Studies on Clean Hydrogen Energy Systems of the Future)

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26 pages, 2307 KiB

Open AccessArticle

Solar Panel Waste Management: Challenges, Opportunities, and the Path to a Circular Economy

by Allison Piedrahita, Laura M. Cárdenas and Sebastian Zapata

Energies 2025, 18(7), 1844; https://doi.org/10.3390/en18071844 - 5 Apr 2025

Viewed by 628

Abstract

The swift global proliferation of solar photovoltaic (PV) technology has significantly contributed to the acceleration of the transition to renewable energy. Projections indicate a significant rise in installed capacity by 2050, suggesting that the extensive implementation of solar panels is transforming energy systems [...] Read more.

The swift global proliferation of solar photovoltaic (PV) technology has significantly contributed to the acceleration of the transition to renewable energy. Projections indicate a significant rise in installed capacity by 2050, suggesting that the extensive implementation of solar panels is transforming energy systems while simultaneously highlighting important issues regarding end-of-life waste management and long-term sustainability. The environmental advantages of photovoltaic (PV) systems are overshadowed by the prevalent reliance on landfilling and inadequate recycling practices, revealing a substantial deficiency in sustainable waste management, especially in areas with underdeveloped policy frameworks. This research study examines the solar panel supply chain, highlighting critical stages, sources of waste generation, existing management practices, and potential areas for enhancement. Waste is classified into four categories, solid, hazardous, electronic (WEEE), and environmental, each necessitating specific management strategies. Regions such as Europe exhibit comprehensive legal frameworks and advanced recycling technologies, whereas others, including Latin America and certain areas of Asia, continue to encounter deficits in policy and infrastructure. The research highlights the implementation of the 6R principles—Recycle, Recover, Reduce, Reuse, Repair, and Refine—within a circular economy framework to improve sustainability, optimize resource utilization, and reduce environmental impact. The findings highlight the necessity for coordinated policies, technological innovation, and international collaboration to ensure a sustainable future for solar energy. This study offers important insights for policymakers, industry stakeholders, and researchers focused on enhancing circularity and sustainability within the photovoltaic sector. Full article

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

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20 pages, 3868 KiB

Open AccessArticle

Wind Power Plant Expert System Diagnostic Knowledge Base Creation

by Radosław Duer, Stanisław Duer, Konrad Zajkowski, Marek Woźniak, Dariusz Bernatowicz, Jacek Paś, Marek Stawowy, Atif Iqbal and Marta Harničárová

Energies 2025, 18(7), 1843; https://doi.org/10.3390/en18071843 - 5 Apr 2025

Viewed by 259

Abstract

Under certain weather circumstances, wind farms might lose their operational integrity. The study describes the process for building a WPP (Wind Power Plant) expert knowledge base for the WPPES system. The article presents the creation of an expert knowledge base on wind farm [...] Read more.

Under certain weather circumstances, wind farms might lose their operational integrity. The study describes the process for building a WPP (Wind Power Plant) expert knowledge base for the WPPES system. The article presents the creation of an expert knowledge base on wind farm equipment that is the basis for the functioning of an intelligent expert system. For this purpose, a functional and diagnostic model of wind farm equipment was presented and described. Functional diagnostic models of objects are the basis for obtaining diagnostic information about the study object (set of facts). The operating conditions of the wind farm equipment and their surroundings have been characterized and described. On this basis, admissible and boundary conditions for the functioning of the tested technical object were determined. The above information specifically supplements the diagnostic information set when building the set of facts and rules. An important part of the article is to describe the principles and conditions for developing a set of diagnostic rules for the knowledge base of an expert system diagnosing wind farm equipment. Building expert knowledge bases is an extremely complex process of transforming diagnostic object information sets into the form of knowledge that is required by an expert system. To this end, an analytical relationship was developed and described as the basis for building a set of inference rules for the examined object. The effectiveness of the developed expert knowledge base is presented in the aspect of its introduction to the expert system knowledge module. Full article

(This article belongs to the Section F5: Artificial Intelligence and Smart Energy)

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Energies, Volume 18, Issue 7 (April-1 2025) – 313 articles

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