Journal Description
Energies
Energies
is a peer-reviewed, open access journal of related scientific research, technology development, engineering policy, and management studies related to the general field of energy, from technologies of energy supply, conversion, dispatch, and final use to the physical and chemical processes behind such technologies. Energies is published semimonthly online by MDPI. The European Biomass Industry Association (EUBIA), Association of European Renewable Energy Research Centres (EUREC), Institute of Energy and Fuel Processing Technology (ITPE), International Society for Porous Media (InterPore), CYTED and others are affiliated with Energies and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, RePEc, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: CiteScore - Q1 (Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.1 days after submission; acceptance to publication is undertaken in 3.3 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Sections: published in 41 topical sections.
- Testimonials: See what our editors and authors say about Energies.
- Companion journals for Energies include: Fuels, Gases, Nanoenergy Advances and Solar.
Impact Factor:
3.2 (2022);
5-Year Impact Factor:
3.3 (2022)
Latest Articles
Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks
Energies 2024, 17(9), 2200; https://doi.org/10.3390/en17092200 (registering DOI) - 03 May 2024
Abstract
Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically
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Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.
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(This article belongs to the Special Issue Reliability Evaluation of Integrated Electricity and Natural Gas Systems)
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Empowering Students to Create Climate-Friendly Schools
by
Oliver Wagner, Lena Tholen, Sebastian Albert-Seifried and Julia Swagemakers
Energies 2024, 17(9), 2199; https://doi.org/10.3390/en17092199 (registering DOI) - 03 May 2024
Abstract
In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with
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In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with knowledge and skills. On the other hand, school buildings are often in bad condition, energy is wasted, and the possibilities for using renewable energies are hardly used. In our “Schools4Future” project, we enabled students and teachers to draw up their own CO2 balances, identify weaknesses in the building, detect wasted electricity, and determine the potential for using renewable energies. Emissions from the school cafeteria, school trips, and paper consumption could also be identified. The fact that the data can be collected by the students themselves provides increased awareness of the contribution made to the climate balance by the various school areas. The most climate-friendly school emits 297 kg whilst the school with the highest emissions emits over one ton CO2 per student and year. Our approach is suitable to qualify students in the sense of citizen science, carry out a scientific investigation, experience self-efficacy through one’s own actions, and engage politically regarding their concerns.
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(This article belongs to the Special Issue Selected Papers from the SDEWES 2023 Conference on Sustainable Development of Energy, Water, and Environment Systems)
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Diagnostics of Interior PM Machine Rotor Faults Based on EMF Harmonics
by
Natalia Radwan-Pragłowska and Tomasz Wegiel
Energies 2024, 17(9), 2198; https://doi.org/10.3390/en17092198 (registering DOI) - 03 May 2024
Abstract
This article presents a detailed study on the diagnosis of rotor faults in an Interior Permanent Magnet Machine based on a mathematical model. The authors provided a wide literature review, mentioning the fault diagnosis methods used for Permanent Magnet Machines. The research emphasizes
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This article presents a detailed study on the diagnosis of rotor faults in an Interior Permanent Magnet Machine based on a mathematical model. The authors provided a wide literature review, mentioning the fault diagnosis methods used for Permanent Magnet Machines. The research emphasizes the necessity of precise assumptions regarding winding construction to accurately analyze the additional harmonics appearing in rotor faults caused by electromotive force (EMF), i.e., rotor eccentricity and magnet damage. The article also discusses specific features appearing in the spectrum of air gap permeance functions and the impact of rotor eccentricity and magnet damage on PM flux density distribution and as a consequence on EMF stator windings. The novelty of the presented content is the analysis of induced EMFs for cases of the simultaneous occurrence of rotor eccentricity and PM damage. The findings of this study provide valuable insights for the diagnosis and understanding of internal asymmetries in Interior PM Machines.
Full article
(This article belongs to the Special Issue New Solutions in Electric Machines and Motor Drives: 2nd Edition)
Open AccessArticle
An Assessment of a Photovoltaic System’s Performance Based on the Measurements of Electric Parameters under Changing External Conditions
by
Agata Zdyb and Dariusz Sobczyński
Energies 2024, 17(9), 2197; https://doi.org/10.3390/en17092197 (registering DOI) - 03 May 2024
Abstract
This article presents an analysis of the performance of a 14.04 kWp grid-connected photovoltaic (PV) installation consisting of monocrystalline silicon, polycrystalline silicon and bifacial glass–glass monocrystalline silicon modules. The photovoltaic system was mounted in Poland, a location characterized by temperate climate conditions. On
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This article presents an analysis of the performance of a 14.04 kWp grid-connected photovoltaic (PV) installation consisting of monocrystalline silicon, polycrystalline silicon and bifacial glass–glass monocrystalline silicon modules. The photovoltaic system was mounted in Poland, a location characterized by temperate climate conditions. On the basis of the obtained results, the photovoltaic parameters were determined in accordance with the international standard. The annual energy yield of the entire system was 1033 kWh/kWp, and the performance ratio achieved was 83%. The highest average daily final yield was in the range of 4.0–4.5 kWh/kWp for each photovoltaic technology under investigation. In the cold part of the year, the efficiency of the photovoltaic modules was estimated to be 15%, and it was estimated to be 7% during the warm part of the year. Array capture losses accounted for around 0.75 kWh/kWp of energy loss per day, whereas the inverter efficiency was over 95% during the months that are beneficial for energy production.
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(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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Performance of Corn Cob Combustion in a Low-Temperature Fluidized Bed
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Rolandas Paulauskas, Marius Praspaliauskas, Ignas Ambrazevičius, Kęstutis Zakarauskas, Egidijus Lemanas, Justas Eimontas and Nerijus Striūgas
Energies 2024, 17(9), 2196; https://doi.org/10.3390/en17092196 (registering DOI) - 03 May 2024
Abstract
This study investigates the combustion of agricultural biomass rich in alkali elements in the fluidized bed. The experiments were performed with smashed corn cob in a 500 kW fluidized bed combustor which was designed for work under low bed temperatures (650–700 °C). During
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This study investigates the combustion of agricultural biomass rich in alkali elements in the fluidized bed. The experiments were performed with smashed corn cob in a 500 kW fluidized bed combustor which was designed for work under low bed temperatures (650–700 °C). During the experiments, the formed compounds from corn cob combustion were measured by sampling particulate matter, and mineral compositions were determined. Also, the temperature profile of the FBC was established. It was determined that the emissions of K and Na elements from the FBC increased from 4 to 7.3% and from 1.69 to 3%, respectively, changing the bed temperature from 650 to 700 °C. Though alkali emissions are reduced at a 650 °C bed temperature, CO emissions are higher by about 50% compared to the case of 700 °C. The addition of 3% of dolomite reduced the pollutant emissions and alkali emissions as well. Potassium content decreased by about 1% and 4%, respectively, at the bed temperatures of 650 °C and 700 °C. The NOx emissions were less than 300 mg/m3 and did not exceed the limit for medium plants regarding DIRECTIVE (EU) 2015/2193. During extended experiments lasting 8 h, no agglomeration of the fluidized bed was observed. Moreover, the proposed configuration of the FBC and its operational parameters prove suitable for facilitating the efficient combustion of agricultural biomass.
Full article
(This article belongs to the Special Issue Efficient Utilization of Thermal Energy: Advanced Biomass Combustion Technologies)
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Prosumer Impact on Cellular Power Systems
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Jens Maiwald and Tino Schütte
Energies 2024, 17(9), 2195; https://doi.org/10.3390/en17092195 (registering DOI) - 03 May 2024
Abstract
This paper explores the impact of an increasing number of prosumers in electricity supply systems and investigates how market mechanisms can mitigate the negative effects. The Regional Energy Market Model simulates a supply system based on cellular structures, employing agent-based modeling to capture
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This paper explores the impact of an increasing number of prosumers in electricity supply systems and investigates how market mechanisms can mitigate the negative effects. The Regional Energy Market Model simulates a supply system based on cellular structures, employing agent-based modeling to capture individual behaviors and simulate real market dynamics. This study includes various supply scenarios, such as a solely photovoltaic scenario and a technically diversified scenario with biogas-fueled combined heat and power units. For each scenario, fixed and flexible pricing scenarios are simulated to analyze their effects. The findings reveal that systems heavily reliant on photovoltaics experience negative effects at certain points due to seasonal limitations, while technically diversified supply scenarios demonstrate fewer drawbacks. Flexible pricing systems stimulate demand in a manner beneficial to the system, creating regional added value, and contributing to the balance between generation and consumption, depending on the supply scenario. However, the study underscores that economic incentives alone are insufficient for balancing generation and consumption. The results highlight the importance of exploring opportunities through the interplay of economic incentive mechanisms and technical possibilities.
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(This article belongs to the Special Issue Smart Grid and Energy Storage)
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Optimal Selection of Distribution, Power, and Type of Luminaires for Street Lighting Designs Using Multi-Criteria Decision Model
by
Nataly Gabriela Valencia Pavón, Alexander Aguila Téllez, Marcelo García Torres, Javier Rojas Urbano and Narayanan Krishnan
Energies 2024, 17(9), 2194; https://doi.org/10.3390/en17092194 (registering DOI) - 03 May 2024
Abstract
This article introduces an innovative design method for public lighting systems that surpasses the limitations of conventional approaches, which rely on predefined lamp characteristics and spatial arrangements. By employing a linear additive model to solve a multi-criteria decision model, our study proposes an
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This article introduces an innovative design method for public lighting systems that surpasses the limitations of conventional approaches, which rely on predefined lamp characteristics and spatial arrangements. By employing a linear additive model to solve a multi-criteria decision model, our study proposes an optimal design methodology considering several key aspects, including the distance between lamps, their type, power, and light distribution. The goal is to achieve optimal illumination that enhances visibility on public roads for drivers and pedestrians while simultaneously minimizing glare and installation costs and maximizing energy efficiency. The proposed methodology is implemented through an algorithm developed in MATLAB R2023b, with results validated through simulations in DIALux evo 12.0. This information is used to construct a decision matrix, assessed using the CRITIC method across 180 different scenarios within a specific case study. The findings demonstrate the effectiveness of multi-criteria decision-making as a tool for significantly improving the planning and design of lighting in public illumination systems, allowing for selecting the optimal combination of parameters that ensure the best lighting conditions.
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(This article belongs to the Section F: Electrical Engineering)
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Open AccessEditorial
Recent Advances in Power Quality Analysis and Robust Control of Renewable Energy Sources in Power Grids
by
Dinko Vukadinović
Energies 2024, 17(9), 2193; https://doi.org/10.3390/en17092193 (registering DOI) - 03 May 2024
Abstract
In modern power grids with a large share of distributed power production, achieving high-power quality is a challenging task [...]
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(This article belongs to the Special Issue Recent Advances in Power Quality Analysis and Robust Control of Renewable Energy Sources in Power Grids)
Open AccessArticle
Enhanced Torrefied Oil-Palm Biomass as an Alternative Bio-Circular Solid Fuel: Innovative Modeling of Optimal Conditions and Ecoefficiency Analysis
by
Attaso Khamwichit, Jannisa Kasawapat, Narongsak Seekao and Wipawee Dechapanya
Energies 2024, 17(9), 2192; https://doi.org/10.3390/en17092192 - 02 May 2024
Abstract
Energy production from coal combustion is responsible for nearly 40% of global CO2 emissions including SOx and NOx. This study aims to produce solid biomass fuels from oil-palm residues by torrefaction, having a high heating value (HHV) equivalent to
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Energy production from coal combustion is responsible for nearly 40% of global CO2 emissions including SOx and NOx. This study aims to produce solid biomass fuels from oil-palm residues by torrefaction, having a high heating value (HHV) equivalent to fossil coals. The experiments were designed using Design Expert version 13 software to optimize the conditions affecting the fuel characteristics of the torrefied products. The statistical analysis suggested that the optimal conditions to achieve a high HHV and fixed carbon content while retaining the mass yield of biomass mainly depended on the temperature and torrefying time, while the size played a less important role in affecting the properties. The optimal conditions were observed to be at 283 °C (120 min) for EFBs, 301 °C (111 min) for PF, and 285 °C (120 min) for PKSs. The maximum HHV of 5229, 5969, and 5265 kcal/kg were achieved for the torrefied EFBs, PF, and PKSs, respectively. The energy efficiency of torrefied biomass was increased to 1.25–1.35. Ecoefficiency analysis suggested that torrefaction should be carried out at high temperatures with a short torrefying time. This low-cost bio-circular torrefied biomass showed promising fuel characteristics that could be potentially used as an alternative to coals.
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(This article belongs to the Special Issue Bioenergy and Waste-to-Energy Technologies to Reach Climate Neutrality)
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Application of Machine Learning for Shale Oil and Gas “Sweet Spots” Prediction
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Hongjun Wang, Zekun Guo, Xiangwen Kong, Xinshun Zhang, Ping Wang and Yunpeng Shan
Energies 2024, 17(9), 2191; https://doi.org/10.3390/en17092191 - 02 May 2024
Abstract
With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for “sweet spots”
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With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for “sweet spots” prediction in shale oil and gas areas. Taking the Duvernay shale oil and gas field in Canada as an example, this paper attempts to build recoverable shale oil and gas reserve prediction models using machine learning methods and geological and development big data, to predict the distribution of recoverable shale oil and gas reserves and provide a basis for well location deployment and engineering modifications. The research results of the machine learning model in this study are as follows: ① Three machine learning methods were applied to build a prediction model and random forest showed the best performance. The R2 values of the built recoverable shale oil and gas reserves prediction models are 0.7894 and 0.8210, respectively, with an accuracy that meets the requirements of production applications; ② The geological main controlling factors for recoverable shale oil and gas reserves in this area are organic matter maturity and total organic carbon (TOC), followed by porosity and effective thickness; the main controlling factor for engineering modifications is the total proppant volume, followed by total stages and horizontal lateral length; ③ The abundance of recoverable shale oil and gas reserves in the central part of the study area is predicted to be relatively high, which makes it a favorable area for future well location deployment.
Full article
(This article belongs to the Section H1: Petroleum Engineering)
Open AccessArticle
Experimental Study on Thermal Environment and Thermal Comfort of Passenger Compartment in Winter with Personal Comfort System
by
Yuxin Hu, Lanping Zhao, Xin Xu, Guomin Wu and Zhigang Yang
Energies 2024, 17(9), 2190; https://doi.org/10.3390/en17092190 - 02 May 2024
Abstract
The combined heating method of seat heating and air conditioning (A/C) was applied in the passenger compartment under different experiment conditions, using thermocouples to continuously measure the wall surfaces and air temperatures in the passenger compartment and the passengers’ skin temperatures of 17
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The combined heating method of seat heating and air conditioning (A/C) was applied in the passenger compartment under different experiment conditions, using thermocouples to continuously measure the wall surfaces and air temperatures in the passenger compartment and the passengers’ skin temperatures of 17 segments. Meanwhile, a subjective evaluation questionnaire survey was conducted using a nine-point evaluation scale on the local and overall thermal sensation and thermal comfort of the passengers, and the data from the questionnaire were analyzed with the ANOVA method. The results showed that the use of the heating pad directly affected the changes in human skin temperature, which in turn affected the local and overall thermal sensation and thermal comfort. For the two thermally stimulated segments of the back and under the thighs, the skin temperature of the back was higher than that of the thighs. Using the heating pad resulted in a rapid increase in the mean skin temperature in the early period of the experiment. Thermal sensation of the back and under-thighs shifted rapidly towards the hot zone in the first 10 min, and then settled around +3, with even more significant differences between the groups. Thermal sensations in non-thermally stimulated segments changed in relation to their position on the heating pad, with slower changes in those at the “distal” end of the body, the head and the feet. Continued use of the heating pads at lower ambient temperatures maintained overall thermal comfort at a neutral level in the range of 0–1, whereas at higher ambient temperatures there was a gradual deterioration of local and overall thermal comfort.
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(This article belongs to the Section B: Energy and Environment)
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A Comparative Study on Load Assessment Methods for Offshore Wind Turbines Using a Simplified Method and OpenFAST Simulations
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Satish Jawalageri, Subhamoy Bhattacharya, Soroosh Jalilvand and Abdollah Malekjafarian
Energies 2024, 17(9), 2189; https://doi.org/10.3390/en17092189 - 02 May 2024
Abstract
Simplified methods are often used for load estimations during the initial design of the foundations of offshore wind turbines (OWTs). However, the reliability of simplified methods for designing different OWTs needs to be studied. This paper provides a comparative study to evaluate the
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Simplified methods are often used for load estimations during the initial design of the foundations of offshore wind turbines (OWTs). However, the reliability of simplified methods for designing different OWTs needs to be studied. This paper provides a comparative study to evaluate the reliability of simplified approaches. The foundation loads are calculated for OWTs at the mudline level using a simplified approach and OpenFAST simulations and compared. Three OWTs, NREL 5 MW, DTU 10 MW, and IEA 15 MW, are used as reference models. An Extreme Turbulence Model wind load at a rated wind speed, combined with a 50-year Extreme Wave Height (EWH) and Extreme Operating Gust (EOG) wind load and a 1-year maximum wave height are used as the load combinations in this study. In addition, the extreme loads are calculated using both approaches for various metocean data from five different wind farms. Further, the pile penetration lengths calculated using the mudline loads via two methods are compared. The results show that the simplified method provides conservative results for the estimated loads compared to the OpenFAST results, where the extent of conservativism is studied. For example, the bending moment and shear force at the mudline using the simplified approach are 23% to 69% and 32% to 53% higher compared to the OpenFAST results, respectively. In addition, the results show that the simplified approach can be effectively used during the initial phases of monopile foundation design by using factors such as 1.5 and 2 for the shear force and bending moment, respectively.
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(This article belongs to the Special Issue Offshore Wind Support Structure Design)
Open AccessArticle
Research on Hybrid Rectifier for High Power Electrolytic Hydrogen Production Based on Modular Multilevel Converter
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Cheng Huang, Yang Tan and Xin Meng
Energies 2024, 17(9), 2188; https://doi.org/10.3390/en17092188 - 02 May 2024
Abstract
Aiming at the problem that silicon-controlled rectifiers (SCR) and pulse width modulation (PWM) rectifiers cannot balance high power levels, high hydrogen production efficiency, and high grid connected quality in the current research on rectifier power supplies for electrolytic hydrogen production, a new hybrid
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Aiming at the problem that silicon-controlled rectifiers (SCR) and pulse width modulation (PWM) rectifiers cannot balance high power levels, high hydrogen production efficiency, and high grid connected quality in the current research on rectifier power supplies for electrolytic hydrogen production, a new hybrid rectifier topology based on a modular multilevel converter (MMC) is proposed. The hybrid topology integrates a silicon-controlled rectifier (SCR) with an auxiliary power converter, wherein the SCR is designated as the primary power source for electrolytic hydrogen production. The auxiliary converter employs a cascaded modular multilevel converter (MMC) and an input-series-output-parallel (ISOP) phase-shifted full-bridge (PSFB) arrangement. This configuration allows the auxiliary converter to effectively mitigate AC-side harmonics and minimize DC-side ripple, concurrently transmitting a small amount of power. The effectiveness of the hybrid rectifier in achieving low ripple and harmonic distortion outputs was substantiated through hardware-in-the-loop experiments. Notably, the hybrid topology is characterized by its enhanced electric-to-hydrogen conversion efficiency, elevated power density, cost efficiency, and improved grid compatibility.
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(This article belongs to the Special Issue Power Electronics Applications in Microgrid and Renewable Energy Systems)
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The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review
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Mohammad Mehdi Amiri, Mohammad Taghi Ameli, Goran Strbac, Danny Pudjianto and Hossein Ameli
Energies 2024, 17(9), 2187; https://doi.org/10.3390/en17092187 - 02 May 2024
Abstract
The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This
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The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This paper presents a comprehensive review of the state-of-the-art research and developments concerning the flexibility in the operation of low-carbon integrated gas and electricity networks (IGENs) as part of the whole system approach. Methods and solutions to provide and improve flexibility in the mentioned systems are studied and categorized. Flexibility is the system’s ability to deal with changes and uncertainties in the network while maintaining an acceptable level of reliability. The presented review underscores the significance of this convergence in facilitating demand-side management, renewable energy integration, and overall system resilience. By highlighting the technical, economic, and regulatory aspects of such integration, this paper aims to guide researchers, policymakers, and industry stakeholders toward effective decision-making and the formulation of comprehensive strategies that align with the decarbonization of energy systems.
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(This article belongs to the Special Issue Whole-Energy System Modeling)
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Do Energy Consumption and CO2 Emissions Significantly Influence Green Tax Levels in European Countries?
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Claudia Diana Sabău-Popa, Alexandra Maria Bele, Adrian Negrea, Dorin Cristian Coita and Adriana Giurgiu
Energies 2024, 17(9), 2186; https://doi.org/10.3390/en17092186 - 02 May 2024
Abstract
In this article, we analyze the correlation between GDP/capita variation, primary and renewable energy consumption and greenhouse gas emissions on the one hand, and green taxes on the other. Green taxes are the main instruments used to limit activities that have a negative
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In this article, we analyze the correlation between GDP/capita variation, primary and renewable energy consumption and greenhouse gas emissions on the one hand, and green taxes on the other. Green taxes are the main instruments used to limit activities that have a negative impact on the environment. These consist of taxes paid by producers and/or consumers for any activity that generates pollution. The results of dynamic regressions, validated by the applied robustness tests, indicate a significant and positive correlation between primary energy consumption and total environmental taxes, respectively energy taxes. At the same time, this shows that variation in GDP/capita significantly and positively influences transport taxes and pollution taxes. In contrast, net greenhouse gas emissions and the supply, transformation and consumption of renewable sources and waste do not significantly influence the total green taxes and their components. This finding is useful to both academic research and government policies for the realistic substantiation of the levels of green tax revenues and for establishing appropriate measures meant to reduce CO2 emissions.
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(This article belongs to the Section C: Energy Economics and Policy)
Open AccessArticle
Research on Thermal Adaptability of Flexible Operation in Different Types of Coal-Fired Power Units
by
Haijiao Wei, Yuanwei Lu, Yanchun Yang, Yuting Wu, Kaifeng Zheng and Liang Li
Energies 2024, 17(9), 2185; https://doi.org/10.3390/en17092185 - 02 May 2024
Abstract
The flexible mode of operation of coal-fired units can accommodate large-scale renewable power integration into the grid, providing more grid capacity. The flexibility transformation of coal-fired units in thermal power plants can be achieved through main steam extraction and reheated steam extraction. A
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The flexible mode of operation of coal-fired units can accommodate large-scale renewable power integration into the grid, providing more grid capacity. The flexibility transformation of coal-fired units in thermal power plants can be achieved through main steam extraction and reheated steam extraction. A 300 MW subcritical unit, 600 MW subcritical unit and 660 MW ultra-supercritical unit with six flexible operation modes were chosen as the research model to investigate the thermal adaptability for flexible operation. The results show that from the perspective of the source of steam extraction, the main steam extraction scheme is suitable for the flexible adjustment of peak load capacity, and the reheated extraction scheme is suitable for the flexible operation of low load and high thermal efficiency. Moreover, from the perspective of thermal performance adaptability, the 600 MW unit has a wider load regulation capacity than the 300 MW and 660 MW units, and is suitable as the peak shaving unit. This work can provide theoretical guidance for different types of coal-fired units in choosing flexible operation schemes.
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(This article belongs to the Special Issue Advanced Applications of Solar and Thermal Storage Energy)
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Forecasting the Power Generation Mix in Italy Based on Grey Markov Models
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Guglielmo D’Amico, Alex Karagrigoriou and Veronica Vigna
Energies 2024, 17(9), 2184; https://doi.org/10.3390/en17092184 - 02 May 2024
Abstract
This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The
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This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey Model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which could provide powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Results show an improvement in the performance of more than 50% in terms of Root Mean Squared Error (RMSE) when the Markov chain is integrated in the analysis. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.
Full article
(This article belongs to the Section F: Electrical Engineering)
Open AccessArticle
Enhancement of perovskite photodetector using MAPbI3 with formamidinium bromide
by
DongJae Shin and HyungWook Choi
Energies 2024, 17(9), 2183; https://doi.org/10.3390/en17092183 - 02 May 2024
Abstract
In this study, a perovskite-based mixed cation/anion ultraviolet photodetector with an added halide material is fabricated using perovskite combined with an ABX_3 structure. Mixed cation/anion perovskite thin films of MAPbI3/FABr are manufactured through a relatively simple solution process and employed as
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In this study, a perovskite-based mixed cation/anion ultraviolet photodetector with an added halide material is fabricated using perovskite combined with an ABX_3 structure. Mixed cation/anion perovskite thin films of MAPbI3/FABr are manufactured through a relatively simple solution process and employed as light-absorption layers. In the produced thin film, SnO2–sodium dodecylbenzenesulfonate acts as an electron transport layer and spiro-OMeTAD acts as a hole injection layer. Compared to a single cation/anion perovskite, the fabricated device exhibits phase stability and optoelectronic properties, and demonstrates a responsivity of 72.2 mA/W and a detectability of 4.67 × 1013 Jones. In addition, the films show an external quantum efficiency of 56%. This suggests that mixed cation/anion films can replace single cation/anion perovskite films. Thus, photodetectors based on lead halides that can be applied in various fields have recently been manufactured.
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Open AccessArticle
Forecasting Oil Prices with Non-Linear Dynamic Regression Modeling
by
Pedro Moreno, Isabel Figuerola-Ferretti and Antonio Muñoz
Energies 2024, 17(9), 2182; https://doi.org/10.3390/en17092182 - 02 May 2024
Abstract
The recent energy crisis has renewed interest in forecasting crude oil prices. This paper focuses on identifying the main drivers determining the evolution of crude oil prices and proposes a statistical learning forecasting algorithm based on regression analysis that can be used to
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The recent energy crisis has renewed interest in forecasting crude oil prices. This paper focuses on identifying the main drivers determining the evolution of crude oil prices and proposes a statistical learning forecasting algorithm based on regression analysis that can be used to generate future oil price scenarios. A combination of a generalized additive model with a linear transfer function with ARIMA noise is used to capture the existence of combinations of non-linear and linear relationships between selected input variables and the crude oil price. The results demonstrate that the physical market balance or fundamental is the most important metric in explaining the evolution of oil prices. The effect of the trading activity and volatility variables are significant under abnormal market conditions. We show that forecast accuracy under the proposed model supersedes benchmark specifications, including the futures prices and analysts’ forecasts. Four oil price scenarios are considered for expository purposes.
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(This article belongs to the Topic Energy Market and Energy Finance)
Open AccessArticle
Choosing the Most Suitable Working Fluid for a CTEC
by
Aliet Achkienasi, Rodolfo Silva, Edgar Mendoza and Luis D. Luna
Energies 2024, 17(9), 2181; https://doi.org/10.3390/en17092181 - 02 May 2024
Abstract
This study aims to explore additional fluids beneficial for coastal thermal energy converter (CTEC) operation. Ammonia’s thermodynamic properties, characterized by higher condensation temperatures and pressures, demand significantly elevated operating pressures, resulting in a substantial energy load for efficient operation. Thus, exploring alternatives such
[...] Read more.
This study aims to explore additional fluids beneficial for coastal thermal energy converter (CTEC) operation. Ammonia’s thermodynamic properties, characterized by higher condensation temperatures and pressures, demand significantly elevated operating pressures, resulting in a substantial energy load for efficient operation. Thus, exploring alternatives such as R134a becomes crucial, particularly considering its potential as a better working fluid for power generation in a Rankine cycle. The research methodology involves employing computational fluid dynamics (CFD) simulations alongside experimental investigations to examine the performance of an axial turbine concept under different working fluids. The results obtained indicate that R134a is the most appropriate working fluid for an axial turbine within a CTEC, outperforming ammonia, thereby implying significantly better operational efficiency.
Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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