Energies

19 pages, 11278 KiB

Open AccessArticle

Compensation of the Current Imbalance of an Interleaved DC–DC Buck Converter, Sensorless Online Solution Based on Offline Fuzzy Identification and Post-Linearization

by Robert Baždarić, Jasmin Ćelić and Danjel Vončina

Energies 2023, 16(12), 4836; https://doi.org/10.3390/en16124836 - 20 Jun 2023

Viewed by 888

Abstract

This paper presents a new approach to compensate for the current imbalance of an interleaved DC–DC buck converter (IBC), in which the current sensors are not involved in the operation of the converter when it is connected to an invariable load. The current [...] Read more.

This paper presents a new approach to compensate for the current imbalance of an interleaved DC–DC buck converter (IBC), in which the current sensors are not involved in the operation of the converter when it is connected to an invariable load. The current sensors are only used during the offline identification process that builds the universal fuzzy model of the converter’s steady states. Model building involves an upstream identification phase, followed by further dimensionality reduction of the model and error minimization. The method presented here discusses the mathematical complexity of the analytical modelling of hybrid systems and opposes it with a complexity-reduced identification by learning from data. An offline rendered model of the stable and steady states of the IBC is used as a mapping of the required inverter output current to n-fold asymmetric duty cycles, which are distributed among the IBC phases to allow arbitrarily accurate load sharing. The mapping is carried out in the mathematically normalized space of variables or in the physical sense RMS values, achieving the desired robustness in a noisy environment and stability. The final and canonical feedback control is built from the standard and optimized PI controller, which is compensated by the identified IBC model correction. The only measured feedback of the whole controller is the output voltage. Even when applied to the simulation model (physical MATLAB platform) of a two-phase IBC with the built-in system asymmetry, the presented methodology is also applicable to the n-phase IBC without loss of generality. Full article

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

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21 pages, 3982 KiB

Open AccessEditor’s ChoiceArticle

Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids

by M. Usman Saleem, Mustafa Shakir, M. Rehan Usman, M. Hamza Tahir Bajwa, Noman Shabbir, Payam Shams Ghahfarokhi and Kamran Daniel

Energies 2023, 16(12), 4835; https://doi.org/10.3390/en16124835 - 20 Jun 2023

Cited by 18 | Viewed by 3725

Abstract

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand [...] Read more.

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers’ energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings. Full article

(This article belongs to the Special Issue Applications of Advanced Control and Optimization Paradigms in Renewable Energy Systems)

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16 pages, 5084 KiB

Open AccessArticle

Subcooling Effect on PCM Solidification: A Thermostat-like Approach to Thermal Energy Storage

by Nicola Bianco, Andrea Fragnito, Marcello Iasiello, Gerardo Maria Mauro and Luigi Mongibello

Energies 2023, 16(12), 4834; https://doi.org/10.3390/en16124834 - 20 Jun 2023

Viewed by 1054

Abstract

Choosing the right phase change material (PCM) for a thermal energy storage (TES) application is a crucial step in guaranteeing the effectiveness of the system. Among a variety of PCMs available, the choice for a given application is established by several key factors, [...] Read more.

Choosing the right phase change material (PCM) for a thermal energy storage (TES) application is a crucial step in guaranteeing the effectiveness of the system. Among a variety of PCMs available, the choice for a given application is established by several key factors, e.g., latent heat, stability, and melting point. However, phenomena such as subcooling—for which PCM cools in a liquid state below its solidification point—can lead to a reduction in the amount of energy stored or released, reducing the TES overall effectiveness, and also in some inaccuracies when modeling the problem. Thus, understanding the effects of subcooling on PCM performance is crucial for modeling and optimizing the design and the performance of TES systems. To this end, this work analyzes the PCM discharging phase in a cold thermal energy storage coupled to a chiller system. A first conduction-based predictive model is developed based on enthalpy–porosity formulation. Subcooling phenomena are encompassed through a control variable formulation, which takes its cue from the operation of a thermostat. Then, thermal properties of the PCM, i.e., the phase change range and specific heat capacity curve with temperature, are evaluated by using differential scanning calorimetry (DSC), in order to derive a second predictive model based on these new data, without including subcooling, for the sake of comparison with the first one. Experimental results from the storage tank confirm both model reliability and the fact that the PCM suffers from subcooling. Between the two numerical models developed, the first one that considers subcooling proves it is able to predict with satisfactory accuracy (RMSE < 1 °C) the temperature evolution on different tank levels. Full article

(This article belongs to the Special Issue Theoretical and Experimental Analysis of Phase Change Materials for Thermal Energy Storage Applications)

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27 pages, 4222 KiB

Open AccessFeature PaperArticle

Design and Performance Analysis of a Novel Integrated Solar Combined Cycle (ISCC) with a Supercritical CO₂ Bottom Cycle

by Zuxian Zhang, Liqiang Duan, Zhen Wang and Yujie Ren

Energies 2023, 16(12), 4833; https://doi.org/10.3390/en16124833 - 20 Jun 2023

Viewed by 808

Abstract

The integrated solar combined cycle (ISCC) system is a proven solution for grid-connected power generation from solar energy. How to further improve the ISCC system efficiency and propose a more efficient system solution has become a research focus. A novel gas turbine combined [...] Read more.

The integrated solar combined cycle (ISCC) system is a proven solution for grid-connected power generation from solar energy. How to further improve the ISCC system efficiency and propose a more efficient system solution has become a research focus. A novel gas turbine combined cycle (GTCC) benchmark system is proposed by replacing the conventional steam Rankine bottom cycle with a supercritical CO₂ Brayton cycle, whose output power and efficiency are increased by 9.07 MW and 1.3%, respectively, compared to those of the conventional GTCC system. Furthermore, the novel ISCC systems are established with the parabolic trough solar collector (PTC) and the solar tower (ST) collector coupled to the novel GTCC system. Thermal performance analysis, exergy performance analysis, and the sensitivity analysis of the ISCC systems have been performed, and the results show that the system efficiencies of both ISCC systems are lower than that of the GTCC system, at 57.1% and 57.5%, respectively, but the power generation of the ISCC system with PTC is greater than that of the benchmark system, while that of the ISCC system with ST is less than that of the benchmark system. The photoelectric efficiency of the ISCC system with PTC is 27.6%, which is 2.1% greater than that of ISCC system with ST. In the ISCC system with PTC, the components with the highest exergy destruction and the lowest exergy efficiency are the combustion chamber, and PTC, respectively. ST is the component with the highest exergy destruction and the lowest exergy efficiency in the ISCC system with ST. With the increase in direct normal irradiance (DNI), the total output power, solar energy output power, and photoelectric efficiency of the ISCC system with PTC increase, while the system efficiency decreases; the solar energy output power and photoelectric efficiency of the ISCC system with ST increase, while the total output power and system efficiency decrease. The photoelectric efficiency of the ISCC system with PTC is greater when the DNI is greater than 600 W/m²; conversely, the photoelectric efficiency of the ISCC system with ST is greater. After sensitivity analysis, the optimal intercooler pressure for the ISCC system is 11.3 MPa. Full article

(This article belongs to the Topic Energy Saving and Energy Efficiency Technologies)

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25 pages, 10294 KiB

Open AccessArticle

Role of Altitude in Influencing the Spray Combustion Characteristics of a Heavy-Duty Diesel Engine in a Constant Volume Combustion Chamber. Part I: Free Diesel Jet

by Chengguan Wang, Xiaozhi Qi, Tao Wang, Diming Lou, Piqiang Tan, Zhiyuan Hu, Liang Fang and Rong Yang

Energies 2023, 16(12), 4832; https://doi.org/10.3390/en16124832 - 20 Jun 2023

Cited by 1 | Viewed by 948

Abstract

Heavy-duty diesel engines operating in plateau regions experience deteriorated combustion. However, the lack of up-to-date information on the spray-combustion process limits the fundamental understanding of the role of altitude. In this work, the in-cylinder thermodynamic conditions of a real diesel engine operating under [...] Read more.

Heavy-duty diesel engines operating in plateau regions experience deteriorated combustion. However, the lack of up-to-date information on the spray-combustion process limits the fundamental understanding of the role of altitude. In this work, the in-cylinder thermodynamic conditions of a real diesel engine operating under different altitudes were reproduced in a constant-volume combustion chamber (CVCC). The liquid spray, ignition, and combustion processes were visualized in detail using different optical diagnostics. Apart from predictable results, some interesting new findings were obtained to improve the understanding of free spray-combustion processes with different altitudes. The spatial distributions of ignition kernels provided direct evidence of higher peak pressure rise rates for high-altitude diesel engines. The percent of stoichiometric air was calculated to confirm that the net effect of altitude was an increase in the amount of air-entrained upstream of the lifted flame; therefore, the soot levels deduced from flame images were inconsistent with those from real engines, revealing that accelerating the soot oxidation process could effectively reduce engine soot emissions in plateau regions. Finally, a novel schematic diagram of the spray flame structure was proposed to phenomenologically describe the role of altitude in influencing the spray-combustion process of a free jet. Full article

(This article belongs to the Special Issue Experimental Investigation, Modeling and Optimization of Modern Internal Combustion Engines toward Their Sustainable Application in Future Road Mobility)

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28 pages, 5335 KiB

Open AccessArticle

The Effects of Vaporisation Models on the FCC Riser Reactor

by Thabang W. Selalame, Raj Patel, Iqbal Mohammed Mujtaba and Yakubu Mandafiya John

Energies 2023, 16(12), 4831; https://doi.org/10.3390/en16124831 - 20 Jun 2023

Cited by 1 | Viewed by 782

Abstract

This work presents a steady-state one-dimensional model of the FCC riser considering the vaporisation of the gas oil feed and subsequent cracking reactions. The evaporation of droplets is studied using three models: the classical homogeneous model and the heterogeneous vaporisation models from the [...] Read more.

This work presents a steady-state one-dimensional model of the FCC riser considering the vaporisation of the gas oil feed and subsequent cracking reactions. The evaporation of droplets is studied using three models: the classical homogeneous model and the heterogeneous vaporisation models from the literature. Droplets are modelled using the Lagrangian framework model for particles moving through a fluid. This was coupled with the gas–solid flow field describing the catalyst particulate transport in the riser. Cracking reaction kinetics are modelled using a four-lumped model. The model was then validated against published plant data. The model performed well in terms of gas oil conversion, gasoline yield, pressure drop, and phase temperature profiles. Therefore, it is suitable for use in the design and optimisation of new and existing FCC unit risers, particularly in cost–benefit analysis considering the current push away from petroleum energy sources. It was found that vaporisation models are largely insignificant in terms of gas oil conversion profiles and gasoline yield for usual operation conditions of FCC risers, which is a finding that had yet to be proven in the literature. Vaporisation models are shown to only affect conversion and yield when the initial droplet exceeds

2000 μ m

. Full article

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

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25 pages, 6267 KiB

Open AccessArticle

Distributed Intelligence in Autonomous PEM Fuel Cell Control

by Abel Rubio, Wilton Agila, Leandro González and Jonathan Aviles-Cedeno

Energies 2023, 16(12), 4830; https://doi.org/10.3390/en16124830 - 20 Jun 2023

Cited by 3 | Viewed by 1347

Abstract

A combination of perceptive and deliberative processes is necessary to ensure the efficient and autonomous control of proton exchange membrane fuel cells (PEMFCs) under optimal humidification conditions. These processes enable monitoring and control tasks across various application scenarios and operating conditions. Consequently, it [...] Read more.

A combination of perceptive and deliberative processes is necessary to ensure the efficient and autonomous control of proton exchange membrane fuel cells (PEMFCs) under optimal humidification conditions. These processes enable monitoring and control tasks across various application scenarios and operating conditions. Consequently, it becomes crucial to adjust parameter values corresponding to different states of the PEMFC during its operation. In this context, this work presents the design and development of an architecture for the control and management of a PEMFC with a maximum power output of 500 [W] based on intelligent agents operating under optimal conditions (membrane humidification). The proposed architecture integrates perception and action algorithms that leverage sensory and contextual information using heuristic algorithms. It adopts a hierarchical structure with distinct layers, each featuring varying time windows and levels of abstraction. Notably, this architecture demonstrates its effectiveness in achieving the desired energy efficiency objective, as evidenced by successful validation tests conducted with different electrical power values delivered by the fuel cell, encompassing three distinct operating states (dry, normal, and flooded). An exemplary application of this scheme is the dynamic control of the humidification of the polymeric membrane, which further highlights the capabilities of this architecture. Full article

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

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23 pages, 4348 KiB

Open AccessEditor’s ChoiceReview

Enhancing the Levelized Cost of Hydrogen with the Usage of the Byproduct Oxygen in a Wastewater Treatment Plant

by Franziska Hönig, Ganesh Deepak Rupakula, Diana Duque-Gonzalez, Matthias Ebert and Ulrich Blum

Energies 2023, 16(12), 4829; https://doi.org/10.3390/en16124829 - 20 Jun 2023

Cited by 2 | Viewed by 1837

Abstract

In order to harmonizFranziska Hönige the supply and demand of green energy, new future-proof technologies are needed. Here, hydrogen plays a key role. Within the current framework conditions, the production of green hydrogen is not yet economically viable. The use of the oxygen [...] Read more.

In order to harmonizFranziska Hönige the supply and demand of green energy, new future-proof technologies are needed. Here, hydrogen plays a key role. Within the current framework conditions, the production of green hydrogen is not yet economically viable. The use of the oxygen produced and the possible increase in efficiency associated with it mostly remain unconsidered. The aim is to demonstrate that the economic efficiency of a power-to-gas (PtG) project can be increased by using the byproduct oxygen. In this research project, a water electrolyzer connected to grid is powered to supply hydrogen to a hydrogen refueling station. By utilizing the byproduct oxygen from water electrolysis for a wastewater treatment plant (WWTP), it is shown that the net present value (NPV) of the project can be improved by up to 13% compared to the initial scenario. If a photovoltaic (PV) system is used in addition to grid electricity for higher green hydrogen production, the NPV can be further improved by up to 58%. The levelized cost of hydrogen (LCOH) is calculated for different scenarios with and without oxygen configuration. A sensitivity analysis is then performed to find important parameters. Full article

(This article belongs to the Special Issue Hydrogen in the Energy Transition: From Production to End-Use)

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21 pages, 3961 KiB

Open AccessArticle

Audit-Based Energy Performance Analysis of Multifamily Buildings in South-East Poland

by Piotr Michalak, Krzysztof Szczotka and Jakub Szymiczek

Energies 2023, 16(12), 4828; https://doi.org/10.3390/en16124828 - 20 Jun 2023

Cited by 4 | Viewed by 925

Abstract

Multifamily buildings account for about half of all residential buildings in Poland and about 70% of the urban population live in them. Most of them require thermal refurbishment. Evaluation of a building’s energy performance with the use of correlation models has been very [...] Read more.

Multifamily buildings account for about half of all residential buildings in Poland and about 70% of the urban population live in them. Most of them require thermal refurbishment. Evaluation of a building’s energy performance with the use of correlation models has been very rarely used in relation to buildings in Poland. This method is simple, fast and can improve the decision process on thermal modernisation. It is especially important at the pre-design stage of planned investments. This paper presents an attempt to develop correlations that could be used in the energy assessment of multifamily buildings. For this purpose a dataset containing of 29 audits of multifamily buildings was used. The statistical analysis was performed for buildings before and after planned refurbishment. Obtained relationships showed strong correlation between thermal demand for space heating or domestic hot water and ventilation airflow and thermal transmittance of windows (R² > 0.6). After designed modernisation the number of strong correlations decreased. Energy for domestic hot water was correlated with the number of inhabitants (R² = 0.6). Energy for space heating was correlated with the number of users and heated volume of a building. Full article

(This article belongs to the Collection Energy Efficiency and Environmental Issues)

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21 pages, 10128 KiB

Open AccessArticle

Multiparameter Regression of a Photovoltaic System by Applying Hybrid Methods with Variable Selection and Stacking Ensembles under Extreme Conditions of Altitudes Higher than 3800 Meters above Sea Level

by Jose Cruz, Christian Romero, Oscar Vera, Saul Huaquipaco, Norman Beltran and Wilson Mamani

Energies 2023, 16(12), 4827; https://doi.org/10.3390/en16124827 - 20 Jun 2023

Cited by 1 | Viewed by 908

Abstract

The production of solar energy at altitudes higher than 3800 m above sea level is not constant because the relevant factors are highly varied and complex due to extreme solar radiation, climatic variations, and hostile environments. Therefore, it is necessary to create efficient [...] Read more.

The production of solar energy at altitudes higher than 3800 m above sea level is not constant because the relevant factors are highly varied and complex due to extreme solar radiation, climatic variations, and hostile environments. Therefore, it is necessary to create efficient prediction models to forecast solar production even before implementing photovoltaic systems. In this study, stacking techniques using ElasticNet and XGBoost were applied in order to develop regression models that could collect a maximum number of features, using the LASSO, Ridge, ElasticNet, and Bayesian models as a base. A sequential feature selector (SFS) was used to reduce the computational cost and optimize the algorithm. The models were implemented with data from a string photovoltaic (PV) system in Puno, Peru, during April and August 2021, using 15 atmospheric and photovoltaic system variables in accordance with the European standard IEC 61724-20170. The results indicate that ElasticNet reduced the MAE by 30.15% compared to the base model, and that the XGBoost error was reduced by 30.16% using hyperparameter optimization through modified random forest research. It is concluded that the proposed models reduce the error of the prediction system, especially the stacking model using XGBoost with hyperparameter optimization. Full article

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

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14 pages, 3066 KiB

Open AccessArticle

Anti-Condensation Temperature Control Strategy of the Concrete Radiant Roof

by Bobo Zhang, Qin Sun, Lin Su, Kaijun Dong, Weimin Luo, Haifeng Guan, Zhenhua Shao and Wei Wu

Energies 2023, 16(12), 4826; https://doi.org/10.3390/en16124826 - 20 Jun 2023

Viewed by 874

Abstract

Radiation cooling, as a new terminal mode that has been gradually emerging in recent years, has attracted more and more attention. However, the problem of condensation has become a vital bottleneck restricting the broad application of radiation-cooling technology. This paper used the numerical [...] Read more.

Radiation cooling, as a new terminal mode that has been gradually emerging in recent years, has attracted more and more attention. However, the problem of condensation has become a vital bottleneck restricting the broad application of radiation-cooling technology. This paper used the numerical simulation method of Ansys Fluent to study the effect of different water supply parameters on the concrete radiant roof’s heat transfer performance, temperature uniformity analysis, and anti-condensation temperature control strategy. The accuracy of the simulation model was verified by comparing the numerical simulation values and measured values of temperature monitoring points. In thermal performance research, the inlet temperature significantly impacted the cooling capacity and radiant surface temperature compared with the inlet flow velocity. In the uniformity study, the distance between the serpentine pipes area and the concrete edge was easily neglected, which was also an important factor affecting the distribution of temperature uniformity. Regarding anti-condensation and performance improvement research, first supplying water at low temperatures and then dynamically adjusting high-temperature water could effectively avoid condensation and improve the radiant roof’s heat transfer performance. The research results could provide technical references for the practical application of radiation roof anti-condensation temperature control technology. Full article

(This article belongs to the Special Issue Research on Energy, Environment, and Sustainable Development)

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15 pages, 29515 KiB

Open AccessArticle

Low-Voltage LDO Regulator Based on Native MOS Transistor with Improved PSR and Fast Response

by Grzegorz Blakiewicz

Energies 2023, 16(12), 4825; https://doi.org/10.3390/en16124825 - 20 Jun 2023

Viewed by 1311

Abstract

In this paper, a low-voltage low-dropout analog regulator (ALDO) based on a native n-channel MOS transistor is proposed. Application of the native transistor with the threshold voltage close to zero allows elimination of the charge pump in low-voltage regulators using the pass element [...] Read more.

In this paper, a low-voltage low-dropout analog regulator (ALDO) based on a native n-channel MOS transistor is proposed. Application of the native transistor with the threshold voltage close to zero allows elimination of the charge pump in low-voltage regulators using the pass element in a common drain configuration. Such a native pass transistor configuration allows simplification of regulator design and improved performance, with supply voltages below 1 V, compared to commonly used regulators with p-channel MOS transistors. In the presented design of ALDO regulator in 180 nm CMOS X-FAB technology, an output voltage of 0.7 V was achieved with an output current of 10 mA and a supply voltage of 0.8 V. Simulation results show that despite the low supply voltage, output voltage spikes do not exceed 70 mV at the worst technology corner when output current transients from 100 µA to 10 mA. Under such conditions, stable operation and power supply rejection PSR = 35 dB were achieved with an output capacitance of 0–500 pF. The proposed regulator allows to push the limit of ALDO regulator applications to voltages below 1 V with only slight degradation of its performance. Full article

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

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29 pages, 552 KiB

Open AccessSystematic Review

Oil Sector and Sentiment Analysis—A Review

by Marcus Vinicius Santos, Fernando Morgado-Dias and Thiago C. Silva

Energies 2023, 16(12), 4824; https://doi.org/10.3390/en16124824 - 20 Jun 2023

Cited by 1 | Viewed by 1693

Abstract

Oil markets reveal considerably volatile behaviour due to a range of factors. Exogenous factors, such as the COVID-19 pandemic and ongoing wars and conflicts, impose even more difficulties for prediction purposes. As a tool to better understand and improve forecasting models, many researchers [...] Read more.

Oil markets reveal considerably volatile behaviour due to a range of factors. Exogenous factors, such as the COVID-19 pandemic and ongoing wars and conflicts, impose even more difficulties for prediction purposes. As a tool to better understand and improve forecasting models, many researchers are using sentiment analysis techniques to identify the sentiments being emanated in the news and on social media. Following the PRISMA standards, this work systematically reviewed 34 studies out of 320 from the Scopus and Web of Science databases. The results indicate that one can use several different sources to construct a text dataset and develop a sentiment analysis. For instance, Reuters, Oilprice.com, and Twitter are among the more popular ones. Among the approaches used for extracting public sentiment, it became apparent that machine learning-based methods have been increasing in prevalence in recent years, both when applied alone and in conjunction with lexicon-based methods. Finally, regarding the purpose of employing sentiment analysis, the most favourable goal for collecting sentiments concerning the oil market is to forecast oil prices. There is a consensus among the authors that sentiment analysis improves the quality of predictive models, making them more accurate. This work aims to assist academics, researchers, and investors interested in the oil sector. Full article

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

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14 pages, 2654 KiB

Open AccessArticle

Ab Initio Modeling of CuGa_1−xIn_xS₂, CuGaS_2(1−x)Se_2x and Ag_1−xCu_xGaS₂ Chalcopyrite Solid Solutions for Photovoltaic Applications

by Jurij Grechenkov, Aleksejs Gopejenko, Dmitry Bocharov, Inta Isakoviča, Anatoli I. Popov, Mikhail G. Brik and Sergei Piskunov

Energies 2023, 16(12), 4823; https://doi.org/10.3390/en16124823 - 20 Jun 2023

Cited by 2 | Viewed by 1089

Abstract

Chalcopyrites are ternary semiconductor compounds with successful applications in photovoltaics. Certain chalcopyrites are well researched, yet others remain understudied despite showing promise. In this study, we use ab initio methods to study CuGaS₂, AgGaS₂, and CuGaSe₂ chalcopyrites with [...] Read more.

Chalcopyrites are ternary semiconductor compounds with successful applications in photovoltaics. Certain chalcopyrites are well researched, yet others remain understudied despite showing promise. In this study, we use ab initio methods to study CuGaS₂, AgGaS₂, and CuGaSe₂ chalcopyrites with a focus on their less studied solid solutions. We use density functional theory (DFT) to study the effects that atomic configurations have on the properties of a solid solution and we calculate the optical absorption spectra using a many-body perturbation theory. Our theoretical simulations predict that excess of In and Se in the solid solutions leads to narrowing of the band gap and to the broadening of the absorption spectra. Obtained results show promise for possible photovoltaic applications, as well as developed methodology can be used for further study of other promising chalcopyritic compounds. Full article

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

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19 pages, 425 KiB

Open AccessArticle

Modernization Roadmaps for Existing Buildings under Limited Energy Resources and Craftwork Capacities

by Jan Richarz, Nico Fuchs, Dominik Hering and Dirk Müller

Energies 2023, 16(12), 4822; https://doi.org/10.3390/en16124822 - 20 Jun 2023

Cited by 1 | Viewed by 1180

Abstract

Great potential for saving carbon emissions lies in modernizing European buildings. Multi-year modernization roadmaps can plan modernization measures in terms of time and are able to consider temporal interactions. Therefore, we have developed a mixed-integer program that determines modernization roadmaps. These roadmaps include [...] Read more.

Great potential for saving carbon emissions lies in modernizing European buildings. Multi-year modernization roadmaps can plan modernization measures in terms of time and are able to consider temporal interactions. Therefore, we have developed a mixed-integer program that determines modernization roadmaps. These roadmaps include changing the energy supply system, improving the envelope, and considering annually varying boundary conditions. High craftwork capacities are required to implement the necessary modernizations to meet climate goals. Unfortunately, studies showed that the current shortage of craftworkers will intensify in the next years. Other important limitations correspond to energy resources. Recent crises show that many energy systems need to handle these limitations. Therefore, we extended the mixed-integer program by a method to handle these limitations inside the roadmaps. By the use of data from 90 interviews with craftwork specialists about the time needed to realize modernization measures, the method is applied. The main purpose is to analyze how modernization strategies change under limited resources, especially in terms of craftwork capacities. Hence, the method is exemplified by a representative single-family dwelling. Within this use case, modernization roadmaps with different craftwork capacity levels were calculated. The results show that modernization roadmaps change comprehensively over these levels. Key findings are that costs and emissions rise with decreasing craftwork capacities. Furthermore, smaller storages and pv systems are implemented at low craftwork capacities. The electrification of the heat supply supported by medium insulation standards should also be implemented with limited craftwork capacities. Full article

(This article belongs to the Special Issue Energy Efficiency through Building Simulation)

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13 pages, 2901 KiB

Open AccessArticle

Linking Cost Decline and Demand Surge in the Hydrogen Market: A Case Study in China

by Danlu Xu, Zhoubin Liu, Jiahui Zhu, Qin Fang and Rui Shan

Energies 2023, 16(12), 4821; https://doi.org/10.3390/en16124821 - 20 Jun 2023

Viewed by 975

Abstract

Hydrogen is crucial in achieving global energy transition and carbon neutrality goals. Existing market estimates typically presume linear or exponential growth but fail to consider how market demand responds to the declining cost of underlying technologies. To address this, this study utilizes a [...] Read more.

Hydrogen is crucial in achieving global energy transition and carbon neutrality goals. Existing market estimates typically presume linear or exponential growth but fail to consider how market demand responds to the declining cost of underlying technologies. To address this, this study utilizes a learning curve model to project the cost of electrolyzers and its subsequent impact on hydrogen market, aligning with a premise that the market demand is proportional to the cost of hydrogen. In a case study of China’s hydrogen market, projecting from 2020 to 2060, we observed substantial differences in market evolution compared to exponential growth scenarios. Contrary to exponential growth scenarios, China’s hydrogen market experiences faster growth during the 2020–2040 period rather than later. Such differences underscore the necessity for proactive strategic planning in emerging technology markets, particularly for those experiencing rapid cost decline, such as hydrogen. The framework can also be extended to other markets by using local data, providing valuable insights to investors, policymakers, and developers engaged in the hydrogen market. Full article

(This article belongs to the Special Issue Prospects and Challenges of Energy Transition)

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18 pages, 1686 KiB

Open AccessArticle

An Adaptive Centralized Protection and Relay Coordination Algorithm for Microgrid

by Regin Bose Kannaian, Belwin Brearley Joseph and Raja Prabu Ramachandran

Energies 2023, 16(12), 4820; https://doi.org/10.3390/en16124820 - 20 Jun 2023

Cited by 1 | Viewed by 1108

Abstract

To meet the increased customer demands, microgrid evolved. The structure of microgrid changes dynamically due to the intermittent nature of renewable-based generation, status of the distributed generator and opening of breakers for fault/maintenance. Hence, the magnitude of fault current is dynamic in nature. [...] Read more.

To meet the increased customer demands, microgrid evolved. The structure of microgrid changes dynamically due to the intermittent nature of renewable-based generation, status of the distributed generator and opening of breakers for fault/maintenance. Hence, the magnitude of fault current is dynamic in nature. In order to deal with these dynamic changes, this paper addresses an adaptive central microgrid controller-based protection and relay coordination scheme, which revises the relay settings dynamically (both radial and looped configuration) for every change in topology. In the proposed algorithm, the primary relay responds to a fault immediately since the individual relays are given with fault level setting. For any abnormality in the network, the fault location is determined both via local relay and microgrid central controller (MCC). Hence, even though the local relay fails to identify the fault due to high fault impedance, the MCC locates the fault accurately and isolates the minimum faulty part. The coordination between relays is carried out by MCC in a time-graded manner based on microgrid central protection and relay coordination algorithm. The proposed algorithm is tested using Matlab in a microgrid built based on the IEEE 33 bus distribution network. Full article

(This article belongs to the Special Issue Optimal Planning, Integration and Control of Smart Microgrid Systems with Renewable Energy)

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17 pages, 2917 KiB

Open AccessArticle

Interpretable Hybrid Experiment Learning-Based Simulation Analysis of Power System Planning under the Spot Market Environment

by Wei Liao, Yi Yang, Qingwei Wang, Ruoyu Wang, Xieli Fu, Yinghua Xie and Junhua Zhao

Energies 2023, 16(12), 4819; https://doi.org/10.3390/en16124819 - 20 Jun 2023

Viewed by 783

Abstract

The electricity spot market plays a significant role in promoting the self-improvement of the overall resource utilization efficiency of the power system and advancing energy conservation and emission reduction. This paper analyzes and compares the potential impacts of spot market operations on system [...] Read more.

The electricity spot market plays a significant role in promoting the self-improvement of the overall resource utilization efficiency of the power system and advancing energy conservation and emission reduction. This paper analyzes and compares the potential impacts of spot market operations on system planning, considering the differences between planning methods in traditional and spot market environments through theoretical analysis and model comparison. Furthermore, we conduct research and analysis on grid planning methods under the spot market environment with the goal of maximizing social benefits. Unlike the pricing approach based on historical price data in traditional market simulation processes, a data-driven approach that combines experimental economics and machine learning is proposed, specifically using mixed empirical learning to simulate unit bidding strategies in market transactions. A simulation model for electricity spot market trading is constructed to analyze the performance of the planning results in the spot market environment. The case study results indicate that the proposed planning methods can enable the grid to operate well in the spot market environment, maintain relatively stable nodal prices, and ensure the integration of a high proportion of clean energy. Full article

(This article belongs to the Special Issue Optimal Planning and Operation in RES-Rich Power Systems under Electricity and Carbon Emission Market Environment)

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21 pages, 2661 KiB

Open AccessArticle

Reducing CO₂ Emissions during the Operation of Unmanned Transport Vessels with Diesel Engines

by Tadeusz Szelangiewicz and Katarzyna Żelazny

Energies 2023, 16(12), 4818; https://doi.org/10.3390/en16124818 - 20 Jun 2023

Cited by 1 | Viewed by 898

Abstract

Environmental protection is one of the most challenging tasks facing mankind. Reducing CO₂ emissions in the global economy, including maritime transport, is being pursued in various ways, one of them being the design work leading to the construction and operation of unmanned [...] Read more.

Environmental protection is one of the most challenging tasks facing mankind. Reducing CO₂ emissions in the global economy, including maritime transport, is being pursued in various ways, one of them being the design work leading to the construction and operation of unmanned ships. Unmanned vessels operating on longer routes will still have internal combustion propulsion. However, they will not have the superstructure and the various systems and equipment necessary for the crew. This will result in an unmanned vessel having less weight, less displacement and, therefore, less size, resistance and propulsion power than a manned vessel for the same transport capacity. Consequently, the unmanned vessel will emit less CO₂. This paper presents a novel method for predicting fuel consumption and CO₂ emissions for unmanned container ships. The method uses regression relationships of geometric and operational parameters for manned container ships developed for this purpose to determine such relationships for unmanned ships. On this basis, it is shown what the level of CO₂ reduction will be compared to manned container ships. Full article

(This article belongs to the Special Issue Innovative Research and Application of Alternative Fuels in the Propulsion of Transport Means)

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18 pages, 7292 KiB

Open AccessArticle

A Consideration of the Single-Phase Photovoltaic and Energy Storage Joint Regulation of a Three-Phase Unbalanced Control Strategy in a Power Distribution System

by Min Wang, Huilin Wang, Fanglin Zuo, Jie Zou, Yuan Chen and Zixuan Yu

Energies 2023, 16(12), 4817; https://doi.org/10.3390/en16124817 - 20 Jun 2023

Viewed by 661

Abstract

With a large amount of distributed power and energy storage access, the traditional three-phase unbalanced treatment of a power distribution system is mainly aimed at the three-phase unbalance of a load, which cannot effectively address the three-phase unbalance problem of a power distribution [...] Read more.

With a large amount of distributed power and energy storage access, the traditional three-phase unbalanced treatment of a power distribution system is mainly aimed at the three-phase unbalance of a load, which cannot effectively address the three-phase unbalance problem of a power distribution network after a large number of single-phase photovoltaic access. Therefore, this paper proposes a three-phase unbalanced treatment strategy for the distribution network, which considers the joint regulation ability of single-phase photovoltaic and energy storage and the regulation ability of a reactive power compensation device. Firstly, the joint regulation ability of single-phase photovoltaic and energy storage under different photovoltaic permeability is analyzed. Secondly, according to the joint regulation ability of single-phase photovoltaic and energy storage and the regulation ability of reactive power compensation device, the three-phase power optimization model is constructed to minimize the three-phase unbalance degree and regulation cost, and the JAYA optimization algorithm is used to solve the model. Finally, the 33-node distribution system is used to verify the effectiveness of the proposed strategy. Full article

(This article belongs to the Special Issue Advances in Operation, Optimization and Control of Modern Distribution Network)

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10 pages, 2908 KiB

Open AccessArticle

Facile Synthesis of Sea-Urchin-like VN as High-Performance Anode for Lithium-Ion Batteries

by Zhaowei Hu, Weifeng Huang, Huifang Li, Yizhou Zhang, Peng Wang, Xiaojun Wang and Zhiming Liu

Energies 2023, 16(12), 4816; https://doi.org/10.3390/en16124816 - 20 Jun 2023

Viewed by 810

Abstract

Lithium-ion batteries are still the main theme of the contemporary market. Commercial graphite has struggled to meet the demand of high energy density for various electronic products due to its low theoretical capacity. Therefore, exploring for a new anode with high capacity is [...] Read more.

Lithium-ion batteries are still the main theme of the contemporary market. Commercial graphite has struggled to meet the demand of high energy density for various electronic products due to its low theoretical capacity. Therefore, exploring for a new anode with high capacity is important. Vanadium nitride has attracted widespread attention due to its high theoretical specific capacity and good chemical/thermal stability. However, vanadium nitride is accompanied by huge volume expansion and nanoparticle agglomeration during the electrochemical reaction, which limits its application. Herein, sea-urchin-like vanadium nitride (SUK-VN) was successfully prepared with a simple hydrothermal method combined with an annealing strategy to boost the actual capacity of the vanadium nitride. The special sea-urchin-like morphology effectively suppresses the agglomeration of vanadium nitride nanoparticles and exposes more reactive sites, which facilitates the electrochemical performance of electrode materials. In the half-cells, sea-urchin-like vanadium nitride exhibits a specific capacity of 361.5 mAh g⁻¹ at 0.1 A g⁻¹ after 60 cycles, and even still achieves a specific capacity of 164.5 with a Coulomb efficiency of approximately 99.9% at 1 A g⁻¹ after 500 cycles. Such a strategy provides the potential to enhance the electrochemical properties of vanadium nitride anodes in terms of solving the nanoparticle agglomeration. Full article

(This article belongs to the Special Issue Nanomaterials for Advanced Energy Storage and Conversion)

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12 pages, 3751 KiB

Open AccessArticle

Fresnel Lens Solar-Pumped Laser with Four Rods and Beam Merging Technique for Uniform and Stable Emission under Tracking Error Influence

by Bruno D. Tibúrcio, Dawei Liang, Joana Almeida, Dário Garcia, Miguel Catela, Hugo Costa and Cláudia R. Vistas

Energies 2023, 16(12), 4815; https://doi.org/10.3390/en16124815 - 20 Jun 2023

Viewed by 802

Abstract

Significant numerical improvements in Fresnel lens Nd:YAG solar laser collection efficiency, laser quality factors and tracking error compensation capacity by two Fresnel lenses as primary solar concentrators are reported here. A Nd:YAG four-rod side-pumping configuration was investigated. The four-rod side-pumping scheme consisted of [...] Read more.

Significant numerical improvements in Fresnel lens Nd:YAG solar laser collection efficiency, laser quality factors and tracking error compensation capacity by two Fresnel lenses as primary solar concentrators are reported here. A Nd:YAG four-rod side-pumping configuration was investigated. The four-rod side-pumping scheme consisted of two large aspherical lenses and four semi-cylindrical pump cavities, where the Nd:YAG laser rods were placed, enabling an efficient solar pumping of the laser crystals. A 104.4 W continuous-wave multimode solar laser power was achieved, corresponding to 29.7 W/m² collection efficiency, which is 1.68 times that of the most efficient experimental Nd:YAG side-pumped solar laser scheme with heliostat–parabolic mirror systems. End-side-pumped configuration has led to the most efficient multimode solar lasers, but it may cause more prejudicial thermal effects, poor beam quality factors and a lack of access to both rod end-faces to optimize the resonant cavity parameters. In the present work, an eight-folding-mirror laser beam merging technique was applied, aiming to attain one laser emission from the four laser rods that consist of the four-rod side-pumping scheme with a higher brightness figure of merit. A 79.8 W multimode laser output power was achieved with this arrangement, corresponding to 22.7 W/m². The brightness figure of merit was 0.14 W, being 1.6, 21.9 and 15.7 times that of previous experimental Nd:YAG solar lasers pumped by Fresnel lenses. A significant advance in tracking error tolerance was also numerically attained, leading to a 1.5 times enhancement in tracking error width at 10% laser power loss (TEW_10%) compared to previous experimental results. Full article

(This article belongs to the Special Issue Advances in Photovoltaic/Solar Collectors and Their Potential for an Industrial Decarbonization)

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32 pages, 19417 KiB

Open AccessArticle

Research on Low-Frequency Stability under Emergency Power Supply Scheme of Photovoltaic and Battery Access Railway Traction Power Supply System

by Ying Wang, Yueyang Xin, Ziyun Xie, Xiuqing Mu and Xiaoqiang Chen

Energies 2023, 16(12), 4814; https://doi.org/10.3390/en16124814 - 20 Jun 2023

Cited by 2 | Viewed by 1445

Abstract

Photovoltaics and batteries can be connected to a traction power supply system through a railway power conditioner (RPC) to switch between different control strategies. This can address power quality issues or provide emergency traction for locomotives that unexpectedly lose power and even break [...] Read more.

Photovoltaics and batteries can be connected to a traction power supply system through a railway power conditioner (RPC) to switch between different control strategies. This can address power quality issues or provide emergency traction for locomotives that unexpectedly lose power and even break through traditional energy barriers in the railway field, achieving a low-carbon power supply for railway energy, and a mutual backup with substations. However, methods to coordinate the control strategies of PV and the battery locomotive traction have not been clearly revealed, nor has the actual stability of the system. In this study, to address the above issues, an emergency power supply scheme is proposed for the first time that utilizes a dual-mode RPC inverter combined with a coordinated control strategy for the PV and battery, achieving the traction of locomotives. In addition, a one-dimensional impedance model was established for the PV system, battery system, locomotive (CRH3), and RPC projected onto the dq coordinate system, and the critical amplitude margin (CAM) was defined to quantitatively analyze the sensitivity and laws of different parameters concerning the low-frequency stability of the system. At the same time, impedance ratios and passive criteria were used to reveal the stability mechanism, and parameter adjustment criteria and design suggestions were put forward. Finally, the feasibility of the emergency power supply scheme of the “PV–battery locomotive network” coupling system and the correctness of the low-frequency stability study were verified using the Starsim semi-physical experiment platform. Full article

(This article belongs to the Topic Advances in Renewable Energy and Energy Storage)

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13 pages, 1101 KiB

Open AccessReview

A Review of Groundwater Heat Pump Systems in the Italian Framework: Technological Potential and Environmental Limits

by Martina Gizzi, Federico Vagnon, Glenda Taddia and Stefano Lo Russo

Energies 2023, 16(12), 4813; https://doi.org/10.3390/en16124813 - 20 Jun 2023

Cited by 1 | Viewed by 1125

Abstract

For new buildings in densely urbanised cities, groundwater heat pump systems (GWHPs) represent a concrete, effective solution for decarbonising existing energy systems. Environmental factors must be considered to limit the GWHP system’s impact on the subsurface. Particular attention must be given to the [...] Read more.

For new buildings in densely urbanised cities, groundwater heat pump systems (GWHPs) represent a concrete, effective solution for decarbonising existing energy systems. Environmental factors must be considered to limit the GWHP system’s impact on the subsurface. Particular attention must be given to the long-term sustainability of groundwater abstraction modalities and the development of a thermally affected zone around re-injection wells. Simplified solutions and numerical models have been applied to predict subsurface heat transport mechanisms; these simulations allow researchers to consider site-specific geological conditions, transient heat and groundwater flow regimes, and anisotropies in the subsurface media. This paper presents a comprehensive overview of the current research on GWHPs and discusses the benefits and limitations of their diffusion in Italy. The sources used provide information on and examples of the correct methodological approaches for depicting the induced variations while avoiding the overestimation or underestimation of the impact that GWHPs have on exploited aquifers. Full article

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

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14 pages, 2132 KiB

Open AccessArticle

Research on Displacement Efficiency by Injecting CO₂ in Shale Reservoirs Based on a Genetic Neural Network Model

by Shunli Qin, Juhua Li, Jingyou Chen, Xueli Bi and Hui Xiang

Energies 2023, 16(12), 4812; https://doi.org/10.3390/en16124812 - 20 Jun 2023

Cited by 1 | Viewed by 919

Abstract

Carbon dioxide injection can help solve two issues in shale reservoir production. Firstly, it can reduce carbon emissions while, secondly, improving unconventional reservoir recovery. There are many controlling factors for CO₂ injection to enhance oil recovery in shale reservoirs, and the effect [...] Read more.

Carbon dioxide injection can help solve two issues in shale reservoir production. Firstly, it can reduce carbon emissions while, secondly, improving unconventional reservoir recovery. There are many controlling factors for CO₂ injection to enhance oil recovery in shale reservoirs, and the effect of field implementation varies greatly. The key to popularizing this extraction technology is determining the main controlling factors of CO₂ displacement efficiency. Using CO₂ shale displacement laboratory results, the grey correlation analysis method was used to determine the main controlling factors affecting core oil displacement efficiency, such as shale reservoir physical parameters (rock compressibility, porosity, median pore size, matrix permeability, TOC, and oil saturation) and engineering parameters (soaking time and injection pressure). The genetic algorithm (GA) was introduced to optimize the backpropagation (BP) neural network to construct the prediction model of the CO₂ indoor displacement experiments in shale cores. The results showed that the injection pressure among the engineering parameters, the CO₂ soaking time among the gas injection parameters, and the porosity among the shale physical parameters were the main controlling factors affecting the oil displacement efficiency. The prediction accuracy of the genetic neural network model improved, and the coefficient of determination (R²) reached 0.983. Compared with the conventional neural network model, the mean absolute error (MAE) was reduced by 30%, the root mean square error (RMSE) was reduced by 46%, and the R² increased by 11%. Optimizing the learning and training of the prediction model significantly reduces the cost of laboratory experiments. The deep-learning model completed by training can intuitively show the degree of influence of input parameters on output parameters, providing a theoretical basis for the study of CO₂ displacement mechanisms in shale reservoirs. Full article

(This article belongs to the Special Issue Advances in Unconventional Oil and Gas Accumulation, Reservoir Evaluation and Seepage Mechanism)

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21 pages, 4936 KiB

Open AccessArticle

A Two-Step Site Selection Concept for Underground Pumped Hydroelectric Energy Storage and Potential Estimation of Coal Mines in Henan Province

by Qianjun Chen, Zhengmeng Hou, Xuning Wu, Shengyou Zhang, Wei Sun, Yanli Fang, Lin Wu, Liangchao Huang and Tian Zhang

Energies 2023, 16(12), 4811; https://doi.org/10.3390/en16124811 - 20 Jun 2023

Cited by 1 | Viewed by 1168

Abstract

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical [...] Read more.

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical to the planning and implementation of UPHES in old coal mines. This paper introduces a two-step site selection concept, including a screening assessment followed by a comprehensive assessment, to determine suitable locations for UPHES. The screening indicators in the screening assessment comprise geological features, mine water disasters, and minimum installed capacity, while the analytic hierarchy process (AHP) is applied in the comprehensive assessment. Additionally, coal mines in Henan Province are preliminarily screened through the screening assessment and the potential for UPHES is thoroughly investigated. The estimated volume of the drifts and shafts in old coal mines is approximately 1.35

\times

10⁷ m³, while in producing coal mines, it is around 2.96

\times

10⁷ m³. Furthermore, the corresponding annual potential for UPHES is 1468.9 GWh and 3226.3 GWh, respectively. By consuming surplus wind and solar power, UPHES is able to reduce 4.68

\times

10⁵ tonnes of carbon dioxide (CO₂) emissions. The study provides preliminary guidance for policy-makers in developing UPHES in old coal mines. Full article

(This article belongs to the Topic Carbon-Energy-Water Nexus in Global Energy Transition)

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13 pages, 4811 KiB

Open AccessArticle

Impact on Distribution Transformer Life Using Electric Vehicles with Long-Range Battery Capacity

by Amanda M. P. Barros, Jorge H. Angelim and Carolina M. Affonso

Energies 2023, 16(12), 4810; https://doi.org/10.3390/en16124810 - 20 Jun 2023

Viewed by 1722

Abstract

This paper presents a comparative analysis of the effects of short-range and long-range electric vehicles charging on transformer life. Long-range vehicles are expected to become more common in the future. They have higher battery capacity and charge at higher power levels, modifying demand [...] Read more.

This paper presents a comparative analysis of the effects of short-range and long-range electric vehicles charging on transformer life. Long-range vehicles are expected to become more common in the future. They have higher battery capacity and charge at higher power levels, modifying demand profile. A probabilistic analysis is performed using the Monte Carlo Simulation, evaluating the transformer hottest-spot temperature and the aging acceleration factor. Residential demand is modeled based on real electricity measurements, and EVs’ demand is modeled based on real data collected from a trial project developed in the United Kingdom. Simulations are conducted considering the influence of ambient temperature analyzing summer and winter seasons and several EV penetration levels. Results show the impacts caused by long-range vehicles are more severe because they charge at higher power levels, especially during winter, when residential demand is higher. For penetration level of 50% during summer, the use of long-range EVs brings a minimum equivalent aging factor of 5.2, which means the transformer aged 124.8 h in a cycle of only 24 h, decreasing its lifetime. Full article

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

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11 pages, 1120 KiB

Open AccessArticle

Protein Extraction, Precipitation, and Recovery from Chlorella sorokiniana Using Mechanochemical Methods

by Ashley Cutshaw, Henry Frost, Sibel Uludag-Demirer, Yan Liu and Wei Liao

Energies 2023, 16(12), 4809; https://doi.org/10.3390/en16124809 - 20 Jun 2023

Cited by 2 | Viewed by 1782

Abstract

Protein extraction, precipitation, and recovery methods were evaluated by this study using a green alga—Chlorella sorokiniana. A mechanochemical cell disruption process was applied to facilitate protein extraction from microalgal biomass. Optimization of the mechanochemical process resulted in milling conditions that achieved [...] Read more.

Protein extraction, precipitation, and recovery methods were evaluated by this study using a green alga—Chlorella sorokiniana. A mechanochemical cell disruption process was applied to facilitate protein extraction from microalgal biomass. Optimization of the mechanochemical process resulted in milling conditions that achieved a protein extraction of 52.7 ± 6.45%. The consequent acid precipitation method was optimized to recover 98.7% of proteins from the microalgal slurry. The measured protein content of the protein isolate was 41.4% w/w. These results indicate that the precipitation method is successful at recovering the extracted proteins in the algal slurry; however, the removal of non-protein solids during centrifugation and pH adjustment is not complete. The energy balance analysis elucidated that the energy demand of the protein extraction and recovery operation, at 0.83 MJ/kg dry algal biomass, is much lower than previous studies using high-pressure homogenization and membrane filtration. This study concludes that mechanochemical protein extraction and recovery is an effective, low-energy processing method, which could be used by algal biorefineries to prepare algal proteins for value-added chemical production as well as to make algal carbohydrates and lipids in the residual biomass more accessible for biofuel production. Full article

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20 pages, 4512 KiB

Open AccessArticle

Cooperative Game Cooperative Control Strategy for Electric Vehicles Based on Tariff Leverage

by Feng Zhou, Weizhen Shi, Xiaomei Li, Chao Yang and Ting Hao

Energies 2023, 16(12), 4808; https://doi.org/10.3390/en16124808 - 20 Jun 2023

Viewed by 732

Abstract

To address the negative impact of large-scale disorderly grid connection of EVs on the stable operation of the power grid, a cooperative game cooperative control strategy for EVs based on tariff leverage is proposed, taking the grid-side and user-side economy as the objective [...] Read more.

To address the negative impact of large-scale disorderly grid connection of EVs on the stable operation of the power grid, a cooperative game cooperative control strategy for EVs based on tariff leverage is proposed, taking the grid-side and user-side economy as the objective function, taking into account the EV load state constraint, distribution grid power constraint, bi-directional charging and discharging pile power constraint, dynamic tariff constraint, and cooperative game members’ revenue constraint. A dynamic cooperative game model based on bi-directional charging and discharging piles is established, and the weight of users in the game is increased. Based on the cooperative game model, an optimal real-time tariff is determined for both the electric power operators and the charging and discharging pile users and based on the real-time updated dynamic tariff and the EV power connected to the charging and discharging pile at the current moment, a genetic algorithm is used to solve the simulation based on the Receding Horizon Control principle. The simulation results show that this control strategy has a smoother load curve and better peak and valley reduction than the fixed tariff and the time-of-use tariff, and it reduces the operating cost of the electric power operators. In addition, it brings the best economic benefits to the users, with the overall revenue of the charging and discharging piles increasing by up to 6.3% under the dynamic tariff. Full article

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

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26 pages, 1292 KiB

Open AccessArticle

The Role of State in Managing the Wind Energy Projects: Risk Assessment and Justification of the Economic Efficiency

by Galina Chebotareva, Inna Čábelková, Wadim Strielkowski, Luboš Smutka, Anna Zielińska-Chmielewska and Stanislaw Bielski

Energies 2023, 16(12), 4807; https://doi.org/10.3390/en16124807 - 19 Jun 2023

Viewed by 995

Abstract

Our paper focuses on assessing the role of state funding in supporting wind energy projects with a focus on economic efficiency and risk assessment. In particular, we analyze the new program aimed at supporting Russian renewable energy (RE) projects envisaged for the period [...] Read more.

Our paper focuses on assessing the role of state funding in supporting wind energy projects with a focus on economic efficiency and risk assessment. In particular, we analyze the new program aimed at supporting Russian renewable energy (RE) projects envisaged for the period from 2024–2035 that involves a reduction in investments in such projects and the introduction of large fines for non-compliance with regulatory requirements for localization and export. These strict rules imposed by the regulatory authorities, as well as the withdrawal by foreign manufacturers of equipment for renewable energy from the domestic energy market, put into doubt the economic feasibility of the participation of sector players in state-supported programs. Our paper assesses the economic justification for the practicality of the Russian energy market to implement renewable energy projects under the influence of negative environmental factors and the reduction of state support programs. We employ a case study of wind energy projects carried out in 2018–2020 as a part of the first sector support program. Our methodology is based on the calculations of the classical indicators of economic efficiency of projects (NPV, IRR, and DPP). Our own approach reveals that these indicators are supplemented by taking into account the cost of specific political, environmental, and economic risks of wind energy projects. Our results reveal that, at the moment, Russian wind energy projects in various scenarios retain a sufficient margin of financial strength and are able to withstand a reduction in the amount of financial support from the state. Our findings allow the formulation of some practical recommendations for reducing the share of governmental support for wind energy projects on the local energy market as a measure of cutting costs and increasing overall economic efficiency. Full article

(This article belongs to the Special Issue Effective and Efficient Management Practices in Energy Sources and Energy Consumption)

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