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Energies, Volume 17, Issue 2 (January-2 2024) – 269 articles

Cover Story (view full-size image): In the quest to harness the advantages of renewable hydrogen electrolysis energy systems, this study uses a deterministic system model to compare future scenarios, including oxygen processing energy demand, against base cases. Byproduct oxygen gas from growing large-scale electrolysis could displace other oxygen production and introduce viable alternative processes that reduce emissions and green hydrogen costs. Wind and solar-PV electricity time-series feed an electrolysis model, and the required gas post-processing energies are calculated within each hourly timestep to maintain a renewable-only input. The model was validated against two base cases and then compared against the oxygen-inclusion scenarios. The work proposes, through demonstration, the inclusion of oxygen in similar models to highlight potential system benefits. View this paper
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24 pages, 5076 KiB  
Article
Investigation of the Performance of Battery Thermal Management Based on Direct Refrigerant Cooling: Simulation, Validation of Results, and Parametric Studies
by Suparat Jamsawang, Saharat Chanthanumataporn, Kittiwoot Sutthivirode and Tongchana Thongtip
Energies 2024, 17(2), 543; https://doi.org/10.3390/en17020543 - 22 Jan 2024
Viewed by 1806
Abstract
This study proposes a simulation technique for investigating a battery thermal management system based on direct refrigerant cooling (BTMS-DRC). The main focus is to investigate the temperature uniformity and working temperature of the module housing. The simulation technique employs a finite element method [...] Read more.
This study proposes a simulation technique for investigating a battery thermal management system based on direct refrigerant cooling (BTMS-DRC). The main focus is to investigate the temperature uniformity and working temperature of the module housing. The simulation technique employs a finite element method for a combined conduction–convection heat transfer to predict the module housing temperature. The refrigerant side is based on two-phase flow evaporation, which is represented by the convection heat transfer under a certain refrigerant saturation temperature. The real BTMS-DRC, which is based on the dual-evaporator vapor compression refrigeration system, is constructed for experimentation with the test bench. The simulated result is validated with the experimental results to ensure correction of the modelling. Error rates of approximately 2.9–7.2% are noted throughout the specified working conditions. The BTMS can produce temperatures of less than 35 °C under conditions where 80–320 W heat is generated. The difference in the temperature of the module is around 1.7–4.2 °C. This study also investigates the impact of heat generation, the convection heat transfer coefficient (href), the refrigerant saturation temperature, and thermal conductivity on the module’s temperature. The thermal conductivity ranges from 25 to 430 W/m·K, while the href ranges from 80 to 400 W/m2·K. Full article
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11 pages, 1317 KiB  
Article
Economical Operation and Hazardous Air Pollutant Emissions of Biodegradable Sludge Combustion Process in Commercial Fluidized Bed Plant
by Ha-Na Jang, Myung Kyu Choi and Hang Seok Choi
Energies 2024, 17(2), 542; https://doi.org/10.3390/en17020542 - 22 Jan 2024
Viewed by 1107
Abstract
Waste sludge is characterized by high moisture, volatile compounds, toxic compounds, and ashes. The efficient operation of a commercial fluidized bed combustion (FBC) plant is important for reducing operational costs. We selected a commercial FBC plant for industrial waste sludge combustion to investigate [...] Read more.
Waste sludge is characterized by high moisture, volatile compounds, toxic compounds, and ashes. The efficient operation of a commercial fluidized bed combustion (FBC) plant is important for reducing operational costs. We selected a commercial FBC plant for industrial waste sludge combustion to investigate the mass balance of the FBC process and the performance of the air pollution control device. Based on fuel analysis, the flow rate of incineration air was calculated as 4567 Nm3/h. After FBC combustion, the flow rate of the incineration gas increased to 8493.8 Nm3/h. Analysis of the heat balance showed that some heat potential was lost through leakage during the combustion process. The temperature of the incineration gas decreased to 200 °C at the inlet of the air pollution control device. According to the hazardous air pollutant emission testing of sampling points, the operation factors of lime slurry injection for SOx and HCl in the semi-dry reactor were 64.20 and 4.81 kg/h, respectively. In the wet scrubber, the operation factors of NaOH for SOx and HCl were 23.88 and 3.14 kg/h, respectively. At these operation factors, the available waste generation in the semi-dry reactor and wet scrubber was optimized to 76.6 and 42.57 kg/h, respectively. Full article
(This article belongs to the Section I2: Energy and Combustion Science)
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14 pages, 3094 KiB  
Article
Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium
by Chiara Magni, Robbe Peeters, Sylvain Quoilin and Alessia Arteconi
Energies 2024, 17(2), 541; https://doi.org/10.3390/en17020541 - 22 Jan 2024
Cited by 1 | Viewed by 1709
Abstract
Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow [...] Read more.
Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow for recovering waste heat sources and upgrading them at temperatures up to 200 °C. Moreover, the coupling of these devices with thermal storage units can unlock the flexibility potential deriving from the industrial sector electrification by means of Demand-Side Management strategies. The aim of this paper is to quantify the impact on the energy system due to the integration of industrial high-temperature heat pumps and thermal storage units by means of a detailed demand–supply model. To do that, the industrial heat demand is investigated through a set of thermal process archetypes. High-temperature heat pumps and thermal storage units for industrial use are included in the open-source unit commitment and optimal dispatch model Dispa-SET used for the representation of the energy system. The case study analyzed is Belgium, and the analysis is performed for different renewable penetration scenarios in 2040 and 2050. The results demonstrate the importance of a proper sizing of the heat pump and thermal storage capacity. Furthermore, it is obtained that the electrification of the thermal demand of industrial processes improves the environmental impact (84% reduction in CO2 emissions), but the positive effect of the energy flexibility provided by the heat pumps is appreciated only in the presence of a very high penetration of renewable energy sources. Full article
(This article belongs to the Section J: Thermal Management)
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16 pages, 6775 KiB  
Article
Independent Control of Active and Reactive Power Flow for a Single-Phase, Unidirectional Onboard Power Converter Connecting the DC Power Bus to the AC Bus
by Tomasz Binkowski and Paweł Szcześniak
Energies 2024, 17(2), 540; https://doi.org/10.3390/en17020540 - 22 Jan 2024
Viewed by 1197
Abstract
The paper presents a proposed system that supplies a 400 Hz single-phase onboard grid from the DC onboard bus. This system enables independent compensation of reactive power in the AC grid. Independent control of active and reactive power flow requires the decomposition of [...] Read more.
The paper presents a proposed system that supplies a 400 Hz single-phase onboard grid from the DC onboard bus. This system enables independent compensation of reactive power in the AC grid. Independent control of active and reactive power flow requires the decomposition of current in the grid into active and reactive components. Independent control of active and reactive power requires the use of synchronizers that operate in the dq frame system. If synchronization is performed with a single-phase grid, the transformation of dq requires the virtual quadrature signals. Standard quadrature signal generation systems use a second-order generalized integrator. To improve the dynamics of the system, the paper proposes a new quadrature generator that operates on the basis of trigonometric calculations instead of a second-order integration system. The developed system was implemented in a proportional-resonant current control system. Tests carried out in steady state and in dynamic states related to typical grid disturbances proved significantly better dynamic properties than those of a standard integrator-based system. Full article
(This article belongs to the Section F3: Power Electronics)
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56 pages, 12342 KiB  
Article
Relative Comparison of Benefits of Floor Slab Insulation Methods, Using Polyiso and Extruded Polystyrene Materials in South Africa, Subject to the New National Building Energy Efficiency Standards
by Emmanuel Kabundu, Sijekula Mbanga, Brink Botha and Emma Ayesu-Koranteng
Energies 2024, 17(2), 539; https://doi.org/10.3390/en17020539 - 22 Jan 2024
Cited by 1 | Viewed by 1272
Abstract
This article aims to assess the benefits of floor slab insulation measures using extruded polystyrene (XPS) and polyisocyanurate (also referred to as polyiso or PIR) insulation materials at various levels of insulation thicknesses for a detached residential building. An EnergyPlus simulation analysis was [...] Read more.
This article aims to assess the benefits of floor slab insulation measures using extruded polystyrene (XPS) and polyisocyanurate (also referred to as polyiso or PIR) insulation materials at various levels of insulation thicknesses for a detached residential building. An EnergyPlus simulation analysis was carried out within the seven energy zones (represented by eight locations) of South Africa in accordance with the South African national code for building energy efficiency (SANS10400-XA). The energy savings and payback periods related to the use of the insulation over a lifecycle period of 50 years were assessed. Cape Town (zone 4) behaved differently from other locations and hardly benefited from the application of floor slab insulation measures. Generally, polyiso (PIR) insulation performed better than XPS for vertical gap insulation, and lower insulation thicknesses required higher insulation depths to maximize energy savings. Similarly, lower insulation thicknesses (25 mm and 50 mm) required higher perimeter insulation widths to maximize energy savings for horizontal perimeter insulation, especially in Sutherland (zone 6) and Cape Town. The maximization of energy savings was also achieved at low insulation thickness for the full floor slab insulation method, except for Sutherland and Fraserburg (zone 7). The locations that benefitted most from the floor slab insulation methods were Pretoria (zone 5), Thohoyandou (zone 3), Sutherland (zone 6), Fraserburg (zone 7), Welkom (zone 1), Ixopo (zone 5H), Witbank (zone 2), and Cape Town (zone 4), in that order. Generally, higher net energy savings are achieved in areas with lower humidity levels and areas with greater annual sums of both cooling and heating degree days. Full article
(This article belongs to the Special Issue Advances in Energy Efficiency and Conservation of Green Buildings)
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48 pages, 21736 KiB  
Review
Overview on Permanent Magnet Motor Trends and Developments
by Vasileios I. Vlachou, Georgios K. Sakkas, Fotios P. Xintaropoulos, Maria Sofia C. Pechlivanidou, Themistoklis D. Kefalas, Marina A. Tsili and Antonios G. Kladas
Energies 2024, 17(2), 538; https://doi.org/10.3390/en17020538 - 22 Jan 2024
Cited by 5 | Viewed by 4480
Abstract
The extreme environmental issues and the resulting need to save energy have turned attention to the electrification of energy applications. One of the key components involved in energy efficiency improvements is the appropriate conception and manufacturing of electric machines. This paper overviews the [...] Read more.
The extreme environmental issues and the resulting need to save energy have turned attention to the electrification of energy applications. One of the key components involved in energy efficiency improvements is the appropriate conception and manufacturing of electric machines. This paper overviews the electromagnetic analysis governing the behavior of permanent magnets that enable substantial efficiency gains in recent electric machine developments. Particular emphasis is given to modeling the properties and losses developed in permanent magnets in emerging high speed applications. In addition, the investigation of properties and harmonic losses related to ferromagnetic materials constituting the machine magnetic circuits are equally analyzed and discussed. The experimental validation of the implemented methodologies and developed models with respect to the obtained precision is reported. The introduction of mixed numerical techniques based on the finite element method intended to appropriately represent the different physical phenomena encountered is outlined and discussed. Finally, fast and accurate simulation techniques including aggregated lumped parameter models considering harmonic losses associated with inverter supplies are discussed. Full article
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21 pages, 2399 KiB  
Review
Thermochemical Production of Hydrogen from Biomass: Pyrolysis and Gasification
by José Juan Alvarado-Flores, Jorge Víctor Alcaraz-Vera, María Liliana Ávalos-Rodríguez, Erandini Guzmán-Mejía, José Guadalupe Rutiaga-Quiñones, Luís Fernando Pintor-Ibarra and Santiago José Guevara-Martínez
Energies 2024, 17(2), 537; https://doi.org/10.3390/en17020537 - 22 Jan 2024
Cited by 3 | Viewed by 4526
Abstract
Today, hydrogen is one of the best options for generating electrical energy, for both industrial and residential use. The greatest volume of hydrogen produced today derives from processes that utilize petroleum. Although hydrogen has numerous benefits, continuing to produce it by these means [...] Read more.
Today, hydrogen is one of the best options for generating electrical energy, for both industrial and residential use. The greatest volume of hydrogen produced today derives from processes that utilize petroleum. Although hydrogen has numerous benefits, continuing to produce it by these means is undesirable. This document presents a review of the literature on biohydrogen production based on an analysis of over 15 types of terrestrial and marine biomasses. The fundamental components of different production systems are described, with a focus on the thermochemical processes of pyrolysis and gasification, which have been identified as two of the most effective, practical ways to produce hydrogen from biomass. It also discusses catalysts, solid residues, and residual water that are used in the thermochemical production of biohydrogen. The article ends with an analysis of hydrogen and its benefits as an energy option with great potential in the short term to participate in the transition from fossil fuels. Full article
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22 pages, 18104 KiB  
Article
Battery State of Health Estimation Using the Sliding Interacting Multiple Model Strategy
by Richard Bustos, Stephen Andrew Gadsden, Mohammad Biglarbegian, Mohammad AlShabi and Shohel Mahmud
Energies 2024, 17(2), 536; https://doi.org/10.3390/en17020536 - 22 Jan 2024
Cited by 2 | Viewed by 1121
Abstract
Due to their nonlinear behavior and the harsh environments to which batteries are subjected, they require a robust battery monitoring system (BMS) that accurately estimates their state of charge (SOC) and state of health (SOH) to ensure each battery’s safe operation. In this [...] Read more.
Due to their nonlinear behavior and the harsh environments to which batteries are subjected, they require a robust battery monitoring system (BMS) that accurately estimates their state of charge (SOC) and state of health (SOH) to ensure each battery’s safe operation. In this study, the interacting multiple model (IMM) algorithm is implemented in conjunction with an estimation strategy to accurately estimate the SOH and SOC of batteries under cycling conditions. The IMM allows for an adaptive mechanism to account for the decaying battery capacity while the battery is in use. The proposed strategy utilizes the sliding innovation filter (SIF) to estimate the SOC while the IMM serves as a process to update the parameter values of the battery model as the battery ages. The performance of the proposed strategy was tested using the well-known B005 battery dataset available at NASA’s Prognostic Data Repository. This strategy partitions the experimental dataset to build a database of different SOH models of the battery, allowing the IMM to select the most accurate representation of the battery’s current conditions while in operation, thus determining the current SOH of the battery. Future work in the area of battery retirement is also considered. Full article
(This article belongs to the Special Issue Battery Modelling, Applications, and Technology)
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23 pages, 5478 KiB  
Article
The Early Detection of Faults for Lithium-Ion Batteries in Energy Storage Systems Using Independent Component Analysis with Mahalanobis Distance
by Seunghwan Jung, Minseok Kim, Eunkyeong Kim, Baekcheon Kim, Jinyong Kim, Kyeong-Hee Cho, Hyang-A Park and Sungshin Kim
Energies 2024, 17(2), 535; https://doi.org/10.3390/en17020535 - 22 Jan 2024
Cited by 1 | Viewed by 1629
Abstract
In recent years, battery fires have become more common owing to the increased use of lithium-ion batteries. Therefore, monitoring technology is required to detect battery anomalies because battery fires cause significant damage to systems. We used Mahalanobis distance (MD) and independent component analysis [...] Read more.
In recent years, battery fires have become more common owing to the increased use of lithium-ion batteries. Therefore, monitoring technology is required to detect battery anomalies because battery fires cause significant damage to systems. We used Mahalanobis distance (MD) and independent component analysis (ICA) to detect early battery faults in a real-world energy storage system (ESS). The fault types included historical data of battery overvoltage and humidity anomaly alarms generated by the system management program. These are typical preliminary symptoms of thermal runaway, the leading cause of lithium-ion battery fires. The alarms were generated by the system management program based on thresholds. If a fire occurs in an ESS, the humidity inside the ESS will increase very quickly, which means that threshold-based alarm generation methods can be risky. In addition, industrial datasets contain many outliers for various reasons, including measurement and communication errors in sensors. These outliers can lead to biased training results for models. Therefore, we used MD to remove outliers and performed fault detection based on ICA. The proposed method determines confidence limits based on statistics derived from normal samples with outliers removed, resulting in well-defined thresholds compared to existing fault detection methods. Moreover, it demonstrated the ability to detect faults earlier than the point at which alarms were generated by the system management program: 15 min earlier for battery overvoltage and 26 min earlier for humidity anomalies. Full article
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26 pages, 12113 KiB  
Article
Photovoltaic-Based q-ZSI STATCOM with MDNESOGI Control Scheme for Mitigation of Harmonics
by Kanagaraj Nallaiyagounder, Vijayakumar Madhaiyan, Ramasamy Murugesan and Obaid Aldosari
Energies 2024, 17(2), 534; https://doi.org/10.3390/en17020534 - 22 Jan 2024
Cited by 1 | Viewed by 1162
Abstract
Static compensators (STATCOMs) are often used in distribution systems to enhance power quality. There is a need to enhance the performance of STATCOM to optimize its utilization and facilitate the provision of additional ancillary services. This paper employs the multilayer discrete noise-eliminating second [...] Read more.
Static compensators (STATCOMs) are often used in distribution systems to enhance power quality. There is a need to enhance the performance of STATCOM to optimize its utilization and facilitate the provision of additional ancillary services. This paper employs the multilayer discrete noise-eliminating second order generalized integrator (MDNESOGI) to regulate the quasi-impedance source inverter (qZSI)-STATCOM for power exchange with the grid. Compared to conventional second-order generalized integrator (SOGI), MDNESOGI exhibits a higher capability for rejecting DC offset. In instances of abnormal grid operation or system malfunction, the inclusion of DC rejection capability enhances the robustness and reliability of the system. The suggested control algorithm only requires two integrators, three mathematical operators, and a damping factor, making it far easier to implement than transformation-based methods. The distorted load current is broken down into its active and reactive components using this control mechanism. The reference currents are then calculated by multiplying these parts by their corresponding voltage standards. The DC offset is reduced and transient oscillations in the weight component are eliminated by adjusting the damping factor. The suggested algorithm effectively handles power quality tasks like (a) reducing harmonic distortion, (b) compensating for reactive power, (c) adjusting for power factor, and (d) balancing the load under different conditions in the distribution system. The experimental study results are used to examine the stability of the proposed control scheme in both static and dynamic scenarios. In addition, a comparison to traditional methods is provided to demonstrate the new method’s superiority. Experimentation results show that the suggested controller is superior to its contemporaries in all scenarios where power quality is a factor, meeting the IEEE standard requirements. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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20 pages, 3312 KiB  
Article
Distributed Coordinated Operation of Active Distribution Networks with Electric Heating Loads Based on Dynamic Step Correction ADMM
by Shoudong Li, Guangqing Bao and Yanwen Hu
Energies 2024, 17(2), 533; https://doi.org/10.3390/en17020533 - 22 Jan 2024
Viewed by 843
Abstract
In order to change the centralized operation framework of the active distribution network with electric heating loads (EHLs), a distributed optimization method is proposed for the coordinated operation of the active distribution network with EHLs. Firstly, considering the thermal delay effect and heat [...] Read more.
In order to change the centralized operation framework of the active distribution network with electric heating loads (EHLs), a distributed optimization method is proposed for the coordinated operation of the active distribution network with EHLs. Firstly, considering the thermal delay effect and heat loss of the thermal system, a centralized optimization operation model for active distribution networks with EHLs is established. Then, based on the centralized optimization operation model, it is rephrased as a standard sharing problem, and a distributed optimization operation model for the EHL active distribution network is established based on the alternating direction multiplier method (ADMM) solution. In the process of solving ADMM, dynamic step correction was further considered. By updating the steps during the iteration process, the number of iterations was reduced, and the convergence and computational efficiency of ADMM were improved. Finally, the effectiveness of the distributed coordinated operation method proposed in this paper was simulated and verified by constructing an IEEE33 distribution system. The results showed that the proposed distributed coordinated operation method has strong robustness to the randomness of the number of distributed units and parameters, and EHLs participating in coordinated operation can expand the consumption space of wind power and photovoltaic power, and improve the economic efficiency of system operation. Full article
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22 pages, 6429 KiB  
Article
Designing a High-Order Sliding Mode Controller for Photovoltaic- and Battery Energy Storage System-Based DC Microgrids with ANN-MPPT
by Tushar Kanti Roy, Amanullah Maung Than Oo and Subarto Kumar Ghosh
Energies 2024, 17(2), 532; https://doi.org/10.3390/en17020532 - 22 Jan 2024
Cited by 5 | Viewed by 1387
Abstract
This paper introduces a robust proportional integral derivative higher-order sliding mode controller (PID-HOSMC) based on a double power reaching law (DPRL) to enhance large-signal stability in DC microgrids. The microgrid integrates a solar photovoltaic (SPV) system, an energy storage system (ESS), and DC [...] Read more.
This paper introduces a robust proportional integral derivative higher-order sliding mode controller (PID-HOSMC) based on a double power reaching law (DPRL) to enhance large-signal stability in DC microgrids. The microgrid integrates a solar photovoltaic (SPV) system, an energy storage system (ESS), and DC loads. Efficient DC-DC converters, including bidirectional and boost converters, are employed to maintain a constant voltage level despite the lower SPV output power. An artificial neural network (ANN) generates the optimal reference voltage for the SPV system. The dynamical model, which incorporates external disturbances, is initially developed and based on this model, and the PID-HOSMC is designed to control output power by generating switching gate pulses. Afterwards, Lyapunov stability theory is used to demonstrate the model’s closed-loop stability, and theoretical analysis indicates that the controller can converge tracking errors to zero within a finite time frame. Finally, a comparative numerical simulation result is presented, demonstrating that the proposed controller exhibits a 58% improvement in settling time and an 82% improvement in overshoot compared to the existing controller. Experimental validation using processor-in-the-loop (PIL) confirms the proposed controller’s performance on a real-time platform. Full article
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20 pages, 2293 KiB  
Article
A Study on the Measurement of Regional Energy Consumption Efficiency and Decomposition of Its Influencing Factors in China: New Evidence for Achieving SDGs
by Xiumei Miao, Yong Wu and Fangrong Ren
Energies 2024, 17(2), 531; https://doi.org/10.3390/en17020531 - 22 Jan 2024
Cited by 2 | Viewed by 1046
Abstract
With the growth of global population and economic development, people are facing the problem of increasing scarcity of renewable energy and unsustainable energy use. To achieve the sustainable development goals (SDGs) proposed by the United Nations, research on energy consumption efficiency has become [...] Read more.
With the growth of global population and economic development, people are facing the problem of increasing scarcity of renewable energy and unsustainable energy use. To achieve the sustainable development goals (SDGs) proposed by the United Nations, research on energy consumption efficiency has become particularly important. This research evaluates the energy consumption efficiency of 270 cities in China through an improved EBM model and finds a common phenomenon of low energy consumption efficiency in the cities, with the highest efficiency in northeast China and the lowest efficiency in eastern China. In addition, the efficiency of industrial exhaust emissions most significantly positively correlates with the efficiency of employed population and total energy consumption efficiency, while the efficiency of regional GDP does not significantly correlate with the efficiency of the two input variables. Using the LMDI method to decompose the driving factors of energy consumption efficiency in the cities, we find that the most important factor affecting energy consumption efficiency is their own energy endowment. Therefore, to improve the energy consumption efficiency of its cities, the China government should comprehensively consider factors such as regional economic development level, industrial structure, and technological level differences, formulate relevant energy-saving and emission-reduction policies, focus on optimizing the energy consumption structure, encourage technological progress and innovation, and help increase investment in science and technology. Full article
(This article belongs to the Collection Energy Transition Towards Carbon Neutrality)
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14 pages, 2111 KiB  
Article
Ozonation and Changes in Biodegradable Organic Substances in Drinking Water Treatment: The Future of Green Technology
by Agata Rosińska and Klaudia Rakocz
Energies 2024, 17(2), 530; https://doi.org/10.3390/en17020530 - 22 Jan 2024
Cited by 1 | Viewed by 1054
Abstract
Studies were carried out to assess changes in biodegradable dissolved organic carbon (BDOC) and assimilable organic carbon (AOC) in groundwater and surface waters after two processes: ozonation and ozonation/UV. The tested water was in contact with O3 firstly for 4 and secondly [...] Read more.
Studies were carried out to assess changes in biodegradable dissolved organic carbon (BDOC) and assimilable organic carbon (AOC) in groundwater and surface waters after two processes: ozonation and ozonation/UV. The tested water was in contact with O3 firstly for 4 and secondly for 15 min. Three doses of disinfectant were used: 1.6 mg/L, 5.0 mg/L, and 10.0 mg/L. The UV radiation time was 10 and 30 min. The greatest change in AOC and BDOC for groundwater was observed at an O3 dose of 10.0 mg/L and a contact time of 15 min, by 400 and 197%, respectively. On the other hand, for surface water, it was shown that after the ozonation/UV process, the AOC and BDOC content decreased after both 10 and 30 min of radiation in comparison to the water after ozonation. The AOC content decreased by 33% and 22%, respectively, and the BDOC content by 27% and 31%, respectively. The results obtained in this study provide new information on the effect of different ozonation conditions and the combined method on the level of biodegradable organic fraction of water. It is recommended that BDOC and AOC should be monitored in Poland as routine indicators during the preparation of drinking water. Full article
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23 pages, 4290 KiB  
Article
Machine Learning-Based Automated Fault Detection and Diagnostics in Building Systems
by William Nelson and Christopher Dieckert
Energies 2024, 17(2), 529; https://doi.org/10.3390/en17020529 - 22 Jan 2024
Viewed by 2984
Abstract
Automated fault detection and diagnostics analysis in commercial building systems using machine learning (ML) can improve the building’s efficiency and conserve energy costs from inefficient equipment operation. However, ML can be challenging to implement in existing systems due to a lack of common [...] Read more.
Automated fault detection and diagnostics analysis in commercial building systems using machine learning (ML) can improve the building’s efficiency and conserve energy costs from inefficient equipment operation. However, ML can be challenging to implement in existing systems due to a lack of common data standards and because of a lack of building operators trained in ML techniques. Additionally, results from ML procedures can be complicated for untrained users to interpret. Boolean rule-based analysis is standard in current automated fault detection and diagnostics (AFDD) solutions but limits analysis to the rules defined and calibrated by energy engineers. Boolean rule-based analysis and ML can be combined to create an effective fault detection and diagnostics (FDD) tool. Three examples of ML’s advantages over rule-based analysis are explored by analyzing functional building equipment. ML can detect long-term faults in the system caused by a lack of system maintenance. It can also detect faults in system components with incomplete sets of sensors by modeling expected system operations and by making comparisons to actual system operations. An example of ML detecting a failure in a building is shown along with a demonstration of the soft decision boundaries of ML-based FDD compared to Boolean rule-based FDD analysis. The results from the three examples are used to demonstrate the strengths and weaknesses of using ML for AFDD analysis. Full article
(This article belongs to the Special Issue Machine Learning and Deep Learning for Energy Systems II)
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16 pages, 6259 KiB  
Article
Experimental Investigation of Fracture Propagation in Clayey Silt Hydrate-Bearing Sediments
by Yanjiang Yu, Kaixiang Shen and Haifeng Zhao
Energies 2024, 17(2), 528; https://doi.org/10.3390/en17020528 - 22 Jan 2024
Cited by 3 | Viewed by 1116
Abstract
More than 90% of the natural gas hydrate resources are reserved as marine clayey silt sediments. It is of great significance to efficiently develop a clayey silt hydrate. At present, there are problems of low single well production and small depressurization range in [...] Read more.
More than 90% of the natural gas hydrate resources are reserved as marine clayey silt sediments. It is of great significance to efficiently develop a clayey silt hydrate. At present, there are problems of low single well production and small depressurization range in its production test, which is still a long way from commercial exploitation. The combination of hydraulic fracturing technology and other methods such as depressurization method is regarded as one of the potential technical means to achieve the commercial exploitation of the hydrate. However, compared with shale gas reservoirs and coalbed methane reservoirs, clayey silt hydrate reservoirs have special mechanical properties, resulting in unique hydraulic fracturing processes. Therefore, it is necessary to study the fracture initiation and propagation laws of clayey silt hydrate reservoirs. To this end, we carried out large-scale (30 × 30 × 30 cm) true triaxial hydraulic fracturing experiments using a simulated material with similar mechanics, porosity, and permeability to clayey silt hydrate-bearing sediments. The effects of completion method, fracturing method, and fracturing fluid displacement on hydraulic fracture propagation of clayey silt hydrate-bearing sediments were studied. The results showed that a perforated completion can significantly increase the fracture reconstruction area and decrease the fracture initiation pressure compared to an open hole completion. Due to the small horizontal stress difference, it is feasible to carry out temporary plugging fracturing in clayey silt hydrate reservoirs. Temporary plugging fracturing can form steering fractures and significantly improve fracture complexity and fracture area. Increasing the fracturing fluid displacement can significantly increase the fracture area as well. When conducting fracturing in clayey silt hydrate-bearing sediments, the fracturing fluid filtration area is obviously larger than the fracture propagation area. Therefore, it is recommended to use a high-viscosity fracturing fluid to reduce the filtration of the fracturing fluid and improve the fracturing fluid efficiency. This study preliminarily explores the feasibility of temporary plugging fracturing in clayey silt hydrate reservoirs and analyzes the effect of completion methods on the propagation of fracturing fractures, which can provide a reference for the research conducted on the fracturing stimulation of clayey silt hydrate reservoirs. Full article
(This article belongs to the Special Issue Advances in Reservoir Simulation)
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18 pages, 5188 KiB  
Article
Optimization Design of Closed-Loop Thermosyphons: Experimentation and Computational Fluid Dynamics Modeling
by Natthakit Ritthong, Sommart Thongkom, Apichai Sawisit, Boonyabhorn Duangsa and Wirote Ritthong
Energies 2024, 17(2), 527; https://doi.org/10.3390/en17020527 - 22 Jan 2024
Viewed by 1719
Abstract
The well-established practice of integrating heat pipes into thermosyphons is recognized for its efficacy in achieving energy savings. This integration facilitates heat transfer and fluid circulation without requiring additional pumps or energy input, resulting in reduced consumption, lowered operational costs, and an overall [...] Read more.
The well-established practice of integrating heat pipes into thermosyphons is recognized for its efficacy in achieving energy savings. This integration facilitates heat transfer and fluid circulation without requiring additional pumps or energy input, resulting in reduced consumption, lowered operational costs, and an overall improvement in system efficiency. This research explores the energy-saving potential of closed-loop thermosyphons, with a specific focus on their integration in latent heat-based heat pipe technologies in industrial settings. The study systematically investigates the influence of thermosyphon orientation on energy efficiency through a combination of experiments and computational fluid dynamics (CFD) simulations. Thereby, it results in superior heat transfer rates in forced convection scenarios. A closed-loop thermosyphon heat exchanger undergoes evaluation in three panel installation configurations relative to the ground, taking into consideration factors including copper diameters, coolants (with or without R410a), and temperature conditions. CFD validation identifies an efficient thermosyphon design—a panel oriented perpendicularly to the ground and filled with R410a refrigerant at 90 °C. It utilizes a 19.05 mm copper tube for forced convection. This optimized design demonstrates a commendable heat transfer rate of 1485 W and a heat transfer coefficient of 1252 W/(m2·K), significantly enhancing thermal process efficiency and resulting in notable energy savings. Full article
(This article belongs to the Section J: Thermal Management)
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19 pages, 7009 KiB  
Article
Enhancing Ocean Thermal Energy Conversion Performance: Optimized Thermoelectric Generator-Integrated Heat Exchangers with Longitudinal Vortex Generators
by Yi-Cheng Chung and Chun-I Wu
Energies 2024, 17(2), 526; https://doi.org/10.3390/en17020526 - 22 Jan 2024
Cited by 1 | Viewed by 1844
Abstract
The effective utilization of renewable energy has become critical to technological advancement for the energetic transition from fossil fuels to clean and sustainable sources. Ocean Thermal Energy Conversion (OTEC) technology, which generates electricity by leveraging the temperature differential between surface and deep ocean [...] Read more.
The effective utilization of renewable energy has become critical to technological advancement for the energetic transition from fossil fuels to clean and sustainable sources. Ocean Thermal Energy Conversion (OTEC) technology, which generates electricity by leveraging the temperature differential between surface and deep ocean waters, enables stable power generation around the clock. In this domain, the combination of thermoelectric generators (TEGs) and heat exchangers has exhibited immense potential for ameliorating the deficiencies of conventional OTEC. This study uses finite element numerical simulation of the COMSOL5.5 software to investigate the fluid dynamics characteristics of heat exchangers with flat fins and different types of longitudinal vortex generators (LVGs) under the same number of fins. This research encompasses heat exchangers with rectangular, triangular, and trapezoidal LVGs. Concurrently, the analysis examines how the vortices generated by the LVGs influence the thermoelectric performance of the TEGs. The results demonstrate that heat exchangers integrating flat fins and LVGs can enhance the power generation efficiency of TEGs. However, the pumping power required by the LVGs constrains the thermoelectric conversion efficiency. Compared to rectangular and triangular LVGs, trapezoidal LVGs achieve a superior balance between output and pumping power. Heat exchangers utilizing trapezoidal LVGs can attain the highest TEG thermoelectric conversion efficiency with a specific seawater flow velocity. Overall, these findings provide valuable reference information for applying TEGs and heat exchangers in OTEC design. Full article
(This article belongs to the Section I: Energy Fundamentals and Conversion)
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17 pages, 2748 KiB  
Article
Performance Evaluation of Multiple Machine Learning Models in Predicting Power Generation for a Grid-Connected 300 MW Solar Farm
by Obaid Aldosari, Salem Batiyah, Murtada Elbashir, Waleed Alhosaini and Kanagaraj Nallaiyagounder
Energies 2024, 17(2), 525; https://doi.org/10.3390/en17020525 - 22 Jan 2024
Cited by 3 | Viewed by 1398
Abstract
Integrating renewable energy sources (RES), such as photovoltaic (PV) systems, into power system networks increases uncertainty, leading to practical challenges. Therefore, an accurate photovoltaic (PV) power prediction model is required to provide essential data that supports smooth power system operation. Hence, the work [...] Read more.
Integrating renewable energy sources (RES), such as photovoltaic (PV) systems, into power system networks increases uncertainty, leading to practical challenges. Therefore, an accurate photovoltaic (PV) power prediction model is required to provide essential data that supports smooth power system operation. Hence, the work presented in this paper compares and discusses the results of different machine learning (ML) techniques in predicting the power produced by the 300 MW Sakaka PV Power Plant in the north of Saudi Arabia. The validation of the presented work is performed using real-world operational data obtained from the specified solar farm. Several performance measures, including accuracy, precision, recall, F1 Score, and mean square error (MSE), are used in this work to evaluate the performance of the different ML approaches and determine the most precise prediction model. The obtained results show that the Support Vector Machine (SVM) with a Radial basis function (RBF) is the most effective approach for optimizing solar power prediction in large-scale solar farms. Full article
(This article belongs to the Special Issue New Insights into Distributed Energy Systems)
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19 pages, 4842 KiB  
Article
Experimental Study of the Fluid Contents and Organic/Inorganic Hydrocarbon Saturations, Porosities, and Permeabilities of Clay-Rich Shale
by Fenglan Wang, Binhui Li, Sheng Cao, Jiang Zhang, Quan Xu and Qian Sang
Energies 2024, 17(2), 524; https://doi.org/10.3390/en17020524 - 22 Jan 2024
Cited by 3 | Viewed by 1037
Abstract
Unlike conventional reservoirs, shale is particularly complex in its mineral composition. As typical components in shale reservoirs, clay and organic matter have different pore structures and strong interactions with fluids, resulting in complex fluid occurrence-states in shale. For example, there are both free [...] Read more.
Unlike conventional reservoirs, shale is particularly complex in its mineral composition. As typical components in shale reservoirs, clay and organic matter have different pore structures and strong interactions with fluids, resulting in complex fluid occurrence-states in shale. For example, there are both free water and adsorbed water in clay, and both free oil and ad/absorbed oil in organic matter. Key properties such as fluid content, organic/inorganic porosity, and permeability in clay-rich shale have been poorly characterized in previous studies. In this paper, we used a vacuum-imbibition experimental method combined with nuclear magnetic resonance technique and mathematical modeling to characterize the fluid content, organic/inorganic porosity, saturation, and permeability of clay-rich shale. We conducted vacuum-imbibition experiments on both shale samples and pure clay samples to distinguish the adsorbed oil and water in clay and organic matter. The effects of clay content and total organic matter content (TOC) on porosity and adsorbed-fluid content are then discussed. Our results show that, for the tested samples, organic porosity accounts for 26–76% of total porosity. The oil content in organic matter ranges from 29% to 69% of the total oil content, and 2% to 58% of the organic oil content is ad/absorbed in kerogen. The inorganic porosity has a weak positive correlation with clay content, and organic porosity increases with rising levels of organic matter content. The organic permeability is 1–3 orders of magnitude lower than the inorganic permeability. Full article
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15 pages, 1858 KiB  
Article
The Effect of Bakery Waste Addition on Pine Sawdust Pelletization and Pellet Quality
by Sławomir Obidziński, Joanna Szyszlak-Bargłowicz, Grzegorz Zając, Małgorzata Kowczyk-Sadowy, Małgorzata Krasowska, Aneta Sienkiewicz, Paweł Cwalina, Damian Faszczewski and Jacek Wasilewski
Energies 2024, 17(2), 523; https://doi.org/10.3390/en17020523 - 22 Jan 2024
Cited by 3 | Viewed by 1336
Abstract
This paper presents research findings on the pelleting process of pine sawdust using bakery waste in a pelletizer. The addition of bakery waste (white wheat–rye bread, whole-grain rye bread, and pumpkin bread) to pine sawdust had a beneficial effect on the kinetic strength [...] Read more.
This paper presents research findings on the pelleting process of pine sawdust using bakery waste in a pelletizer. The addition of bakery waste (white wheat–rye bread, whole-grain rye bread, and pumpkin bread) to pine sawdust had a beneficial effect on the kinetic strength of the pellets obtained, an increase of up to approximately three percentage points. The density of pellets with the addition of bakery waste also increased, while the bulk density of the pellets decreased. The addition of bakery waste also had a positive effect on the power demand of the pelletizer. It was reduced from 3.08% (at a 10% addition of white wheat–rye bread) to 22.18% (at a 20% addition of pumpkin bread), compared to the process of compacting pure pine sawdust. In addition, all the pellets containing bakery waste had a lower energy yield (EY) determined based on lower heating value and energy inputs. This index was lower by 53 Wh·kg−1 for pine sawdust pellets with a 10% addition of pumpkin bread. The greatest reduction, on the other hand, was by 173 Wh·kg−1 for pellets, with a 20% addition of white wheat–rye bread. In each case, an increase in the share of bakery additives resulted in a decrease in the energy yield from the pellets obtained. The smallest reduction in EY was found when pumpkin bread was used as an additive (from 53 to 133 Wh·kg−1). Considering all the parameters analyzed characterizing the pellets obtained, it was concluded that the addition of bakery residues to pelletized pine sawdust should not exceed 10%. Further increases in the proportion of bakery waste did not yield relative benefits, due to the deterioration of the energy characteristics of the pellets obtained. Full article
(This article belongs to the Special Issue Research on Sustainable Biomass Conversion)
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23 pages, 10410 KiB  
Article
Retrofitting Biomass Combined Heat and Power Plant for Biofuel Production—A Detailed Techno-Economic Analysis
by Hao Chen, Erik Dahlquist and Konstantinos Kyprianidis
Energies 2024, 17(2), 522; https://doi.org/10.3390/en17020522 - 22 Jan 2024
Cited by 1 | Viewed by 1539
Abstract
Existing combined heat and power plants usually operate on part-load conditions during low heating demand seasons. Similarly, there are boilers designated for winter use that remain inactive for much of the year. This brings a concern about the inefficiency of resource utilization. Retrofitting [...] Read more.
Existing combined heat and power plants usually operate on part-load conditions during low heating demand seasons. Similarly, there are boilers designated for winter use that remain inactive for much of the year. This brings a concern about the inefficiency of resource utilization. Retrofitting existing CHP plants (especially for those with spare boilers) for biofuel production could increase revenue and enhance resource efficiency. This study introduces a novel approach that combines biomass gasification and pyrolysis in a polygeneration process that is based on utilizing existing CHP facilities to produce biomethane, bio-oil, and hydrogen. In this work, a detailed analysis was undertaken of retrofitting an existing biomass combined heat and power plant for biofuel production. The biofuel production plant is designed to explore the polygeneration of hydrogen, biomethane, and bio-oil via the integration of gasification, pyrolysis, and renewable-powered electrolysis. An Aspen Plus model of the proposed biofuel production plant is established followed by a performance investigation of the biofuel production plant under various design conditions. An economic analysis is carried out to examine the profitability of the proposed polygeneration system. Results show that the proposed polygeneration system can achieve 40% carbon efficiency with a payback period of 9 years and an internal rate of return of 17.5%, without the integration of renewable hydrogen. When integrated with renewable-power electrolysis, the carbon efficiency could be significantly improved to approximately 90%; however, the high investment cost associated with the electrolyzer system makes this integration economically unfavorable. Full article
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18 pages, 10952 KiB  
Article
The Coordinated Power Control of Flexible DC Microgrids in Sustainably Optimized Yacht Marinas
by Andrea Alessia Tavagnutti, Serena Bertagna, Marco Dalle Feste, Massimiliano Chiandone, Daniele Bosich, Vittorio Bucci and Giorgio Sulligoi
Energies 2024, 17(2), 521; https://doi.org/10.3390/en17020521 - 21 Jan 2024
Viewed by 1216
Abstract
Nowadays, the industrial world is undergoing a disruptive transformation towards more environmentally sustainable solutions. In the blue economy, this new approach is not only expressed in the domain of actual vessels, but also in the development of charging infrastructure, displaying a notable transition [...] Read more.
Nowadays, the industrial world is undergoing a disruptive transformation towards more environmentally sustainable solutions. In the blue economy, this new approach is not only expressed in the domain of actual vessels, but also in the development of charging infrastructure, displaying a notable transition towards more eco-friendly solutions. The key focus lies in adopting flexible power systems capable of integrating renewable energy sources and storage technologies. Such systems play a crucial role in enabling a shift towards low-emission maritime transport. The emissions reduction goal extends beyond onboard shipboard distribution systems, encompassing also the design of supplying platforms and marinas. This study explores the implementation of a controlled DC microgrid tailored to efficient management of power flows within a yacht marina. Once having established the interfaces for the vessels at berth, the integration between the vessels, the onshore photovoltaic plant and the battery storage unit is made possible thanks to the coordinated management of multiple power converters. The overarching goal is to curtail reliance on external energy sources. Within this DC microgrid framework, a centralized controller assumes a pivotal role in orchestrating the power sources and loads. This coordinated management is essential to achieve sustainable operations, ultimately leading to the reduction of emissions from both ships and onshore power plants. Full article
(This article belongs to the Special Issue Sustainable/Renewable Energy Systems Analysis and Optimization)
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24 pages, 6298 KiB  
Article
The Impact of Priority in Coordinated Traffic Lights on Tram Energy Consumption
by Anna Górka, Andrzej Czerepicki and Tomasz Krukowicz
Energies 2024, 17(2), 520; https://doi.org/10.3390/en17020520 - 21 Jan 2024
Cited by 2 | Viewed by 1427
Abstract
Traffic signal priority issues have been a research subject for several decades in Poland and worldwide. Traffic control algorithms have evolved considerably during this period and have become increasingly advanced. Most of them operate within coordinated street sequences, which adds to their complexity. [...] Read more.
Traffic signal priority issues have been a research subject for several decades in Poland and worldwide. Traffic control algorithms have evolved considerably during this period and have become increasingly advanced. Most of them operate within coordinated street sequences, which adds to their complexity. Tramway priority affects traffic conditions for other road users, so many aspects must be taken into account when choosing a priority solution. Typically, one of the main criteria for evaluating the effectiveness of priority is reducing travel time for the priority vehicle while ensuring that the travel times of other traffic participants through the intersection are maintained or slightly deteriorated. However, the energy aspects are often overlooked. This publication aims to investigate how local priority for tramways in traffic signals of coordinated streets affects energy consumption for tramway traction needs. The study was conducted using a microscopic modeling method with PTV Vissim software (ver. 2021). The models were built for coordinated sequences with different levels of priority. Real traffic control algorithms with priority were implemented into the model on the sequence of Marymoncka Street and Grochowska Street in Warsaw. Then, by introducing changes to the parameters of the algorithms, their effect on traffic characteristics, including estimated power consumption, was studied. The results obtained from the computer simulation were statistically processed using R software (ver. 4.3.2). The analysis results prove the effectiveness of tramway priority operation, show its impact on electricity consumption, and allow us to determine the limits of its effective application. Thus, they complement the knowledge of the impact of tramway priority on traffic. The research results also have practical value, as they help us to make rational decisions in the process of designing traffic control algorithms at intersections with a multi-criteria approach. Full article
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22 pages, 5371 KiB  
Article
Robust Collaborative Scheduling Strategy for Multi-Microgrids of Renewable Energy Based on a Non-Cooperative Game and Profit Allocation Mechanism
by Xiedong Gao and Xinyan Zhang
Energies 2024, 17(2), 519; https://doi.org/10.3390/en17020519 - 21 Jan 2024
Cited by 1 | Viewed by 1310
Abstract
The Multiple Microgrid System (MMG) facilitates synergistic complementarity among various energy sources, reduces carbon emissions, and promotes the integration of renewable energy generation. In this context, we propose a two-stage robust cooperative scheduling model for MMGs based on non-cooperative game theory and a [...] Read more.
The Multiple Microgrid System (MMG) facilitates synergistic complementarity among various energy sources, reduces carbon emissions, and promotes the integration of renewable energy generation. In this context, we propose a two-stage robust cooperative scheduling model for MMGs based on non-cooperative game theory and a benefit allocation mechanism. In the first stage, considering electricity price fluctuations and uncertainties in wind and solar power outputs, a robust optimization approach is applied to establish an electric energy management model for MMGs. This model enables point-to-point energy sharing among microgrids. In the second stage, addressing the benefit allocation problem for shared electric energy, we introduce a Cost Reduction Ratio Distribution (CRRD) model based on non-cooperative game theory. The generalized Nash equilibrium is utilized to determine the benefit distribution for shared electric energy. Finally, through case studies, the proposed model is validated, ensuring fair returns for each microgrid. The results indicate that the proposed model optimizes the operational states of individual microgrids, reduces operational costs for each microgrid, and lowers the overall total operational costs of the MMG system. Additionally, an investigation is conducted into the impact of electricity price uncertainty coefficients and confidence levels of wind and solar uncertainties on the operational costs of microgrids. Full article
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16 pages, 3673 KiB  
Article
Prospects of Hydrogen Application as a Fuel for Large-Scale Compressed-Air Energy Storages
by Iliya K. Iliev, Alexander V. Fedyukhin, Daniil V. Semin, Yulia S. Valeeva, Stanislav A. Dronov and Ivan H. Beloev
Energies 2024, 17(2), 518; https://doi.org/10.3390/en17020518 - 20 Jan 2024
Viewed by 1531
Abstract
A promising method of energy storage is the combination of hydrogen and compressed-air energy storage (CAES) systems. CAES systems are divided into diabatic, adiabatic, and isothermal cycles. In the diabatic cycle, thermal energy after air compression is discharged into the environment, and the [...] Read more.
A promising method of energy storage is the combination of hydrogen and compressed-air energy storage (CAES) systems. CAES systems are divided into diabatic, adiabatic, and isothermal cycles. In the diabatic cycle, thermal energy after air compression is discharged into the environment, and the scheme implies the use of organic fuel. Taking into account the prospects of the decarbonization of the energy industry, it is advisable to replace natural gas in the diabatic CAES scheme with hydrogen obtained by electrolysis using power-to-gas technology. In this article, the SENECA-1A project is considered as a high-power hybrid unit, using hydrogen instead of natural gas. The results show that while keeping the 214 MW turbines powered, the transition to hydrogen reduces carbon dioxide emissions from 8.8 to 0.0 kg/s, while the formation of water vapor will increase from 17.6 to 27.4 kg/s. It is shown that the adiabatic CAES SENECA-1A mode, compared to the diabatic, has 0.0 carbon dioxide and water vapor emission with relatively higher efficiency (71.5 vs. 62.1%). At the same time, the main advantage of the diabatic CAES is the possibility to produce more power in the turbine block (214 vs. 131.6 MW), having fewer capital costs. Thus, choosing the technology is a subject of complex technical, economic, and ecological study. Full article
(This article belongs to the Special Issue Advanced Engineering and Green Energy)
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33 pages, 29140 KiB  
Article
A Multi-Source Power System’s Load Frequency Control Utilizing Particle Swarm Optimization
by Zhengwei Qu, Waqar Younis, Yunjing Wang and Popov Maxim Georgievitch
Energies 2024, 17(2), 517; https://doi.org/10.3390/en17020517 - 20 Jan 2024
Cited by 4 | Viewed by 1566
Abstract
Electrical power networks consist of numerous energy control zones connected by tie-lines, with the addition of nonconventional sources resulting in considerable variations in tie-line power and frequency. Under these circumstances, a load frequency control (LFC) loop gives constancy and security to interconnected power [...] Read more.
Electrical power networks consist of numerous energy control zones connected by tie-lines, with the addition of nonconventional sources resulting in considerable variations in tie-line power and frequency. Under these circumstances, a load frequency control (LFC) loop gives constancy and security to interconnected power systems (IPSs) by supplying all consumers with high-quality power at a nominal frequency and tie-line power change. This article proposes employing a proportional–integral–derivative (PID) controller to effectively control the frequency in a one-area multi-source power network comprising thermal, solar, wind, and fuel cells and in a thermal two-area tie-line IPS. The particle swarm optimization (PSO) technique was utilized to tune the PID controller parameters, with the integral time absolute error being utilized as an objective function. The efficacy and stability of the PSO-PID controller methodology were further tested in various scenarios for proposed networks. The frequency fluctuations associated with the one-area multi-source power source and with the two-area tie-line IPS’s area 1 and area 2 frequency variations were 59.98 Hz, 59.81 Hz, and 60 Hz, respectively, and, in all other investigated scenarios, they were less than that of the traditional PID controller. The results clearly show that, in terms of frequency responses, the PSO-PID controller performs better than the conventional PID controller. Full article
(This article belongs to the Section F: Electrical Engineering)
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42 pages, 3780 KiB  
Review
Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue
by Paweł Pijarski and Adrian Belowski
Energies 2024, 17(2), 516; https://doi.org/10.3390/en17020516 - 20 Jan 2024
Cited by 4 | Viewed by 2568
Abstract
The challenges currently faced by network operators are difficult and complex. Presently, various types of energy sources with random generation, energy storage units operating in charging or discharging mode and consumers with different operating characteristics are connected to the power grid. The network [...] Read more.
The challenges currently faced by network operators are difficult and complex. Presently, various types of energy sources with random generation, energy storage units operating in charging or discharging mode and consumers with different operating characteristics are connected to the power grid. The network is being expanded and modernised. This contributes to the occurrence of various types of network operating states in practice. The appearance of a significant number of objects with random generation in the power system complicates the process of planning and controlling the operation of the power system. It is therefore necessary to constantly search for new methods and algorithms that allow operators to adapt to the changing operating conditions of the power grid. There are many different types of method in the literature, with varying effectiveness, that have been or are used in practice. So far, however, no one ideal, universal method or methodology has been invented that would enable (with equal effectiveness) all problems faced by the power system to be solved. This article presents an overview and a short description of research works available in the literature in which the authors have used modern methods to solve various problems in the field of power engineering. The article is an introduction to the special issue entitled Advances in the Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering. It is an overview of various current problems and the various methods used to solve them, which are used to cope with difficult situations. The authors also pointed out potential research gaps that can be treated as areas for further research. Full article
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16 pages, 476 KiB  
Article
Reconfigurable Intelligent Surface-Assisted Secure Communication in Cognitive Radio Systems
by Xinshui Wang, Xu Wang, Jimin Ge, Zhibin Liu, Yuefeng Ma and Xingwang Li
Energies 2024, 17(2), 515; https://doi.org/10.3390/en17020515 - 20 Jan 2024
Cited by 1 | Viewed by 1130
Abstract
A reconfigurable intelligent reflective surface (RIS)-assisted cognitive radio (CR) multiple-input multiple-output (MIMO) secure communication system is considered. In the presence of an eavesdropper, a primary base station (PBS) and a cognitive base station (CBS) equipped with multiple antennas communicate to a primary user [...] Read more.
A reconfigurable intelligent reflective surface (RIS)-assisted cognitive radio (CR) multiple-input multiple-output (MIMO) secure communication system is considered. In the presence of an eavesdropper, a primary base station (PBS) and a cognitive base station (CBS) equipped with multiple antennas communicate to a primary user (PU) and a secondary user (SU), respectively. In order to maximize the achievable secrecy rate of the system, the secrecy rate maximization problem is first transformed into a secure energy efficiency (SEE) problem using an objective function. Then, the security energy efficiency of the system is maximized by jointly optimizing the transmit beam formation of the base station and the reflected beam formation of the smart reflecting surface under the conditions that the total transmitted power constraint and the interference power constraint are satisfied. To address the difficulty in solving the resulting optimization problem, we apply an algorithm based on alternating optimization and semidefinite relaxation, as well as Dinklbach’s algorithm, to solve the problem. Simulation results show that this method can significantly improve the safety energy efficiency of the system. Full article
(This article belongs to the Section F1: Electrical Power System)
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21 pages, 4682 KiB  
Article
Enhancing Energy Management Strategies for Extended-Range Electric Vehicles through Deep Q-Learning and Continuous State Representation
by Christian Montaleza, Paul Arévalo, Jimmy Gallegos and Francisco Jurado
Energies 2024, 17(2), 514; https://doi.org/10.3390/en17020514 - 20 Jan 2024
Viewed by 1377
Abstract
The efficiency and dynamics of hybrid electric vehicles are inherently linked to effective energy management strategies. However, complexity is heightened due to uncertainty and variations in real driving conditions. This article introduces an innovative strategy for extended-range electric vehicles, grounded in the optimization [...] Read more.
The efficiency and dynamics of hybrid electric vehicles are inherently linked to effective energy management strategies. However, complexity is heightened due to uncertainty and variations in real driving conditions. This article introduces an innovative strategy for extended-range electric vehicles, grounded in the optimization of driving cycles, prediction of driving conditions, and predictive control through neural networks. First, the challenges of the energy management system are addressed by merging deep reinforcement learning with strongly convex objective optimization, giving rise to a pioneering method called DQL-AMSGrad. Subsequently, the DQL algorithm has been implemented, allowing temporal difference-based updates to adjust Q values to maximize the expected cumulative reward. The loss function is calculated as the mean squared error between the current estimate and the calculated target. The AMSGrad optimization method has been applied to efficiently adjust the weights of the artificial neural network. Hyperparameters such as the learning rate and discount factor have been tuned using data collected during real-world driving tests. This strategy tackles the “curse of dimensionality” and demonstrates a 30% improvement in adaptability to changing environmental conditions. With a 20%-faster convergence speed and a 15%-superior effectiveness in updating neural network weights compared to conventional approaches, it also highlights an 18% reduction in fuel consumption in a case study with the Nissan Xtrail e-POWER system, validating its practical applicability. Full article
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