Energies

39 pages, 2275 KiB

Open AccessReview

Feasibility of Food Organics and Garden Organics as a Promising Source of Biomethane: A Review on Process Optimisation and Impact of Nanomaterials

by Shweta Mitra and Prasad Kaparaju

Energies 2024, 17(16), 4198; https://doi.org/10.3390/en17164198 - 22 Aug 2024

Viewed by 589

Abstract

Anaerobic digestion (AD) of food waste (FW) is considered an environmentally sustainable process that can divert the disposal of FW to landfill and prevent greenhouse gas (GHG) emissions in managing the FW. Although several studies have attempted to demonstrate the AD of FW, [...] Read more.

Anaerobic digestion (AD) of food waste (FW) is considered an environmentally sustainable process that can divert the disposal of FW to landfill and prevent greenhouse gas (GHG) emissions in managing the FW. Although several studies have attempted to demonstrate the AD of FW, low methane yields and a high incidence of process instability have been reported due to the rapid generation and accumulation of volatile fatty acids (VFAs). This paper reviews the recent research and development with high variation in FW composition, such as the carbon-to-nitrogen (C/N) ratio and, consequently, the effect of its physicochemical composition on process performance and methane yields. The paper highlights the significance of optimizing the anaerobic co-digestion (AcoD) of FW with carbon-rich substrates such as garden waste (GW) and/or the addition of trace elements as strategies that can improve the process performance and methane yields from FW. This review focuses on the factors effecting the feasibility of food organics and garden organics (FOGO) as a substrate for methane production. The review also critically analyses the prospects of enhancement of biomethane yield by optimizations of the impactful parameters. The progress in research related to these methods and identifying existing limitations to efficient AD of FOGO are the key findings of this review. This review also assesses the impact of nanotechnology on the process performance of the digester. The integration of FO and GO in AD processes has demonstrated enhanced biogas yields, improved process stability, and better waste management outcomes compared to the digestion of either substrate alone. Despite these advantages, challenges such as feedstock variability, process optimization, and the need for advanced pretreatment methods remain. Addressing these issues through continued research and technological innovations will be crucial for maximizing the efficiency and scalability of AD systems. Moreover, the economic feasibility and policy frameworks supporting AD need further development to promote broader adoption. Full article

(This article belongs to the Special Issue Biomass Conversion Technologies: 3rd Edition)

► Show Figures

Graphical abstract

14 pages, 2664 KiB

Open AccessArticle

Short-Circuit Fault Diagnosis on the Windings of Three-Phase Induction Motors through Phasor Analysis and Fuzzy Logic

by Josue A. Reyes-Malanche, Efrain Ramirez-Velasco, Francisco J. Villalobos-Pina and Suresh K. Gadi

Energies 2024, 17(16), 4197; https://doi.org/10.3390/en17164197 - 22 Aug 2024

Viewed by 466

Abstract

An induction motor is an electric machine widely used in various industrial and commercial applications due to its efficiency and simple design. In this regard, a methodology based on the electric phasor analysis of line currents and the variations in the phase angles [...] Read more.

An induction motor is an electric machine widely used in various industrial and commercial applications due to its efficiency and simple design. In this regard, a methodology based on the electric phasor analysis of line currents and the variations in the phase angles among these line currents is proposed. The values in degrees of the angles between every pair of line currents were introduced to a fuzzy logic algorithm based on the Mamdani model, developed using the Matlab toolbox for detection and isolation of the inter-turn short-circuit faults on the windings of an induction motor. To carry out the analysis, the induction motor was modified in its stator windings to artificially induce short-circuit faults of different magnitudes. The current signals are acquired in real time using a digital platform developed in the Delphi 7 high-level language communicating with a float point unit Digital Signal Processor (DSP) TMS320F28335 by Texas Instruments. The proposed method not only detects the short circuit faults but also isolates the faulty winding. Full article

(This article belongs to the Special Issue Advanced Technologies in Partial Discharge Detection and Fault Diagnosis)

► Show Figures

Figure 1

15 pages, 2313 KiB

Open AccessArticle

An Impact Assessment of a Transportable BESS on the Protection of Conventional Distribution Systems

by Antonio E. C. Momesso, Pedro H. A. Barra, Pedro I. N. Barbalho, Eduardo N. Asada, José C. M. Vieira and Denis V. Coury

Energies 2024, 17(16), 4196; https://doi.org/10.3390/en17164196 - 22 Aug 2024

Viewed by 441

Abstract

The integration of new battery technologies has become a focal point for distribution utilities, driven by decreasing costs and the need for fast responsiveness. Transportable battery energy storage systems (TBESSs) offer additional flexibility, allowing connection at multiple substations or grid feed points. However, [...] Read more.

The integration of new battery technologies has become a focal point for distribution utilities, driven by decreasing costs and the need for fast responsiveness. Transportable battery energy storage systems (TBESSs) offer additional flexibility, allowing connection at multiple substations or grid feed points. However, concerns remain regarding their impact on distribution systems (DSs), particularly on protection devices (PDs). This study addresses these concerns by investigating the influence of TBESSs on the protection systems of a real-world distribution network. Given the lack of studies in the current literature on this topic, this research aims to fill this gap by examining the potential effects of TBESS integration on PDs, such as reclosers and fuses, within a DS. Utilizing a model based on real data from a Brazilian utility, we conducted simulations to analyze the effects of TBESSs in both charging and discharging modes on the protection systems of three feeders. The methodology involved assessing variations in the operation times and coordination of PDs to determine if TBESS integration would necessitate adjustments to existing protection configurations. The results demonstrated that TBESS integration resulted in only minor variations in PD operating times, typically within hundredths of a second, indicating a negligible impact on protection performance. Consequently, no significant modifications to the protection system are required to accommodate TBESSs. These findings suggest that TBESSs can be seamlessly integrated into existing distribution networks, maintaining system reliability and operational integrity. This study provides valuable insights and a robust procedure for utilities to analyze the integration of TBESSs, supporting the effective deployment of modern energy storage solutions in DSs. Full article

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

► Show Figures

Figure 1

41 pages, 5173 KiB

Open AccessArticle

Onboard Neuro-Fuzzy Adaptive Helicopter Turboshaft Engine Automatic Control System

by Serhii Vladov, Maryna Bulakh, Victoria Vysotska and Ruslan Yakovliev

Energies 2024, 17(16), 4195; https://doi.org/10.3390/en17164195 - 22 Aug 2024

Viewed by 439

Abstract

A modified onboard neuro-fuzzy adaptive (NFA) helicopter turboshaft engine (HTE) automatic control system (ACS) is proposed, which is based on a circuit consisting of a research object, a regulator, an emulator, a compensator, and an observer unit. In this scheme, it is proposed [...] Read more.

A modified onboard neuro-fuzzy adaptive (NFA) helicopter turboshaft engine (HTE) automatic control system (ACS) is proposed, which is based on a circuit consisting of a research object, a regulator, an emulator, a compensator, and an observer unit. In this scheme, it is proposed to use the proposed AFNN six-layer hybrid neuro-fuzzy network (NFN) with Sugeno fuzzy inference and a Gaussian membership function for fuzzy variables, which makes it possible to reduce the HTE fuel consumption parameter transient process regulation time by 15.0 times compared with the use of a traditional system automatic control (clear control), 17.5 times compared with the use of a fuzzy ACS (fuzzy control), and 11.25 times compared with the use of a neuro-fuzzy reconfigured ACS based on an ANFIS five-layer hybrid NFN. By applying the Lyapunov method as a criterion, its system stability is proven at any time, with the exception of the initial time, since at the initial time the system is in an equilibrium state. The use of the six-layer ANFF NFN made it possible to reduce the I and II types of error in the HTE fuel consumption controlling task by 1.36…2.06 times compared with the five-layer ANFIS NFN. This work also proposes an AFNN six-layer hybrid NFN training algorithm, which, due to adaptive elements, allows one to change its parameters and settings in real time based on changing conditions or external influences and, as a result, achieve an accuracy of up to 99.98% in the HTE fuel consumption controlling task and reduce losses to 0.2%. Full article

(This article belongs to the Section I: Energy Fundamentals and Conversion)

► Show Figures

Figure 1

35 pages, 5814 KiB

Open AccessArticle

A Cost-Effective Energy Management Approach for On-Grid Charging of Plug-in Electric Vehicles Integrated with Hybrid Renewable Energy Sources

by Mohd Bilal, Pitshou N. Bokoro, Gulshan Sharma and Giovanni Pau

Energies 2024, 17(16), 4194; https://doi.org/10.3390/en17164194 - 22 Aug 2024

Viewed by 676

Abstract

Alternative energy sources have significantly impacted the global electrical sector by providing continuous power to consumers. The deployment of renewable energy sources in order to serve the charging requirements of plug-in electric vehicles (PEV) has become a crucial area of research in emerging [...] Read more.

Alternative energy sources have significantly impacted the global electrical sector by providing continuous power to consumers. The deployment of renewable energy sources in order to serve the charging requirements of plug-in electric vehicles (PEV) has become a crucial area of research in emerging nations. This research work explores the techno-economic and environmental viability of on-grid charging of PEVs integrated with renewable energy sources in the Surat region of India. The system is designed to facilitate power exchange between the grid network and various energy system components. The chosen location has contrasting wind and solar potential, ensuring diverse renewable energy prospects. PEV charging hours vary depending on the location. A novel metaheuristic-based optimization algorithm, the Pufferfish Optimization Algorithm (POA), was employed to optimize system component sizing by minimizing the system objectives including Cost of Energy (COE) and the total net present cost (TNPC), ensuring a lack of power supply probability (LPSP) within a permissible range. Our findings revealed that the optimal PEV charging station configuration is a grid-tied system combining solar photovoltaic (SPV) panels and wind turbines (WT). This setup achieves a COE of USD 0.022/kWh, a TNPC of USD 222,762.80, and a life cycle emission of 16,683.74 kg CO₂-equivalent per year. The system also reached a 99.5% renewable energy penetration rate, with 3902 kWh/year of electricity purchased from the grid and 741,494 kWh/year of energy sold back to the grid. This approach could reduce reliance on overburdened grids, particularly in developing nations. Full article

(This article belongs to the Special Issue Novel Energy Management Approaches in Microgrid Systems)

► Show Figures

Figure 1

36 pages, 7249 KiB

Open AccessReview

A Review on Key Technologies and Developments of Hydrogen Fuel Cell Multi-Rotor Drones

by Zenan Shen, Shaoquan Liu, Wei Zhu, Daoyuan Ren, Qiang Xu and Yu Feng

Energies 2024, 17(16), 4193; https://doi.org/10.3390/en17164193 - 22 Aug 2024

Viewed by 619

Abstract

Multi-rotor drones, a kind of unmanned equipment which is widely used in the military, commercial consumption and other fields, have been developed very rapidly in recent years. However, their short flight time has hindered the expansion of their application range. This can be [...] Read more.

Multi-rotor drones, a kind of unmanned equipment which is widely used in the military, commercial consumption and other fields, have been developed very rapidly in recent years. However, their short flight time has hindered the expansion of their application range. This can be addressed by utilizing hydrogen fuel cells, which exhibit high energy density, strong adaptability to ambient temperature, and no pollution emissions, as the power source. Accordingly, the application of hydrogen fuel cells as the power source in multi-rotor drones is a promising technology that has attracted significant research attention. This paper summarizes the development process of hydrogen fuel cell multi-rotor drones and analyzes the key obstacles that need to be addressed for the further development of hydrogen fuel cell multi-rotor drones, including structural light weight, hydrogen storage methods, energy management strategies, thermal management, etc. Additionally, prospects for the future development of hydrogen fuel cell multi-rotor drones are presented. Full article

(This article belongs to the Special Issue Hydrogen Energy Technologies: Recent Advances in Production, Storage and Applications—2nd Edition)

► Show Figures

Figure 1

37 pages, 7983 KiB

Open AccessArticle

Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive

by Hassen Moussa, Saber Krim, Hichem Kesraoui, Majdi Mansouri and Mohamed Faouzi Mimouni

Energies 2024, 17(16), 4192; https://doi.org/10.3390/en17164192 - 22 Aug 2024

Viewed by 391

Abstract

This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). The SOSMC-STA is suggested for overcoming the shortcomings of the [...] Read more.

This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). The SOSMC-STA is suggested for overcoming the shortcomings of the Proportional Integral Controller (PIC) and the Conventional Sliding Mode Controller (CSMC). Indeed, the main limitations of the PIC are the slower speed response, the tuning difficulty of its parameters, and the sensitivity to changes in system parameters, including variations in process dynamics, load changes, or changes in setpoint. It is also limited to linear systems. Regarding the CSMC technique, its limitation is the chattering phenomenon, characterized by the rapid switching of the control signal. This phenomenon includes high-frequency oscillations which induce wear and tear on mechanical systems, adversely affecting performance. Secondly, this paper also proposes a Loss Model Controller (LMC) for FPIM energy optimization. Thus, the suggested LMC chooses the optimal flux magnitude required by the FPIM for each applied load torque, which consequently reduces the losses and the FPIM efficiency. The performance of the optimized DFOC-SOSMC-STA based on the LMC is verified using numerical simulation under the Matlab environment. The analysis of the simulation results shows that the DFOC-SOSMC-STA guarantees a high dynamic response, chattering reduction, good precision, and robustness in case of external load or parameter disturbances. Moreover, the DFOC-SOSMC-STA, combined with the LMC, reduces losses and increases efficiency. Full article

(This article belongs to the Topic Industrial Control Systems)

► Show Figures

Figure 1

33 pages, 1014 KiB

Open AccessReview

Extending the Lifetime of Offshore Wind Turbines: Challenges and Opportunities

by Mahmood Shafiee

Energies 2024, 17(16), 4191; https://doi.org/10.3390/en17164191 - 22 Aug 2024

Viewed by 643

Abstract

A significant number of first-generation offshore wind turbines (OWTs) have either reached or are approaching the end of their operational lifespan and need to be upgraded or replaced with more modern units. In response to this concern, governments, regulatory bodies and industries have [...] Read more.

A significant number of first-generation offshore wind turbines (OWTs) have either reached or are approaching the end of their operational lifespan and need to be upgraded or replaced with more modern units. In response to this concern, governments, regulatory bodies and industries have initiated the development of effective end-of-life (EOL) management strategies for offshore wind infrastructure. Lifetime extension is a relatively new concept that has recently gained significant attention within the offshore wind energy community. Extending the service lifetime of OWTs can yield many benefits, such as reduced capital cost, increased return on investment (ROI), improved overall energy output, and reduced toxic gas emissions. Nevertheless, it is important to identify and prepare for the challenges that may limit the full exploitation of the potential for OWT lifetime extension projects. The objective of this paper is to present a detailed PESTLE analysis to evaluate the various political, economic, sociological, technological, legal, and environmental challenges that must be overcome to successfully implement lifetime extension projects in the offshore wind energy sector. We propose a decision framework for extending the lifetime of OWTs, involving the degradation mechanisms and failure modes of components, remaining useful life estimation processes, safety and structural integrity assessments, economic and environmental evaluations, and the selection of lifetime extension technologies among remanufacturing, retrofitting, and reconditioning. Finally, we outline some of the opportunities that lifetime extension can offer for the wind energy industry to foster a more circular and sustainable economy in the future. Full article

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

► Show Figures

Figure 1

19 pages, 4301 KiB

Open AccessArticle

Load Prediction of Regional Heat Exchange Station Based on Fuzzy Clustering Based on Fourier Distance and Convolutional Neural Network–Bidirectional Long Short-Term Memory Network

by Yuwen You, Zhonghua Wang, Zhihao Liu, Chunmei Guo and Bin Yang

Energies 2024, 17(16), 4190; https://doi.org/10.3390/en17164190 - 22 Aug 2024

Viewed by 354

Abstract

Cogeneration is an important means for heat supply enterprises to obtain heat, and accurate load prediction is particularly crucial. The heat load of a centralized heat supply system is influenced by various factors such as outdoor meteorological parameters, the building envelope structure, and [...] Read more.

Cogeneration is an important means for heat supply enterprises to obtain heat, and accurate load prediction is particularly crucial. The heat load of a centralized heat supply system is influenced by various factors such as outdoor meteorological parameters, the building envelope structure, and regulation control, which exhibit a strong coupling and nonlinearity. It is essential to identify the key variables affecting the heat load at different heating stages through data mining techniques and to use deep learning algorithms to precisely regulate the heating system based on load predictions. In this study, a heat station in a northern Chinese city is taken as the subject of research. We apply the Fuzzy Clustering based on Fourier distance (FCBD-FCM) algorithm to transform the factors influencing the long and short-term load prediction of heat supply from the time domain to the frequency domain. This transformation is used to analyze the degree of their impact on load changes and to extract factors with significant influence as the multifeatured input variables for the prediction model. Five neural network models for load prediction are established, namely, Backpropagation (BP), convolutional neural network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and CNN-BiLSTM. These models are compared and analyzed for their performance in long-term, short-term, and ultrashort-term heating load prediction. The findings indicate that the load prediction accuracy is high when multifeatured input variables are based on fuzzy clustering. Furthermore, the CNN-BiLSTM model notably enhances the prediction accuracy and generalization ability compared to other models, with the Mean Absolute Percentage Error (MAPE) averaging within 3%. Full article

(This article belongs to the Topic Advanced Operation, Control, and Planning of Intelligent Energy Systems)

► Show Figures

Figure 1

42 pages, 4835 KiB

Open AccessReview

Multiparametric Methods for Rapid Classification of Diesel Fuel Quality Used in Automotive Engine Systems

by Michal Borecki, Mateusz Geca, Li Zan, Przemysław Prus and Michael L. Korwin-Pawlowski

Energies 2024, 17(16), 4189; https://doi.org/10.3390/en17164189 - 22 Aug 2024

Viewed by 398

Abstract

Fuels should behave appropriately in all sections of the engine system: the engine, fuel delivery system, and tank. Fuel quality can be linked to the following three crucial areas: performance, fitness for current use, and stability. Classical methods of diesel fuel examination mostly [...] Read more.

Fuels should behave appropriately in all sections of the engine system: the engine, fuel delivery system, and tank. Fuel quality can be linked to the following three crucial areas: performance, fitness for current use, and stability. Classical methods of diesel fuel examination mostly rely on the absolute value measurement of one specific parameter while stabilizing outside conditions. In contrast, multiparametric methods depend on simultaneously measuring a set of parameters. Therefore, multiparametric methods open the possibility of intriguing new examinations and classifications of diesel fuel quality while raising specific issues relating to the instrumentation and construction of sensing devices. This paper presents a review, based on the published literature and the authors’ research, of the current state-of-the-art multiparametric methods for rapid diesel fuel quality classification and related instrumentation, systematizing the various types of methods from the point of view of the principles of their operation. The main conclusion is that different measuring procedures use similar methods of data processing. Moreover, the heavy, costly, and complex devices that enable standard examinations can be converted to simpler devices in the future, whose cost of use is significantly lower. However, to achieve this, progress in electronic devices is required. Full article

(This article belongs to the Special Issue Engine Combustion Characteristics, Performance, and Emission)

► Show Figures

Figure 1

23 pages, 4264 KiB

Open AccessArticle

Waste-to-Energy in the Circular Economy Transition and Development of Resource-Efficient Business Models

by Dzintra Atstaja, Natalija Cudecka-Purina, Viktor Koval, Jekaterina Kuzmina, Janis Butkevics and Hanna Hrinchenko

Energies 2024, 17(16), 4188; https://doi.org/10.3390/en17164188 - 22 Aug 2024

Viewed by 442

Abstract

The consistent rise of the per capita waste generation rate has led to an escalation of waste quantities and the need to expand waste disposal methods. Efforts to develop clean and affordable energy systems are increasingly linked to waste-to-energy as part of the [...] Read more.

The consistent rise of the per capita waste generation rate has led to an escalation of waste quantities and the need to expand waste disposal methods. Efforts to develop clean and affordable energy systems are increasingly linked to waste-to-energy as part of the transition to a circular economy (CE). A resource-efficient waste-to-energy business model within a CE offers a variety of environmentally friendly waste management options based on their overall environmental impacts but also makes efficient use of available resources and technologies to convert different types of waste into energy, which helps reduce the adverse effects on the environment and create additional energy sources. This research aims to identify innovative waste management solutions to foster the implementation of CE and a more resource-efficient business model. The research methodology is based on qualitative and quantitative research, triangulation, material flow assessment, and systems dynamics. The value of this study is within the analysis of existing waste-to-energy plant case studies to identify a set of recommendations and appropriate business models for the countries that are at an early stage of evaluation of such facilities. This study found that waste-to-energy plants are critical to achieving the EU’s waste disposal targets by 2035. The findings highlight the importance of supporting mechanisms in the waste sector, such as structural funds, as the industry primarily focuses on societal health and safety and environmental protection, alongside resource efficiency and circularity potential. Full article

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

► Show Figures

Figure 1

14 pages, 3705 KiB

Open AccessArticle

Medium–Long-Term PV Output Forecasting Based on the Graph Attention Network with Amplitude-Aware Permutation Entropy

by Shuyi Shen, Yingjing He, Gaoxuan Chen, Xu Ding and Lingwei Zheng

Energies 2024, 17(16), 4187; https://doi.org/10.3390/en17164187 - 22 Aug 2024

Viewed by 333

Abstract

Medium–long-term photovoltaic (PV) output forecasting is of great significance to power grid planning, power market transactions, power dispatching operations, equipment maintenance and overhaul. However, PV output fluctuates greatly due to weather changes. Furthermore, it is frequently challenging to ensure the accuracy of forecasts [...] Read more.

Medium–long-term photovoltaic (PV) output forecasting is of great significance to power grid planning, power market transactions, power dispatching operations, equipment maintenance and overhaul. However, PV output fluctuates greatly due to weather changes. Furthermore, it is frequently challenging to ensure the accuracy of forecasts for medium–long-term forecasting involving a long time span. In response to the above problems, this paper proposes a medium–long-term forecasting method for PV output based on amplitude-aware permutation entropy component reconstruction and the graph attention network. Firstly, the PV output sequence data are decomposed by ensemble empirical mode decomposition (EEMD), and the decomposed intrinsic mode function (IMF) subsequences are combined and reconstructed according to the amplitude-aware permutation entropy. Secondly, the graph node feature sequence is constructed from the reconstructed subsequences, and the mutual information of the node feature sequence is calculated to obtain the graph node adjacency matrix which is applied to generate a graph sequence. Thirdly, the graph attention network is utilized to forecast the graph sequence and separate the PV output forecasting results. Finally, an actual measurement system is used to experimentally verify the proposed method, and the outcomes indicate that the proposed method, which has certain promotion value, can improve the accuracy of medium–long-term forecasting of PV output. Full article

(This article belongs to the Special Issue Advances in Integration of Renewable Energy Technologies and Distribution Systems)

► Show Figures

Figure 1

16 pages, 2399 KiB

Open AccessArticle

Doing More with Less: Applying Low-Frequency Energy Data to Define Thermal Performance of House Units and Energy-Saving Opportunities

by Amina Irakoze, Han-Sung Choi and Kee-Han Kim

Energies 2024, 17(16), 4186; https://doi.org/10.3390/en17164186 - 22 Aug 2024

Viewed by 324

Abstract

High-frequency energy data, such as hourly and sub-hourly energy, provide various options for assessing building energy performance. However, the scarcity of such energy data is among the challenges of applying most of the existing energy analysis approaches in large-scale building energy remodeling projects. [...] Read more.

High-frequency energy data, such as hourly and sub-hourly energy, provide various options for assessing building energy performance. However, the scarcity of such energy data is among the challenges of applying most of the existing energy analysis approaches in large-scale building energy remodeling projects. The purpose of this study is to develop a practical method to define the energy performance of residential house units using monthly energy data that are relatively easy to obtain for existing building stock. In addition, based on the defined energy use characteristics, house units are classified, and energy retrofit measures are proposed for energy-inefficient units. In this study, we applied a change-point regression model to investigate the heterogeneity in the monthly gas consumption of 200 house units sampled from four apartment complexes in Ulsan, Republic of Korea. Using a four-quadrant plane and the fitted model parameters, we identified most energy-inefficient house units and their potential energy-saving measures are assessed. The results indicate that around a 41% energy reduction through enhanced thermal properties and heating systems was achieved. The study responds to the need for a straightforward procedure for identifying and prioritizing the best targets for effective energy upgrades of existing buildings. Full article

(This article belongs to the Special Issue Advances in Energy Management and Control for Smart Buildings)

► Show Figures

Figure 1

16 pages, 4341 KiB

Open AccessArticle

Study on the Gas Phase Liquid Carrying Velocity of Deep Coalbed Gas Well with Atomization Assisted Production

by Ruidong Wu, Haidong Wang, Gangxiang Song, Dongping Duan, Chunguang Zhang, Wenjuan Zhu and Yikun Liu

Energies 2024, 17(16), 4185; https://doi.org/10.3390/en17164185 - 22 Aug 2024

Viewed by 326

Abstract

In order to clarify the gas-phase carrying capacity after the atomization of water from the bottom of deep coalbed wells, considering characteristics of atomization-assisted production and the dynamic equilibrium principle of gas–liquid two-phase flow in the wellbore, the gas-phase liquid-carrying drop model was [...] Read more.

In order to clarify the gas-phase carrying capacity after the atomization of water from the bottom of deep coalbed wells, considering characteristics of atomization-assisted production and the dynamic equilibrium principle of gas–liquid two-phase flow in the wellbore, the gas-phase liquid-carrying drop model was established, and the solution method of the upstream and downstream driving force of liquid drop flow was studied. We also verified the theoretical model through physical simulation. Then, the law for the influence of droplet size, wellbore inclination, wellbore diameter, and wellhead back pressure of the critical liquid-carrying velocity in the gas phase is analyzed using the model. The results show the following: ① the larger the diameter of atomized droplets, the greater the gravity force applied to it, the worse the ability to be carried by the gas phase, a onefold increase in droplet diameter corresponds to the increase in the minimum critical velocity of the gas phase by 1.45 times; ② with the increase in wellbore inclination, the liquid-carrying capacity of the gas phase decreases, and the minimum critical liquid-carrying velocity of equal diameter droplets increases by 0.01438 m/s or 1.27 times for the increase in wellbore inclination by 10°; ③ with the increase in wellbore diameter, both the driving force of a droplet of equal diameter and the flow resistance through the gas phase in the wellbore decrease within the range of a driving pressure difference of 0.2 Mpa; the decrease in liquid-carrying velocity caused by the decrease in received flow resistance can reach the maximum value of 0.0473 m/s; ④ with the increase in wellhead back pressure, the driving force of equal-diameter droplets decreases, the resistance against passing through the high-concentration gas phase increases, and the gas-phase-carrying droplets start the game; ⑤ the atomization-assisted production has the function of drainage gas recovery, and the adoption of atomization-assisted production technology can increase the production time of a coalbed gas flowing well, enabling the wells to have a good transition time interval for the conversion of flowing wells to pumping ones, which provides a precise production dynamic basis for the efficient design and implements the overall strategy of drainage gas recovery by deep-well pumping. In short, this technology has the high-efficiency liquid-carrying function of “water atomization to help liquid-phase flow and increase gas production”, as well as obvious technical advantages, which can provide a new idea for the development of deep coalbed methane wells and other types of gas wells with water. Full article

(This article belongs to the Special Issue Advances in the Development of Geoenergy: 2nd Edition)

► Show Figures

Figure 1

17 pages, 7198 KiB

Open AccessArticle

Machine Learning in Cartel Screening—The Case of Parallel Pricing in a Fuel Wholesale Market

by Sylwester Bejger

Energies 2024, 17(16), 4184; https://doi.org/10.3390/en17164184 - 22 Aug 2024

Viewed by 373

Abstract

The detection and deterrence of collusive agreements among firms, such as price-fixing cartels, remain pivotal in maintaining market competition. This study investigates the application of machine learning methodologies in the behavioral screening process for detecting collusion, with a specific focus on parallel pricing [...] Read more.

The detection and deterrence of collusive agreements among firms, such as price-fixing cartels, remain pivotal in maintaining market competition. This study investigates the application of machine learning methodologies in the behavioral screening process for detecting collusion, with a specific focus on parallel pricing behaviors in the wholesale fuel market. By employing unsupervised learning techniques, this research aims to identify patterns indicative of collusion—referred to as collusion markers—within time series data. This paper outlines a comprehensive screening research plan based on the CRISP-DM model, detailing phases from business understanding to monitoring. It emphasizes the significance of machine learning methods, including distance measures, motifs, discords, and semantic segmentation, in uncovering these patterns. A case study of the Polish wholesale fuel market illustrates the practical application of these techniques, demonstrating how anomalies and regime changes in price behavior can signal potential collusion. The findings suggest that unsupervised machine learning methods offer a robust alternative to traditional statistical and econometric tools, particularly due to their ability to process large and complex datasets without predefined models. This research concludes that these methods can significantly enhance the detection of collusive behaviors, providing valuable insights for antitrust authorities. Full article

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

► Show Figures

Figure 1

13 pages, 8131 KiB

Open AccessArticle

Study on Flow Heat Transfer and Particle Deposition Characteristics in a Kettle Reboiler

by Xue Liu, Qi Sun, Hui Tang, Wei Peng, Mingbao Zhang, Gang Zhao and Tairan Fu

Energies 2024, 17(16), 4183; https://doi.org/10.3390/en17164183 - 22 Aug 2024

Viewed by 366

Abstract

A kettle reboiler uses the latent heat from the condensation of high-temperature and high-pressure steam in the tube to produce low-pressure saturated steam in the outer shell. The deposition of particles on the tube may change the boiling heat transfer mode from nucleate [...] Read more.

A kettle reboiler uses the latent heat from the condensation of high-temperature and high-pressure steam in the tube to produce low-pressure saturated steam in the outer shell. The deposition of particles on the tube may change the boiling heat transfer mode from nucleate boiling to natural convection, thereby deteriorating the heat transfer performance of the kettle reboiler. Therefore, it is very important to explore the deposition characteristics of particles in the kettle reboiler. In this study, the RPI boiling model based on the Euler–Euler method is used to analyze the water boiling process on the surface of the tube bundle. The DRW model and critical adhesion velocity model based on the Euler–Lagrangian method are used to calculate the motion of particles during the boiling process and the deposition (rebound) behavior. The results show that the boiling of liquid water enhances the local flow velocity of the fluid, so that the maximum flow velocity appears around the near-wall region. The local high-speed flow disperses the particles in the wake flow of the tube bundle, which inhibits the impact of particles on the wall. As the particle size increases, the wall adhesion and fluid drag on the particles are weakened, and the gravity effect gradually becomes dominant, increasing the residence time of the particles in the tube bundle and the frequency of particle impact on the wall. The particle deposition ratio first decreases and then increases. Ultimately, most particles will be deposited in the low-speed area at the end of the tube bundle. Full article

(This article belongs to the Special Issue Heat Transfer and Multiphase Flow)

► Show Figures

Figure 1

25 pages, 1040 KiB

Open AccessArticle

Optimal Vehicle-to-Grid Strategies for Energy Sharing Management Using Electric School Buses

by Ruengwit Khwanrit, Saher Javaid, Yuto Lim, Chalie Charoenlarpnopparut and Yasuo Tan

Energies 2024, 17(16), 4182; https://doi.org/10.3390/en17164182 - 22 Aug 2024

Viewed by 506

Abstract

In today’s power systems, electric vehicles (EVs) constitute a significant factor influencing electricity dynamics, with their important role anticipated in future smart grid systems. An important feature of electric vehicles is their dual capability to both charge and discharge energy to/from their battery [...] Read more.

In today’s power systems, electric vehicles (EVs) constitute a significant factor influencing electricity dynamics, with their important role anticipated in future smart grid systems. An important feature of electric vehicles is their dual capability to both charge and discharge energy to/from their battery storage. Notably, the discharge capability enables them to offer vehicle-to-grid (V2G) services. However, most V2G research focuses on passenger cars, which typically already have their own specific usage purposes and various traveling schedules. This situation may pose practical challenges in providing ancillary services to the grid. Conversely, electric school buses (ESBs) exhibit a more predictable usage pattern, often deployed at specific times and remaining idle for extended periods. This makes ESBs more practical for delivering V2G services, especially when prompted by incentive price signals from grid or utility companies (UC) requesting peak shaving services. In this paper, we introduce a V2G energy sharing model focusing on ESBs in various schools in a single community by formulating the problem as a leader–follower game. In this model, the UC assumes the role of the leader, determining the optimal incentive price to offer followers for discharging energy from their battery storage. The UC aims to minimize additional costs from generating energy during peak demand. On the other hand, schools in a community possessing multiple ESBs act as followers, seeking the optimal quantity of discharged energy from their battery storage. They aim to maximize utility by responding to the UC’s incentive price. The results demonstrate that the proposed model and algorithm significantly aid the UC in reducing the additional cost of energy generation during peak periods by 36% compared to solely generating all electricity independently. Furthermore, they substantially reduce the utility bills for schools by up to 22.6% and lower the peak-to-average ratio of the system by up to 9.5%. Full article

(This article belongs to the Special Issue Advances in Battery Technologies for Electric Vehicles)

► Show Figures

Figure 1

23 pages, 8186 KiB

Open AccessArticle

On the Influence of H₂ Addition on NH₃ Laminar Flame Speed under Engine-like Conditions

by Flavio Bochicchio, Marco D’Amato, Vinicio Magi and Annarita Viggiano

Energies 2024, 17(16), 4181; https://doi.org/10.3390/en17164181 - 22 Aug 2024

Viewed by 394

Abstract

As zero-carbon fuels, hydrogen and ammonia are of great interest in the transition toward a climate-neutral transportation system. In order to use these fuels and their blends in reciprocating engines, a characterization of the combustion of NH₃/H₂/air mixtures at [...] Read more.

As zero-carbon fuels, hydrogen and ammonia are of great interest in the transition toward a climate-neutral transportation system. In order to use these fuels and their blends in reciprocating engines, a characterization of the combustion of NH₃/H₂/air mixtures at high pressures and temperatures is needed. The aim of this work is to compute the Laminar Flame Speed (LFS) of NH₃/H₂/air mixtures by varying the thermochemical conditions of the reactants. For this purpose, several simulations have been carried out using different kinetic reaction mechanisms. The accuracy of the model has been assessed by comparing the results with experimental data available in the scientific literature. Finally, the influence of mixture composition and thermodynamic conditions of the reactants on LFS has been assessed by considering temperature and pressure values relevant to automotive applications and not yet explored in the literature. By adding H₂ to NH₃/air mixtures, LFS increases exponentially. By plotting the logarithm of LFS as a function of the H₂ mole fraction, the numerical results are well fitted by using a second-degree polynomial regression. However, a linear regression is accurate enough if the H₂ mole fraction does not exceed 0.6. Regarding the effect of pressure, the decrease in LFS with increasing pressure is less important as pressure increases. On the other hand, LFS increases with temperature, and this effect is more pronounced as the H₂ mole fraction decreases and pressure increases. Full article

(This article belongs to the Special Issue Advances in Combustion Strategies and Fuels for Sustainable Energy and Propulsion)

► Show Figures

Figure 1

21 pages, 2628 KiB

Open AccessArticle

A Thermodynamic-Based Black-Box Modeling Approach for the Comprehensive Analysis of Vortex Tube Applications

by Robert Sager, Nils Hendrik Petersen and Manfred Wirsum

Energies 2024, 17(16), 4180; https://doi.org/10.3390/en17164180 - 22 Aug 2024

Viewed by 308

Abstract

To combat climate change successfully, enhancing existing processes is imperative alongside exploring new regenerative technologies. For this purpose, new components must be considered to improve the efficiency of thermodynamic processes. A promising candidate is the Ranque–Hilsch vortex tube due to its low investment [...] Read more.

To combat climate change successfully, enhancing existing processes is imperative alongside exploring new regenerative technologies. For this purpose, new components must be considered to improve the efficiency of thermodynamic processes. A promising candidate is the Ranque–Hilsch vortex tube due to its low investment cost and maintenance. Previous research has highlighted the thermodynamic advantages of employing a vortex tube in various applications, such as Brayton cycles or as a replacement for conventional expansion valves. However, to assess the potential of the vortex tube within a thermodynamic process, a computationally efficient but precise model of the vortex tube is required. Existing modeling approaches often fail to accurately predict experimental trends or require information such as geometry data that are not available for potential analyses. Thus, the present study proposes a novel thermodynamic-based black-box modeling approach: the vortex tube efficiency is introduced by incorporating operating and geometrical conditions into a single parameter. The vortex tube efficiency is systematically investigated for different operating conditions and various fluids and compared with available experimental results. The resulting modeling approach allows the qualitative and quantitative prediction of vortex tube behavior for air at various operating pressures and cold gas fractions. Further experimental investigations are required for a comprehensive quantitative description of vortex tubes with different geometries and working fluids. Full article

(This article belongs to the Section J: Thermal Management)

► Show Figures

Figure 1

26 pages, 11909 KiB

Open AccessArticle

The Influence of Stops on the Selected Route of the City ITS on the Energy Efficiency of the Public Bus

by Miroslaw Smieszek, Vasyl Mateichyk and Jakub Mosciszewski

Energies 2024, 17(16), 4179; https://doi.org/10.3390/en17164179 - 22 Aug 2024

Viewed by 324

Abstract

Public transport is an important part of sustainable economic development, sustainable cities, and communities. Reducing energy consumption in public transport can be achieved through better organisation of the transport system, changes in infrastructure, the use of new energy-efficient means of transport, and other [...] Read more.

Public transport is an important part of sustainable economic development, sustainable cities, and communities. Reducing energy consumption in public transport can be achieved through better organisation of the transport system, changes in infrastructure, the use of new energy-efficient means of transport, and other ways to achieve intelligent mobility. The operation of a city bus involves frequent stops. These stops are due to the need to exchange passengers at bus stops and traffic conditions. Each stop and the subsequent acceleration process require additional energy consumption. In this paper, an analysis of bus operation within the Rzeszów ITS on a selected route is carried out to determine the energy consumption in these special modes. First, the number and duration of stops were determined based on data recorded during the bus operation using the tracker. Then, taking into account the idle fuel consumption and the energy consumption required to reach a set speed, the total energy consumption associated with the stops was determined. The results obtained on the selected route indicate a significant share of energy associated with stops at bus stops and outside bus stops in total fuel consumption. These shares are about 26.2% and about 42.5%, respectively. The opportunity to improve the energy efficiency of the city bus on the route due to the reduction of stops at bus stops by introducing on-demand stops as one of the elements of ITS has been evaluated. The number of stops related to traffic conditions can be reduced by further improving traffic management and measures to modify urban infrastructure. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

► Show Figures

Figure 1

10 pages, 69195 KiB

Open AccessArticle

Size-Dispersed Calcium Phosphate-Based Paints for Sustainable, Durable Cool Roof Applications

by Andrew Caratenuto, Sunny Leung, Nathaniel LeCompte and Yi Zheng

Energies 2024, 17(16), 4178; https://doi.org/10.3390/en17164178 - 22 Aug 2024

Viewed by 382

Abstract

Passive radiative cooling materials are widely recognized as attractive innovations for reducing emissions and expanding life-saving cooling access. Despite immense research attention, the adoption of such technologies is limited largely due to a lack of scalability and cost compatibility with market needs. While [...] Read more.

Passive radiative cooling materials are widely recognized as attractive innovations for reducing emissions and expanding life-saving cooling access. Despite immense research attention, the adoption of such technologies is limited largely due to a lack of scalability and cost compatibility with market needs. While paint and coating-based approaches offer a more sensible solution, many demonstrations suffer from issues such as a low solar reflectance performance or a lack of material sustainability due to the use of harmful solvents. In this work, we demonstrate a passive radiative cooling paint which achieves an extremely high solar reflectance value of 98% using a completely water-based formulation. Material sustainability is promoted by incorporating size-dispersed calcium phosphate biomaterials, which offer broadband solar reflectance, as well as a self-crosslinking water-based binder, providing water resistance and durability without introducing harmful materials. Common industry pigments are integrated within the binder for comparison, illustrating the benefit of finely-tuned particle size distributions for broadband solar reflectance, even in low-refractive-index materials such as calcium phosphates. With scalability, outdoor durability, and eco-friendly materials, this demonstrated paint offers a practical passive radiative cooling approach without exacerbating other environmental issues. Full article

(This article belongs to the Section D1: Advanced Energy Materials)

► Show Figures

Figure 1

17 pages, 3137 KiB

Open AccessArticle

Variability and Sensitivity of Models Used to Estimate Photovoltaic Production

by Nícolas M. F. T. S. Araújo, Susane Eterna Leite Medeiros and Raphael Abrahão

Energies 2024, 17(16), 4177; https://doi.org/10.3390/en17164177 - 22 Aug 2024

Viewed by 323

Abstract

Using renewable energies is one of the alternatives to mitigate climate change. Among them, photovoltaic energy has shown a relevant growth of participation in the electric sector. In the backdrop of such growth, in countries such as Brazil, photovoltaic energy has surpassed the [...] Read more.

Using renewable energies is one of the alternatives to mitigate climate change. Among them, photovoltaic energy has shown a relevant growth of participation in the electric sector. In the backdrop of such growth, in countries such as Brazil, photovoltaic energy has surpassed the generation of electricity by petroleum derivatives since 2019. The significant growth in photovoltaic generation around the world can be attributed to several key factors, including abundant sunlight, supportive government policies, falling solar panel costs, environmental concerns, energy diversification goals, investor interest, job creation, and local manufacturing. However, photovoltaic system performance is heavily tied to weather variability. Different models are used to account for this meteorological dependence; however, there is a gap regarding the differences in the outputs of these models. The study presented here investigates the variability and sensitivity of the models used to estimate photovoltaic production (

P_{p v}

). Six models were compared by percentage difference analysis. Statistical analyses from the perspective of variability revealed that the difference between the

P_{p v}

estimated by these models reaches a 12.89% absolute power difference. Considering that temperature and solar irradiance are the meteorological variables that most influence

P_{p v}

, the sensitivity analysis focused on these. Regarding sensitivity, in the context of temperature changes, the average relative difference in

P_{p v}

between models can reach up to 5.32% for a 10 °C change, while in the context of changes in solar irradiance, the average relative difference can reach up to 19.05% for a change of 41.67 W/m². The consideration of the variability and sensitivity of the main sets of equations used to estimate the potential of photovoltaic energy production can help refine methodologies and assumptions in future research in this area. There are variations and sensitivities, as observed, of such magnitude that, depending on the set of equations adopted in the study, they can alter the conclusion about photovoltaic energy production in a given region. Accurate estimations are pivotal not only for feasibility analyses but also for gauging economic and socio-environmental impacts. These divergences can, in turn, reformulate feasibility analyses and compromise the reliability of photovoltaic energy systems, thus leading to different economic and socio-environmental consequences. Full article

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

► Show Figures

Figure 1

23 pages, 7739 KiB

Open AccessArticle

Techno-Economic Design and Optimization of Hybrid Energy Systems

by Thokozile Mazibuko, Katleho Moloi and Kayode Akindeji

Energies 2024, 17(16), 4176; https://doi.org/10.3390/en17164176 - 22 Aug 2024

Viewed by 555

Abstract

The power generation capacity must be increased to accommodate population growth and address the lack of electricity access in rural areas. Traditional power plants in South Africa are unable to keep up with the growing demand for electricity. By strategically planning and building [...] Read more.

The power generation capacity must be increased to accommodate population growth and address the lack of electricity access in rural areas. Traditional power plants in South Africa are unable to keep up with the growing demand for electricity. By strategically planning and building clusters of renewable energy sources like solar and wind, microgrid operators can provide a sustainable solution that boosts electricity supply while being cost-effective and environmentally friendly. Utilizing renewable energy can help alleviate strain on power plants by reducing peak demand in constrained distribution networks. The benefits of renewable energy include lower electricity expenses, enhanced system reliability, investment reallocation, and reduced environmental impact. These advantages will enhance the efficiency of the power system and contribute economic value to society. However, integrating solar power into the network infrastructure presents challenges such as fundamental changes in network structure, its intermittent nature due to unpredictability, and geographical constraints, which can complicate the task of grid operators in balancing electricity supply and demand within system limits while minimizing costs. The study employs Homer Pro 3.18.1 software to assess the economic costs and benefits of effectively integrating renewable technologies into the power grid. The aim is to evaluate the economic and technical feasibility of investing in renewable energy projects within the network. The research outcomes can guide power system operators, planners, and designers in leveraging solar energy to drive economic growth and industrial advancement, as well as assist independent power producers in making informed investment choices. Full article

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

► Show Figures

Figure 1

22 pages, 4462 KiB

Open AccessArticle

Experimental Investigation of Physicochemical Properties of the Produced Biodiesel from Waste Frying Oil and Its Blend with Diesel Fuel

by Grzegorz Wcisło, Agnieszka Leśniak, Dariusz Kurczyński and Bolesław Pracuch

Energies 2024, 17(16), 4175; https://doi.org/10.3390/en17164175 - 22 Aug 2024

Viewed by 423

Abstract

The imperative of utilising alternative fuels for the operation of internal combustion engines stems from the requirements to reduce the emissions of greenhouse gases and other contaminants, the substantial demand for fuels, and the diminishing reserves of natural resources. The global inclination towards [...] Read more.

The imperative of utilising alternative fuels for the operation of internal combustion engines stems from the requirements to reduce the emissions of greenhouse gases and other contaminants, the substantial demand for fuels, and the diminishing reserves of natural resources. The global inclination towards sustainable development necessitates the employment of biofuels as a substitute for fossil fuels. Nonetheless, the expenditures on raw materials for the manufacture of biodiesel remain substantial, thus underlining the importance of exploring solutions for reducing them. An instance of this could be the utilisation of plant and animal by-products, such as used frying oils and slaughterhouse waste, as feedstock for biodiesel production. Not only will this facilitate the creation of less costly biofuel, but it will also provide an effective solution for the management of post-production waste. The objective of the research delineated in this paper was to ascertain select physicochemical attributes of second-generation biodiesel, derived from spent frying oil, as well as mixtures of this biodiesel with diesel and biodiesel concentrations of 10, 20, and 30% (v/v). The biodiesel produced is the waste frying oil methyl esters WFOME. The proprietary GW-201 reactor was employed in the production of biodiesel. For WFOME biodiesel, DF diesel, and their blends—B10, B20, and B30—properties that influence the formation process of the combustible mixture, autoignition, and combustion of fuel–air mixtures in self-ignition engines were determined. The conducted research has established that “B” type fuels prepared from WFOME and DF present a viable alternative to fossil fuels. Pure biodiesel exhibited a marginally reduced lower heating value, however, in the case of fuel mixtures comprising up to 30% (v/v) biodiesel and diesel, the lower heating values approximated that of diesel. An elevated cetane number alongside an increased flash point of pure B100 biodiesel have been noted. The values of cetane number for WFOME and DF mixtures were found to be either comparable or marginally higher than those of pure DF diesel fuel. Full article

(This article belongs to the Special Issue New Challenges in Waste-to-Energy and Bioenergy Systems)

► Show Figures

Figure 1

22 pages, 4692 KiB

Open AccessArticle

Refining Long Short-Term Memory Neural Network Input Parameters for Enhanced Solar Power Forecasting

by Linh Bui Duy, Ninh Nguyen Quang, Binh Doan Van, Eleonora Riva Sanseverino, Quynh Tran Thi Tu, Hang Le Thi Thuy, Sang Le Quang, Thinh Le Cong and Huyen Cu Thi Thanh

Energies 2024, 17(16), 4174; https://doi.org/10.3390/en17164174 - 22 Aug 2024

Viewed by 433

Abstract

This article presents a research approach to enhancing the quality of short-term power output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) recurrent neural network. Typically, time-related indicators are used as inputs for forecasting models of PV generators. However, this [...] Read more.

This article presents a research approach to enhancing the quality of short-term power output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) recurrent neural network. Typically, time-related indicators are used as inputs for forecasting models of PV generators. However, this study proposes replacing the time-related inputs with clear sky solar irradiance at the specific location of the power plant. This feature represents the maximum potential solar radiation that can be received at that particular location on Earth. The Ineichen/Perez model is then employed to calculate the solar irradiance. To evaluate the effectiveness of this approach, the forecasting model incorporating this new input was trained and the results were compared with those obtained from previously published models. The results show a reduction in the Mean Absolute Percentage Error (MAPE) from 3.491% to 2.766%, indicating a 24% improvement. Additionally, the Root Mean Square Error (RMSE) decreased by approximately 0.991 MW, resulting in a 45% improvement. These results demonstrate that this approach is an effective solution for enhancing the accuracy of solar power output forecasting while reducing the number of input variables. Full article

(This article belongs to the Special Issue Recent Advances in Applications of Smart Grid Technologies)

► Show Figures

Figure 1

16 pages, 1877 KiB

Open AccessArticle

Use of Extended Exergy Analysis to Quantify Advantages and Drawbacks of Decentralizing Industrial Production Lines

by Enrico Sciubba

Energies 2024, 17(16), 4173; https://doi.org/10.3390/en17164173 - 22 Aug 2024

Viewed by 350

Abstract

In the ongoing debate about the feasibility of enforcing a transition to decentralized energy conversion systems, arguments are often presented that lack scientific rigor. Granted, the issue is multi-faceted and fundamentally multi-disciplinary, and possible solutions strongly depend on the selection of location as [...] Read more.

In the ongoing debate about the feasibility of enforcing a transition to decentralized energy conversion systems, arguments are often presented that lack scientific rigor. Granted, the issue is multi-faceted and fundamentally multi-disciplinary, and possible solutions strongly depend on the selection of location as well as on local climate and demographics. Furthermore, decentralizing the final energy distribution leads to potential socio-economic considerations that involve value judgements. However, the most serious problem is that media have appropriated the topic and are often publishing opinion papers authored by non-specialists and even by representatives of interest groups. The present paper proposes an approach that is innovative on two counts: first, it treats “final energy” as any other commodity and therefore expands the field of investigation to the problems arising from the decentralization of a generic production line or technological chain; second, it argues that a method solidly rooted in Thermodynamics, the Extended Exergy Accounting, may be used to quantify the total amount of primary exergy resources requested by a decentralized strategy (as opposed to a centralized one), so that a comparison can be performed and discussed on a rational, unbiased and scientific basis. This is an introductory paper that reports some theoretical results of the method: realistic applications are perforce excluded because the idea is that the procedure must be drafted in such a way to be applicable to different socio-economic scenarios and locations and to remain valid under a broad range of boundary conditions. Full article

(This article belongs to the Special Issue Innovative Approaches in Thermodynamics and Use of Digital Techniques to Promote More Sustainable and More Affordable Final Energy Uses)

► Show Figures

Figure 1

17 pages, 1748 KiB

Open AccessCase Report

Thermoeconomic Evaluation of a High-Performance Solar Biogas Polygeneration System

by José Luciano Batista Moreira, Adriano da Silva Marques, Taynara Geysa Silva do Lago, Victor Carlos de Lima Arruda and Monica Carvalho

Energies 2024, 17(16), 4172; https://doi.org/10.3390/en17164172 - 22 Aug 2024

Viewed by 369

Abstract

Because of the higher efficiencies achieved by polygeneration systems compared with conventional generation systems, they have been increasingly adopted to reduce the consumption of resources and consequent environmental damage. Heat dissipated by equipment can be harnessed and reused in a cascade manner. This [...] Read more.

Because of the higher efficiencies achieved by polygeneration systems compared with conventional generation systems, they have been increasingly adopted to reduce the consumption of resources and consequent environmental damage. Heat dissipated by equipment can be harnessed and reused in a cascade manner. This study applies the Theory of Exergetic Cost (TEC), a thermoeconomic approach, to a high-performance polygeneration system. The system includes a biogas-fueled internal combustion engine, a water–ammonia absorption refrigeration system driven by the engine’s exhaust gases, and a set of photovoltaic panels with a cooling system coupled to solar panels and a hot water storage tank. The pieces of equipment are dimensioned and selected according to the energy demands of a hotel. Then, the temperature, pressure, and energy flows are established for each point of the system. Mass, energy, and exergy balances are developed to determine exergy flows and efficiencies. The main component in terms of exergy and operation costs is the engine, which consumes 0.0613 kg/s of biogas, produces 376.80 kW of electricity, and provides thermal energy for the refrigeration system (101.57 kW) and the hot water tank (232.55 kW), considering the average operating regime throughout the day. The levelized costs are 2.69 USD/h for electricity, 1.70 USD/h for hot water (thermal energy tank), and 1.73 USD/h for chilled water (absorption chiller). The thermoeconomic diagnosis indicated that the hot water tank and the engine are the most sensitive to changes in the maintenance factor. Reducing operating expenses by 20% for the tank and engine lowers energy costs by 10.75% for the tank and 9.81% for the engine. Full article

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

► Show Figures

Figure 1

26 pages, 1407 KiB

Open AccessArticle

Optimal Operation of a Novel Small-Scale Power-to-Ammonia Cycle under Possible Disturbances and Fluctuations in Electricity Prices

by Pascal Koschwitz, Chiara Anfosso, Rafael Eduardo Guedéz Mata, Daria Bellotti, Leon Roß, José Angel García, Jochen Ströhle and Bernd Epple

Energies 2024, 17(16), 4171; https://doi.org/10.3390/en17164171 - 21 Aug 2024

Viewed by 466

Abstract

Power-to-Ammonia (P2A) is a promising technology that can provide a low-emission energy carrier for long-term storage. This study presents an optimization approach to a novel small-scale containerized P2A concept commissioned in 2024. A dynamic nonlinear optimization problem of the P2A concept is set [...] Read more.

Power-to-Ammonia (P2A) is a promising technology that can provide a low-emission energy carrier for long-term storage. This study presents an optimization approach to a novel small-scale containerized P2A concept commissioned in 2024. A dynamic nonlinear optimization problem of the P2A concept is set up, employing the non-commercial MOSAIC^® software V3.0.1 in combination with the NEOS^® server. In total, seven optimization solvers, ANTIGONE^®, CONOPT^®, IPOPT^®, KNITRO^®, MINOS^®, PATHNLP^®, and SNOPT^®, are used. The first and main part of this work optimizes several disturbance scenarios of the concept and aims to determine the optimal reactor temperature profile to counter the disturbances. The optimization results suggest, for example, lowering the reactor temperature profile if the hydrogen and nitrogen inlet streams into the system decrease. The second part of this work presents a crude dynamic optimal scheduling model. This part aims to determine the amount of ammonia to be produced and sold given a randomized price of electricity for three consecutive points in time. The optimization results recommend decreasing production when the price of electricity is high and vice versa. However, the dynamic model must be improved to include fluctuations in the price of ammonia. Then, it can be used as a real-time optimization tool. Full article

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

► Show Figures

Figure 1

18 pages, 6368 KiB

Open AccessArticle

The Current Harmonic Impact on Active Power Losses and Temperature Distribution in Power Cables

by Natalia Radwan-Pragłowska, Dominik Mamcarz, Paweł Albrechtowicz and Bartosz Rozegnał

Energies 2024, 17(16), 4170; https://doi.org/10.3390/en17164170 - 21 Aug 2024

Viewed by 437

Abstract

The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, [...] Read more.

The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, the skin effect occurs, and the current carrying capacity of cables is reduced. This results in the increase in and uneven distribution of the temperature inside the conductor. This paper presents a comparison of the temperature distribution inside a power cable for an ideal 50 Hz sine wave and highly distorted current

(T H D_{I} = 41 %)

. The calculated active power losses for the IEC 60287-1-1:2006+A1:2014 standard and the method described in the literature were used as a basis for further calculations. The obtained results revealed the problem of the uneven distribution of the conductor temperature. Considering the skin effect, increasing the temperature in the outer layers leads to severe damage and faster insulation aging. The abovementioned phenomenon is a decrease in the permissible load capacity of the conductor. The table given in the IEC 60364-5-52 standard summarizes the percentage contribution of the third harmonic to the current waveform. For percentages between 15% and 33%, the current carrying capacity is reduced by up to 86% of the full-load current rating. In addition, consideration of thermal conditions forces the use of cables with larger cross-sections. This leads to their non-optimal use and makes the investment more expensive from an economic point of view. Full article

(This article belongs to the Special Issue Energy, Electrical and Power Engineering 2024)

► Show Figures

Figure 1

21 pages, 57556 KiB

Open AccessArticle

Simulation Study on the Heat Transfer Characteristics of Oil Shale under Different In Situ Pyrolysis Methods Based on CT Digital Rock Cores

by Yuxing Zhang and Dong Yang

Energies 2024, 17(16), 4169; https://doi.org/10.3390/en17164169 - 21 Aug 2024

Viewed by 463

Abstract

To analyze the heat transfer characteristics of oil shale under different in situ pyrolysis methods from a microscopic perspective, a combination of experimental and simulation approaches was employed. Initially, high-temperature in situ pyrolysis experiments on single-fracture oil shale were conducted using high-temperature steam [...] Read more.

To analyze the heat transfer characteristics of oil shale under different in situ pyrolysis methods from a microscopic perspective, a combination of experimental and simulation approaches was employed. Initially, high-temperature in situ pyrolysis experiments on single-fracture oil shale were conducted using high-temperature steam and electrical methods. Subsequently, micro-CT scanning technology was utilized to obtain digital rock cores under different in situ pyrolysis conditions. Finally, these digital rock cores were seamlessly integrated with COMSOL 6.0 to achieve numerical simulations of high-temperature steam convective heating and electrical conductive heating in the in situ state. The relevant conclusions are as follows: Firstly, during the in situ pyrolysis of oil shale with high-temperature steam convective heating, the overall temperature increase is uniform and orderly. Heat is conducted gradually from the pores and fractures to the matrix. The uneven distribution of pores and fractures causes an uneven temperature field, but no localized overheating occurs, which can effectively enhance the pyrolysis efficiency. Secondly, the heat transfer direction in electrical conductive heating is primarily inward along the normal direction of the heat source end face. The closer the section is to the heat source end face, the higher the rate of temperature increase. Within 1 s, the temperature rise at 100 μm (near the heat source end face) is 2.27 times that at 500 μm (near the farthest cross-section from the heat source end face). The heat transfer effect of high-temperature steam convective heating consistently surpasses that of electrical conductive heating. The T_c value initially increases and then decreases as pyrolysis progresses, reaching a maximum of 1.61331 at 0.4 s, but T_c remains greater than 1 throughout. Finally, in the initial stages of pyrolysis, the high-temperature region formed by conductive heating is superior to that of convective heating. However, once the heat carrier fluid flow stabilizes, the volume of the high-temperature region formed by convective heating grows rapidly compared to that of conductive heating. At 1 s, the volume of the high-temperature region formed by convective heating reaches 5.22 times that of the high-temperature region formed by conductive heating. Full article

(This article belongs to the Special Issue Recent Advances in Oil Shale Conversion Technologies)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Energies, Volume 17, Issue 16 (August-2 2024) – 336 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI