Energies

14 pages, 5770 KiB

Open AccessArticle

Study of Blockage Effects of Metro Train on Critical Velocity in Sloping Subway Tunnel Fires with Longitudinal Ventilation

by Haitao Wang and Huanhuan Gao

Energies 2022, 15(15), 5762; https://doi.org/10.3390/en15155762 - 8 Aug 2022

Cited by 7 | Viewed by 2294

Abstract

Critical velocity is very important for smoke control in longitudinally ventilated subway tunnel fires. Numerical investigations are conducted in this paper to study the impacts of metro train blockages on critical velocity in sloping subway tunnel fires by using fire dynamics simulator (FDS) [...] Read more.

Critical velocity is very important for smoke control in longitudinally ventilated subway tunnel fires. Numerical investigations are conducted in this paper to study the impacts of metro train blockages on critical velocity in sloping subway tunnel fires by using fire dynamics simulator (FDS) tunnel models validated with the field-experiment data. Moreover, a global model of critical velocity is presented for the blocked zone of a metro train in subway tunnel fires including influencing factors of the blockage ratio and tunnel slope. The results show that the reduction ratio of critical velocity in the blocked zone is less than the metro-train blockage ratio. The correction factor between the critical velocity reduction ratio and metro-train blockage ratio is 0.545. The aerodynamic shadow zone downstream of a subway train blockage has important impacts on the critical velocity. The critical velocity in the unblocked zone of a metro train is higher than that in the blocked zone of a metro train blockage. The reason is that smoke flow is hindered by the metro train blockage in subway tunnel fires. With an increase in the blockage–fire source distance, the critical velocity first decreases and then tends to be constant. The global model presented can accurately predict the critical velocity in a sloping subway tunnel with a train blockage. The results may provide beneficial suggestions for designing ventilation systems for subway tunnels. Full article

(This article belongs to the Special Issue Experiments and Simulations of Combustion Process)

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19 pages, 2736 KiB

Open AccessArticle

A Comparative Method for Assessment of Sustainable Energy Development across Regions: An Analysis of 30 Provinces in China

by Jiayang Chen, Ying Kong, Shunyong Yin and Jianjun Xia

Energies 2022, 15(15), 5761; https://doi.org/10.3390/en15155761 - 8 Aug 2022

Cited by 5 | Viewed by 1851

Abstract

Sustainable energy development (SED) has attracted the attention of the whole world. It has a wide range of concepts and rich connotations, which is difficult to be described with a single indicator. Therefore, scholars usually use multiple indicators to evaluate SED in multiple [...] Read more.

Sustainable energy development (SED) has attracted the attention of the whole world. It has a wide range of concepts and rich connotations, which is difficult to be described with a single indicator. Therefore, scholars usually use multiple indicators to evaluate SED in multiple dimensions. Existing studies mostly took countries as the research objects, and there were fewer studies on sub-regions (provincial-level regions). In fact, due to factors such as resource endowment and industrial structure, there would be obvious differences in the energy system of different regions even within a country, such as China. This study took 30 provinces in China from 2010 to 2019 as the research object, and constructed a provincial-level SED evaluation system. Analytical methods of indicator contribution were also proposed to evaluate the improvement of specific indicators and their contribution to SED on both spatial and temporal scales. The findings could help identify where provinces are doing well or poorly in SED, thereby clarifying priorities for future improvements. Full article

(This article belongs to the Special Issue Sustainable Management of Energy Resources, Energy Strategies and Climate Change)

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14 pages, 1575 KiB

Open AccessArticle

MILP-Based Profit Maximization of Electric Vehicle Charging Station Based on Solar and EV Arrival Forecasts

by Andu Dukpa and Boguslaw Butrylo

Energies 2022, 15(15), 5760; https://doi.org/10.3390/en15155760 - 8 Aug 2022

Cited by 21 | Viewed by 4374

Abstract

Electric vehicles (EVs) will be dominating the modes of transport in the future. Current limitations discouraging the use of EVs are mainly due to the characteristics of the EV battery and lack of easy access to charging stations. Charging schedules of EVs are [...] Read more.

Electric vehicles (EVs) will be dominating the modes of transport in the future. Current limitations discouraging the use of EVs are mainly due to the characteristics of the EV battery and lack of easy access to charging stations. Charging schedules of EVs are usually uncoordinated, whereas coordinated charging offers several advantages, including grid stability. For a solar photovoltaic (PV)-based charging station (CS), optimal utilization of solar power results in an increased revenue and efficient utilization of related equipment. The solar PV and the arrival of EVs for charging are both highly stochastic. This work considers the solar PV forecast and the probability of EV arrival to optimize the operation of an off-grid, solar PV-based commercial CS with a battery energy storage system (BESS) to realize maximum profit. BESS supports the sale of power when the solar PV generation is low and subsequently captures energy from the solar PV when the generation is high. Due to contrasting characteristics of the solar PV and EV charging pattern, strategies to maximize the profit are proposed. One such strategy is to optimally size the BESS to gain maximum profit. A mixed integer linear programming (MILP) method is used to determine the optimal solution. Full article

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Graphical abstract

15 pages, 1393 KiB

Open AccessReview

Review on Boiling Heat Transfer Enhancement Techniques

by Chandan Swaroop Meena, Ashwani Kumar, Sanghati Roy, Alessandro Cannavale and Aritra Ghosh

Energies 2022, 15(15), 5759; https://doi.org/10.3390/en15155759 - 8 Aug 2022

Cited by 42 | Viewed by 5595

Abstract

Boiling is considered an important mode of heat transfer (HT) enhancement and has several industrial cooling applications. Boiling has the potential to minimize energy losses from HT devices, compared with other convection or conduction modes of HT enhancement. The purpose of this review [...] Read more.

Boiling is considered an important mode of heat transfer (HT) enhancement and has several industrial cooling applications. Boiling has the potential to minimize energy losses from HT devices, compared with other convection or conduction modes of HT enhancement. The purpose of this review article was to analyze, discuss, and compare existing research on boiling heat transfer enhancement techniques from the last few decades. We sought to understand the effect of nucleation sites on plain and curved surfaces and on HT enhancement, to suggest future guidelines for researchers to consider. This would help both research and industry communities to determine the best surface structure and surface manufacturing technique for a particular fluid. We discuss pool boiling HT enhancement, and present conclusions and recommendations for future research. Full article

(This article belongs to the Special Issue Heat Transfer Enhancement and Fluid Flow Features Due to the Addition of Nanoparticles in Engineering Applications)

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26 pages, 1536 KiB

Open AccessArticle

Environmental and Energy Conditions in Sustainable Regional Development

by Brygida Klemens, Brygida Solga, Krystian Heffner and Piotr Gibas

Energies 2022, 15(15), 5758; https://doi.org/10.3390/en15155758 - 8 Aug 2022

Cited by 1 | Viewed by 2003

Abstract

Climate change is taking place on a global scale and it is substantially affected by human activity, including increasing greenhouse gas emissions. One of the thematic objectives of EU’s new financial objective is a more environmentally friendly low-emission Europe that promotes clean and [...] Read more.

Climate change is taking place on a global scale and it is substantially affected by human activity, including increasing greenhouse gas emissions. One of the thematic objectives of EU’s new financial objective is a more environmentally friendly low-emission Europe that promotes clean and fair energy transformation, green investments, and a circular economy, among others. The Polish economy is mainly based on energy production from conventional sources (fossil fuels). Considering that the demand for electricity in Poland is predicted to increase by as much as 50% until 2040, it is necessary to take action aimed at increasing the share of renewable energy sources. The subject of analysis is the Opolskie Voivodeship (a NUTS 2 type region), the capital of which features the biggest Polish coal power plant. In 2014–2019, it was expanded by two units with 1800 MW in total capacity, thereby indicating that investments in energy obtained from conventional sources are still implemented and to a large extent at that (the expansion has been the biggest infrastructural investment in Poland since 1989). The Opolskie region is characterised by substantial excess in acceptable environmental burden (dust pollution, among others). The aim of the paper is to evaluate the key environmental conditions for the Opolskie region’s development in terms of the assumptions of the domestic and EU energy policies. The Opolskie region’s developmental challenges in the environmental area were determined on the basis of selected indicator estimations up to 2030. The research hypothesis assumes that the environmental conditions for the Opolskie region’s development are unfavourable. The methodological part features an analysis of the cause and effect dependencies in the “environment” area, which enabled an assessment of the Opolskie Voivodeship’s current situation as well as an analysis of the dependencies relevant to the region’s development. This was followed by an estimation of selected indicators in the “environment” area until 2030, which allowed for an assessment of their probable levels and thereby a specification of the region’s development conditions. The estimation was conducted using the data available in public statistics, i.e., Statistics Poland’s data. The indicators estimated for 2030 were presented using three forecasting methods: (a) the monotonic trend, (b) the yearly average change rate, and (c) the logarithmic trend. Full article

(This article belongs to the Special Issue Sustainable Development, Energy Economics and Economic Analysis)

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11 pages, 1974 KiB

Open AccessArticle

Analysis of the Impact of Propanol-Gasoline Blends on Lubricant Oil Degradation and Spark-Ignition Engine Characteristics

by Muhammad Kashif Jamil, Maaz Akhtar, Muhammad Farooq, Muhammad Mujtaba Abbas, Saad, Muhammad Khuzaima, Khurshid Ahmad, Md Abul Kalam and Anas Abdelrahman

Energies 2022, 15(15), 5757; https://doi.org/10.3390/en15155757 - 8 Aug 2022

Cited by 3 | Viewed by 2424

Abstract

Alcoholic fuels have recently come to light as a sustainable source for powering today’s vehicles. Various studies have investigated the effects of alcoholic fuels on engine efficiency and emission characteristics. However, scarce literature is available for their effects on lubricant. Therefore, propanol-gasoline fuel [...] Read more.

Alcoholic fuels have recently come to light as a sustainable source for powering today’s vehicles. Various studies have investigated the effects of alcoholic fuels on engine efficiency and emission characteristics. However, scarce literature is available for their effects on lubricant. Therefore, propanol-gasoline fuel mixtures, with concentrations of 9% (P9) and 18% (P18) propanol, were made to compare their engine characteristics and lubricating oil condition with that of pure gasoline (0 percent propanol (P0)). To determine the rate of deterioration, the characteristics of the lubricating oil were evaluated after 100 h of engine operation, as suggested by the manufacturer. When compared with unused lube oil, P18 showed reductions in flash point temperature and kinematic viscosity of 14% and 36%, respectively, at 100 °C. For P18, which contains Fe (27 PPM), Al (11 PPM), and Cu (14 PPM), the highest wear element concentrations in the lubricating oil were found. The moisture in the degraded oil was well within the allowable limit for the three fuel mixtures. With the increase in propanol percentage in the propanol-gasoline blend, the engine performance was increased. Compared to P9 and P0, P18 had the partially unburned emissions. Full article

(This article belongs to the Special Issue Thermal Power Systems and Alternative Energy)

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14 pages, 3845 KiB

Open AccessArticle

Medium-Voltage Distribution Network Parameter Optimization Using a Thyristor Voltage Regulator

by Elena Sosnina, Aleksey Kralin, Anatoly Asabin and Evgeny Kryukov

Energies 2022, 15(15), 5756; https://doi.org/10.3390/en15155756 - 8 Aug 2022

Cited by 2 | Viewed by 2048

Abstract

The article is devoted to the study of steady-state conditions of a distribution network containing a thyristor voltage regulator. The thyristor voltage regulator (TVR) is a new controlled semiconductor device developed at Nizhny Novgorod State Technical University n.a. R.E. Alekseev (NNSTU). The TVR [...] Read more.

The article is devoted to the study of steady-state conditions of a distribution network containing a thyristor voltage regulator. The thyristor voltage regulator (TVR) is a new controlled semiconductor device developed at Nizhny Novgorod State Technical University n.a. R.E. Alekseev (NNSTU). The TVR allows the optimization of the parameters of 6–20 kV distribution networks (currents and voltages) by voltage regulation. An analytical calculation of electromagnetic processes of a distribution network with the TVR has been carried out. The verification of the obtained results has been made using a computer simulation. The dependences of the current and power on additional voltage introduced by the TVR under different voltage regulation modes have been obtained. It has been shown that the use of the TVR enables optimal flow distribution to be ensured over the power transmission lines in proportion to their transfer capability when changing load power and its power factor. Full article

(This article belongs to the Special Issue Smart Solutions and Devices for the Power Industry)

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14 pages, 3934 KiB

Open AccessArticle

Experimental Study on the Sweep Law of CO₂ Miscible Flooding in Heterogeneous Reservoir in Jilin

by Wen Li, Hongwei Yu, Zhengming Yang, Jinlong Li, Xinliang Chen and Longfei Ma

Energies 2022, 15(15), 5755; https://doi.org/10.3390/en15155755 - 8 Aug 2022

Cited by 6 | Viewed by 1974

Abstract

It is very important to effectively describe the sweep characteristics of CO₂ miscible flooding based on physical models for actual reservoir development. In this study, based on the geological characteristics of the Jilin ultra-low permeability reservoir, which has significant vertical heterogeneity, a [...] Read more.

It is very important to effectively describe the sweep characteristics of CO₂ miscible flooding based on physical models for actual reservoir development. In this study, based on the geological characteristics of the Jilin ultra-low permeability reservoir, which has significant vertical heterogeneity, a two-dimensional double-layer heterogeneous visualization model with a permeability contrast of 10 and thickness contrast of 2 was designed to perform experimental research on the sweep law of CO₂ miscible flooding with an injection-production mode of “united injection and single production”. With the goal of determining the obvious differences in the gas absorption capacity and displacement power of the two layers, the CO₂ dynamic miscible flooding characteristics were comprehensively analyzed, and the sweep law of CO₂ miscible flooding, including the oil and gas flow trend, migration direction of the oil–gas interface, and distribution characteristics of the miscible zone, was further studied in combination with the oil displacement effect. In this experiment, the gas absorption capacity was the key factor affecting the sweep efficiency of the CO₂ miscible flooding. Under the combined influence of the internal and external control factors of the reservoir thickness, permeability, and injection-production mode, the gas absorption capacity of the high-permeability layer was much greater than that of the low-permeability layer, resulting in the retention of a large amount of remaining oil in the low-permeability layer, which effectively displaced and swept the oil in the high-permeability layer. The gas absorption capacity of the reservoir, gravitational differentiation, and miscible mass transfer were key factors affecting the migration of the oil–gas interface and distribution of the miscible zone. The entire displacement process could be divided into three stages: ① The gas-free rapid oil production stage, which was dominated by the displacement; ② the low gas–oil ratio stable oil production stage, which was jointly affected by the displacement and miscible mass transfer; and ③ the high gas–oil ratio slow oil production stage, which was dominated by the effect of CO₂ carrying. Full article

(This article belongs to the Topic Porous Flow of Energy & CO₂ Transformation and Storage in Deep Formations)

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Graphical abstract

24 pages, 12630 KiB

Open AccessArticle

Implementation and Design of FREEDM System Differential Protection Method Based on Internet of Things

by Ahmed Y. Hatata, Mohamed A. Essa and Bishoy E. Sedhom

Energies 2022, 15(15), 5754; https://doi.org/10.3390/en15155754 - 8 Aug 2022

Cited by 6 | Viewed by 2211

Abstract

This paper introduces an enhancement of the protection and operation of the Future Renewable Electric Energy Delivery and Management (FREEDM) system. It uses the solid-state transformers to connect the residential A.C. and D.C. microgrids to the distribution system and fault isolation devices for [...] Read more.

This paper introduces an enhancement of the protection and operation of the Future Renewable Electric Energy Delivery and Management (FREEDM) system. It uses the solid-state transformers to connect the residential A.C. and D.C. microgrids to the distribution system and fault isolation devices for faulty line isolation. In this paper, a current differential protection scheme has been proposed to detect faults in the FREEDM-based microgrid network. This method is based on the current measurement at the two-line terminals using phasor measurement units to ensure data synchronization and minimize the measuring error. Also, a communication scheme that is based on the Internet of things technology and Wi-Fi is constructed for data monitoring and interlinking between the relays, transducers, and the fault isolation devices in the two-terminals lines. A hypothetical FREEDM system has been used for the verification and testing of the proposed method. Different fault types at different locations and fault resistances have been applied to prove the effectiveness of the proposed protection method in detecting the fault condition. The performance of the proposed method is investigated using the security, dependability, and accuracy indices. A prototype of the FREEDM system is designed, implemented, and tested using the Proteus software simulator and in the laboratory. The results prove the efficiency of the proposed protection method in detecting and isolating the fault conditions in a fast, reliable, and accurate manner. Moreover, the protection scheme achieved high accuracy for all faults, equal to 98.825%. Full article

(This article belongs to the Special Issue Modern Technologies for Renewable Energy Development and Utilization)

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29 pages, 6702 KiB

Open AccessReview

Tunnel Oxide Deposition Techniques and Their Parametric Influence on Nano-Scaled SiO_x Layer of TOPCon Solar Cell: A Review

by Hasnain Yousuf, Muhammad Quddamah Khokhar, Muhammad Aleem Zahid, Matheus Rabelo, Sungheon Kim, Duy Phong Pham, Youngkuk Kim and Junsin Yi

Energies 2022, 15(15), 5753; https://doi.org/10.3390/en15155753 - 8 Aug 2022

Cited by 5 | Viewed by 7396

Abstract

In addition to the different technologies of silicon solar cells in crystalline form, TOPCon solar cells have an exceptionally great efficiency of 26%, accomplished by the manufacturing scale technique for industrialization, and have inordinate cell values of 732.3 mV open-circuit voltage (V_oc [...] Read more.

In addition to the different technologies of silicon solar cells in crystalline form, TOPCon solar cells have an exceptionally great efficiency of 26%, accomplished by the manufacturing scale technique for industrialization, and have inordinate cell values of 732.3 mV open-circuit voltage (V_oc) and a fill factor (FF) of 84.3%. The thickness of tunnel oxide, which is less than 2 nm in the TOPCon cell, primarily affects the electrical properties and efficiency of the cell. In this review, various techniques of deposition were utilized for the layer of SiO_x tunnel oxide, such as thermal oxidation, ozone oxidation, chemical oxidation, and plasma-enhanced chemical vapor deposition (PECVD). To monitor the morphology of the surface, configuration of annealing, and rate of acceleration, a tunnel junction structure of oxide through a passivation quality of better V_oc on a wafer of n-type cell might be accomplished. The passivation condition of experiments exposed to rapid thermal processing (RTP) annealing at temperatures more than 900 °C dropped precipitously. A silicon solar cell with TOPCon technology has a front emitter with boron diffusion, a tunnel-SiO_x/n⁺-poly-Si/ SiN_x:H configuration on the back surface, and electrodes on both sides with screen printing technology. The saturation current density (J₀) for such a configuration on a refined face remains at 1.4 fA/cm² and is 3.8 fA/cm² when textured surfaces of the cell are considered, instead of printing with silver contacts. Following the printing of contacts with Ag, the J₀ of the current configuration improves to 50.8 fA/cm² on textured surface of silicon, which is moderately lesser for the metal contact. Tunnel oxide layers were deposited using many methods such as chemical, ozone, thermal, and PECVD oxidation are often utilized to deposit the thin SiO_x layer in TOPCon solar cells. The benefits and downsides of each approach for developing a SiO_x thin layer depend on the experiment. Thin SiO_x layers may be produced using HNO₃:H₂SO₄ at 60 °C. Environmentally safe ozone oxidation may create thermally stable SiO_x layers. Thermal oxidation may build a tunnel oxide layer with low surface recombination velocity (10 cm/s). PECVD oxidation can develop SiO_x on several substrates at once, making it cost-effective. Full article

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8 pages, 211 KiB

Open AccessEditorial

Editorial for the Special Issue “Verifying the Targets—Selected Papers from the 55th International Universities Power Engineering Conference (UPEC 2020)”

by Gianfranco Chicco, Andrea Mazza, Salvatore Musumeci, Enrico Pons and Angela Russo

Energies 2022, 15(15), 5752; https://doi.org/10.3390/en15155752 - 8 Aug 2022

Viewed by 1354

Abstract

The 55th International Universities Power Engineering Conference (UPEC 2020) has been held on 1–4 September 2020 in the Virtual Conference mode because of the limitations due to the pandemics, hosted by Politecnico di Torino, Torino, Italy [...] Full article

(This article belongs to the Special Issue Verifying the Targets—Selected Papers from the 55th International Universities Power Engineering Conference (UPEC 2020))

5 pages, 193 KiB

Open AccessEditorial

Energy in Smart Urban Transportation with Systemic Use of Electric Vehicles

by Grzegorz Karoń

Energies 2022, 15(15), 5751; https://doi.org/10.3390/en15155751 - 8 Aug 2022

Cited by 8 | Viewed by 1502

Abstract

In the progressive development of Electric Vehicles (EVs) and the transformation of transport towards electromobility and decarbonization of cities, many different problems are being faced related to energy management in transport in smart cities [...] Full article

10 pages, 2090 KiB

Open AccessArticle

Effect of Temperature Conditions in Arctic Offshore Oil Fields on the Rheological Properties of Various Based Drilling Muds

by Ekaterina Leusheva and Valentin Morenov

Energies 2022, 15(15), 5750; https://doi.org/10.3390/en15155750 - 8 Aug 2022

Cited by 6 | Viewed by 2135

Abstract

During well drilling in offshore conditions beyond the North of the Arctic Circle, there are often problems associated with deviations in the rheological parameters of the drilling mud as the temperature changes. Mud temperature in the upper part of the well in most [...] Read more.

During well drilling in offshore conditions beyond the North of the Arctic Circle, there are often problems associated with deviations in the rheological parameters of the drilling mud as the temperature changes. Mud temperature in the upper part of the well in most cases is in the range up to 20 °C, whereas in the productive formation it is up to 80 °C and more. For such conditions, it is necessary to estimate the influence of temperature on the rheological parameters of drilling fluids, which is done in this paper. Compositions of water-based and hydrocarbon-based muds that may be used in the conditions of the offshore hydrocarbon fields were considered. The paper presents the authors’ formula for a drilling mud that possesses more stable rheological parameters in the temperature conditions of the offshore oil field and is more environmentally friendly. The physical properties of the newly designed drilling mud were measured with laboratory equipment. Rheological investigations were carried out under varying temperatures up to 80 °C. The results of the experiments show the newly designed drilling mud to be more stable than its hydrocarbon-based analogue. Besides, the newly developed composition has a lower content of solid phase, which is also an important parameter for the process of sea wells construction, often characterized by a narrow window of permissible pressure. Full article

(This article belongs to the Special Issue Advances in Techniques of Construction, Development and Operation of Oil and Gas Wells)

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33 pages, 11151 KiB

Open AccessArticle

Intelligent Action Planning for Well Construction Operations Demonstrated for Hole Cleaning Optimization and Automation

by Gurtej Singh Saini, Parham Pournazari, Pradeepkumar Ashok and Eric van Oort

Energies 2022, 15(15), 5749; https://doi.org/10.3390/en15155749 - 8 Aug 2022

Cited by 6 | Viewed by 2606

Abstract

Reactive and biased human decision-making during well construction operations can result in problems ranging from minor inefficiencies to events that can have far-reaching negative consequences for safety, environmental compliance and cost. A system that can automatically generate an optimal action sequence from any [...] Read more.

Reactive and biased human decision-making during well construction operations can result in problems ranging from minor inefficiencies to events that can have far-reaching negative consequences for safety, environmental compliance and cost. A system that can automatically generate an optimal action sequence from any given state to meet an operation’s objectives is therefore highly desirable. Moreover, an intelligent agent capable of self-learning can offset the computation and memory costs associated with evaluating the action space, which is often vast. This paper details the development of such action planning systems by utilizing reinforcement learning techniques. The concept of self-play used by game AI engines (such as AlphaGo and AlphaZero in Google’s DeepMind group) is adapted here for well construction tasks, wherein a drilling agent learns and improves from scenario simulations performed using digital twins. The first step in building such a system necessitates formulating the given well construction task as a Markov Decision Process (MDP). Planning is then accomplished using Monte Carlo tree search (MCTS), a simulation-based search technique. Simulations, based on the MCTS’s tree and rollout policies, are performed in an episodic manner using a digital twin of the underlying task(s). The results of these episodic simulations are then used for policy improvement. Domain-specific heuristics are included for further policy enhancement, considered factors such as trade-offs between safety and performance, the distance to the goal state, and the feasibility of taking specific actions from specific states. We demonstrate our proposed action planning system for hole cleaning, a task which to date has proven difficult to optimize and automate. Comparing the action sequences generated by our system to real field data, it is shown that it would have resulted in significantly improved hole cleaning performance compared to the action taken in the field, as quantified by the final state reached and the long-term reward. Such intelligent sequential decision-making systems, which use heuristics and exploration–exploitation trade-offs for optimum results, are novel applications in well construction and may pave the way for the automation of tasks that until now have been exclusively controlled by humans. Full article

(This article belongs to the Topic Drilling, Completion and Well Engineering for the Natural Energy Resources Extraction, Storage and Sustainable Management)

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29 pages, 12302 KiB

Open AccessArticle

Geochemical Characteristics and Environmental Implications of Trace Elements of the Paleocene in the West Lishui Sag, East China Sea Basin

by Shuai Yang, Qiang Fu, Jinshui Liu, Wenrui Ma, Bing Yang, Zhiwei Zhu and Wen Teng

Energies 2022, 15(15), 5748; https://doi.org/10.3390/en15155748 - 8 Aug 2022

Cited by 3 | Viewed by 1848

Abstract

Analysis of the sedimentary environment during the clastic formation process is of great significance for reservoir evaluation and desert prediction. This paper focused on the Paleocene in the West Lishui Sag, East China Sea Basin. XRF fluorescence diffraction and carbon and oxygen isotope [...] Read more.

Analysis of the sedimentary environment during the clastic formation process is of great significance for reservoir evaluation and desert prediction. This paper focused on the Paleocene in the West Lishui Sag, East China Sea Basin. XRF fluorescence diffraction and carbon and oxygen isotope tests were carried out on core samples from four wells. Based on the geochemical characteristics of the samples and the changes in the elemental ratios, combined with the lithologic characteristics and sedimentary structure of the samples, the paleoclimate, paleosalinity, paleobathymetric, paleoredox, paleotemperature, and other paleoenvironmental characteristics were analyzed. The results show that the characteristics of major and trace elements were similar in the lower Mingyuefeng Formation (E₁m²), Upper Lingfeng Formation (E₁l¹), Lower Lingfing Formation (E₁l²), and Yueguifeng Formation (E₁y). The Paleocene in the West Lishui Sag was mainly in the reducing environment of brackish-salt water with weak water stratification. The water depth showed a trend of becoming deeper, then shallower, and then deeper. The paleoclimate in the West Lishui Sag was warm on the whole. However, the content of Sr became smaller after later deposition, so the calculated paleowater temperature was higher. In addition, oxygen isotopes were affected by diagenesis, resulting in a negative oxygen isotope value. The paleoproductivity was low, and the hydrocarbon generation potential was poor. The content of nutrient elements mainly came from terrigenous input rather than biological origin, and terrigenous intrusion characteristics gradually increased from E₁y to E₁m². The study also shows that paleoproductivity was affected by the paleoclimate and paleowater depth. Warm and humid climate and deep water body were conducive to the accumulation of paleoproductivity. Full article

(This article belongs to the Section H1: Petroleum Engineering)

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15 pages, 7058 KiB

Open AccessArticle

Numerical Demonstration of Unsupervised-Learning-Based Noise Reduction in Two-Dimensional Rayleigh Imaging

by Minnan Cai, Hua Jin, Beichen Lin, Wenjiang Xu and Yancheng You

Energies 2022, 15(15), 5747; https://doi.org/10.3390/en15155747 - 8 Aug 2022

Cited by 1 | Viewed by 1851

Abstract

The conventional denoising method in Rayleigh imaging in a general sense requires an additional hardware investment and the use of the underlying physics. This work demonstrates an alternative image denoising reconstruction model based on unsupervised learning that aims to remove Mie scattering and [...] Read more.

The conventional denoising method in Rayleigh imaging in a general sense requires an additional hardware investment and the use of the underlying physics. This work demonstrates an alternative image denoising reconstruction model based on unsupervised learning that aims to remove Mie scattering and shot noise interference from two-dimensional (2D) Rayleigh images. The model has two generators and two discriminators whose parameters can be trained with either feature-paired or feature-unpaired data independently. The proposed network was extensively evaluated with a qualitative examination and quantitative metrics, such as PSNR, ER, and SSIM. The results demonstrate that the feature-paired training network exhibits a better performance compared with several other networks reported in the literature. Moreover, when the flame features are not paired, the feature-unpaired training network still yields a good agreement with ground truth data. Specific indicators of the quantitative evaluation show a promising denoising ability with a peak signal-to-noise ratio of ~37 dB, an overall reconstruction error of ~1%, and a structure similarity index of ~0.985. Additionally, the pre-trained unsupervised model based on unpaired training can be generalized to denoise Rayleigh images with extra noise or a different Reynolds number without updating the model parameters. Full article

(This article belongs to the Special Issue Recent Advances in Thermofluids, Combustion and Energy Systems)

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19 pages, 1351 KiB

Open AccessArticle

Volume-of-Fluid Based Finite-Volume Computational Simulations of Three-Phase Nanoparticle-Liquid-Gas Boiling Problems in Vertical Rectangular Channels

by Anele Mavi and Tiri Chinyoka

Energies 2022, 15(15), 5746; https://doi.org/10.3390/en15155746 - 8 Aug 2022

Cited by 7 | Viewed by 2308

Abstract

This study develops robust numerical algorithms for the simulation of three-phase (solid-liquid-gas) boiling and bubble formation problems in rectangular channels. The numerical algorithms are based on the Finite Volume Methods (FVM) and implement both the volume-of-fluid (VOF) methods for liquid-gas interface tracking as [...] Read more.

This study develops robust numerical algorithms for the simulation of three-phase (solid-liquid-gas) boiling and bubble formation problems in rectangular channels. The numerical algorithms are based on the Finite Volume Methods (FVM) and implement both the volume-of-fluid (VOF) methods for liquid-gas interface tracking as well as the volume-fraction methods to account for the concentration of embedded solid nano-particles in the liquid phase. Water is used as the base-liquid and the solid phase is modelled via metallic nano-particles (both aluminium oxide and titanium oxide nano-particles are considered) that are homogeneously mixed within the liquid phase. The gas phase is considered as a vapour arising from the bolling processes of the liquid-phase. The finite volume methodology is implemented on the OpenFOAM software platform, specifically by careful modification and manipulation of existing OpenFOAM solvers. The governing fluid dynamical equations, for the three-phase boiling problem, take into account the thermal conductivity effects of the solid (nano-particle), the momentum and energy equations for both the liquid-phase and the gas-phase, and finally the decoupled mass conservation equations for the liquid- and gas- phases. The decoupled mass conservation equations are specifically used to model the phase change between the liquid- and gas- phases. In addition to the FVM and VOF numerical methodologies for the discretization of the governing equations, the pressure-velocity coupling is resolved via the PIMPLE algorithm, a combination of the Pressure Implicit with Splitting of Operator (PISO) and the Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) algorithms. The computational results are presented graphically with respect to variations in time as well as in the nano-particle volume fractions. The simulations and results accurately capture the formation of vapour bubbles in the two-phase (particle-free) liquid-gas flow and additionally the computational algorithms are similarly demonstrated to accurately illustrate and capture simulated boiling processes. The presence of the nano-particles is demonstrated to enhance the heat-transfer, boiling, and bubble formation processes. Full article

(This article belongs to the Special Issue Recent Advances in Heat Transfer and Two-Phase Flow Performance)

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20 pages, 5479 KiB

Open AccessArticle

DC-DC High-Step-Up Quasi-Resonant Converter to Drive Acoustic Transmitters

by Emad Roshandel, Amin Mahmoudi, Solmaz Kahourzade and Hamid Davazdah-Emami

Energies 2022, 15(15), 5745; https://doi.org/10.3390/en15155745 - 8 Aug 2022

Cited by 3 | Viewed by 2437

Abstract

This paper proposes a quasi-resonant step-up DC-DC converter to provide the DC-link voltage for piezoelectric transmitters (PZETs). The resonance not only provides a soft-switching condition for the converter switches, but also helps to decrease the converter element sizes for marine applications. Operation modes [...] Read more.

This paper proposes a quasi-resonant step-up DC-DC converter to provide the DC-link voltage for piezoelectric transmitters (PZETs). The resonance not only provides a soft-switching condition for the converter switches, but also helps to decrease the converter element sizes for marine applications. Operation modes of the proposed converter are discussed. The current and voltage of the converter components are derived analytically, and hence the converter gain is obtained. The performance of the proposed high-step-up, high-power density converter is examined through a comprehensive simulation study. The simulation results demonstrate the soft-switching operation and short transient time required for the converter to reach the reference output voltage. The converter output voltage remains unchanged when an inverter with a passive filter is placed at its output while supplying the PZET. The proposed DC-DC converter is prototyped to validate the converter gain and soft-switching operation experimentally. The converter gain and soft-switching results in simulation are well matched with those of the experimental tests. The converter efficiency in three different switching frequencies is obtained experimentally. The power density of the proposed topology is determined via the designing of a printed circuit board. The experimental results demonstrate the appropriate gain and efficiency of the converter in the tested power range. Full article

(This article belongs to the Topic Power Converters)

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20 pages, 3085 KiB

Open AccessArticle

Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak? Fresh Evidence Using Machine Learning Models

by Kais Tissaoui, Taha Zaghdoudi, Abdelaziz Hakimi, Ousama Ben-Salha and Lamia Ben Amor

Energies 2022, 15(15), 5744; https://doi.org/10.3390/en15155744 - 8 Aug 2022

Cited by 8 | Viewed by 2266

Abstract

This paper uses two competing machine learning models, namely the Support Vector Regression (SVR) and the eXtreme Gradient Boosting (XGBoost) against the Autoregressive Integrated Moving Average ARIMAX (p,d,q) model to identify their predictive performance of the crude oil volatility index before and during [...] Read more.

This paper uses two competing machine learning models, namely the Support Vector Regression (SVR) and the eXtreme Gradient Boosting (XGBoost) against the Autoregressive Integrated Moving Average ARIMAX (p,d,q) model to identify their predictive performance of the crude oil volatility index before and during COVID-19. In terms of accuracy, forecasting results reveal that the SVR model dominates the XGBoost and ARIMAX models in predicting the crude oil volatility index before COVID-19. However, the XGBoost model provides more accurate predictions of the crude oil volatility index than the SVR and ARIMAX models during the pandemic. The inverse cumulative distribution of residuals suggests that both ML models produce good results in terms of convergence. Findings also indicate that there is a fast convergence to the optimal solution when using the XGBoost model. When analyzing the feature importance, the Shapley Additive Explanation Method reveals that the SVR performs significantly better than the XGBoost in terms of feature importance. During the pandemic, the predictive power of the CBOE Volatility Index and Economic Policy Uncertainty index for forecasting the crude oil volatility index is improved compared to the pre-COVID-19 period. These findings imply that investor fear-induced uncertainty in the financial market and economic policy uncertainty are the most significant features and hence represent substantial sources of uncertainty in the oil market. Full article

(This article belongs to the Special Issue Political Economy of Energy Policies)

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18 pages, 4530 KiB

Open AccessArticle

A Novel Virtual Sensor Modeling Method Based on Deep Learning and Its Application in Heating, Ventilation, and Air-Conditioning System

by Delin Wang and Xiangshun Li

Energies 2022, 15(15), 5743; https://doi.org/10.3390/en15155743 - 8 Aug 2022

Cited by 1 | Viewed by 1728

Abstract

Realizing the dynamic redundancy of sensors is of great significance to ensure the energy saving and normal operation of the heating, ventilation, and air-conditioning (HVAC) system. Building a virtual sensor model is an effective method of redundancy and fault tolerance for hardware sensors. [...] Read more.

Realizing the dynamic redundancy of sensors is of great significance to ensure the energy saving and normal operation of the heating, ventilation, and air-conditioning (HVAC) system. Building a virtual sensor model is an effective method of redundancy and fault tolerance for hardware sensors. In this paper, a virtual sensor modeling method combining the maximum information coefficient (MIC) and the spatial–temporal attention long short-term memory (STA-LSTM) is proposed, which is named MIC-STALSTM, to achieve the dynamic and nonlinear modeling of the supply and return water temperature at both ends of the chiller. First, MIC can extract the influencing factors highly related to the target variables. Then, the extracted impact factors via MIC are used as the input variables of the STA-LSTM algorithm in order to construct an accurate virtual sensor model. The STA-LSTM algorithm not only makes full use of the LSTM algorithm’s advantages in handling historical data series information, but also achieves adaptive estimation of different input variable feature weights and different hidden layer temporal correlations through the attention mechanism. Finally, the effectiveness and feasibility of the proposed method are verified by establishing two virtual sensors for different temperature variables in the HVAC system. Full article

(This article belongs to the Special Issue Designing, Modeling and Optimizing Energy and Environmental Systems for Buildings)

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19 pages, 5897 KiB

Open AccessArticle

An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

by Shamim Akhtar, Muhamad Zahim Bin Sujod and Syed Sajjad Hussain Rizvi

Energies 2022, 15(15), 5742; https://doi.org/10.3390/en15155742 - 8 Aug 2022

Cited by 10 | Viewed by 2485

Abstract

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics [...] Read more.

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics Lab (SEIL) of the Indian Institute of Technology (IIT) conducted an experimental study in 2019 to collect massive data on university campus energy consumption. The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing algorithms in terms of efficacy. On the contrary, a reverse ranking is observed in terms of efficiency. This is grounded in the fact that Bagged Trees is most effective algorithm for the said application and Medium Trees is the most efficient one. Likewise, Fine Trees has the optimum tradeoff between efficacy and efficiency. Full article

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

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13 pages, 6330 KiB

Open AccessArticle

Measurement of Gas Flow Rate at Gasification of Low-Melting Materials in a Flow-Through Gas Generator

by Dmitry A. Vnuchkov, Valery I. Zvegintsev, Denis G. Nalivaichenko and Sergey M. Frolov

Energies 2022, 15(15), 5741; https://doi.org/10.3390/en15155741 - 8 Aug 2022

Cited by 4 | Viewed by 2045

Abstract

A semi-empirical method is proposed for determining the rate of gas production in a flow-through gas generator (GG) with the allocation of a part of the gas flow produced by gasification of a low-melting solid material (LSM) in the total gas flow rate [...] Read more.

A semi-empirical method is proposed for determining the rate of gas production in a flow-through gas generator (GG) with the allocation of a part of the gas flow produced by gasification of a low-melting solid material (LSM) in the total gas flow rate through the GG. The method is verified by test fires with polypropylene sample gasification by hot air under conditions of incoming supersonic flow with Mach number 2.43, 2.94, and 3.81 and stagnation temperature 600–700 K. The mean flow rates of gasification products obtained in test fires were 0.08 kg/s at Mach 2.43, 0.10 kg/s at Mach 2.94, and 0.05–0.02 kg/s at Mach 3.81. For obtaining 1 kg of gasification products in the test fires there was a need of 1.61 to 2.86 kg of gasifying agent. Full article

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17 pages, 4732 KiB

Open AccessArticle

Analysis of Energy Loss on a Tunable Check Valve through the Numerical Simulation

by Edward Lisowski, Grzegorz Filo and Janusz Rajda

Energies 2022, 15(15), 5740; https://doi.org/10.3390/en15155740 - 8 Aug 2022

Cited by 3 | Viewed by 2537

Abstract

The article presents a study of the flow through a tunable check valve used as a hydraulic lock in a system with an actuator. Special attention is given to energy losses of the liquid stream in the poppet gap. In the first stage [...] Read more.

The article presents a study of the flow through a tunable check valve used as a hydraulic lock in a system with an actuator. Special attention is given to energy losses of the liquid stream in the poppet gap. In the first stage of the research, CFD methods were used to determine the speed and pressure distributions for the fixed values of the input flow rate and the poppet position. The values of the jet angle and pressures determined based on the CFD results were used to build a simulation model of the entire hydraulic system in Matlab/Simulink environment. The influence of the spring parameters pressing the poppet against the valve seat on the pressure drop and thus on the amount of energy lost was investigated. In particular, the spring stiffness and initial tension were studied. The obtained results were used to develop guidelines for constructing a valve prototype. Finally, the results of simulation tests were verified based on the actual valve characteristic obtained on a test bench. Full article

(This article belongs to the Special Issue Computer-Aided Design of Hydraulic Systems)

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19 pages, 9670 KiB

Open AccessArticle

Double Impedance-Substitution Control of DFIG Based Wind Energy Conversion System

by Yu Zhang, Jiahong Liu, Meilan Zhou, Chen Li and Yanling Lv

Energies 2022, 15(15), 5739; https://doi.org/10.3390/en15155739 - 8 Aug 2022

Cited by 4 | Viewed by 1701

Abstract

In a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS), when the grid voltage sags severely, the rotor side converter (RSC) suffers from overvoltage and overcurrent owing to the large electromotive force (EMF). To ensure that the converter operates within a safe [...] Read more.

In a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS), when the grid voltage sags severely, the rotor side converter (RSC) suffers from overvoltage and overcurrent owing to the large electromotive force (EMF). To ensure that the converter operates within a safe range when grid faults occur, this paper proposes a double impedance-substitution control (DISC) strategy to improve the system’s low-voltage ride through (LVRT) capability. When the grid voltage sag is detected, the grid side converter (GSC) and RSC are connected in parallel to the rotor circuit by changing the topology of the system. In the new topology, GSC and RSC are equivalent to inductive impedance by controlling, which can not only suppress the overvoltage and overcurrent at the rotor side, but also effectively reduce the torque ripple. Additionally, the DISC strategy can provide reactive power support to the grid during LVRT. Finally, the simulation results show that the DISC strategy can maintain the current flowing through the RSC within ±1 p.u., and compared with the existing control strategy, the effectiveness of the proposed method was further demonstrated. Full article

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

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18 pages, 2073 KiB

Open AccessArticle

Research on Evaluation Method of Digital Project Cloud Model Considering Weight Sensitivity

by Ye Zhu, Jinchao Li, Xinyi Lan, Shiqiang Lu and Jie Yu

Energies 2022, 15(15), 5738; https://doi.org/10.3390/en15155738 - 7 Aug 2022

Cited by 2 | Viewed by 1804

Abstract

Digitization is a driving force for social development and corporate innovation. Digital projects have become an indispensable part of the sustainable development of enterprises. However, due to the imperfect decision-making system of digital projects and the lack of experience of traditional enterprises’ digital [...] Read more.

Digitization is a driving force for social development and corporate innovation. Digital projects have become an indispensable part of the sustainable development of enterprises. However, due to the imperfect decision-making system of digital projects and the lack of experience of traditional enterprises’ digital projects, the decision-making of digital projects is an unavoidable challenge in the digital transformation of enterprises. For the digital project decision of the STATE GRID Corporation of China, this paper conducts a sensitivity analysis of digital project evaluation index weights based on cloud model theory, on top of historical successful project experience to support digital project decision-making. Firstly, this paper establishes a comprehensive evaluation index system for digitalization projects from five aspects: economic efficiency, interconnection, intelligent management, value release, and development innovation. The coefficient of variation method is used for index screening, and the weight intervals are formed by four subjective and objective assignment methods. Then, the LSOM model is established to generate the weight values in the interval, and, finally, the sensitivity of digital project comprehensive evaluation indexes is analyzed based on the cloud model to select the most robust index weights for project evaluation and choose the optimal project. The feasibility of the proposed method is verified by arithmetic examples. Full article

(This article belongs to the Special Issue Energy Digitalisation and Data)

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12 pages, 2481 KiB

Open AccessArticle

Why Should We Test the Wideband Transformation Accuracy of Inductive Current Transformers?

by Ernest Stano, Piotr Kaczmarek and Michal Kaczmarek

Energies 2022, 15(15), 5737; https://doi.org/10.3390/en15155737 - 7 Aug 2022

Cited by 13 | Viewed by 1691

Abstract

Inductive current transformers are characterized by different transformation accuracies for higher harmonics of distorted primary currents. Therefore, it is highly required to perform the tests of their metrological properties to choose the best unit that ensures the lowest values of current error and [...] Read more.

Inductive current transformers are characterized by different transformation accuracies for higher harmonics of distorted primary currents. Therefore, it is highly required to perform the tests of their metrological properties to choose the best unit that ensures the lowest values of current error and phase displacement. This study presents a comparison of two manufactured inductive current transformers. The results indicate that some inductive current transformers may be used to accurately transform distorted currents, enabling proper distortion of power metering and quality evaluation. However, to obtain adequate transformation properties in the wide frequency range, the cross-section of the magnetic core of the inductive current transformer should be oversized. Moreover, it is required to use a permalloy magnetic core instead of the typical transformer steel core. In the analyzed case, the metrological performance depends mainly on its accuracy for transforming the main component of the distorted primary current and self-generation of the low-order higher harmonics. This paper constitutes the starting point to define the limiting values of current error and phase displacement for the future wideband accuracy class extension for inductive CTs. Full article

(This article belongs to the Special Issue Development of Voltage and Current Transformers in Power System)

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12 pages, 2835 KiB

Open AccessArticle

Performance Enhancement of Interdigitated Heterojunction Solar Cells with Discotic Molecule

by Zhi Zhang, Yao Wang, Qun Chen and Zhipan Zeng

Energies 2022, 15(15), 5736; https://doi.org/10.3390/en15155736 - 7 Aug 2022

Viewed by 1576

Abstract

Ordered interdigitated heterojunction as a promising nanostructure has attracted considerable attention due to its potential application in solar cells. However, a suitable construction to achieve effective free carrier transport in these nanostructures remains a challenge. In this study, interdigitated nanostructure was fabricated by [...] Read more.

Ordered interdigitated heterojunction as a promising nanostructure has attracted considerable attention due to its potential application in solar cells. However, a suitable construction to achieve effective free carrier transport in these nanostructures remains a challenge. In this study, interdigitated nanostructure was fabricated by combining vertically orientated TiO₂ nanotube array with discotic liquid crystal Copper (II) 2,9,16,23-tetra-tert-butyl-29H,31H-phthalocyanine (tbCuPc). These discotic molecules were assembled as homeotropic alignment in the interdigitated nanostructure, which enhanced the carrier mobility of active layer considerably. The performance of photovoltaic cells with this interdigitated heterojunction was improved. Molecule orientation leading to charge carrier mobility enhancement was found to play a key role in improving the power conversion efficiency of the devices substantially. Full article

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19 pages, 965 KiB

Open AccessArticle

Power Management of a Plug-in Hybrid Electric Vehicle Using Neural Networks with Comparison to Other Approaches

by Da Huo and Peter Meckl

Energies 2022, 15(15), 5735; https://doi.org/10.3390/en15155735 - 7 Aug 2022

Cited by 12 | Viewed by 2139

Abstract

Many researchers spent much effort on the online power management strategies for plug-in hybrid vehicles (PHEVs) and hybrid electric vehicles (HEVs). Nowadays, artificial neural networks (ANNs), one of the machine learning techniques, have also been applied to this problem due to their good [...] Read more.

Many researchers spent much effort on the online power management strategies for plug-in hybrid vehicles (PHEVs) and hybrid electric vehicles (HEVs). Nowadays, artificial neural networks (ANNs), one of the machine learning techniques, have also been applied to this problem due to their good performance in learning non-linear and complicated multi-inputs multi-outputs (MIMO) dynamic systems. In this paper, an ANN is applied to the online power management for a plug-in hybrid electric vehicle (PHEV) by predicting the torque split between an internal combustion engine (ICE) and an electric motor (e-Motor) to optimize the greenhouse gas (

G H G

) emissions by using dynamic programming (DP) results as training data. Dynamic programming can achieve a global minimum solution while it is computationally intensive and requires prior knowledge of the entire drive cycle. As such, this method cannot be implemented in real-time. The DP-based ANN controller can get the benefit of using an ANN to fit the DP solution so that it can be implemented in real-time for an arbitrary drive cycle. We studied the hyper-parameters’ effects on the ANN model and different structures of ANN models are compared. The minimum training mean square error (MSE) models in each comparison set are selected for comparison with DP and equivalent consumption minimization strategy (ECMS). The total

G H G

emissions and state of charge (

S O C

) are the metrics used for the analysis and comparison. All the selected ANNs provide results that are comparable to the optimal DP solution, which indicates that ANNs are almost as good as the DP solution. It is found that the multiple hidden-layer ANN shows more efficiency in the training process than the single hidden-layer ANN. By comparing the results with ECMS, the ANN shows great potential in real-time application with the smallest deviation from the results of DP. In addition, our approach does not require any additional trip information, and its output (torque split) is more directly implementable on real vehicles. Full article

(This article belongs to the Special Issue Smart Energy Management for Electric and Hybrid Electric Vehicles)

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24 pages, 6780 KiB

Open AccessArticle

Shielding Design Optimization of the Helium-Cooled Pebble Bed Breeding Blanket for the EU DEMO Fusion Reactor

by Iole Palermo, Francisco A. Hernández, Pavel Pereslavtsev, David Rapisarda and Guangming Zhou

Energies 2022, 15(15), 5734; https://doi.org/10.3390/en15155734 - 7 Aug 2022

Cited by 4 | Viewed by 1867

Abstract

The helium-cooled pebble bed (HCPB) breeding blanket (BB) is one of the two driver-blanket candidates for the European DEMO fusion reactor. Recent design activities were focused, among other objectives, on the achievement of an efficient shielding system to adequately protect the vacuum vessel [...] Read more.

The helium-cooled pebble bed (HCPB) breeding blanket (BB) is one of the two driver-blanket candidates for the European DEMO fusion reactor. Recent design activities were focused, among other objectives, on the achievement of an efficient shielding system to adequately protect the vacuum vessel (VV) and toroidal field coils (TFCs). Several shielding options have been studied in terms of architecture (e.g., in-BB shield and ex-BB shield) and materials (e.g., B₄C, WC, WB, YHx, and ZrHx). In this study, the B₄C material was selected as the most attractive option considering not only shielding performance but also availability, industrialization, experience, and cost factors. Subsequently, we performed a parametric study by implementing different thicknesses of a B₄C external shield and reporting information of its effect on shielding performance, structural behavior, swelling and tritium breeding. Furthermore, a detailed structure for the VV was developed considering an internal layered configuration comprising steels/water with different boron contents. Corresponding shielding analyses were conducted regarding influence on neutron attenuation when implementing such a VV structure for both the baseline consolidated design of the HCPB and one of the previously developed and improved BSS configurations. The most critical responses (neutron flux and dpa) were fully established only using 10 cm B₄C and an improved VV configuration. Full article

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15 pages, 9855 KiB

Open AccessArticle

Variable Incremental Controller of Permanent-Magnet Synchronous Motor for Voltage-Based Flux-Weakening Control

by Hyunjae Lee, Gunbok Lee, Gildong Kim and Jingeun Shon

Energies 2022, 15(15), 5733; https://doi.org/10.3390/en15155733 - 7 Aug 2022

Cited by 1 | Viewed by 1781

Abstract

This study presents a variable incremental controller for flux-weakening control in the high-speed operation area of a permanent-magnetic synchronous motor (PMSM). In general, voltage-based flux-weakening control utilizes a reference voltage and a PI controller to generate a flux component current. In this paper, [...] Read more.

This study presents a variable incremental controller for flux-weakening control in the high-speed operation area of a permanent-magnetic synchronous motor (PMSM). In general, voltage-based flux-weakening control utilizes a reference voltage and a PI controller to generate a flux component current. In this paper, the voltage-based flux-weakening control is performed using the variable incremental controller instead of the PI controller. The variable incremental controller can control the flux component current using only the maximum speed and maximum current of the motor. A method for properly setting an appropriate variable incremental controller using acceleration is additionally presented. A variable incremental controller is applied and, accordingly, the overshoot of the motor speed can be reduced and the speed error of the motor can be minimized by reducing the difference between the actual motor and targeted accelerations. This method can simplify the design of a controller that utilizes flux-weakening control and can be applied to railroad cars whose acceleration does not alter frequently to increase the effect of motor control. Full article

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

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