Journal Description
Energies
Energies
is a peer-reviewed, open access journal of related scientific research, technology development, engineering, and the studies in policy and management and is published semimonthly online by MDPI. The European Biomass Industry Association (EUBIA), Polish Society of Applied Electromagnetics (PTZE), Association of European Renewable Energy Research Centres (EUREC), Institute for Chemical Processing of Coal (IChPW), International Society for Porous Media (InterPore) and CYTED are affiliated with Energies and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, RePEc, AGRIS, Inspec, CAPlus / SciFinder, and many other databases.
- Journal Rank: CiteScore - Q1 (Control and Optimization)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 15.9 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the first half of 2021).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Energies.
- Sections: published in Twenty-seven topical sections.
- Companion journals for Energies include: Fuels, Gases, Nanoenergy Advances and Solar.
Impact Factor:
3.004 (2020)
;
5-Year Impact Factor:
3.085 (2020)
Latest Articles
Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation
Energies 2021, 14(17), 5377; https://doi.org/10.3390/en14175377 (registering DOI) - 30 Aug 2021
Abstract
Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the
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Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the available renewable energy resources as a fuel-saver simply to reduce fossil-fuel consumption. This is related mainly to the inherently variable and non-dispatchable nature of renewable energy resources, which poses a threat to power system reliability and requires utilities to maintain power-balancing reserves to match the supply from renewable energy resources with the real-time demand levels. Thus, further efforts are needed to mitigate the risk that comes with integrating renewable resources into the electricity grid. Hence, an integrated strategy is being created to determine the optimal size of the hybrid wind-solar photovoltaic power systems (HWSPS) using heuristic optimization with a numerical iterative algorithm such that the output fluctuation is minimized. The research focuses on sizing the HWSPS to reduce the impact of renewable energy resource intermittency and generate the maximum output power to the grid at a constant level periodically based on the availability of the renewable energy resources. The process of determining HWSPS capacity is divided into two major steps. A genetic algorithm is used in the initial stage to identify the optimum wind farm. A numerical iterative algorithm is used in the second stage to determine the optimal combination of photovoltaic plant and battery sizes in the search space, based on the reference wind power generated by the moving average, Savitzky–Golay, Gaussian and locally weighted linear regression techniques. The proposed approach has been tested on an existing wind power project site in the southern part of the Sultanate of Oman using a real weather data. The considered land area dimensions are 2 × 2 km. The integrated tool resulted in 39 MW of wind farm, 5.305 MW of PV system, and 0.5219 MWh of BESS. Accordingly, the estimated cost of energy based on the HWSPS is 0.0165 EUR/kWh.
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(This article belongs to the Special Issue BIWAES 2021—Biennial International Workshop Advances in Energy Studies "Empowering Communities, Beyond Energy Scarcity")
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Open AccessEditorial
Special Issue: “Energy Data Analytics for Smart Meter Data”
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Energies 2021, 14(17), 5376; https://doi.org/10.3390/en14175376 (registering DOI) - 30 Aug 2021
Abstract
Smart electricity meters are a cornerstone for the realization of next-generation electrical power grids [...]
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(This article belongs to the Special Issue Energy Data Analytics for Smart Meter Data)
Open AccessReview
Distributed Generation and Renewable Energy Integration into the Grid: Prerequisites, Push Factors, Practical Options, Issues and Merits
Energies 2021, 14(17), 5375; https://doi.org/10.3390/en14175375 - 29 Aug 2021
Abstract
Power system operators are in search of proven solutions to improve the penetration levels of distributed generators (DGs) in the grid while minimizing cost. This transition is driven, among others, by global climate concerns, the growing power demand, the need for greater flexibility,
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Power system operators are in search of proven solutions to improve the penetration levels of distributed generators (DGs) in the grid while minimizing cost. This transition is driven, among others, by global climate concerns, the growing power demand, the need for greater flexibility, the ageing grid infrastructure and the need to diversify sources of energy production. Distributed renewables would not easily substitute the conventional electric grid system, perhaps because the latter is a well-established technology and it would not be prudent to abandon it, while the new distributed renewable energy technologies are generally not adequately developed to support the total load. Thus, it is becoming increasingly necessary to consider sustainable options such as integrating renewable energy sources into the existing power grid. This study is a review that is mainly hinged on distributed generation (DG) classification, the challenges of DG to grid integration, practical options used in DG integration, lessons learned from some countries with successful DG to grid integration, push factors in the growth of DGs and the merits of DG to grid integration. These standpoints of DG to grid interconnection are critical in conducting grid planning and operational studies, which should be conducted in strict observance of aspects such as optimal technology selection, optimal capacity and a suitable connection point of DGs in the network. Therefore, the perspectives highlighted regarding DG can assist power system engineers, developers of DG plants and policymakers in developing a power network that is stable, efficient and reliable.
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(This article belongs to the Section Clean Energy)
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Open AccessArticle
Geospatial Analysis and Environmental Impact Assessment of a Holistic and Interdisciplinary Approach to the Biogas Sector
Energies 2021, 14(17), 5374; https://doi.org/10.3390/en14175374 (registering DOI) - 29 Aug 2021
Abstract
Crop-based biogas energy production, in combination with electricity generation under subsidy schemes, is no longer considered a favourable business model for biogas plants. Switching to low-cost or gate fee feedstocks and utilising biogas via alternative pathways could contribute to making existing plants fit
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Crop-based biogas energy production, in combination with electricity generation under subsidy schemes, is no longer considered a favourable business model for biogas plants. Switching to low-cost or gate fee feedstocks and utilising biogas via alternative pathways could contribute to making existing plants fit for future operations and could open up new space for further expansion of the biogas sector. The aim of this study was to combine a holistic and interdisciplinary approach for both the biogas production side and the utilisation side to evaluate the impact of integrating the biogas sector with waste management systems and energy systems operating with a high share of renewable energy sources. The geospatial availability of residue materials from agriculture, industry and municipalities was assessed using QGIS software for the case of Northern Croatia with the goal of replacing maize silage in the operation of existing biogas plants. Furthermore, the analysis included positioning new biogas plants, which would produce renewable gas. The overall approach was evaluated through life cycle assessment using SimaPro software to quantify the environmental benefits and identify the bottlenecks of the implemented actions. The results showed that the given feedstocks could replace 212 GWh of biogas from maize silage in the relevant region and create an additional 191 GWh of biomethane in new plants. The LCA revealed that the proposed measures would contribute to the decarbonisation of natural gas by creating environmental benefits that are 36 times greater compared to a business-as-usual concept. The presented approach could be of interest to stakeholders in the biogas sector anywhere in the world to encourage further integration of biogas technologies into energy and environmental transitions.
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(This article belongs to the Special Issue Biogas Production-Converting Waste to Energy and Bio-Products of Added Value)
Open AccessArticle
Self-Oscillating Boost Converter of Wiegand Pulse Voltage for Self-Powered Modules
Energies 2021, 14(17), 5373; https://doi.org/10.3390/en14175373 - 29 Aug 2021
Abstract
This paper introduces a new method of electricity generation using a Wiegand sensor. The Wiegand sensor consists of a magnetic wire and a pickup coil wound around it. This sensor generates a pulse voltage of approximately 5 V and 20 µs width as
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This paper introduces a new method of electricity generation using a Wiegand sensor. The Wiegand sensor consists of a magnetic wire and a pickup coil wound around it. This sensor generates a pulse voltage of approximately 5 V and 20 µs width as an induced voltage in the pickup coil. The aim of this study is to generate a DC voltage of 5 V from the sensor, which is expected to be used as a power source in self-powered devices and battery-less modules. We report on the design and verification of a self-oscillating boost converter circuit in this paper. A DC voltage obtained by rectifying and smoothing the pulse voltage generated from the Wiegand sensor was boosted by the circuit. A stable DC output voltage in the order of 5 V for use as a power supply in electronics modules was successfully obtained. A quantitative analysis of the power generated by the Wiegand sensor revealed a suitable voltage–current range for application in self-powered devices and battery-less modules.
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(This article belongs to the Special Issue Advanced Energy Harvesting Technologies)
Open AccessArticle
Simulation and Performance Analysis of Air-Type PVT Collector with Interspaced Baffle-PV Cell Design
Energies 2021, 14(17), 5372; https://doi.org/10.3390/en14175372 - 29 Aug 2021
Abstract
A Photovoltaic Thermal (PVT) collector produces heat and electricity simultaneously. Air-type PVT collector uses air as a transfer medium to take heat from PV back side surface. The performance of the air-type PVT collector is affected by design elements such as PV types,
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A Photovoltaic Thermal (PVT) collector produces heat and electricity simultaneously. Air-type PVT collector uses air as a transfer medium to take heat from PV back side surface. The performance of the air-type PVT collector is affected by design elements such as PV types, inside structures in heat collecting space (baffle or fins), the shape of the air pathway, etc. In this study, an advanced air-type PVT collector was designed with curved baffles (absorber) to improve thermal performance. Within the air-type PVT collector, PV cells were arranged in an interspaced design, and the curved baffles were located in the collecting space to increase heat efficiently. The absorber received solar radiation directly and was utilized as baffles for improving thermal performance. The air-type PVT collector was fabricated and tested in an outdoor environment considering the climatic conditions of Daejeon, Republic of Korea. In addition, based on experiment parameters and data, the annual thermal and electrical performances of the system were analyzed by simulation modeling using the TRNSYS program. Thermal and electrical efficiencies were 37.1% and 6.4% (according to module area) for outdoor test conditions, respectively. Numerical and experimental results were in good agreement with an error of 4% and 0.24% for thermal and electrical efficiencies, respectively. Annual heat gain was 644 kWh th/year, and generated power was 118 kWh el/year.
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(This article belongs to the Special Issue Building Energy and Environment)
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Adaptive Online Sequential Extreme Learning Machine with Kernels for Online Ship Power Prediction
Energies 2021, 14(17), 5371; https://doi.org/10.3390/en14175371 - 29 Aug 2021
Abstract
With the in-depth penetration of renewable energy in the shipboard power system, the uncertainty of its output power and the variability of sea conditions have brought severe challenges to the control of shipboard integrated power system. In order to provide additional accurate signals
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With the in-depth penetration of renewable energy in the shipboard power system, the uncertainty of its output power and the variability of sea conditions have brought severe challenges to the control of shipboard integrated power system. In order to provide additional accurate signals to the power control system to eliminate the influence of uncertain factors, this study proposed an adaptive kernel based online sequential extreme learning machine to accurately predict shipboard electric power fluctuation online. Three adaptive factors are introduced, which control the kernel function scale adaptively to ensure the accuracy and speed of the algorithm. The electric power fluctuation data of real-ship under two different sea conditions are used to verify the effectiveness of the algorithm. The simulation results clearly demonstrate that in the case of ship power fluctuation prediction, the proposed method can not only meet the rapidity demand of real-time control system, but also provide accurate prediction results.
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(This article belongs to the Section Solar Energy and Photovoltaic Systems)
Open AccessArticle
Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System)
by
, , , , and
Energies 2021, 14(17), 5370; https://doi.org/10.3390/en14175370 - 29 Aug 2021
Abstract
Bathymetry is a subset of hydrography, aimed at measuring the depth of waterbodies and waterways. Measurements are taken inter alia to detect natural obstacles or other navigational obstacles that endanger the safety of navigation, to examine the navigability conditions, anchorages, waterways and other
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Bathymetry is a subset of hydrography, aimed at measuring the depth of waterbodies and waterways. Measurements are taken inter alia to detect natural obstacles or other navigational obstacles that endanger the safety of navigation, to examine the navigability conditions, anchorages, waterways and other commercial waterbodies, and to determine the parameters of the safe depth of waterbodies in the vicinity of ports, etc. Therefore, it is necessary to produce precise and reliable seabed maps, so that any hazards that may occur, particularly in shallow waterbodies, can be prevented, including the high dynamics of hydromorphological changes. This publication is aimed at developing a concept of an innovative autonomous unmanned system for bathymetric monitoring of shallow waterbodies. A bathymetric and topographic system will use autonomous unmanned aerial and surface vehicles to study the seabed relief in the littoral zone (even at depths of less than 1 m), in line with the requirements set out for the most stringent International Hydrographic Organization (IHO) order—exclusive. Unlike other existing solutions, the INNOBAT system will enable the coverage of the entire surveyed area with measurements, which will allow a comprehensive assessment of the hydrographic and navigation situation in the waterbody to be conducted.
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(This article belongs to the Special Issue Positioning Algorithm, System and Application Using Radio Frequency (RF))
Open AccessArticle
Comparison of Optimized and Conventional Models of Passive Solar Greenhouse—Case Study: The Indoor Air Temperature, Irradiation, and Energy Demand
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, , , , , and
Energies 2021, 14(17), 5369; https://doi.org/10.3390/en14175369 (registering DOI) - 28 Aug 2021
Abstract
This study was carried out to optimize a computational model of a new underground passive solar greenhouse to improve thermal performance, storage, and saving of heat solar energy. Optimized and conventional passive solar greenhouse were compared in regards of indoor air temperature, irradiation,
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This study was carried out to optimize a computational model of a new underground passive solar greenhouse to improve thermal performance, storage, and saving of heat solar energy. Optimized and conventional passive solar greenhouse were compared in regards of indoor air temperature, irradiation, and energy demand. Six different materials were used in the conventional model. In addition, TRNSYS software was employed to determine heat demand and irradiation in the greenhouse. The results showed that the annual total heating requirement in the optimized model was 30% lower than a conventional passive solar system. In addition, the resulting average air temperature in the optimized model ranged from −4 to 33.1 °C in the four days of cloud, snow, and sun. The average air temperature in the conventional passive solar greenhouse ranged from −8.4 to 24.7 °C. The maximum monthly heating requirement was 796 MJ/m2 for the Wtype87 model (100-mm lightweight concrete block) and the minimum value was 190 MJ/m2 for the Wtype45 model (50-mm insulation with 200-mm clay tile) in a conventional passive solar greenhouse while the monthly heating requirement estimated 126 MJ/m2 for the optimized greenhouse model. The predictability of the TRNSYS model was calculated with a coefficient of determination (R2) of 95.95%.
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(This article belongs to the Special Issue Energy Security and the Transition toward Green Energy Production)
Open AccessArticle
Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO
by
, , , , and
Energies 2021, 14(17), 5368; https://doi.org/10.3390/en14175368 - 28 Aug 2021
Abstract
Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence,
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Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability.
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(This article belongs to the Collection Feature Papers in Smart Grids and Microgrids)
Open AccessArticle
Development and Experimental Validation of an Adaptive, Piston-Damage-Based Combustion Control System for SI Engines: Part 1—Evaluating Open-Loop Chain Performance
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, , , , , , and
Energies 2021, 14(17), 5367; https://doi.org/10.3390/en14175367 - 28 Aug 2021
Abstract
This work is focused on the development and validation of a spark advance controller, based on a piston “damage” model and a predictive knock model. The algorithm represents an integrated and innovative way to manage both the knock intensity and combustion phase. It
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This work is focused on the development and validation of a spark advance controller, based on a piston “damage” model and a predictive knock model. The algorithm represents an integrated and innovative way to manage both the knock intensity and combustion phase. It is characterized by a model-based open-loop algorithm with the capability of calculating with high accuracy the spark timing that achieves the desired piston damage in a certain period, for knock-limited engine operating conditions. Otherwise, it targets the maximum efficiency combustion phase. Such controller is primarily thought to be utilized under conditions in which feedback is not needed. In this paper, the main models and the structure of the open-loop controller are described and validated. The controller is implemented in a rapid control prototyping device and validated reproducing real driving maneuvers at the engine test bench. Results of the online validation process are presented at the end of the paper.
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(This article belongs to the Special Issue Advances in Spark-Ignition Engines)
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Evaluation of Dairy Wastewater Treatment Systems Using Carbon Footprint Analysis
Energies 2021, 14(17), 5366; https://doi.org/10.3390/en14175366 - 28 Aug 2021
Abstract
Modernisation of municipal and industrial wastewater treatment plants (WWTPs) should be carried out, taking into account its impact on global warming, e.g., through carbon footprint (CF) analysis. An important industrial sector in Poland is the dairy industry. In dairy WWTPs, the aerobic sewage
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Modernisation of municipal and industrial wastewater treatment plants (WWTPs) should be carried out, taking into account its impact on global warming, e.g., through carbon footprint (CF) analysis. An important industrial sector in Poland is the dairy industry. In dairy WWTPs, the aerobic sewage sludge stabilisation applied thus far is being replaced by the anaerobic process. This change is positive due to the possibility of energy production, but it is unclear how it affects greenhouse gases (GHG) emissions. The aim of the research was to perform CF analysis for two scenarios of dairy WWTP operation. The analysis was based on the real operating data of the current system (current scenario) and project of its modernisation (alternative scenario). The current scenario consists of mechanical and dissolved air flotation (DAF) treatment, biological treatment in sequence batch reactors (SBRs), aerobic sewage sludge stabilisation and its final farmland usage. The alternative scenario assumes replacing aerobic stabilisation with anaerobic stabilisation and a combined heat and power (CHP) system. The CF calculations were based on empirical models, taking into account different emission input parameters, expressed in CO2 equivalents (CO2e). The total CF of the current scenario was 22 kg CO2e PE−1 year−1, while the alternative was 45 kg CO2e PE−1 year−1. The largest share in the current scenario belongs to emissions from WWTPs and energy use, while in the alternative, there is the addition of emissions from biogas use.
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(This article belongs to the Special Issue Wastewater, Water and Energy)
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The Role of Universities in Sustainable Development and Circular Economy Strategies
Energies 2021, 14(17), 5365; https://doi.org/10.3390/en14175365 - 28 Aug 2021
Abstract
In this article, the conditions and determinants of the introduction and development of the circular economy (CE) in Poland were presented against the background of the widely discussed essence of circular economy, with particular emphasis on the Polish mining sector. In addition, the
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In this article, the conditions and determinants of the introduction and development of the circular economy (CE) in Poland were presented against the background of the widely discussed essence of circular economy, with particular emphasis on the Polish mining sector. In addition, the European Green Deal—an action plan for a sustainable economy for the entire European Union, was discussed. Particular attention was paid to the role of human resources in the area of supporting research and stimulating innovation, and in the area of activating education and training. These issues are further discussed in the next chapter by presenting the forms, ways and scope of education for sustainable development in the international context. Another chapter describes the EIT Raw Materials KAVA 5 RIS competition in Poland (in Kraków) at AGH-UST from 2019 to 2022, an international project in a consortium of four universities whose main objective is to strengthen entrepreneurship in the V4 countries in line with the recommendations of the “Green action plan for SMEs” in a way to meet the requirements of circular economy. The initiatives and trainings carried out within the framework of this project were discussed, and the results of the student survey on the level of knowledge achieved regarding entrepreneurship in the area of the raw materials industry were analysed. The validity and necessity of continuous education in eco-responsible citizenship has thus been confirmed.
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(This article belongs to the Special Issue Toward the Circular Economy in the Energy Sector: The Role of Higher Education)
Open AccessArticle
IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain
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, , , , and
Energies 2021, 14(17), 5364; https://doi.org/10.3390/en14175364 (registering DOI) - 28 Aug 2021
Abstract
Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable
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Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric-based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters.
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(This article belongs to the Special Issue IoT Systems for Energy Applications)
Open AccessReview
The Challenges of Low Voltage Distribution System State Estimation—An Application Oriented Review
Energies 2021, 14(17), 5363; https://doi.org/10.3390/en14175363 - 28 Aug 2021
Abstract
Global trends such as the growing share of renewable energy sources in the generation mix, electrification, e-mobility, and the increasing number of prosumers reshape the electricity value chain, and distribution systems are necessarily affected. These systems were planned, developed, and operated as a
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Global trends such as the growing share of renewable energy sources in the generation mix, electrification, e-mobility, and the increasing number of prosumers reshape the electricity value chain, and distribution systems are necessarily affected. These systems were planned, developed, and operated as a passive structure for decades with low level of observability. Due to the increasing number of system states, real time operation planning and flexibility services are the key in transition to an active grid management. In this pathway, distribution system state estimation (DSSE) has a great potential, but the real demonstration of this technique is in an early stage, especially on low-voltage level. This paper focuses on the gap between theory and practice and summarizes the limits of low-voltage DSSE implementation. The literature and the main findings follow the general structure of a state estimation process (meter placement, bad data detection, observability, etc.) giving a more essential and traceable overview structure. Moreover, the paper provides a comprehensive mapping of the possible use-cases state estimation and evaluates 27 different experimental sites to conclude on the practical applicability aspects.
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Open AccessArticle
Healthy and Faulty Experimental Performance of a Typical HVAC System under Italian Climatic Conditions: Artificial Neural Network-Based Model and Fault Impact Assessment
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, , , , and
Energies 2021, 14(17), 5362; https://doi.org/10.3390/en14175362 - 28 Aug 2021
Abstract
The heating, ventilation, and air conditioning (HVAC) system serving the test room of the SENS i-Lab of the Department of Architecture and Industrial Design of the University of Campania Luigi Vanvitelli (Aversa, south of Italy) has been experimentally investigated through a series of
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The heating, ventilation, and air conditioning (HVAC) system serving the test room of the SENS i-Lab of the Department of Architecture and Industrial Design of the University of Campania Luigi Vanvitelli (Aversa, south of Italy) has been experimentally investigated through a series of tests performed during both summer and winter under both normal and faulty scenarios. In particular, five distinct typical faults have been artificially implemented in the HVAC system and analyzed during transient and steady-state operation. An optimal artificial neural network-based system model has been created in the MATLAB platform and verified by contrasting the experimental data with the predictions of twenty-two different neural network architectures. The selected artificial neural network architecture has been coupled with a dynamic simulation model developed by using the TRaNsient SYStems (TRNSYS) software platform with the main aims of (i) making available an experimental dataset characterized by labeled normal and faulty data covering a wide range of operating and climatic conditions; (ii) providing an accurate simulation tool able to generate operation data for assisting further research in fault detection and diagnosis of HVAC units; and (iii) evaluating the impact of selected faults on occupant indoor thermo-hygrometric comfort, temporal trends of key operating system parameters, and electric energy consumptions.
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(This article belongs to the Topic Numerical Methods and Computer Simulations in Energy Analysis)
Open AccessArticle
Effect of Operating Conditions on the Performance of Gas–Liquid Mixture Roots Pumps
Energies 2021, 14(17), 5361; https://doi.org/10.3390/en14175361 - 28 Aug 2021
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The performance of the gas–liquid mixture Roots pump at different operating conditions is investigated in this paper. The pump efficiency was first increased from 48% to 64%, and then decreased to 59% with the increased inlet CO2 volume fraction (from 0.8 to
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The performance of the gas–liquid mixture Roots pump at different operating conditions is investigated in this paper. The pump efficiency was first increased from 48% to 64%, and then decreased to 59% with the increased inlet CO2 volume fraction (from 0.8 to 1). The increased rotational speed (from 1000 rpm to 4000 rpm) and pressure ratio (from 2 to 10) can lead to a reduction in the pump’s efficiency from 67% to 43% and from 48% to 33%, respectively. The variation in the pump’s efficiency is affected by the volumetric efficiency and the flow efficiency simultaneously. The high pressure and the CO2 volume fraction in the outlet zone can increase the leakage, leading to a reduction in the volumetric efficiency. The flow efficiency decreases with the increase in the local pressure at the outlet zone and the backflow density. The outlet zone pressure can also affect the fluid properties by changing the density of the gas phase. Therefore, the combined effect of the outlet zone pressure and the working fluid properties is considered to be the main factor affecting the performance. This paper further explores the suitability of Roots pumps for compressing gas–liquid mixtures.
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Crude Oil–Brine–Rock Interactions in Tight Chalk Reservoirs: An Experimental Study
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, , , and
Energies 2021, 14(17), 5360; https://doi.org/10.3390/en14175360 - 28 Aug 2021
Abstract
We present a systematic study of crude oil–brine–rock interactions in tight chalk cores at reservoir conditions. Flooding experiments are performed on outcrops (Stevns Klint) as well as on reservoir core plugs from Dan field, the Ekofisk and Tor formations. These studies are carried
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We present a systematic study of crude oil–brine–rock interactions in tight chalk cores at reservoir conditions. Flooding experiments are performed on outcrops (Stevns Klint) as well as on reservoir core plugs from Dan field, the Ekofisk and Tor formations. These studies are carried out in core plugs with reduced pore volumes, i.e., short core samples and aged with a dynamic ageing method. The method was evaluated by three different oil compositions. A series of synthetic multicomponent brines and designed fluid injection scenarios are investigated; injection flow rates are optimized to ensure that a capillary-dominant regime is maintained. Changes in brine compositions and fluid distribution in the core plugs are characterized using ion chromatography and X-ray computed tomography, respectively. First, we show that polar components in the oil phase play a major role in wettability alteration during ageing; this controls the oil production behavior. We also show that, compared to seawater, both formation water and ten-times-diluted seawater are better candidates for enhanced oil recovery in the Dan field. Finally, we show that the modified flow zone indicator, a measure of rock quality, is likely the main variable responsible for the higher oil recoveries observed in Tor core samples.
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(This article belongs to the Topic Enhanced Oil Recovery Technologies)
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Sensorless Speed Control of Brushed DC Motor Based at New Current Ripple Component Signal Processing
Energies 2021, 14(17), 5359; https://doi.org/10.3390/en14175359 - 28 Aug 2021
Abstract
Signal processing of the brushed DC motor current was developed in this paper to obtain information about a rotor speed from a measured motor current. The brushed DC motor current contains a signal with a frequency proportional to the rotor speed. This signal
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Signal processing of the brushed DC motor current was developed in this paper to obtain information about a rotor speed from a measured motor current. The brushed DC motor current contains a signal with a frequency proportional to the rotor speed. This signal is the outcome of a commutation process occurring in the brushed DC motor, and it is called a ripple component. Since the number of ripples in the measured motor current per one rotation is constant, the rotor speed can be estimated. A discrete bandpass filter with a floating bandwidth was developed as the main part of signal processing. This new interpretation of the bandpass filter was used to extract a frequency of the ripple component from the measured motor current. This frequency was used to acquire information about the estimated rotor speed. The estimated speed was set as a feedback value to a cascade control structure to provide sensorless speed control. The advantages and limitations of this approach are presented in this paper. Based on simulations and experimental results, it was confirmed that the proposed sensorless speed control is robust, accurate, and works precisely in a wide range of speeds.
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(This article belongs to the Special Issue Applications of Modern Methods to Control of Electric Drives)
Open AccessArticle
Techno-Economic Analysis of the Oxy-Fuel Combustion Power Cycles with Near-Zero Emissions
Energies 2021, 14(17), 5358; https://doi.org/10.3390/en14175358 - 28 Aug 2021
Abstract
This paper is devoted to improvement of environmental safety in hydrocarbon-firing TPPs. Despite the development of renewable power sources, the number of traditional power production facilities continues its growth. The toxic emission mitigation in traditional TPPs has been deeply investigated, but the problem
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This paper is devoted to improvement of environmental safety in hydrocarbon-firing TPPs. Despite the development of renewable power sources, the number of traditional power production facilities continues its growth. The toxic emission mitigation in traditional TPPs has been deeply investigated, but the problem of greenhouse gas atmospheric emissions is of topical interest. Oxy-fuel technology reduces CO2 emissions and is highly efficient and environmentally safe. Also, it requires relatively low capital investments. Thermal efficiency analysis shows that the Allam cycle facilities have the best efficiency. Their thermodynamic parameters can be optimized with minimal primary costs and capital investments. This newly developed analysis was used to compare the investment efficiency of projects for the buildup of oxy-fuel and combined cycle facilities. Without emission quote payments, the NPV of combined cycle projects is 16% higher, as well as having a lower DPP. The electricity production primary costs in oxy-fuel and combined cycle facilities are similar, which reflects the technologies’ similarity and similar fuel costs. Implementation of carbon dioxide emission quote marketing makes oxy-fuel facilities more investment-attractive. Parametric studies show that when Russia implements CO2 emission quotes compatible with the current EU level, an oxy-fuel facility erection project will be financially reasonable. Thus, it can be concluded that the construction of oxy-fuel power plants is one of the most promising and investment-attractive solutions to reduce CO2 emissions in the energy sector for large industrialized countries. The managerial consequences of their implementation will include the stabilization of greenhouse gas emissions while ensuring the financial stability of the energy industry.
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(This article belongs to the Special Issue Climate Change and Low-Carbon Economy)
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