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Energies, Volume 13, Issue 18 (September-2 2020) – 399 articles

Cover Story (view full-size image): Atomistic modelling and experiments have been combined to accelerate the depth of understanding of dye:TiO2 orientations and their influence on the structure of dye-sensitized solar cells. Initial results show dyes prefer to lie horizontally rather than vertically to the surface of TiO2, paving the way to advancing the future design of these solar cell devices. View this paper.
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22 pages, 1988 KiB  
Article
Decomposed Iterative Optimal Power Flow with Automatic Regionalization
by Xinhu Zheng, Dongliang Duan, Liuqing Yang and Haonan Wang
Energies 2020, 13(18), 4987; https://doi.org/10.3390/en13184987 - 22 Sep 2020
Cited by 1 | Viewed by 2073
Abstract
The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques [...] Read more.
The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques are not suitable for large-scale systems and an efficient decomposed implementation of OPF is highly demanded. In this paper, we propose a novel and efficient method to decompose the entire system into multiple sub-systems based on automatic regionalization and acquire the OPF solution across sub-systems via a modified MATPOWER solver. The proposed method is implemented in a modified solver and tested on several IEEE Power System Test Cases. The performance is shown to be more appealing compared with the original solver. Full article
(This article belongs to the Section F: Electrical Engineering)
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20 pages, 17312 KiB  
Article
Thermal Viscous Fingering in Thermal Recovery Processes
by Maureen Austin-Adigio and Ian D. Gates
Energies 2020, 13(18), 4986; https://doi.org/10.3390/en13184986 - 22 Sep 2020
Cited by 5 | Viewed by 2056
Abstract
Heat and fluid flow at the edge of steam chambers found in thermal recovery processes such as steam-assisted gravity drainage and cyclic steam stimulation remain unresolved. Given the multiple phases present and contrast of thermophysical properties, it remains unclear where instabilities occur within [...] Read more.
Heat and fluid flow at the edge of steam chambers found in thermal recovery processes such as steam-assisted gravity drainage and cyclic steam stimulation remain unresolved. Given the multiple phases present and contrast of thermophysical properties, it remains unclear where instabilities occur within this thin, yet critical, zone of the process. In the research reported here, heat and fluid flow are examined in vertical and horizontal sections of a steam chamber to understand the differences between the two orientations by using detailed and fine-gridded thermal reservoir simulation models. The results show that heat transfer in vertical and horizontal directions are different with greater heat transfer found in the vertical orientation. In the vertical direction, heat transfer occurs with mobilized bitumen draining with subsequent steam moving into the emptied pore space. Conduction beyond the edge of the chamber dominates and heated, low viscosity bitumen fingers into cold, higher viscosity bitumen at the edge of the chamber. Relative permeability effects are observed which can interfere with enhanced oil mobility. Full article
(This article belongs to the Section J: Thermal Management)
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11 pages, 1340 KiB  
Article
The Impacts of the Energy Potential of Forest Biomass on the Local Market: An Example of South-Eastern Poland
by Tomasz Dudek
Energies 2020, 13(18), 4985; https://doi.org/10.3390/en13184985 - 22 Sep 2020
Cited by 4 | Viewed by 2371
Abstract
Forest biomass is and will remain a primary source of renewable energy in many EU countries in the coming years. The aim of this study was to determine the energy potential of forest biomass on a regional scale with regard to the needs [...] Read more.
Forest biomass is and will remain a primary source of renewable energy in many EU countries in the coming years. The aim of this study was to determine the energy potential of forest biomass on a regional scale with regard to the needs of its inhabitants in terms of electricity and heat consumption. The study was carried out in south-eastern Poland. Energy potential was calculated based on the determined wood mass and calorific value of wood. The current level of forest biomass acquisition satisfies 4.2% of the needs of the local market in terms of electricity and heat consumption. Taking into account high forest cover of the region (40%), the 60% annual increment of total harvesting, and obtaining biomass at the level of 30% of the total harvesting, waste wood from the forest can meet 58.1% of the needs of the local market in terms of electricity consumption and 14.4% of the need for thermal energy consumption. There is a certain niche in the fuel wood market that is currently unused, presenting the opportunity to develop this sector and generate additional jobs in local markets. However, the increase in obtained forest biomass must be in accordance with the principles of sustainable development. Full article
(This article belongs to the Section L: Energy Sources)
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22 pages, 14634 KiB  
Article
A Novel Data-Energy Management Algorithm for Smart Transformers to Optimize the Total Load Demand in Smart Homes
by Claude Ziad El-Bayeh, Ursula Eicker, Khaled Alzaareer, Brahim Brahmi and Mohamed Zellagui
Energies 2020, 13(18), 4984; https://doi.org/10.3390/en13184984 - 22 Sep 2020
Cited by 12 | Viewed by 2772
Abstract
The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might [...] Read more.
The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might be created, and other solutions are required. Many researchers tried to solve the problem; however, limitations exist because of the decentralized topology of the network. The system operator is not allowed to control the end-users’ load due to security and privacy issues. To overcome this situation, we propose a novel data-energy management algorithm on the transformer’s level that controls the power demand profiles of the householders and exchange energy between them without violating their privacy and security. Our method is compared to an existing one in the literature based on a decentralized control strategy. Simulations show that our approach has reduced the electricity cost of the end-users by 3%, increased the revenue of the system operator, and reduced techno-economic losses by 50% and 42%, respectively. Our strategy shows better performance even with a 100% penetration level of EVs on the network, in which it respects the network’s constraints and maintains the voltage within the recommended limits. Full article
(This article belongs to the Special Issue Community Microgrids)
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12 pages, 4278 KiB  
Article
Aerodynamic Investigation of a Horizontal Axis Wind Turbine with Split Winglet Using Computational Fluid Dynamics
by Miguel Sumait Sy, Binoe Eugenio Abuan and Louis Angelo Macapili Danao
Energies 2020, 13(18), 4983; https://doi.org/10.3390/en13184983 - 22 Sep 2020
Cited by 8 | Viewed by 3517
Abstract
Wind energy is one of the fastest growing renewable energy sources, and the most developed energy extraction device that harnesses this energy is the Horizontal Axis Wind Turbine (HAWT). Increasing the efficiency of HAWTs is one important topic in current research with multiple [...] Read more.
Wind energy is one of the fastest growing renewable energy sources, and the most developed energy extraction device that harnesses this energy is the Horizontal Axis Wind Turbine (HAWT). Increasing the efficiency of HAWTs is one important topic in current research with multiple aspects to look at such as blade design and rotor array optimization. This study looked at the effect of wingtip devices, a split winglet, in particular, to reduce the drag induced by the wind vortices at the blade tip, hence increasing performance. Split winglet implementation was done using computational fluid dynamics (CFD) on the National Renewable Energy Lab (NREL) Phase VI sequence H. In total, there are four (4) blade configurations that are simulated, the base NREL Phase VI sequence H blade, an extended version of the previous blade to equalize length of the blades, the base blade with a winglet and the base blade with split winglet. Results at wind speeds of 7 m/s to 15 m/s show that adding a winglet increased the power generation, on an average, by 1.23%, whereas adding a split winglet increased it by 2.53% in comparison to the extended blade. The study also shows that the increase is achieved by reducing the drag at the blade tip and because of the fact that the winglet and split winglet generating lift themselves. This, however, comes at a cost, i.e., an increase in thrust of 0.83% and 2.05% for the blades with winglet and split winglet, respectively, in comparison to the extended blade. Full article
(This article belongs to the Special Issue Numerical Simulation of Wind Turbines)
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18 pages, 1106 KiB  
Article
Spatial Effects and Nonlinear Analysis of Energy Consumption, Financial Development, and Economic Growth in China
by Huan Zhou, Shaojian Qu, Qinglu Yuan and Shilei Wang
Energies 2020, 13(18), 4982; https://doi.org/10.3390/en13184982 - 22 Sep 2020
Cited by 14 | Viewed by 2079
Abstract
Energy consumption is of great significance to the sustainable development of the economy. Due to the spatial heterogeneity of low-carbon growth in regional economies, the relationship between energy consumption and economic growth is complicated. However, a few researches have been published about spatial [...] Read more.
Energy consumption is of great significance to the sustainable development of the economy. Due to the spatial heterogeneity of low-carbon growth in regional economies, the relationship between energy consumption and economic growth is complicated. However, a few researches have been published about spatial spillover effects and non-linearity of energy consumption and financial development on regional economic growth in China. Based on the panel data of 30 provinces in China from 2007 to 2017, this paper analyzes the spatial spillover effects and threshold effects of energy consumption and financial development on regional economic growth by using spatial and nonlinear econometric methods. The main conclusions are as follows. Spatial econometric methods show that financial development and energy consumption are two factors of production input to promote China’s economic growth. Meanwhile, energy consumption and financial development have spillover effects on regional economic growth. Additionally, the nonlinear econometric method finds that with increasing financial development, the impact of energy consumption on economic growth is segmented. Therefore, relevant policies should be implemented to enhance the role of finance in energy consumption to promote low-carbon growth of China’s economy. Full article
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18 pages, 12644 KiB  
Article
Parametric Design to Maximize Solar Irradiation and Minimize the Embodied GHG Emissions for a ZEB in Nordic and Mediterranean Climate Zones
by Mattia Manni, Gabriele Lobaccaro, Nicola Lolli and Rolf Andre Bohne
Energies 2020, 13(18), 4981; https://doi.org/10.3390/en13184981 - 22 Sep 2020
Cited by 19 | Viewed by 3202
Abstract
This work presents a validated workflow based on an algorithm developed in Grasshopper to parametrically control the building’s shape, by maximizing the solar irradiation incident on the building envelope and minimizing the embodied emissions. The algorithm is applied to a zero-emission building concept [...] Read more.
This work presents a validated workflow based on an algorithm developed in Grasshopper to parametrically control the building’s shape, by maximizing the solar irradiation incident on the building envelope and minimizing the embodied emissions. The algorithm is applied to a zero-emission building concept in Nordic and Mediterranean climate zones. The algorithm enables conducting both energy and environmental assessments through Ladybug tools. The emissions embodied in materials and the solar irradiation incident on the building envelope were estimated in the early design stage. A three-steps optimization process through evolutionary solvers, such as Galapagos (one-objective) and Octopus (multi-objective), has been conducted to shape the most environmentally responsive ZEB model in both climates. The results demonstrated the replicability of the algorithm to optimize the solar irradiation by producing an increment of solar incident irradiation equal to 35% in the Mediterranean area, and to 20% in the Nordic climate. This could contribute to compensate the additional 15% of emissions due to the higher quantities of employed materials in the optimized design. The developed approach, which is based on the parametric design principles for ZEBs, represents a support instrument for designers to develop highly efficient energy solutions in the early design stages. Full article
(This article belongs to the Special Issue Life Cycle Thinking for a Sustainable Built Environment)
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17 pages, 4663 KiB  
Case Report
Energetic and Ecologic Heat Pumps Evaluation in Poland
by Sara Sewastianik and Andrzej Gajewski
Energies 2020, 13(18), 4980; https://doi.org/10.3390/en13184980 - 22 Sep 2020
Cited by 13 | Viewed by 2770
Abstract
The purpose of the work is a comparison of indirect carbon dioxide emissions between the different heat pump types that operate in Polish climate conditions. The analysis embraces air-to-water heat pump, ground-to-water heat pump, water-to-water heat pump and water-to-water heat pump with separating [...] Read more.
The purpose of the work is a comparison of indirect carbon dioxide emissions between the different heat pump types that operate in Polish climate conditions. The analysis embraces air-to-water heat pump, ground-to-water heat pump, water-to-water heat pump and water-to-water heat pump with separating heat exchanger in the selected towns one in each climatic zone in the country. The study starts from determining seasonal coefficient of performance in each location using heating degree days to estimate seasonal heat demand. Seasonal coefficient of performance values enable an assessment which kind of heat pump meets the European Union requirements in every location. Eventually, indirect CO2 emissions that is caused by electrical energy production, are estimated for every heat pump in each location. Ground-to-water heat pump and water-to-water heat pump satisfy these requirements in each climatic zone in Poland. Air-to-water heat pump would be an energetic and ecological viable on a condition that substantial changes were done in Polish electrical energy mix. Full article
(This article belongs to the Special Issue Innovations-Sustainability-Modernity-Openness in Energy Research 2020)
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19 pages, 9090 KiB  
Article
Digital Luminaire Design Using LED Digital Twins—Accuracy and Reduced Computation Time: A Delphi4LED Methodology
by Marc van der Schans, Joan Yu and Genevieve Martin
Energies 2020, 13(18), 4979; https://doi.org/10.3390/en13184979 - 22 Sep 2020
Cited by 10 | Viewed by 2557
Abstract
Light-emitting diode (LED) digital twins enable the implementation of fast digital design flows for LED-based products as the lighting industry moves towards Industry 4.0. The LED digital twin developed in the European project Delphi4LED mimics the thermal-electrical-optical behavior of a physical LED. It [...] Read more.
Light-emitting diode (LED) digital twins enable the implementation of fast digital design flows for LED-based products as the lighting industry moves towards Industry 4.0. The LED digital twin developed in the European project Delphi4LED mimics the thermal-electrical-optical behavior of a physical LED. It consists of two parts: a package-level LED compact thermal model (CTM), coupled to a chip-level multi-domain model. In this paper, the accuracy and computation time reductions achieved by using LED CTMs, compared to LED detailed thermal models, in 3D system-level models with a large number of LEDs are investigated. This is done up to luminaire-level, where all heat transfer mechanisms are accounted for, and up to 60 LEDs. First, we characterize a physical phosphor-converted white high-power LED and apply LED-level modelling to produce an LED detailed model and an LED CTM following the Delphi4LED methodology. It is shown that the steady-state junction temperature errors of the LED CTM, compared to the detailed model, are smaller than 2% on LED-level. To assess the accuracy and the reduction of computation time that can be realized in a 3D system-level model with a large number of LEDs, two use cases are considered: (1) an LED module-level model, and (2) an LED luminaire-level model. In the LED module-level model, the LED CTMs predict junction temperatures within about 6% of the LED detailed models, and reduce the calculation time by up to nearly a factor 13. In the LED luminaire-level model, the LED CTMs predict junctions temperatures within about 1% of LED detailed models and reduce the calculation time by about a factor of 4. This shows that the achievable computation time reduction depends on the complexity of the 3D model environment. Nevertheless, the results demonstrate that using LED CTMs has the potential to significantly decrease computation times in 3D system-level models with large numbers of LEDs, while maintaining junction temperature accuracy. Full article
(This article belongs to the Special Issue Thermal and Electro-thermal System Simulation 2020)
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14 pages, 9124 KiB  
Article
Mayenite Electrides and Their Doped Forms for Oxygen Reduction Reaction in Solid Oxide Fuel Cells
by Navaratnarajah Kuganathan, Ruslan V. Vovk and Alexander Chroneos
Energies 2020, 13(18), 4978; https://doi.org/10.3390/en13184978 - 22 Sep 2020
Viewed by 2321
Abstract
The oxygen reduction reaction is an important reaction at the cathode in solid oxide fuel cells. Materials that exhibit high chemical and mechanical stability, high ionic and electronic conductivity, and are non-toxic are of great interest as cathodes for the reduction of oxygen. [...] Read more.
The oxygen reduction reaction is an important reaction at the cathode in solid oxide fuel cells. Materials that exhibit high chemical and mechanical stability, high ionic and electronic conductivity, and are non-toxic are of great interest as cathodes for the reduction of oxygen. Here, we use density functional theory simulations to examine the efficacy of 12CaO·7Al2O3 and 12SrO·7Al2O3 electrides and their doped forms for the conversion of O2 gas to form O2− in their nanocages via encapsulation. Calculations show that encapsulation is exoergic in the un-doped electrides, and the formation of O2− is confirmed by the charge analysis. A stronger encapsulation is noted for C12A7 electride than the S12A7 electride. The C12A7 electride doped with B or Ga also exhibits exoergic encapsulation, but its encapsulation energy is slightly lower than that calculated for the un-doped C12A7 electride. There is an enhancement in the encapsulation for the S12A7 electride doped with B compared to its un-doped form. Doping of Ga in S12A7 electride exhibits only a very small change in the encapsulation with respect to its un-doped form. The present results can be of interest in the design of cathode material for solid oxide fuel cells. Full article
(This article belongs to the Special Issue Electrocatalysts for Fuel Cells and Hydrogen Production)
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18 pages, 838 KiB  
Article
Impact of COVID-19 on the Level of Energy Poverty in Poland
by Rafal Nagaj and Jaroslaw Korpysa
Energies 2020, 13(18), 4977; https://doi.org/10.3390/en13184977 - 22 Sep 2020
Cited by 45 | Viewed by 4579
Abstract
The main objective of the paper is to determine the impact of the COVID-19 pandemic on the level of energy poverty in Poland. In order to achieve such a goal, the first part of the article presents the definition of energy poverty and [...] Read more.
The main objective of the paper is to determine the impact of the COVID-19 pandemic on the level of energy poverty in Poland. In order to achieve such a goal, the first part of the article presents the definition of energy poverty and the nature of its measures, as well as the determinants and policies of the state addressing the issue of energy poverty mitigation. In the second part of the paper, the results of research into the level of energy poverty are analyzed and the variables affecting energy poverty in Poland during the pandemic are determined. It was established on the basis of these results that the present pandemic contributed to the aggravation of financial difficulties in Polish households with regard to financing expenditure on energy carriers. It was found that COVID-19 had a negative impact on the average disposable income of Polish households, which, with the increase in prices and expenditure on energy carriers, led to an increase in the proportion of disposable income spent on energy carriers. The most affected have been the poorest households. Moreover, the long downward trend in the level of energy poverty in Poland has reversed. Thus, it has been proved that COVID-19 has contributed to the intensification of energy poverty in Poland. The theoretical and empirical considerations contained in this paper may be a valuable source of scientific data on the impact of the pandemic on household energy poverty, while public institutions may find them a source of useful information, helping to create effective instruments to mitigate energy poverty in the Polish economy. Full article
(This article belongs to the Special Issue Management and Technology for Energy Efficiency Development)
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19 pages, 3043 KiB  
Article
A Coupling Diagnosis Method for Sensor Faults Detection, Isolation and Estimation of Gas Turbine Engines
by Linhai Zhu, Jinfu Liu, Yujia Ma, Weixing Zhou and Daren Yu
Energies 2020, 13(18), 4976; https://doi.org/10.3390/en13184976 - 22 Sep 2020
Cited by 5 | Viewed by 2042
Abstract
In this paper a novel fault detection, isolation, and identification (FDI&E) scheme using a coupling diagnosis method with the integration of the model-based method and unsupervised learning algorithm is proposed and developed for monitoring gas turbine sensor faults, which represents an integration of [...] Read more.
In this paper a novel fault detection, isolation, and identification (FDI&E) scheme using a coupling diagnosis method with the integration of the model-based method and unsupervised learning algorithm is proposed and developed for monitoring gas turbine sensor faults, which represents an integration of Square Root Cubature Kalman Filters (SRCKF) and an improved Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. A detection indicator produced by SRCKF with a specific hypothesis is used for extracting sensor fault features against process and measurement noise, as well as operating conditions. Then, an improved DBSCAN is implemented based on a voting scheme to detect and isolate the faulty sensors. Finally, a residual-based fault estimation scheme is proposed to track sensor fault evolution and help to judge the types of faults. Moreover, the observability of the model involved is analyzed to verify the stable operation of the FDI&E scheme. Various experiments for single and concurrent sensor fault scenarios in a dual-spool gas turbine prototype during a whole flight mission are conducted to demonstrate the effectiveness of the proposed FDI&E scheme. Moreover, comparative studies confirm the superiority of our proposed FDI&E scheme than the existing methods in terms of promptness and robustness of the sensor FDI. Full article
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14 pages, 2804 KiB  
Article
Recognition of Variable-Speed Equipment in an Air-Conditioning System Using Numerical Analysis of Energy-Consumption Data
by Rongjiang Ma, Xianlin Wang, Ming Shan, Nanyang Yu and Shen Yang
Energies 2020, 13(18), 4975; https://doi.org/10.3390/en13184975 - 22 Sep 2020
Cited by 4 | Viewed by 1921
Abstract
Motor-driven equipment (ME) is one of the key components in an air-conditioning system, which contributes to the vast majority of the total energy consumption by air-conditioning systems. Distinguishing variable- and constant-speed equipment is important since the energy simulation models of the two types [...] Read more.
Motor-driven equipment (ME) is one of the key components in an air-conditioning system, which contributes to the vast majority of the total energy consumption by air-conditioning systems. Distinguishing variable- and constant-speed equipment is important since the energy simulation models of the two types differ. Traditionally, types of ME are known in advance, and energy consumption data are consequently analyzed. However, in the application scenarios of energy consumption data mining, precedent information on the ME type could be missing. Thus, this study applies this process in reverse, providing new insight into energy consumption data of ME to recognize variable-speed ME in an air-conditioning system. The energy consumption data of ME in an air-conditioning system implemented in a commercial building were collected and numerically analyzed. A proposed simple parameter, coefficient of the median, and several numerical parameters were calculated and used to distinguish variable- from constant-speed ME. Results showed that the energy consumption data distributions of the two types of ME differed. The proposed coefficient of the median could successfully distinguish variable- from constant-speed ME, and it could be applied as an important step in energy consumption data mining of air-conditioning systems. Full article
(This article belongs to the Special Issue Data-Driven Energy-Cost Analysis of HVAC System for Buildings)
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15 pages, 5790 KiB  
Article
Comparative Analysis on Load Characteristic of Intermittently Conditioned Buildings for Different Wall Insulation Forms
by Liting Yuan, Zhiyi Wang, Yanyan Huang and Xiaolong Wang
Energies 2020, 13(18), 4974; https://doi.org/10.3390/en13184974 - 22 Sep 2020
Cited by 2 | Viewed by 1902
Abstract
The Air-conditioning System (ACS), used in office buildings in the hot summer and cold winter zone of China, are always operate intermittently. The dynamic thermal behaviors of building walls with real climate conditions may be different from those with only the representative day’s [...] Read more.
The Air-conditioning System (ACS), used in office buildings in the hot summer and cold winter zone of China, are always operate intermittently. The dynamic thermal behaviors of building walls with real climate conditions may be different from those with only the representative day’s climate conditions, due to the time varying nature of the climate, which will lead to the variation of the ACS loads. A numerical calculation was performed to analyze the effects of insulation form on heat behavior of external walls and ACS loads. The results indicate that cooling transmission load with inside insulation reaches its maximum value when the solar-air temperature in daytime is the highest, while that with outside insulation occurs at the time when the air temperature at night is the highest during summer. Heating transmission load for the wall with external and internal insulation both peaks in the day with lowest mean outdoor temperature during the last non-working period. Inside insulation can be considered a better way to reduce the peak load, peak-valley load difference and energy consumption. Full article
(This article belongs to the Section G: Energy and Buildings)
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21 pages, 1995 KiB  
Article
Seasonal Energy Storage Potential Assessment of WWTPs with Power-to-Methane Technology
by Zoltán Csedő, Botond Sinóros-Szabó and Máté Zavarkó
Energies 2020, 13(18), 4973; https://doi.org/10.3390/en13184973 - 22 Sep 2020
Cited by 17 | Viewed by 2756
Abstract
Power-to-methane technology (P2M) deployment at wastewater treatment plants (WWTPs) for seasonal energy storage might land on the agenda of decision-makers across EU countries, since large WWTPs produce a notable volume of biogas that could be injected into the natural gas grid with remarkable [...] Read more.
Power-to-methane technology (P2M) deployment at wastewater treatment plants (WWTPs) for seasonal energy storage might land on the agenda of decision-makers across EU countries, since large WWTPs produce a notable volume of biogas that could be injected into the natural gas grid with remarkable storage capacities. Because of the recent rapid increase of local photovoltaics (PV), it is essential to explore the role of WWTPs in energy storage and the conditions under which this potential can be realized. This study integrates a techno-economic assessment of P2M technology with commercial/investment attractiveness of seasonal energy storage at large WWTPs. Findings show that a standardized 1 MWel P2M technology would fit with most potential sites. This is in line with the current technology readiness level of P2M, but increasing electricity prices and limited financial resources of WWTPs would decrease the commercial attractiveness of P2M technology deployment. Based on a Hungarian case study, public funding, biomethane feed-in tariff and minimized or compensated surplus electricity sourcing costs are essential to realize the energy storage potential at WWTPs. Full article
(This article belongs to the Special Issue Seasonal Energy Storage with Power-to-Methane Technology)
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30 pages, 1934 KiB  
Article
Restoring Pre-Industrial CO2 Levels While Achieving Sustainable Development Goals
by Mark E. Capron, Jim R. Stewart, Antoine de Ramon N’Yeurt, Michael D. Chambers, Jang K. Kim, Charles Yarish, Anthony T. Jones, Reginald B. Blaylock, Scott C. James, Rae Fuhrman, Martin T. Sherman, Don Piper, Graham Harris and Mohammed A. Hasan
Energies 2020, 13(18), 4972; https://doi.org/10.3390/en13184972 - 22 Sep 2020
Cited by 13 | Viewed by 6547
Abstract
Unless humanity achieves United Nations Sustainable Development Goals (SDGs) by 2030 and restores the relatively stable climate of pre-industrial CO2 levels (as early as 2140), species extinctions, starvation, drought/floods, and violence will exacerbate mass migrations. This paper presents conceptual designs and techno-economic [...] Read more.
Unless humanity achieves United Nations Sustainable Development Goals (SDGs) by 2030 and restores the relatively stable climate of pre-industrial CO2 levels (as early as 2140), species extinctions, starvation, drought/floods, and violence will exacerbate mass migrations. This paper presents conceptual designs and techno-economic analyses to calculate sustainable limits for growing high-protein seafood and macroalgae-for-biofuel. We review the availability of wet solid waste and outline the mass balance of carbon and plant nutrients passing through a hydrothermal liquefaction process. The paper reviews the availability of dry solid waste and dry biomass for bioenergy with CO2 capture and storage (BECCS) while generating Allam Cycle electricity. Sufficient wet-waste biomass supports quickly building hydrothermal liquefaction facilities. Macroalgae-for-biofuel technology can be developed and straightforwardly implemented on SDG-achieving high protein seafood infrastructure. The analyses indicate a potential for (1) 0.5 billion tonnes/yr of seafood; (2) 20 million barrels/day of biofuel from solid waste; (3) more biocrude oil from macroalgae than current fossil oil; and (4) sequestration of 28 to 38 billion tonnes/yr of bio-CO2. Carbon dioxide removal (CDR) costs are between 25–33% of those for BECCS with pre-2019 technology or the projected cost of air-capture CDR. Full article
(This article belongs to the Section A: Sustainable Energy)
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28 pages, 4200 KiB  
Article
Stochastic Fractal Search Optimization Algorithm Based Global MPPT for Triple-Junction Photovoltaic Solar System
by Hegazy Rezk and Ahmed Fathy
Energies 2020, 13(18), 4971; https://doi.org/10.3390/en13184971 - 22 Sep 2020
Cited by 5 | Viewed by 1959
Abstract
A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has [...] Read more.
A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exploration and exploitation phases is one of its main advantages. Therefore, the SFS algorithm has been selected to extract the global maximum power point (MPP) under partial shading conditions. To prove the superiority of the proposed global MPPT–SFS based tracker, several shading scenarios have been considered. The idea of changing the shading scenario is to change the position of the global MPP. The obtained results are compared with common optimizers: Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), Firefly-Algorithm (FA), Invasive-Weed-Optimization (IWO), JAYA and Gravitational Search Algorithm (GSA). The results of comparison confirmed the effectiveness and robustness of the proposed global MPPT–SFS based tracker over ALO, CS, FPA, FA, IWO, JAYA, and GSA. Full article
(This article belongs to the Collection Feature Papers in Sustainable Energy)
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15 pages, 5544 KiB  
Article
Analysis of Energy Exchange with the Ground in a Two-Chamber Vegetable Cold Store, Assuming Different Lengths of Technological Break, with the Use of a Numerical Calculation Method—A Case Study
by Paweł Sokołowski and Grzegorz Nawalany
Energies 2020, 13(18), 4970; https://doi.org/10.3390/en13184970 - 22 Sep 2020
Cited by 9 | Viewed by 1698
Abstract
The paper deals with the impact of the technological break duration during the cold storage cycle on the energy demand of the cold store for vegetables and fruit and the temperature distribution in the ground under the cold store. The studied facility was [...] Read more.
The paper deals with the impact of the technological break duration during the cold storage cycle on the energy demand of the cold store for vegetables and fruit and the temperature distribution in the ground under the cold store. The studied facility was a two-chamber vegetable cold store located in southern Poland used to store carrots (Daucus carota) for nine months a year. The experiments were conducted for 12 months (01.05.2017–30.04.2018). The technological break during this period lasted three months (from 1 July 2018 to 30 September 2018). Continuous measurements (with 1-h frequency) were made in order to determine the boundary conditions for numerical analysis. The measured parameters included indoor air temperature, outdoor air temperature, ground temperature under the building and in its vicinity. There were 22 measuring points andPT100 sensors were used. The numerical analysis was based on the elementary balances method. WUFIplus® software was used as a calculation supporting tool. The numerical analysis was conducted for 14 calculation variants, with different duration of technological break. The calculation model validation was performed and the results showed a good correlation with the experimental data. The results of experimental studies and of calculations showed a significant impact of the technological break duration on the soil distribution in the ground and the building energy demand. A technological break of less than 4 weeks is the most optimal in the summer. The technological break longer than 4 weeks significantly affects the cooling energy demand in the first days of the cooling cycle and significantly extends the time necessary for the ground and the floor to reach the optimum temperature. The analysis of the floor temperature results (points A1–C1) showed that the technological break longer than four weeks causes the average floor temperature to exceed 4.0 °C. Therefore, the optimum solution is technological break lasting 7–35 days. Absence of technological break results in a decrease of energy gains from the ground by 20% relative to a three-month technological break. The impact of technological break duration was clearly seen in terms of energy losses from the cold store to the ground. In case of a 91-day technological break, the energy losses to the ground were 1289.5 kWh/a, while in case of absence of technological break this value was ninefold lower (147.5 kWh/a). Full article
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18 pages, 9136 KiB  
Article
Voltage-Balancing Strategy for Three-Level Neutral-Point-Clamped Cascade Converter under Sequence Smooth Modulation
by Le Yu, Xu Peng, Chao Zhou and Shibin Gao
Energies 2020, 13(18), 4969; https://doi.org/10.3390/en13184969 - 22 Sep 2020
Cited by 3 | Viewed by 1785
Abstract
Three-level neutral-point clamped cascaded converters (3LNPC-CC) are widely used in high power nigh-voltage applications. This paper mainly discusses the open-circuit fault in DC-side of the 3LNPC-CC. Optimized by the sequence pulse modulation, a sequence smooth modulation (SSM) is proposed to keep the DC-side [...] Read more.
Three-level neutral-point clamped cascaded converters (3LNPC-CC) are widely used in high power nigh-voltage applications. This paper mainly discusses the open-circuit fault in DC-side of the 3LNPC-CC. Optimized by the sequence pulse modulation, a sequence smooth modulation (SSM) is proposed to keep the DC-side voltage balance while the 3LNPC-CC suffers open-circuit fault from DC-side. The SSM found efficient switch-state path through a 3-D cube model and simplified the path from thousands of switch state. The SSM avoids the complex calculation in the voltage-balancing modulation, while the dynamic character of it was less influenced. At the same time, the modulation changes the voltage level smoothly and balances the fault DC-side voltage effectively. The characters of the proposed modulation are verified by the simulation and the experiment. Full article
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14 pages, 1586 KiB  
Article
Adaptive Square-Root Unscented Kalman Filter-Based State-of-Charge Estimation for Lithium-Ion Batteries with Model Parameter Online Identification
by Quan Ouyang, Rui Ma, Zhaoxiang Wu, Guotuan Xu and Zhisheng Wang
Energies 2020, 13(18), 4968; https://doi.org/10.3390/en13184968 - 22 Sep 2020
Cited by 33 | Viewed by 2652
Abstract
The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery’s model parameters need to [...] Read more.
The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery’s model parameters need to be extracted through cumbersome prior experiments. To remedy such deficiency, a recursive least squares (RLS) algorithm is utilized for model parameter online identification, and an adaptive square-root unscented Kalman filter (SRUKF) is designed to estimate the battery’s SOC. As demonstrated in extensive experimental results, the designed adaptive SRUKF combined with RLS-based model identification is a promising SOC estimation approach. Compared with other commonly used Kalman filter-based methods, the proposed algorithm has higher precision in the SOC estimation. Full article
(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)
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16 pages, 3115 KiB  
Article
Effect of Silica, Activated Carbon, and Alumina Supports on NiMo Catalysts for Residue Upgrading
by Kirtika Kohli, Ravindra Prajapati, Samir K. Maity and Brajendra Kumar Sharma
Energies 2020, 13(18), 4967; https://doi.org/10.3390/en13184967 - 22 Sep 2020
Cited by 11 | Viewed by 2618
Abstract
The effect of different supports such as silica (SBA-15), activated carbon (AC), and mesoporous alumina (Al2O3) on catalytic activities of hydrotreating nickel molybdenum (NiMo) catalysts was demonstrated for upgrading vacuum residue. Nitrogen adsorption-desorption analysis showed that SBA-15 and the [...] Read more.
The effect of different supports such as silica (SBA-15), activated carbon (AC), and mesoporous alumina (Al2O3) on catalytic activities of hydrotreating nickel molybdenum (NiMo) catalysts was demonstrated for upgrading vacuum residue. Nitrogen adsorption-desorption analysis showed that SBA-15 and the AC-supported NiMo catalyst possessed a very high surface area compared to the alumina-supported catalyst. However, NiMo/Al2O3 catalyst possesses a higher pore diameter and pore volume with an appropriate surface area. X-ray diffraction (XRD) analysis showed that active metals were dispersed in the catalytic supports. Transmission electron microscopy (TEM) analysis revealed the presence of type II active MoS2 sites in the NiMo/Al2O3 catalyst, which showed weak metal-support interactions having a high intrinsic activity. Catalyst activities such as hydrodesulfurization (HDS), hydrodemetallization (HDM) and asphaltene conversion (HDAs), and hydrocracking conversions of a vacuum residue were evaluated. The highest hydrotreating and hydrocracking conversions were observed with the NiMo catalyst supported on mesoporous alumina. The results also supported that the catalyst that has a large pore diameter, high pore volume, and better active metals dispersion is highly desirable for the upgrading of a vacuum residue. Full article
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16 pages, 1901 KiB  
Article
Fault Diagnosis of Traction Transformer Based on Bayesian Network
by Yong Xiao, Weiguo Pan, Xiaomin Guo, Sheng Bi, Ding Feng and Sheng Lin
Energies 2020, 13(18), 4966; https://doi.org/10.3390/en13184966 - 22 Sep 2020
Cited by 18 | Viewed by 2345
Abstract
As the core equipment of a traction power supply system, the traction transformer is very important to ensure the safe and reliable operation of the system. At present, the three-ratio method is mainly used to distinguish transformer faults, whereas such a method has [...] Read more.
As the core equipment of a traction power supply system, the traction transformer is very important to ensure the safe and reliable operation of the system. At present, the three-ratio method is mainly used to distinguish transformer faults, whereas such a method has some defects, such as insufficient coding and over-general fault classification. At the same time, on-site maintenance personnel make an empirical judgment based on various test data, which is subjective and uncertain to a certain extent. For cases with multiple abnormal data and relatively complex conditions, on-site personnel often need to discuss and even dismantle the transformer to identify the fault, which is time-consuming and costly. In order to improve the effect of fault diagnosis for traction transformer, this paper uses Bayesian network to correlate the cause and effect of various tests and faults. By combining the results of field tests, the fault is diagnosed by the causal probability of the Bayesian network, rather than relying on the exception that occurred in a single experiment to judge its fault. The diagnosis results are more accurate and objective by using the Bayesian network. In this paper, the frequent test anomalies of the traction transformer are taken into account in the network, so that the network can more comprehensively analyze the operation situation of the traction transformer and judge the type of fault. According to field situations, based on the existing set of symptoms of the Bayesian network fault diagnosis, this paper further considers the insulation resistance, dielectric loss tangent value, oil and gas, power frequency voltage, and leakage current. By combining the association rules algorithm and the experience of the field operators, the cause–effect relationship of test data and the conditional probability parameters of the network are obtained. Then, the Bayesian network is constructed and used for traction transformer fault diagnosis. The case study shows that the four types of fault diagnosed using the Bayesian network model proposed in this paper are consistent with the fault types inspected by on-site operators, which shows promising engineering application prospects. Full article
(This article belongs to the Section F: Electrical Engineering)
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15 pages, 1600 KiB  
Article
Uncertainty Analysis of Greenhouse Gas (GHG) Emissions Simulated by the Parametric Monte Carlo Simulation and Nonparametric Bootstrap Method
by Kun Mo Lee, Min Hyeok Lee, Jong Seok Lee and Joo Young Lee
Energies 2020, 13(18), 4965; https://doi.org/10.3390/en13184965 - 22 Sep 2020
Cited by 9 | Viewed by 2963
Abstract
Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., [...] Read more.
Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions. Full article
(This article belongs to the Special Issue Life Cycle Assessment of Environmental System)
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17 pages, 2837 KiB  
Article
A Novel Deep Learning Approach for Wind Power Forecasting Based on WD-LSTM Model
by Bingchun Liu, Shijie Zhao, Xiaogang Yu, Lei Zhang and Qingshan Wang
Energies 2020, 13(18), 4964; https://doi.org/10.3390/en13184964 - 22 Sep 2020
Cited by 49 | Viewed by 3359
Abstract
Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve [...] Read more.
Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve accurate prediction of wind power generation in China, a hybrid prediction model based on the combination of Wavelet Decomposition (WD) and Long Short-Term Memory neural network (LSTM) is constructed. Firstly, the nonstationary time series is decomposed into multidimensional components by WD, which can effectively reduce the volatility of the original time series and make them more stable and predictable. Then, the components of the original time series after WD are used as input variables of LSTM to predict the national wind power generation. Forty points were used, 80% as training samples and 20% as testing samples. The experimental results show that the MAPE of WD-LSTM is 5.831, performing better than other models in predicting wind power generation in China. In addition, the WD-LSTM model was used to predict the wind power generation in China under different development trends in the next two years. Full article
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20 pages, 4717 KiB  
Article
Iterative Auction for P2P Renewable Energy Trading with Dynamic Energy Storage Management
by Chen Zhang, Yong Wang and Tao Yang
Energies 2020, 13(18), 4963; https://doi.org/10.3390/en13184963 - 22 Sep 2020
Cited by 7 | Viewed by 1981
Abstract
In this paper, a peer-to-peer (P2P) renewable energy trading mechanism for microgrids when energy suppliers are equipped with storage devices is studied. A dynamic energy storage management strategy based on the local trading price is proposed and each supplier decides the amount of [...] Read more.
In this paper, a peer-to-peer (P2P) renewable energy trading mechanism for microgrids when energy suppliers are equipped with storage devices is studied. A dynamic energy storage management strategy based on the local trading price is proposed and each supplier decides the amount of energy to be sold and stored in real time. An iterative auction algorithm is presented to obtain the market equilibrium and optimal energy allocation schedule. The economic analysis of introducing energy storage devices in this trading market is further studied. Numerical examples of two 7 × 24-h energy trading scenarios with 20 consumers and 20 solar energy producers are used to illustrate the feasibility of this proposed trading mechanism, with sensitivity analysis of different parameters on social welfare. A comparison of the hourly optimal local trading price of these two markets is demonstrated to explain the dynamic process. It is found that in those days with high solar radiation, compared with the market with no storage device, the total cost for buyers in the market when storage devices are used shows a decline of 1.52% and the total profit for sellers shows an increase of 1.27%, which leads to a substantial relative improvement of 118.94% in the overall social welfare. Moreover, a brief economic analysis shows that the advantage of using energy storage in this example is guaranteed after five years of operation. Longer operation time does not mean more benefits considering the deterioration of battery packs and increase of operation and maintenance costs, and the profit reaches its maximum value at the 15th year. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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16 pages, 8139 KiB  
Article
Systematic Analysis of Materials for Coated Adsorbers for Application in Adsorption Heat Pumps or Refrigeration Systems
by Oscar Banos, Sven Ohmann, Felix Alscher, Cornelia Breitkopf, Vicente Pacheco, Maja Glorius and Matthias Veit
Energies 2020, 13(18), 4962; https://doi.org/10.3390/en13184962 - 22 Sep 2020
Cited by 3 | Viewed by 2120
Abstract
Water vapor sorption in salt hydrates is a promising method to realize seasonal solar heat storage. Several of these materials have already shown promising performance for this application. However, a significant bottle neck for applications is the low thermal conductivity. In this study, [...] Read more.
Water vapor sorption in salt hydrates is a promising method to realize seasonal solar heat storage. Several of these materials have already shown promising performance for this application. However, a significant bottle neck for applications is the low thermal conductivity. In this study, several fabrication methods of the fixation of salts and their hydrates on metals to overcome the problem are presented. The products are analyzed concerning the hydration states, the corrosion behavior, the chemical compatibility, and the mechanical stability. Full article
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17 pages, 2074 KiB  
Article
Efficiency versus Equity in Spatial Siting of Electricity Generation: Citizen Preferences in a Serious Board Game in Switzerland
by Franziska Steinberger, Tobias Minder and Evelina Trutnevyte
Energies 2020, 13(18), 4961; https://doi.org/10.3390/en13184961 - 22 Sep 2020
Cited by 6 | Viewed by 2165
Abstract
Energy transitions around the world will change the spatial fingerprint of the electricity sector, but there is a lack of studies on citizen preferences for siting the future mix of electricity technologies. Using the case of Switzerland in 2035, we present a serious [...] Read more.
Energy transitions around the world will change the spatial fingerprint of the electricity sector, but there is a lack of studies on citizen preferences for siting the future mix of electricity technologies. Using the case of Switzerland in 2035, we present a serious board game to form and elicit citizen preferences for spatial siting of a full mix of electricity technologies and we test this game with 44 participants in the city of Zurich. The game proves to help elicit valid preferences of the participants and lead to measurable learning effects about this complex, multi-dimensional topic. The results show that these 44 participants prefer a diverse mix of renewable technologies for Switzerland in 2035. In terms of siting, these participants consistently choose the efficiency strategy, where new plants are concentrated in the areas where they produce most electricity at least cost, in contrast to the strategy of regional equity, where all Swiss regions would equally build new generation and share the benefits and burdens of the energy transition. Full article
(This article belongs to the Section C: Energy Economics and Policy)
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13 pages, 4232 KiB  
Article
Gasification of Cup Plant (Silphium perfoliatum L.) Biomass–Energy Recovery and Environmental Impacts
by Adam Koniuszy, Małgorzata Hawrot-Paw, Cezary Podsiadło, Paweł Sędłak and Ewa Możdżer
Energies 2020, 13(18), 4960; https://doi.org/10.3390/en13184960 - 22 Sep 2020
Cited by 6 | Viewed by 1882
Abstract
Biomass from cup plant (Silphium perfoliatum L.) is considered a renewable energy source that can be converted into alternative fuel. Calorific syngas, a promising type of advanced fuel, can be produced through thermochemical biomass gasification. In this study, the suitability of cup [...] Read more.
Biomass from cup plant (Silphium perfoliatum L.) is considered a renewable energy source that can be converted into alternative fuel. Calorific syngas, a promising type of advanced fuel, can be produced through thermochemical biomass gasification. In this study, the suitability of cup plant biomass for gasification was assessed, including the process energy balance and environmental impacts of waste from syngas purification. Silphium perfoliatum L. was cultivated as a gasification feedstock in different conditions (irrigation, fertilization). The experiments were performed in a membrane gasifier. All obtained energy parameters were compared to the biomass yield per hectare. The toxic effects of liquid waste were assessed using tests analyzing germination/seed root elongation of Sinapsis alba. Leachates collected from condensation tanks of a gas generator were introduced to soil at the following doses: 100, 1000 and 10,000 mg kg−1 DM of soil. The usefulness of Silphium perfoliatum L. for gasification was confirmed. The factors of plant cultivation affected the biomass yield, the volume and calorific value of syngas and the amount of biochar. It was determined that the components found in condensates demonstrate a phytotoxic effect, restricting or inhibiting germination and root elongation of Sinapsis alba. Due to this potential hazard, the possibility of its release to the environment should be limited. Most of the biomass is only used for heating purposes, but the syngas obtained from the cup plant can be used to power cogeneration systems, which, apart from heat, also generate electricity. Full article
(This article belongs to the Special Issue Thermochemical Conversion of Biomass and Waste)
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5 pages, 174 KiB  
Editorial
Special Issue “Selected Papers from the 2018 IEEE International Conference on High Voltage Engineering (ICHVE 2018)”
by Ioannis F. Gonos and Issouf Fofana
Energies 2020, 13(18), 4959; https://doi.org/10.3390/en13184959 - 22 Sep 2020
Viewed by 1669
Abstract
The 2018 IEEE International Conference on High Voltage Engineering and Application (ICHVE 2018) was organized by the National Technical University of Athens, Greece and endorsed by the IEEE Dielectrics and Electrical Insulation Society [...] Full article
18 pages, 38585 KiB  
Article
The Influence of Building Renovations on Indoor Comfort—A Field Test in an Apartment Building
by Paula Ala-Kotila, Terttu Vainio and Jarmo Laamanen
Energies 2020, 13(18), 4958; https://doi.org/10.3390/en13184958 - 22 Sep 2020
Cited by 8 | Viewed by 3594
Abstract
This article presents a field test of how deep renovation affects indoor climate quality. The studied apartment building was built in 1968 and is located in Finland, within the Nordic climate zone. The deep renovation included façade repair with extra insulation, new windows [...] Read more.
This article presents a field test of how deep renovation affects indoor climate quality. The studied apartment building was built in 1968 and is located in Finland, within the Nordic climate zone. The deep renovation included façade repair with extra insulation, new windows with trickle vents, new balcony glass and doors, and the installation of an exhaust air heat pump into the existing mechanical exhaust air ventilation. The indoor climate conditions and building envelope tightness were measured before and after the renovation. As a result of these energy renovation measures, the building envelope tightness improved by nearly 40% and the uncontrolled supply of air (draughts) decreased by approximately 24%. The overall energy consumption of the building decreased by 45%. Above all, the long testing period gives credibility to the study. The field test brought up the challenge of supplying an adequate amount of fresh air. This article highlights the fact that windows are part of a mechanical ventilation system if fresh air is not controlled by being led through inlet ducts. The supply air flow and volume must be ensured by correctly dimensioned valves, and therefore we stress the importance of the technical cooperation of technical designers. Full article
(This article belongs to the Special Issue Energy Performance and Indoor Climate in Buildings)
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