bluuebunny/crossref_metadata_2025 huggingface dataset:
Life Cycle Assessment of Tall Onshore Hybrid Steel Wind Turbine Towers
Authors: Gkantou Michaela , Rebelo Carlos , Baniotopoulos Charalampos
Published: August 2020

Increasing needs for taller wind turbines with bigger capacities, intended for places with high wind velocities or at higher altitudes, have led to new technologies in the wind energy industry. A recently introduced structural system for onshore wind turbine towers is the hybrid steel tower. Comprehension of the environmental response of this hybrid steel structural system is warranted. Even though life cycle assessments (LCAs) for conventional wind turbine tubular towers exist, the environmental performance of this new hybrid structure has not been reported. The present paper examines the LCA of 185 m tall hybrid towers. Considerations made for the LCA procedure are meticulously described, including particular attention at the erection and transportation stage. The highest environmental impacts arise during the manufacturing stage followed by the erection stage. The tower is the component with the largest carbon emissions and energy requirements. The obtained LCA footprints of hybrid towers are also compared to the literature data on conventional towers, resulting in similar environmental impacts.
Efficient FEC Scheme for Solar-Powered WSNs Considering Energy and Link-Quality
Authors: Gil Gun Wook , Kang Minjae , Kim Younghyun , Yoon Ikjune , Noh Dong Kun
Published: August 2020

In solar-powered wireless sensor networks (SP-WSNs), the best use of harvested energy is more important than minimizing energy consumption since energy can be supplied periodically. Meanwhile, as is well known, the reliability of the communication between sensor nodes is very limited due to the resource constraints of sensor nodes. In this paper, we propose an efficient forward error correction (FEC) scheme which can give solar-powered wireless sensor networks more reliable communication. First, the proposed scheme provides energy-adaptive operation for the best use of solar energy. It calculates the amount of surplus energy which can be used for extra operations and then determines the number of additional parity bits for FEC according to this amount of surplus energy. At the same time, it also provides a link quality model that is used to calculate the appropriate number of parity bits for error recovery required for the current data communication environment. Finally, by considering these two parity sizes, it is possible to determine the number of parity bits that can maximize the data reliability without affecting the blacking out of nodes. The evaluation of the performance of the approach was performed by comparing the amount of data collected at the sink node and the number of blackout nodes with other schemes.
Research on D-STATCOM Double Closed-Loop Control Method Based on Improved First-Order Linear Active Disturbance Rejection Technology
Authors: Ma Youjie , Sun Xiaotong , Zhou Xuesong
Published: August 2020

The application of a distribution static synchronous compensator (D-STATCOM) is the best technical means to solve the problem of reactive power compensation and harmonics. The D-STATCOM system has the characteristics of variable parameters, strong coupling, nonlinearity and multi-variability. In order to improve the speed of the dynamic tracking response and anti-disturbance capability of the D-STATCOM, the article proposes an improved Linear Active Disturbance Rejection Controller (LADRC) based on the total disturbance deviation control method. Combined with double closed-loop control, the inner loop takes the current as the state variable, and the outer loop uses the DC side output voltage as the state variable to achieve robust stability of the D-STATCOM and controller output. The simulation results show that the improved LADRC is more stable than the traditional LADRC in controlling the DC voltage waveform of the compensator, reactive current tracking and reactive power compensation waveform when it is disturbed, which verifies the superiority and feasibility of the improved LADRC.
Preference Structure on the Design of Hydrogen Refueling Stations to Activate Energy Transition
Authors: Park Soyeong , Nam Solji , Oh Myoungjin , Choi Ie-jung , Shin Jungwoo
Published: August 2020

As a countermeasure to the greenhouse gas problem, the world is focusing on alternative fuel vehicles (AFVs). The most prominent alternatives are battery electric vehicles (BEV) and fuel cell electric vehicles (FCEVs). This study examines FCEVs, especially considering hydrogen refueling stations to fill the gap in the research. Many studies suggest the important impact that infrastructure has on the diffusion of AFVs, but they do not provide quantitative preferences for the design of hydrogen refueling stations. This study analyzes and presents a consumer preference structure for hydrogen refueling stations, considering the production method, distance, probability of failure to refuel, number of dispensers, and fuel costs as core attributes. For the analysis, stated preference data are applied to choice experiments, and mixed logit is used for the estimation. Results indicate that the supply stability of hydrogen refueling stations is the second most important attribute following fuel price. Consumers are willing to pay more for green hydrogen compared to gray hydrogen, which is hydrogen produced by fossil fuels. Driver fuel type and perception of hydrogen energy influence structure preference. Our results suggest a specific design for hydrogen refueling stations based on the characteristics of user groups.
Electrical Detection of Degradation in Specimens of HVDC Cable Insulation
Authors: Nilsson Douglas Jutsell , Gubanski Stanislaw M. , Serdyuk Yuriy V.
Published: August 2020

One of the challenges in laboratory investigation of degradation and ageing of HVDC cable insulation is related to securing, or in other words, imitating the real service environment of the material specimens. So far, the published data refer to experiments conducted in thermo-oxidative conditions, which is not the case during normal cable operation. In service, the cable insulation is protected by a metallic barrier that blocks the transfer of any substances in and out of the construction. By-products from the cross-linking reactions cannot diffuse out and any foreign substances are blocked from entering the insulation. Thus, in order to generate results that are valid, these conditions must be replicated in laboratory experiments. This contribution presents a methodology elaborated for performing ageing experiments in a hermetically sealed environment. Degradation of the material is evaluated through changes in the electrical tree inception voltage and test object capacitance over time. Securing the environmental isolation is accomplished with an isolation system consisting of a glass enclosure with attached metallic electrodes. Indium is used to create a glass-to-metal seal between the glass and the electrodes. The electrode geometry is of needle–plane type and the needle injection process is semi-automated to ensure specimen repeatability.
Development and Laboratory Testing of a Self-Excited Synchronous Machines without Permanent Magnets
Authors: Marignetti Fabrizio , Di Stefano Roberto Luigi , Rubino Guido , Conti Paolo
Published: August 2020

Today, self-excited synchronous machines are the object of increasing interest because they use neither brushes nor permanent magnets. In fact, the price of rare earth metals is considerably high and still raising. This is the main reason why researchers are looking for suitable alternatives to permanent magnets in the construction of rotating electrical machinery. This paper deals with the design and laboratory testing of a synchronous machine with an efficient layout and an economic construction. The proposed self-excited machine exploits the space harmonics of the magneto-motive force to produce the excitation field. The model analysis is based on the computation of the back EMFs that are associated to the magneto motive force components. The mathematical model suggests an easy way to decouple the rotor windings. The machine has been built and experimental tests have been performed in order to validate the electrical behavior.
Operational Performance of Electric Power Firms: Comparison between Japan and South Korea by Non-Radial Measures
Authors: Sueyoshi Toshiyuki , Ryu Youngbok , Goto Mika
Published: August 2020

This study compares the electric power sectors between Japan and South (S) Korea. Both nations have been under a global trend of deregulation. To assess their progress due to industrial change and technology development, we use Data Envelopment Analysis (DEA) as an assessment tool that enables us to evaluate the level of simultaneous achievements on economic and technological measures, so assessing the degree of holistic development. DEA has been widely applied for performance assessment in the past decades. In this study, the method compares electric power firms by their operational efficiencies. To compare their achievements, it is necessary to develop a new type of DEA application for performance measurement. The proposed approach adds two analytical capabilities. First, the approach needs to handle “zero” in a data set and then restrict multipliers (i.e., weights among inputs and outputs) without any prior information to increase our empirical reliability. No study has simultaneously explored the two capabilities in DEA. Using the proposed method, our empirical study identifies two findings. One of the two is that the electric power industry of S. Korea outperformed that of the Japanese industry in the observed periods (2014–2018) because the Japanese power sector still suffered from an occurrence of the Fukushima Daiichi nuclear plant disaster which occurred on 1 March 2011. However, the difference has been gradually diminishing because the Japanese electricity industry has been gradually recovering from the huge disaster. The other is that the S. Korean power industry has been in a descending trend because the nation has shown technical regress as a result of inconsistent technology development (e.g., shifting its R&D: Research and Development) focus from electrical engineering to chemistry). The former R&D area is essential in maintaining the technical level of S. Korea′s electric power industry.
Community Resilience-Oriented Optimal Micro-Grid Capacity Expansion Planning: The Case of Totarabank Eco-Village, New Zealand
Authors: Mohseni Soheil , Brent Alan C. , Burmester Daniel
Published: August 2020

In the grid-tied micro-grid context, energy resilience can be defined as the time period that a local energy system can supply the critical loads during an unplanned upstream grid outage. While the role of renewable-based micro-grids in enhancing communities’ energy resilience is well-appreciated, the academic literature on the techno-economic optimisation of community-scale micro-grids lacks a quantitative decision support analysis concerning the inclusion of a minimum resilience constraint in the optimisation process. Utilising a specifically-developed, time-based resilience capacity characterisation method to quantify the sustainability of micro-grids in the face of different levels of extended grid power outages, this paper facilitates stakeholder decision-making on the trade-off between the whole-life cost of a community micro-grid system and its degree of resilience. Furthermore, this paper focuses on energy infrastructure expansion planning, aiming to analyse the importance of micro-grid reinforcement to meet new sources of electricity demand—particularly, transport electrification—in addition to the business-as-usual demand growth. Using quantitative case study evidence from the Totarabank Subdivision in New Zealand, the paper concludes that at the current feed-in-tariff rate (NZ$0.08/kWh), the life cycle profitability of resilience-oriented community micro-grid capacity reinforcement is guaranteed within a New Zealand context, though constrained by capital requirements.
A Hybrid vs. On-Grid Photovoltaic System: Multicriteria Analysis of Environmental, Economic, and Technical Aspects in Life Cycle Perspective
Authors: Żelazna Agnieszka , Gołębiowska Justyna , Zdyb Agata , Pawłowski Artur
Published: August 2020

Hybrid photovoltaic installations, defined as on-grid PV system in cooperation with battery energy storage system (BESS), are still rare among the typical investors because the investment cost of the hybrid installation is significantly higher than the one of the on-grid system. However, while considering the broader perspective, such as environmental or technological aspects, the mentioned solution can be competitive with photovoltaic on-grid systems and therefore should be carefully tested in the widest possible context. In this study, the authors compared 3.05 kW of peak power hybrid and on-grid installations operating in temperate climate conditions (Eastern Poland) using economic indicators, such as dynamic generation cost (DGC) and benefit–cost rate (BCR); environmental impact indicators (IMPACT 2002+ and GWP 100a) determined using Life Cycle Assessment (LCA); and technological aspects consideration, including the reliability of examined systems. Creating a ranking of the considered solutions based on the equal weighting factors assigned to the appropriate features allows indicating the technological areas where the competitiveness of hybrid systems justifies the increased investment costs. One such area is business, where the economic criterion, the only negatively assessed one in the standard operation, can be radically changed by the possible financial losses due to interruption of energy supply.
Applications of Game Theory to Design and Operation of Modern Power Systems: A Comprehensive Review
Authors: Navon Aviad , Ben Yosef Gefen , Machlev Ram , Shapira Shmuel , Roy Chowdhury Nilanjan , Belikov Juri , Orda Ariel , Levron Yoash
Published: August 2020

In this work, we review papers that employ game theoretic tools to study the operation and design of modern electric grids. We consider four topics in this context: energy trading, energy balancing, grid planning, and system reliability, and we demonstrate the advantages of using game-theoretic approaches for analyzing complex interactions among independent players. The results and conclusions provide insights regarding many aspects of design and operation, such as efficient methodologies for expansion planning, cyber-security, and frequency stability, or fair-benefit allocation among players. A central conclusion is that modeling the system from the perspective of one entity with unlimited information and control span is often impractical, so correct modeling of the selfish behavior of independent players may be critical for the development of future power systems. Another conclusion is that correct usage of incentives by appropriate regulation or sophisticated pricing mechanisms may improve the social welfare, and, in several cases, the results obtained are as good as those obtained by central planning. Using an extensive content analysis, we point to several trends in the current research and attempt to identify the research directions that are currently at the focus of the community.
Domestic Organic Rankine Cycle-Based Cogeneration Systems as a Way to Reduce Dust Emissions in Municipal Heating
Authors: Kolasiński Piotr
Published: August 2020

Environmental issues are nowadays of great importance. In particular air and water quality should be kept at as high levels as possible. Energy conversion systems and devices which are applied for converting the chemical energy contained in different fuels into heat, electricity and cold in the industry and housing are sources of different gases and solid particle emissions. Medical data show PM2.5 dust in particular is highly dangerous for human health. Therefore, limiting the number of low-quality fuel combustion processes is a key issue of modern energy policy. Statistical data show that domestic heating systems account for a large share of the total emissions of PM2.5 and PM10 dust. For example in Poland in 2017, the share of households in the total annual emissions of PM2.5 dust was equal to ca. 35.8%, while the share of PM2.5 emission in industry (i.e., power generating plants, industrial power plants and technologies) was equal to only 23.6%. A possible way of solving this problem is by the successful replacement of old domestic furnaces by combined heat and power (CHP) or multigeneration boilers which can be used for heating the rooms and sanitary water and generating electricity and cold. Such systems can possibly contribute in the future to significant reductions of dust emissions and air pollution in urban and rural areas by limiting the number of low-quality fuel combustion processes. This article presents design considerations and experimental results related to a domestic micro-CHP unit which is based on organic Rankine cycle (ORC) technology. The main aim of the design works and experiments was therefore the analysis of the possibility of integrating the ORC system with a standard domestic central heating gas-fired boiler. The specially designed micro-ORC system was implemented in the laboratory and experiments were performed using this test stand. The main design aims of the test-stand were: low operating pressure, small working fluid flow, low price and compact dimensions. To meet these aims, volumetric machines were chosen as the expander and working fluid pump. The experimental results were positive and show that it is possible to integrate an ORC system with a standard domestic central heating gas boiler. For different heat source temperatures, the obtained expander power ranged from 109 W to 241 W and the thermodynamic cycle efficiency ranged from 4.3% to 8.8%. These positive research results were achieved partly thanks to the positive features of the different system subassemblies.
Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies
Authors: Tipantuña Christian , Hesselbach Xavier
Published: August 2020

Energy consumption is a critical issue for the communications network operators, impacting deeply the cost of the services, as well as the ecological footprint. Network slicing architecture for 5G mobile communications enables multiple independent virtual networks to be created on top of a common shared physical infrastructure. Each network slice needs different types of resources, including energy, to fulfill the demands requested by each application, operator, or vertical market. The existing literature on network slicing is mainly targeted at the partition of network resources; however, the corresponding management of energy consumption is an unconsidered critical concern. This paper analyzes the requirements for an energy-aware 5G network slicing provisioning according to the 3GPP specifications, proposes an architecture, and studies the strategies to provide efficient energy consumption in terms of renewable and non-renewable sources. NFV and SDN technologies are the essential enablers and leverage the Internet of Things (IoT) connectivity provided by 5G networks. This paper also presents the technical 5G technology documentation related to the proposal, the requirements for adaptive energy management, and the Integer Linear Programming (ILP) formulation of the energy management model. To validate the improvements, an exact optimal algorithmic solution is presented and some heuristic strategies.
An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore
Authors: Onea Florin , Ruiz Andrés , Rusu Eugen
Published: August 2020

The main objective of the present work is to provide a comprehensive picture of the wind conditions in the Spanish continental nearshore considering a state-of-the-art wind dataset. In order to do this, the ERA5 wind data, covering the 20-year time interval from 1999 to 2018, was processed and evaluated. ERA stands for ’ECMWF Re-Analysis’ and refers to a series of research projects at ECMWF (European Centre for Medium-Range Weather Forecasts) which produced various datasets. In addition to the analysis of the wind resources (reported for a 100 m height), the performances of several wind turbines, ranging from 3 to 9.5 MW, were evaluated. From the analysis of the spatial maps it was observed that the Northern part of this region presents significant wind resources, the mean wind speed values exceeding 9 m/s in some locations. On the other hand, in regard to the Southern sector, more energetic conditions are visible close to the Strait of Gibraltar and to the Gulf of Lion. Nevertheless, from the analysis of the data corresponding to these two Southern nearshore points it was observed that the average wind speed was lower than 8 m/s in both summer and winter months. Regarding the considered wind turbines, the capacity factor did in general not exceed 20%—however, we did observe some peaks that could reach to 30%. Finally, it can be highlighted that the Northern part of the Spanish continental nearshore is significant from the perspective of extracting offshore wind energy, especially considering the technologies based on floating platforms. Furthermore, because of the clear synergy between wind and wave energy, which are characteristic to this coastal environment, an important conclusion of the present work is that the implementation of joint wind–wave projects might be effective in the Northwestern side of the Iberian nearshore.
Multi-Step Solar Irradiance Forecasting and Domain Adaptation of Deep Neural Networks
Authors: Guariso Giorgio , Nunnari Giuseppe , Sangiorgio Matteo
Published: August 2020

The problem of forecasting hourly solar irradiance over a multi-step horizon is dealt with by using three kinds of predictor structures. Two approaches are introduced: Multi-Model (MM) and Multi-Output (MO). Model parameters are identified for two kinds of neural networks, namely the traditional feed-forward (FF) and a class of recurrent networks, those with long short-term memory (LSTM) hidden neurons, which is relatively new for solar radiation forecasting. The performances of the considered approaches are rigorously assessed by appropriate indices and compared with standard benchmarks: the clear sky irradiance and two persistent predictors. Experimental results on a relatively long time series of global solar irradiance show that all the networks architectures perform in a similar way, guaranteeing a slower decrease of forecasting ability on horizons up to several hours, in comparison to the benchmark predictors. The domain adaptation of the neural predictors is investigated evaluating their accuracy on other irradiance time series, with different geographical conditions. The performances of FF and LSTM models are still good and similar between them, suggesting the possibility of adopting a unique predictor at the regional level. Some conceptual and computational differences between the network architectures are also discussed.
Constrained Generation Bids in Local Electricity Markets: A Semantic Approach
Authors: Santos Gabriel , Faria Pedro , Vale Zita , Pinto Tiago , Corchado Juan M.
Published: August 2020

The worldwide investment in renewable energy sources is leading to the formation of local energy communities in which users can trade electric energy locally. Regulations and the required enablers for effective transactions in this new context are currently being designed. Hence, the development of software tools to support local transactions is still at an early stage and faces the challenge of constant updates to the data models and business rules. The present paper proposes a novel approach for the development of software tools to solve auction-based local electricity markets, considering the special needs of local energy communities. The proposed approach considers constrained bids that can increase the effectiveness of distributed generation use. The proposed method takes advantage of semantic web technologies, in order to provide models with the required dynamism to overcome the issues related to the constant changes in data and business models. Using such techniques allows the system to be agnostic to the data model and business rules. The proposed solution includes the proposed constraints, application ontology, and semantic rule templates. The paper includes a case study based on real data that illustrates the advantages of using the proposed solution in a community with 27 consumers.
Evolution of Soot Particle Number, Mass and Size Distribution along the Exhaust Line of a Heavy-Duty Engine Fueled with Compressed Natural Gas
Authors: Distaso Elia , Amirante Riccardo , Calò Giuseppe , De Palma Pietro , Tamburrano Paolo
Published: August 2020

An experimental study has been conducted to provide a characterization of the transformations that particle size distributions and the number density of soot particles can encounter along the exhaust line of a modern EURO VI compliant heavy-duty engine, fueled with compressed natural gas. Being aware of the particles history in the exhausts can be of utmost importance to understand soot formation and oxidation dynamics, so that, new strategies for further reducing these emissions can be formulated and present and future regulations met. To this purpose, particle samples were collected from several points along the exhaust pipe, namely upstream and downstream of each device the exhaust gases interact with. The engine was turbocharged and equipped with a two-stage after-treatment system. The measurements were carried out in steady conditions while the engine operated in stoichiometric conditions. Particle emissions were measured using a fast-response particle size spectrometer (DMS500) so that size information was analyzed in the range between 5 and 1000 nm. Particle mass information was derived from size distribution data using a correlation available in the literature. The reported results provide more insight on the particle emission process related to natural gas engines and, in particular, point out the effects that the turbine and the after-treatment devices produce on soot particles. Furthermore, the reported observations suggest that soot particles might not derive only from the fuel, namely, external sources, such as lubricant oil, might have a relevant role in soot formation.
A Case Study to Identify the Hindrances to Widespread Adoption of Electric Vehicles in Qatar
Authors: Khandakar Amith , Rizqullah Annaufal , Ashraf Abdou Berbar Anas , Rafi Ahmed Mohammad , Iqbal Atif , Chowdhury Muhammad E. H. , Uz Zaman S. M. Ashfaq
Published: August 2020

The adoption of electric vehicles (EVs) have proven to be a crucial factor to decreasing the emission of greenhouse gases (GHG) into the atmosphere. However, there are various hurdles that impede people from purchasing EVs. For example, long charging time, short driving range, cost and insufficient charging infrastructures available, etc. This article reports the public perception of EV-adoption using statistical analyses and proposes some recommendations for improving EV-adoption in Qatar. User perspectives on EV-adoption barriers in Qatar were investigated based on survey questionnaires. The survey questionnaires were based on similar studies done in other regions of the world. The study attempted to look at different perspectives of the adoption of EV, when asked to a person who is aware of EVs (technical respondents—people studying/working at universities/research centers and policy makers) or a person who may or may not be aware of EVs (non-technical respondents—people working in banks, governments and private non-academic organizations, etc.). Cumulative survey responses from the two groups were compared and analyzed using two-sample t-test statistical analysis. Detailed analyses showed that—among various major hindrances—raising of public awareness of such greener modes of transportation, the availability of charging options in more places and policy incentives towards EVs would play a major role in EV-adoption. The authors provide recommendations that—along with government incentives—could help make a gradual shift to a greater number of EVs convenient for people of Qatar. The proposed systematic approach for such a study and analysis may help in streamlining research on policies, infrastructures and technologies for efficient penetration of EVs in Qatar.
Long-Term Electricity Demand Prediction via Socioeconomic Factors—A Machine Learning Approach with Florida as a Case Study
Authors: Elkamel Marwen , Schleider Lily , Pasiliao Eduardo L. , Diabat Ali , Zheng Qipeng P.
Published: August 2020

Predicting future energy demand will allow for better planning and operation of electricity providers. Suppliers will have an idea of what they need to prepare for, thereby preventing over and under-production. This can save money and make the energy industry more efficient. We applied a multiple regression model and three Convolutional Neural Networks (CNNs) in order to predict Florida’s future electricity use. The multiple regression model was a time series model that included all the variables and employed a regression equation. The univariant CNN only accounts for the energy consumption variable. The multichannel network takes into account all the time series variables. The multihead network created a CNN model for each of the variables and then combined them through concatenation. For all of the models, the dataset was split up into training and testing data so the predictions could be compared to the actual values in order to avoid overfitting and to provide an unbiased estimate of model accuracy. Historical data from January 2010 to December 2017 were used. The results for the multiple regression model concluded that the variables month, Cooling Degree Days, Heating Degree Days and GDP were significant in predicting future electricity demand. Other multiple regression models were formulated that utilized other variables that were correlated to the variables in the best-selected model. These variables included: number of visitors to the state, population, number of consumers and number of households. For the CNNs, the univariant predictions had more diverse and higher Root Mean Squared Error (RMSE) values compared to the multichannel and multihead network. The multichannel network performed the best out of the three CNNs. In summary, the multichannel model was found to be the best at predicting future electricity demand out of all the models considered, including the regression model based on the datasets employed.
Composed Index for the Evaluation of the Energy Security of Power Systems: Application to the Case of Argentina
Authors: Fuentes Sergio , Villafafila-Robles Roberto , Lerner Eduardo
Published: August 2020

Energy transitions’ trend towards sustainable systems has prompted energy systems to shift from being fossil-fuel-based to rely on renewable energy. These transitions have led the power system to occupy the center of modern infrastructures, so assuring its security has become a priority for policy makers. This work presents a tool based on a multidimensional index, the Power System Security Index (PSIx), for the evaluation of policies affecting the security of the supply of electrical energy. The developed frame is applied to the current power system of Argentina, and it is compared to the system in year 2002. Availability of resources and infrastructure are the strengths of the country, while economic, governability, and research, development and innovation spheres leave room for improvement. The further incorporation of more economies to the study would substantially enrich the statistical analysis of the results.
Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy
Authors: Roh Minyoung , Jeon Seungho , Kim Soontae , Yu Sha , Heshmati Almas , Kim Suduk
Published: August 2020

South Korea has been suffering from high PM2.5 pollution. Previous studies have contributed to establishing PM2.5 mitigation policies but have not considered provincial features and sector-interactions. In that sense, the integrated assessment model (IAM) could complement the shortcomings of previous studies. IAM, capable of analyzing PM2.5 pollution levels at the provincial level in Korea, however, has not been developed yet. Hence, this study (i) expands on IAM which can represent provincial-level spatial resolution in Korea (GCAM-Korea) with air pollutant emissions modeling which focuses on the road transportation sector and (ii) examines the zero-emission vehicles (ZEVs) subsidy policy’s effects on PM2.5 mitigation using the expanded GCAM-Korea. Simulation results show that PM2.5 emissions decrease by 0.6–4.1% compared to the baseline, and the Seoul metropolitan area contributes 38–44% to the overall PM2.5 emission reductions. As the ZEVs subsidy is weighted towards the light-duty vehicle 4-wheels (LDV4W) sector, various spillover effects are found: ZEVs’ share rises intensively in the LDV4W sector leading to an increase in its service costs, and at the same time, driving bus service costs to become relatively cheaper. This, in turn, drives an increase in bus service demand and emissions discharge. Furthermore, this type of impact of the ZEVs subsidy policy does not reduce internal combustion engine vehicles (ICEVs) in freight trucks, although diesel freight trucks are a major contributor to PM2.5 emissions and also to NOx.
Underground Pumped Storage Hydropower Case Studies in Belgium: Perspectives and Challenges
Authors: Morabito Alessandro , Spriet Jan , Vagnoni Elena , Hendrick Patrick
Published: August 2020

To avoid the geographical and topographical prerequisites of the conventional pumped hydro energy storage, the use of underground cavities as water reservoirs allows countries without steep topography, such as Belgium, to increase the potential of the energy storage capacity. Belgium abounds in disused mines and quarries convertible into water basins. In this article, two Belgian case studies are presented and discussed for their singularity. A slate quarry in Martelange is discussed in technical aspects proposing three operating scenarios. Moreover, a preliminary economic analysis of the underground pumped storage system and a greenhouse gas emission evaluation for the storage system’s lifetime are presented. The analysis for a 100 MW power plant estimates a total initial investment of over 12 million euros and two million of CO2 avoided over its lifetime. This article also proposes the use of the coal mine 500 m deep of Pérronnes-lez-Binche. The mine representation discussed here offers a high energy capacity, but the substantial head drop (from about 500 to 200 m) challenges the selection of the hydraulic turbomachinery. A 1D simulation computed in SIMSEN draws out the behaviour of the unusual hydraulic configuration of turbines in series.
Cryo-Mechanical Treatment and Hydrometallurgical Process for Recycling Li-MnO2 Primary Batteries with the Direct Production of LiMnPO4 Nanoparticles
Authors: Schiavi Pier Giorgio , dos Santos Martins Padoan Flavia Carla , Altimari Pietro , Pagnanelli Francesca
Published: August 2020

In this work, an innovative hydrometallurgical recycling route for the recovery of all the materials composing Li-MnO2 primary batteries was proposed. End-of-life batteries were mechanically treated in an innovative pilot plant where a cryogenic crushing was performed. The mechanical treatment allowed for the release of the electrodic powder contained in the batteries with the simultaneous recovery of 44 kg of steel and 18 kg of plastics from 100 kg of batteries. Electrodic powder was employed as the raw material for the synthesis of LiMnPO4 nanoparticles. To obtain the synthesis precursors, selective sequential leaching of Li and Mn was performed. Li was extracted via water washing the electrodic powder and Li2CO3 and a purity of 99% was recovered. The black mass containing Mn oxides was leached using phosphoric acid, which gave a Mn-bearing precursor solution that was directly used for the hydrothermal synthesis of LiMnPO4 nanoparticles. A preliminary materials balance of the process was presented, indicating that the proposed process should be an easy hydrometallurgical route for the recycling of primary lithium batteries. In addition, the simultaneous production of high-value-added products that could be reintroduced into the battery manufacturing chain could ensure the economic feasibility of the process.
Development of a Predictive Model for a Photovoltaic Module’s Surface Temperature
Authors: Jung Dong Eun , Lee Chanuk , Kim Kee Han , Do Sung Lok
Published: August 2020

PV (photovoltaic) systems are receiving the spotlight in Korea due to the Renewable Energy 3020 Implementation Plan (RE3020), which has the goal of reaching 20% for the proportion of renewable energy generation by 2030. Accordingly, the actual performance evaluation of PV systems to achieve the RE3020 has become more important. PV efficiency is mainly determined by various weather conditions (e.g., solar radiation) that affect the power generation of PV systems. However, the efficiency is also affected by changes in module surface temperature. In particular, the efficiency decreases when the module surface temperature rises. That is, the actual PV efficiency falls short of the rated efficiency. The estimation of module surface temperature is critical for evaluating the actual performance of PV systems. Many studies have been conducted to calculate the surface temperature. However, most of the previous studies focused on calculations of current surface temperatures using current environment data, which means that the previous studies have limitations related to timestep. That is, there is a lack of predictive models that calculate the future surface temperatures by using the current measured data. Therefore, this study developed a predictive model using an ANN (artificial neural network) algorithm to determine the surface temperature of PV modules for a future period of time. Then, this study evaluated the actual performance (i.e., power generation) with the predicted surface temperatures.
Optimal Calibration Strategy of a Hybrid Electric Vehicle Equipped with an Ultra-Lean Pre-Chamber SI Engine for the Minimization of CO2 and Pollutant Emissions
Authors: Bozza Fabio , De Bellis Vincenzo , Malfi Enrica , Teodosio Luigi , Tufano Daniela
Published: August 2020

The complexity of modern hybrid powertrains poses new challenges for the optimal control concerning, on one hand, the thermal engine to maximize its efficiency, and, on the other hand, the vehicle to minimize the noxious emissions and CO2. In this context, the engine calibration has to be conducted by considering simultaneously the powertrain management, the vehicle characteristics, and the driving mission. In this work, a calibration methodology for a two-stage boosted ultra-lean pre-chamber spark ignition (SI) engine is proposed, aiming at minimizing its CO2 and pollutant emissions. The engine features a flexible variable valve timing (VVT) control of the valves and an E-compressor, coupled in series to a turbocharger, to guarantee an adequate boost level needed for ultra-lean operation. The engine is simulated in a refined 1D model. A simplified methodology, based on a network of proportional integral derivative (PID) controllers, is presented for the calibration over the whole operating domain. Two calibration variants are proposed and compared, characterized by different fuel and electric consumptions: the first one aims to exclusively maximize the brake thermal efficiency, and the second one additionally considers the electric energy absorbed by the E-compressor and drained from the battery. After a verification against the outcomes of an automatic optimizer, the calibration strategies are assessed based on pollutant and CO2 emissions along representative driving cycles by vehicle simulations. The results highlight slightly lower CO2 emissions with the calibration approach that minimizes the E-compressor consumption, thus revealing the importance of considering the engine calibration phase, the powertrain management, the vehicle characteristics, and its mission.
Implication of m6A mRNA Methylation in Susceptibility to Inflammatory Bowel Disease
Authors: Sebastian-delaCruz Maialen , Olazagoitia-Garmendia Ane , Gonzalez-Moro Itziar , Santin Izortze , Garcia-Etxebarria Koldo , Castellanos-Rubio Ainara
Published: August 2020

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract that develops due to the interaction between genetic and environmental factors. More than 160 loci have been associated with IBD, but the functional implication of many of the associated genes remains unclear. N6-Methyladenosine (m6A) is the most abundant internal modification in mRNA. m6A methylation regulates many aspects of mRNA metabolism, playing important roles in the development of several pathologies. Interestingly, SNPs located near or within m6A motifs have been proposed as possible contributors to disease pathogenesis. We hypothesized that certain IBD-associated SNPs could regulate the function of genes involved in IBD development via m6A-dependent mechanisms. We used online available GWAS, m6A and transcriptome data to find differentially expressed genes that harbored m6A-SNPs associated with IBD. Our analysis resulted in five candidate genes corresponding to two of the major IBD subtypes: UBE2L3 and SLC22A4 for Crohn’s Disease and TCF19, C6orf47 and SNAPC4 for Ulcerative Colitis. Further analysis using in silico predictions and co-expression analyses in combination with in vitro functional studies showed that our candidate genes seem to be regulated by m6A-dependent mechanisms. These findings provide the first indication of the implication of RNA methylation events in IBD pathogenesis.
Estimation of Chilling and Heat Accumulation Periods Based on the Timing of Olive Pollination
Authors: Rojo Jesús , Orlandi Fabio , Ben Dhiab Ali , Lara Beatriz , Picornell Antonio , Oteros Jose , Msallem Monji , Fornaciari Marco , Pérez-Badia Rosa
Published: August 2020

Research Highlights: This paper compares the thermal requirements in three different olive-growing areas in the Mediterranean region (Toledo, central Spain; Lecce, southeastern Italy; Chaal, central Tunisia). A statistical method using a partial least square regression for daily temperatures has been applied to study the chilling and heat requirements over a continuous period. Background and Objectives: The olive is one of the main causes of pollen allergy for the population of Mediterranean cities. The physiological processes of the reproductive cycle that governs pollen emission are associated with temperature, and thermal requirements strongly regulate the different phases of the plant’s life cycle. However, the point when several specific processes occur—Such as the phases within the dormancy period—Is unclear, and the transition between endodormancy and ecodormancy is not easily distinguishable from an empirical point of view. This work focuses on defining the thermal accumulation periods related to the temperature balance needed to meet the chilling and heat requirements for the metabolic activation and budbreak in olive trees. Results and Conclusions: Thermal accumulation patterns in olive trees are strongly associated with the bioclimatic conditions of olive-growing areas, and the olive flowering start dates showed significant differences between the three studied stations. Our results show that the chilling requirements were fulfilled between late autumn and early winter, although the chilling accumulation period was more evident in the coldest and most continental bioclimatic areas (central Spain). The heat accumulation period (forcing period) was clearly defined and showed a close relationship with the timing of olive flowering. Heat requirements were therefore used to generate accurate forecasting models to predict the beginning of the olive bloom and subsequent olive pollen emission. A forecasting model considering both the chilling and heat requirements was generated in Toledo, where the estimated days displayed an error of 2.0 ± 1.8 days from the observed dates. For Lecce, the error was 2.7 ± 2.5 days and for Chaal, 4.2 ± 2.4 days.
Non-Thermal Plasma Can Be Used in Disinfection of Scots Pine (Pinus sylvestris L.) Seeds Infected with Fusarium oxysporum
Authors: Świecimska Magdalena , Tulik Mirela , Šerá Božena , Golińska Patrycja , Tomeková Juliána , Medvecká Veronika , Bujdáková Helena , Oszako Tomasz , Zahoranová Anna , Šerý Michal
Published: August 2020

The aim of this study was to use diffuse coplanar surface barrier discharge (DCSBD) non-thermal plasma for the disinfection of pine seed surfaces infected with Fusarium oxysporum spores. Artificially infected seeds of Scots pine (Pinus sylvestris L.) were treated with plasma for the following exposure times: 1 s, 3 s, 5 s, 10 s, 15 s, 20 s, 30 s, and 60 s, and subsequently germinated on agar medium in Petri dishes at room temperature for the estimation of seed germination and disinfection effect of plasma treatment. Results of the treated samples were compared to the control samples, which were prepared as follows: seeds uninfected and non-treated with plasma (first control); seeds infected with F. oxysporum and non-treated with plasma (second control); and seeds infected with F. oxysporum, non-treated with plasma, but sterilized with 30% perhydrol (third control). Obtained results indicate that 3 s plasma treatment was an optimal time to inhibit F. oxysporum growth, and at the same time, increase the seed germination. In addition, our results are the first to show the practical application of non-thermal plasma in disinfecting infected Scots pine seeds and improving their germination. According to the results of this study, non-thermal plasma can serve as a seed surface disinfectant in the regeneration of different pine species.
Physical and Microstructure Properties of Oyster Mushroom-Soy Protein Meat Analog via Single-Screw Extrusion
Authors: Mohamad Mazlan Mazween , Talib Rosnita A. , Chin Nyuk Ling , Shukri Radhiah , Taip Farah Saleena , Mohd Nor Mohd Zuhair , Abdullah Norazlin
Published: August 2020

Single-screw extrusion of a fibrous-structured meat analog from soy proteins added with low-grade oyster mushroom was successful. Satisfactory extrudates were obtained at a barrel temperature of 140 °C, screw speed range of 100–160 rpm, and oyster mushroom addition at 0%, 7.5%, and 15% via factorial experiments. Single-screw extrusion equipped with a slit die successfully produced expanded oyster mushroom-soy protein extrudates. However, the increase in the oyster mushroom content significantly decreased (p ≤ 0.05) the expansion ratio of the extrudate from 1.26 to 0.98. This result indicated that adding more oyster mushroom restrained the expansion ratio. The extrudates had a medium density range (max of 1393.70 ± 6.30 kg/m3). By adding oyster mushroom, the extrudates attained a higher moisture content (range = 34.77% to 37.93%) compared with the extrudates containing the protein mixture only (range = 26.99% to 32.33%). The increase in screw speed and oyster mushroom significantly increased (p ≤ 0.05) the water absorption index. The increase in the texturization index was significantly influenced (p ≤ 0.05) by oyster mushroom addition rather than the screw speed. A defined fibrous structure supported the high texturization index and small shape of air cells observed in the extrudates.