In this paper we present an approach for real-time simulation and Hardware-in-the-Loop (HIL) testing of Modular Multilevel Converters (MMCs) that rely on switching models while supporting system level analysis. Using the Latency Based Linear Multistep Compound (LB-LMC) approach, we achieved a 50 ns simulation time step for systems composed of several MMC converters and for converters of various complexity. To facilitate system level testing, we introduce the use of a serial communication-based (Aurora) interface for HIL testing of MMC converters and we analyzed the effect that communication latency has on the accuracy of the HIL test. The simulation and HIL results are validated against an MMC laboratory prototype.

Carbon dioxide-based enhanced oil-recovery (CO2-EOR) processes have gained considerable interest among other EOR methods. In this paper, based on the molecular weight of paraffins (n-alkanes), pressure, and temperature, the magnitude of CO2−n-alkanes interfacial tension (IFT) was determined by utilizing soft computing and mathematical modeling approaches, namely: (i) radial basis function (RBF) neural network (optimized by genetic algorithm (GA), gravitational search algorithm (GSA), imperialist competitive algorithm (ICA), particle swarm optimization (PSO), and ant colony optimization (ACO)), (ii) multilayer perception (MLP) neural network (optimized by Levenberg-Marquardt (LM)), and (iii) group method of data handling (GMDH). To do so, a broad range of laboratory data consisting of 879 data points collected from the literature was employed to develop the models. The proposed RBF-ICA model, with an average absolute percent relative error (AAPRE) of 4.42%, led to the most reliable pred... [more]

Transportation data in a smart city environment is increasingly becoming available. This data availability allows building smart solutions that are viewed as meaningful by both city residents and city management authorities. Our research work was based on Lisbon mobility data available through the local municipality, where we integrated and cleaned different data sources and applied a CRISP-DM approach using Python. We focused on mobility problems and interdependence and cascading-effect solutions for the city of Lisbon. We developed data-driven approaches using artificial intelligence and visualization methods to understand traffic and accident problems, providing a big picture to competent authorities and supporting the city in being more prepared, adaptable, and responsive, and better able to recover from such events.

Waterflooding remains the most commonly used method to improve oil recovery. Although the injected brine type is mainly dependent on its availability, few of its characteristics can be controlled during project design. Published laboratory work indicates that the adjustment of injected brine composition can cause an increase in oil production by wettability alteration. This research objective is to propose a novel four-step framework for modeling improved oil recovery by Engineered Water Injection from laboratory to numerical simulation for carbonate formations. We use a geochemical-based model that estimates contact angles to predict wettability alteration. The steps are (1) screening criteria, (2) geochemical evaluation, (3) wettability alteration modeling, and (4) coreflood history-match. We validate our framework by conducting history-match simulations of Brazilian Pre-Salt corefloods. Incremental oil recovery factors are between 5 to 11%, consistent with those reported during expe... [more]

Faced promising development of autonomous vehicles, the concept Mobility as a Service embraces AVs. The autonomous delivery has also been arising and tested for last-mile solution. Accordingly, passenger transportation and delivery service are to be jointly coordinated in the future MaaS. The research niche is summarized as how to embed crowdsourced parcel delivery into MaaS based on AVs. Electricity powered vehicles are to be applied considering energy consumption and air emission. Research questions are identified as what this novel service is and how it works, especially focusing on task coordination and the related information management. The system engineering process-oriented approaches, matching theory, and numerical method have been applied. The service concept has been elaborated, which contains information system architecture model and functional model. The matching condition of this service is summarized. As the embedded delivery can partially share the demand of traditional... [more]

In comparison to lignocellulosic biomass, which is suitable for thermo-chemical valorization, the organic fraction of municipal solid waste (OFMSW) is mainly treated via composting or anaerobic digestion (AD). An efficient utilization of OFMSW is difficult due to variations in its composition. Based on the characteristics of OFMSW, hydrothermal treatment (HTT) experiments at temperatures < 200 °C as an alternative OFMSW-processing were evaluated in this study. The raw OFMSW was characterized with a dry matter (DM)-based organic dry matter (oDM) content of 77.88 ± 1.37 %DM and a higher heating value (HHV) of 15,417 ± 1258 J/gDM. Through HTT at 150, 170 and 185 °C, the oDM contents as well as H/C and O/C ratios were lowered while the HHV increased up to 16,716 ± 257 J/gDM. HTT led to improved fuel properties concerning ash melting, corrosion stress and emission behavior. Negative consequences of the HTT process were higher contents of ash in the biochar as well as accumulated heavy me... [more]

Trolleybus transport is one of the classic means of public transport in cities. Its popularity varied in the past and was largely related to the fuel market situation. As fuel prices fell, electricity-powered transport lost popularity. The situation was similar during fuel crises. Trolleybuses gained in popularity then. Nowadays, the development of alternative power sources (APS) technology makes trolleybus transport partially independent of the overhead contact system, which is its great advantage. It is thus possible to develop trolleybus connections in areas where there is no justification for building overhead wiring infrastructure. The article analyses the development of on-board APS and their spatial diffusion in trolleybus systems in Europe. The main result of the research procedure indicates that the development of battery technologies, which could accelerate the closure of trolleybus transport due to the strong competition of electric buses not requiring an overhead contact li... [more]

Predicting the future peak demand growth becomes increasingly important as more consumer loads and electric vehicles (EVs) start connecting to the grid. Accurate forecasts will enable energy suppliers to meet demand more reliably. However, this is a challenging problem since the peak demand is very nonlinear. This study addresses the research question of how deep learning methods, such as convolutional neural networks (CNNs) and long-short term memory (LSTM) can provide better support to these areas. The goal is to build a suitable forecasting model that can accurately predict the peak demand. Several data from 2004 to 2019 was collected from Panama’s power system to validate this study. Input features such as residential consumption and monthly economic index were considered for predicting peak demand. First, we introduced three different CNN architectures which were multivariate CNN, multivariate CNN-LSTM and multihead CNN. These were then benchmarked against LSTM. We found that the... [more]

The availability of suitable water is an important factor for increasing the cultivated areas and sustainability in arid (i.e., less than 200 mm precipitation per year) and semiarid regions (i.e., 200−700 mm precipitation per year). Therefore, this study aimed to analyze the impact of treated wastewater (TWW) and groundwater (GW) as well as synthetic fertilizers (50% and 100% of the recommended NPK dose; 150−150−60 kg N−P2O5−K2O ha−1) on the growth, biomass, energy traits, and macro and trace elements of maize (Zea mays L.), sorghum (Sorghum bicolor L.), and pearl millet (Pennisetum glaucum L) grown in old cultivated (first location; L1) and virgin soil (L2 and L3) as potential bioenergy crops. The soil in L1 has been irrigated with treated wastewater for the last 15 years and continued to be irrigated with treated wastewater in this investigation. The virgin soil was divided into two parts: the first part was irrigated with TWW, and the second part was irrigated with GW. The experimen... [more]

Water management is a key factor affecting the efficiency of proton exchange membrane fuel cells (PEMFCs). The currently used monitoring methods of PEMFCs provide limited information about which processes or components that humidity has a significant impact upon. Herein, we propose the use of a novel approach of impedance measurements using a multi-sinusoidal perturbation signal, which enables impedance measurements under dynamic operating conditions. The manuscript presents the effect of the relative humidity (RH) of the reactants on the instantaneous impedance of the middle cell in the PEMFC stack as a function of the current load. Analysis of changes in the values of equivalent circuit elements was carried out to determine which process determines the stack’s performance depending on the load range of the fuel cell during operation. Comprehensive impedance analysis showed that to ensure optimal cell operation, the humidity of the reactants should be adjusted depending on the load le... [more]

The article presents issues related to the aging behavior of oil-paper insulations in transformers using different oil- and ester-based insulating fluids. Despite numerous conducted studies on the subject of oil-paper aging, the use of new insulating fluids is creating open questions. In addition, new liquids such as synthetic and natural esters, as well as oil of the newest generation, are being used. Furthermore, there is still little research on the formation of aging markers with this form of the dielectric. For this reason, in this contribution, oil-paper insulations with mineral oil-based insulating fluids, natural and synthetic esters, as well as oil from natural gas, are aged thermally accelerated at 130 °C over a duration of 15 weeks, by considering two cases of free-breathing and hermetically sealed transformers. Therefore, various aging markers are investigated to allow a condition assessment. The results show that differences exist between the fluids and design of the trans... [more]

As an independent power system, the reliability of offshore electric system is closely related to the smooth progress of offshore oil production. There are two major characteristics of this type of power system. One is that it includes a generation system, transmission system, as well as a distribution system, and the other is that the load shedding measures in the event of a fault are different from that of the onshore power grid. Therefore, traditional reliability assessment models and algorithms cannot be used directly. Based on the theory of overall reliability evaluation, a reliability evaluation method suitable for offshore electric systems and the corresponding reliability indicators are proposed in this paper. In state sampling, the overall system sampling is divided into generation system sampling, transmission system sampling, and distribution system sampling based on the hybrid sampling theory. In state assessment, the priority decoupling load shedding model and the cascade... [more]

Digital technologies enable companies to build cyber-physical systems (CPS) in Industry 4.0. In the increasingly popular concept of Industry 4.0, an important research topic is the application of digital technology in industry, and in particular in specific industry sectors. The aim of this paper is to present the tools used in the steel industry in Poland on its way to the full digitalisation that is needed for the development of Industry 4.0. The paper consists of two parts: a literature review and a practical analysis. The paper provides the background information about digitalisation using digital tools in the steel industry in Poland. The paper was prepared based on secondary information and statistical data. The object of the research is the Polish steel sector. This study assumes that digitalisation is the main area of innovation in the steel industry. The digitalisation determines the creation of new or modified products, processes, techniques and expansion of the company’s inf... [more]

Sustainability has been recognized as a major concern globally since the Brudtland Report, in 1987, and further reinforced in 2015 by the United Nations Sustainable Development Goals (UNSDG) 2030. This paper reviews the methodologies and criteria of sustainability applied to fashion products, regarding products’ environmental footprint (environmental life cycle assessment/analysis; e-LCA), the social issues (including the social life cycle assessment/analysis; s-LCA) and the transparency in reporting sustainability. In our review we seek KPIs (key performance indicators) that allow classification of a pair of shoes or a piece of cloth on a scale from A to E, i.e., products can be compared with a benchmark and classified accordingly with a simple labelling scheme, which is easily understandable by the consumers. This approach is similar to those used to classify electrical appliances, housing energy consumption for thermal comfort, food Nutri-Scores, CO2 levels of road vehicles, and tir... [more]

Latent heat storage units for refrigeration processes are promising as alternatives to water/glycol-based storage due to their significantly higher energy densities, which would lead to more compact and potentially more cost-effective storages. In this study, important thermophysical properties of five phase change material (PCM) candidates are determined in the temperature range between −22 and −35 °C and their compatibility with relevant metals and polymers is investigated. The goal is to complement existing scattered information in literature and to apply a consistent testing methodology to all PCMs, to enable a more reliable comparison between them. More specifically, the enthalpy of fusion, melting point, density, compatibility with aluminum, copper, polyethylene (PE), polypropylene (PP), neoprene and butyl rubber, are experimentally determined for 1-heptanol, n-decane, propionic acid, NaCl/water mixtures, and Al(NO3)3/water mixtures. The results of the investigations reveal indiv... [more]

DC-DC converters with constant power loads are mostly used in DC microgrids. Negative impedance and large disturbances of constant power loads may lead to the instability of DC-DC converters. To address this issue, a nonlinear control strategy consisting of an improved passivity-based controller and nonlinear power observer is proposed in this paper. First, an improved passivity-based controller is designed based on the port-controlled Hamiltonian with dissipation model. By proper damping and interconnection injecting, the fast dynamic response of output voltage and stability of the DC-DC converter is achieved. Second, the constant power load is observed by a nonlinear power observer, which is adopted to estimate the power variation of the constant power load within a small settling time and improve the adaptability of the DC-DC converter under power disturbance. Finally, the simulation and experimental results are presented, which illustrate the proposed control strategy not only ensu... [more]

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations... [more]

The composition characteristics of altered coals in the Huaibei Coalfield, China, was investigated through a comparative analysis between altered and unaffected coals from the Wolonghu, Taoyuan and Renlou coal mines. Results indicated that the altered coals in Wolonghu coal mine are mostly anthracite coals, with a maximum vitrinite reflectance of 1.6−3.9% (average of 2.9%). Coals from Wolonghu coal mine were mainly consisted of vitrinite (66.2−97.0%), followed by inertinite (2.0−4.0%) and exinite (0.4−6.9%). Differences in volatile matter content were observed between the altered coals in Wolonghu coal mine and unaffected coals from neighboring coal mines, implying that the chemical composition and maturity of coals were changed after magmatic alteration. In addition, differences in hydrogen element were noted among the coals from Wolonghu, Renlou and Taoyuan coal mines, and the phenomenon of “deficient in hydrogen element” was observed in Wolonghu coals. The aliphatic hydrocarbon stru... [more]

Dissolved gas analysis (DGA) based in insulating oil has become a more mature method in the field of transformer fault diagnosis. However, due to the complexity and diversity of fault types, the traditional modeling method based on oil sample analysis is struggling to meet the industrial demand for diagnostic accuracy. In order to solve this problem, this paper proposes a probabilistic neural network (PNN)-based fault diagnosis model for power transformers and optimizes the smoothing factor of the pattern layer of PNN by the improved gray wolf optimizer (IGWO) to improve the classification accuracy and robustness of PNN. The standard GWO easily falls into the local optimum because the update mechanism is too single. The update strategy proposed in this paper enhances the convergence ability and exploration ability of the algorithm, which greatly alleviates the dilemma that GWO is prone to fall into local optimum when dealing with complex data. In this paper, a reliability analysis of t... [more]

This research compares the potential environmental impacts of heat pumps with gas boilers and scenario analysis through utilising the life cycle approach. The study analyses the current situation with the baseline model and assesses future applications with Circular Economy (CE), Resource Efficiency (RE) and Limited Growth (LG) scenarios. Then, hybrid applications of low-carbon technologies and different manufacturing scenarios are investigated according to baseline and CE scenarios. Our results show that the use and manufacturing phases are responsible for 74% and 14% of all environmental impacts on average as expected. Even though the electricity mix of the UK has decarbonised substantially during the last decade, heat pumps still have higher lifetime impacts than gas boilers in all environmental categories except climate change impact. The carbon intensity of heat pumps is much lower than gas boilers with 0.111 and 0.097 kg CO2e for air source heat pumps and ground source heat pumps... [more]

The article discusses the selection of cables for power lines connecting wind turbine generators at the wind power plant. The screen cross-section of these cables should be selected considering the value of the screen current at double line-to-earth fault. To calculate this current, the dimensions of the cable should be known. However, these parameters are hidden and cannot be used during designing. Therefore, a highly simplified method is currently used in practice. It is shown that the errors from the highly simplified method are up to 33%. Authors propose a simplified method based on open data of cable manufacturers. The proposed method is compared with simulation results of a common model of cable power line and takes into account self and mutual inductances of the cores and screens. It is shown that the error of the proposed method is smaller than 4.0% for real cable power lines at wind power plants. However, for a long section of cable power line (2.5 km) the error of calculation... [more]

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches.... [more]

With the growth of commercial building sizes, it is more beneficial to make them “smart” by controlling the schedule of the heating, ventilation, and air conditioning (HVAC) system adaptively. Single-building-based scheduling methods are more focused on individual interests and usually result in overlapped schedules that can cause voltage deviations in their microgrid. This paper proposes a decentralized management framework that is able to minimize the total electricity costs of a commercial microgrid and limit the voltage deviations. The proposed scheme is a two-level optimization where the lower level ensures the thermal comfort inside the buildings while the upper level consider system-wise constraints and costs. The decentralization of the framework is able to maintain the privacy of individual buildings. Multiple data-driven building models are developed and compared. The effect of the building modeling on the overall operation of coordinated buildings is discussed. The proposed... [more]

In April 2018, the International Maritime Organisation adopted an ambitious plan to contribute to the global efforts to reduce the Greenhouse Gas emissions, as set by the Paris Agreement, by targeting a 50% reduction in shipping’s Green House Gas emissions by 2050, benchmarked to 2008 levels. To meet these challenging goals, the maritime industry must introduce environmentally friendly fuels with negligible, or low SOX, NOX and CO2 emissions. Ammonia use in maritime applications is considered promising, due to its high energy density, low flammability, easy storage and low production cost. Moreover, ammonia can be used as fuel in a variety of propulsors such as fuel cells and can be produced from renewable sources. As a result, ammonia can be used as a versatile marine fuel, exploiting the existing infrastructure, and having zero SOX and CO2 emissions. However, there are several challenges to overcome for ammonia to become a compelling fuel towards the decarbonisation of shipping. Such... [more]

Efficient photon to charge (PTC) transfer is considered to be the cornerstone of technological improvements in the photovoltaic (PV) industry, while it constitutes the most common process in nature. This study aims to investigate the parameters that impact efficient PV-cell photon to charge conversion in two ways: (a) providing a brief research analysis to extract the key features which affect the electrical and optical performance of PV cells’ operation, and (b) investigating the dependance of these characteristics on the photon to charge mechanisms. The former direction focuses on the latest advances regarding the impacts of the microenvironment climate conditions on the PV module and its operational performance, while the latter examines the fundamental determinants of the cell’s efficient operation. The electrical and optical parameters of the bulk PV cells are influenced by both the external microenvironment and the intrinsic photon to charge conversion principles. Light and energ... [more]