This paper presents an active power filter based on a seven-level cascade H-bridge where the main contribution is a control strategy that combines model-based predictive control, the voltage vectors of the converter output levels, the phase shift PWM technique, and suboptimal DC-link voltage control. The proposed scheme greatly simplified the overall control system, making it well suited to compensate the current harmonics distortion at the grid side, generated by nonlinear loads connected to the point of common coupling. In addition, the proposed method achieved a balancing of the capacitor voltages of the seven-level cascade H-bridge converter by using the minimum DC-link voltage sensors. This feature significantly reduced the control system complexity and provided a low computational burden. Experimental results confirmed the feasibility and effectiveness of the proposed controller.

How to detect uric acid is an important issue. For the purpose of preparing a potentiometric uric acid biosensor, this research used nickel oxide (NiO) as the sensing film to deposit it onto the substrate by radio frequency sputtering, then modified it with reduced graphene oxide (rGO) and silver (Ag) nanowires. Reduced graphene oxide (rGO) not only has excellent electrical conductivity, but also can make the surface of the film have a larger surface area, while AgNWs have also been proven to improve catalytic activity; hence, these two materials were chosen as sensor modifiers. Finally, the stability and the various characteristics of the uric acid biosensor were investigated using a voltage−time (V−T) system. The results showed that the AgNW−uricase/rGO/NiO uric acid biosensor has average sensitivity with 4.66 mV/(mg/L). In addition, the sensor has good stability.

In modern electrical power distribution systems, the effective operation of inverter-based arc suppression devices relies on the accuracy of faulty phase selection. In the traditional methods of faulty phase selection for single-phase-to-ground faults (SPGs), power frequency-based amplitude and phase characteristics are used to identify the faulty phase. In the field, when a high-resistance SPG occurs in the system, traditional methods are difficult for accurately identifying the faulty phase because of the weak fault components and complicated process. A novel realizable and effective method of faulty phase selection based on transient current similarity measurements is presented when SPGs occur in resonantly grounded distribution systems in this paper. An optimized Hausdorff distance matrix (MOHD) is proposed and constructed by the transient currents of three phases’ similarity measurements within a certain time window of our method. This MOHD is used to select the sampling time wind... [more]

Climate change has a potential impact on the number of hot and torrid days in the summer period. Due to the occupants’ comfort needs, and because of the high heat loads during the summer period, in several European countries, the energy used for air conditioning in buildings increased. With multiple environmental monitoring systems (Testo Saveris) in two similar offices, having west and east orientation of glazing, 1920 data (internal air, mean radiant temperature) related to operative temperature were collected in order to show the differences between heat loads of rooms with similar geometry in the same building. Data were measured in a 15 min interval. The diffuse and direct solar radiation had been determined for the horizontal and vertical surfaces, using the measured hourly global radiation (Debrecen, Hungary) data for the analyzed days (summer, hot, and torrid days). The local climatic results were compared with other climatic days used in different national standards. The daily... [more]

The revised EU Renewable Energy Directive first introduced renewable energy communities into the EU policy framework and requires Member States to implement a support framework for them. Given the broad scientific evidence showing the benefits of community energy for a just energy transition, a successful implementation across all Member States is essential. However, the preconditions for developing support frameworks differ largely between EU nations, as some countries have long-term experiences with supporting renewable energy communities (i.e., Germany and Denmark), while in other Member States, renewable energy communities are notably non-existent (i.e., Eastern European nations). With the purpose of providing scientific evidence to support the development of a policy framework for renewable energy communities in Eastern European Member States, this article compares key factors for the development of such communities in Bulgaria and Germany, combining a literature review with exper... [more]

Geothermal energy is a key renewable energy for Italy, with an annual electric production of 6.18 TWh. The future of geothermal energy is concerned with clarity over the CO2 emissions from power plants and geological contexts where CO2 is produced naturally. The Mt. Amiata volcanic−geothermal area (AVGA) is a formidable natural laboratory for investigating the relative roles of natural degassing of CO2 and CO2 emissions from geothermal power plants (GPPs). This research is based on measuring the soil gas flux in the AVGA and comparing the diffuse volcanic soil gas emissions with the emissions from geothermal fields in operation. The natural flux of soil gas is high, independently from the occurrence of GPPs in the area, and the budget for natural diffuse gas flux is high with respect to power plant gas emissions. Furthermore, the CO2 emitted from power plants seems to reduce the amount of natural emissions because of the gas flow operated by power plants. During the GPPs’ life cycle, C... [more]

The modular multilevel converter−bidirectional DC−DC converter (MMC−BDC) has been proposed to be utilized in the vessel integrated power system to interconnect the medium voltage bus and the distributed energy storage elements. In the shipboard applications, MMC−BDC faces unbalanced sub-module power operation because of the inconsistent state-of-charge (SOC) of the energy storage elements. Researchers have investigated into the unbalanced operation principle of MMC−BDC and proposed some unbalanced operation control strategies, but these traditional strategies do not perform well in both aspects of operating range and efficiency. Therefore, this paper proposes a novel Lyapunov-function-based feedback linearization control strategy for the independent sub-module voltage control of MMC−BDC, which not only shows wide unbalanced operation range and high efficiency, but also realizes the decoupling and symmetrical control of the sub-module capacitor voltages.

The use of artificial intelligence (AI) is increasing in various sectors of photovoltaic (PV) systems, due to the increasing computational power, tools and data generation. The currently employed methods for various functions of the solar PV industry related to design, forecasting, control, and maintenance have been found to deliver relatively inaccurate results. Further, the use of AI to perform these tasks achieved a higher degree of accuracy and precision and is now a highly interesting topic. In this context, this paper aims to investigate how AI techniques impact the PV value chain. The investigation consists of mapping the currently available AI technologies, identifying possible future uses of AI, and also quantifying their advantages and disadvantages in regard to the conventional mechanisms.

The influence of film-hole position on internal and external heat transfer was investigated using Computational Fluid Dynamics (CFD). A simplified geometry of an integrated configuration of a ribbed channel, film hole and mainstream passage is modeled to represent a turbine internal and external cooling scheme. The proposed configurations with nine different positions of film holes are parameterized to conduct a series of CFD calculations at a target blowing ratio of 0.8, 1.1 and 1.7. Since the present study is taking a comparative approach, CFX with SST models is applied as a primary tool and the results are compared with Fluent solver for selected cases (total 36 cases). Among the proposed nine positions, the film holes located in the separated flow region of a ribbed channel showed considerable enhancement in film effectiveness with minimum reduction and potential improvement in internal heat transfer. The finding offers a design opportunity to enhance internal as well as external h... [more]

Passive systems are fundamental for the safe development of Nuclear Power Plant (NPP) technology. The accurate assessment of their reliability is crucial for their use in the nuclear industry. In this paper, we present a review of the approaches and procedures for the reliability assessment of passive systems. We complete the work by discussing the pending open issues, in particular with respect to the need of novel sensitivity analysis methods, the role of empirical modelling and the integration of passive safety systems assessment in the (static/dynamic) Probabilistic Safety Assessment (PSA) framework.

In recent literature, the impact of economic policy uncertainty (EPU) on macro aspects have been investigated, but the aspect of energy, precisely renewable energy still to explore. The motivation of the study is to produce fresh evidence regarding the nexus between EPU and renewable energy consumption (REC) with the mediating role of forcing direct investment (FDI) and financial development (FD) in BRIC nations for the period 1997q1−2018q4. The study applied unit root tests following Ng-Perron and Zivot and Andrews for detecting variable’s stationary properties. The long-run cointegration was evaluated by implementing Bayer, Hanck combined the cointegration test, Bound testing approach, and tBDM test. Both linear and non-linear ARDL were implemented to evaluate long-run and short-run shocks, and directional causality was assessed through a non-granger causality test. Furthermore, the study implemented robustness by implementing fully-modified OLS, dynamic OLS, and canonical cointegrat... [more]

Commercializing direct methanol fuel cells (DMFC) demands cost-effective cation exchange membranes. Herein, a polymeric blend is prepared from low-cost and eco-friendly polymers (i.e., iota carrageenan (IC) and polyvinyl alcohol (PVA)). Zirconium phosphate (ZrPO4) was prepared from the impregnation−calcination method and characterized by energy dispersive X-ray analysis (EDX map), X-ray diffraction analysis (XRD), Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy (TEM), then incorporated as a bonding and doping agent into the polymer blend with different concentrations. The new fabricated membranes were characterized by SEM, FTIR, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and XRD. The results revealed that the membranes’ physicochemical properties (oxidative stability, tensile strength) are enhanced with increasing doping addition, and they realized higher results than Nafion 117 because of increasing numbers of hydrog... [more]

Hybridization of sources is spreading worldwide by utilizing renewable sources and storage units as standard parts of every grid. The conjunction of energy source and storage type open the door to reshaping the sustainability and robustness of the mains while improving system parameters such as efficiency and fuel consumption. The solution fits existing networks as well as new ones. The study proposes the creation of an accurate optimal sizing procedure for setting the required rating of each type of source. The first step is to model the storage and energy sources by using real experimental results for creating the generic database. Then, data on the mission profile, system constraints, and the minimization target function are inserted. The mission profile is then analyzed to determine the minimum and maximum energy source rating. Next, the real time energy management system controller is used to find the set of solutions for each available energy source and the optimal compatible sto... [more]

Crude oil is a major energy source that is exploited globally to achieve economic growth. To meet the growing demands for oil, in an environment of stringent environmental regulations and economic and technical pressure, industries have been required to develop novel oil salvaging techniques. The remaining ~70% of the world’s conventional oil (one-third of the available total petroleum) is trapped in depleted and marginal reservoirs, and could thus be potentially recovered and used. The only means of extracting this oil is via microbial enhanced oil recovery (MEOR). This tertiary oil recovery method employs indigenous microorganisms and their metabolic products to enhance oil mobilization. Although a significant amount of research has been undertaken on MEOR, the absence of convincing evidence has contributed to the petroleum industry’s low interest, as evidenced by the issuance of 400+ patents on MEOR that have not been accepted by this sector. The majority of the world’s MEOR field t... [more]

In this paper, an advanced electrothermal simulation strategy is applied to a 3.3 kV silicon carbide MOSFET power module. The approach is based on a full circuital representation of the module, where use is made of the thermal equivalent of the Ohm’s law. The individual transistors are described with subcircuits, while the dynamic power-temperature feedback is accounted for through an equivalent thermal network enriched with controlled sources enabling nonlinear thermal effects. A synchronous step-up DC-DC converter and a single-phase inverter, both incorporating the aforementioned power module, are simulated. Good accuracy was ensured by considering electromagnetic effects due to parasitics, which were experimentally extracted in a preliminary stage. Low CPU times are needed, and no convergence issues are encountered in spite of the high switching frequencies. The impact of some key parameters is effortlessly quantified. The analysis witnesses the efficiency and versatility of the app... [more]

The purpose of this study was to compare insulation performance between a base case that applied the existing steel pipe frame and an alternative case that reduced thermal bridging by applying a truss-shaped insulation frame (TIF) to a back frame type curtain wall. Insulation performance was compared by obtaining the effective U-factor and the lowest indoor surface temperature through a three-dimensional steady-state heat transfer simulation. In addition, mock-up tests were performed to compare the U-factors of the base case and alternative case. The simulation results showed that the effective U-factor of the alternative case was 36% lower than in the base case, a significant heat loss reduction. The lowest indoor surface temperature of the alternative case was 0.5 °C higher than in the base case, showing that the surface condensation risk also decreased. In the mock-up test results, the alternative case U-factor was 33% lower than in the base case, confirming the associated large hea... [more]

This paper focuses on autonomous navigation for an electric freight vehicle designed to collect freight autonomously using pallet handling robots installed in the vehicle. Apart from autonomous vehicle navigation, the primary hurdle for vehicle autonomy is the autonomous collection of freight irrespective of freight orientation/location. This research focuses on generating parking pose for the vehicle irrespective of the orientation of freight for its autonomous collection. Freight orientation is calculated by capturing the freight through onboard sensors. Afterward, this information creates a parking pose using mathematical equations and knowledge of the vehicle and freight collection limitations. Separate parking spots are generated for separate loading bays of the vehicle depending on the availability of the loading bay. Finally, results are captured and verified for different orientations of freight to conclude the research.

The urban heat island (UHI) effect resulted from urbanization as well as industrialization has become a major environmental problem. UHI effect aggravates global warming and endangers human health. Thus, mitigating the UHI effect has become a primary task to address these challenges. This paper verifies the feasibility of a three-dimensional turbulent porous media model. Using this model, the authors simulate the urban canopy wind-heat environment. The temperature and flow field over a city with a concentric circular structure are presented. The impact of three factors (i.e., anthropogenic heat, ambient crosswind speed, and porosity in the central area) on turbulent flow and heat transfer in the central business district of a simplified city model with a concentric circular structure were analyzed. It is found that the three-dimensional turbulent porous media model is suitable for estimating the UHI effect. The UHI effect could be mitigated by reducing the artificial heat and improving... [more]

Existing Reynolds Averaged Navier−Stokes-based transition models do not accurately predict separation induced transition for low pressure turbines. Therefore, in this paper, a novel framework based on computational fluids dynamics (CFD) driven machine learning coupled with multi-expression and multi-objective optimization is explored to develop models which can improve the transition prediction for the T106A low pressure turbine at an isentropic exit Reynolds number of Re2is=100,000. Model formulations are proposed for the transfer and laminar eddy viscosity terms of the laminar kinetic energy transition model using seven non-dimensional pi groups. The multi-objective optimization approach makes use of cost functions based on the suction-side wall-shear stress and the pressure coefficient. A family of solutions is thus developed, whose performance is assessed using Pareto analysis and in terms of physical characteristics of separated-flow transition. Two models are found which bring th... [more]

The article focuses on research on the functioning of liquid fuel supply chains, supplying troops carrying out peacekeeping and stabilisation operations in a foreign territory. Timely and complete supplies of fuels in war conditions determine the achievement of the assumed goals of a military operation. They often determine the health and life of soldiers. For this reason, the role of building the resilience of supply chains to disruptions, the type and frequency of which is entirely different from the undesirable events occurring in civil goods flows, is increasing. Therefore, the critical concept supporting building the resilience of fuel supply chains is risk management in these chains. The authors have developed a risk analysis method that integrates the Kaplan and Garrick approach and the fuzzy theory. The analysis identifies the existing disturbances and assigns them to the individual phases of the supply process. To illustrate the applicability of the proposed method, the author... [more]

The raw materials sector plays a key role in the Polish economy. The mineral raw material industry encompasses many different, sometimes highly specialized activities, such as exploration, mining, hauling, mineral processing, metallurgy and metal refining, as well as risk assessment, management (environmental, financial, legal) and marketing. The purpose of the article is to identify the market gap for business for entities or individuals in the mineral resources sector in Poland. Taking into account the European Union regulations which enforce the closure of hard coal mines in Poland by 2050, it is reasonable to identify such a gap in the raw materials area, especially since the current situation may turn out to be a new revival of the raw materials market after the pandemic period. Based on the NACE classification, a key area was identified, which is dedicated to potential entrepreneurs in the mineral resources area. Based on an internal analysis, the sectors directly related to the... [more]

Cybersecurity is a critical issue for Real-Time IoT applications since high performance and low latencies are required, along with security requirements to protect the large number of attack surfaces to which IoT devices are exposed. Elliptic Curve Cryptography (ECC) is largely adopted in an IoT context to provide security services such as key-exchange and digital signature. For Real-Time IoT applications, hardware acceleration for ECC-based algorithms can be mandatory to meet low-latency and low-power/energy requirements. In this paper, we propose a fast and configurable hardware accelerator for NIST P-256/-521 elliptic curves, developed in the context of the European Processor Initiative. The proposed architecture supports the most used cryptography schemes based on ECC such as Elliptic Curve Digital Signature Algorithm (ECDSA), Elliptic Curve Integrated Encryption Scheme (ECIES), Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Menezes-Qu-Vanstone (ECMQV). A modified version... [more]

In this study, we examine how Battery Storage (BES) and Thermal Storage (TES) combined with solar Photovoltaic (PV) and Concentrated Solar Power (CSP) technologies with an increased storage duration and rental cost together with diversification would influence the Moroccan mix and to what extent the variability (i.e., adequacy risk) can be reduced; this is done using recent (2013) cost data and under various penetration scenarios. To do this, we use MERRA-2 climate reanalysis to simulate hourly demand and capacity factors (CFs) of wind, solar PV and CSP without and with increasing storage capabilities—as defined by the CSP Solar Multiple (SM) and PV Inverter Loading Ratio (ILR). We adjust these time series to observations for the four Moroccan electrical zones over the year 2018. Our objective is to maximize the renewable (RE) penetration and minimize the imbalances between RE production and consumption considering three optimization strategies. We analyze mixes along Pareto fronts usi... [more]

The operation state detection of numerous smart meters is a significant problem caused by manual on-site testing. This paper addresses the problem of improving the malfunction detection efficiency of smart meters using deep learning and proposes a novel evaluation model of operation state for smart meter. This evaluation model adopts recurrent neural networks (RNN) to predict power consumption. According to the prediction residual between predicted power consumption and the observed power consumption, the malfunctioning smart meter is detected. The training efficiency for the prediction model is improved by using transfer learning (TL). This evaluation uses an accumulator algorithm and threshold setting with flexibility for abnormal detection. In the simulation experiment, the detection principle is demonstrated to improve efficient replacement and extend the average using time of smart meters. The effectiveness of the evaluation model was verified on the actual station dataset. It has... [more]

Agricultural waste, particularly lignocellulose, has been used in the second generation of biogas. Coffee pulp and chicken feathers can be developed as biogas raw materials because of their suitability as a biogas substrate. This study investigates the effect of the percentage of total solids (TS), carbon to nitrogen ratio (C/N, g/g), and delignification pretreatment on biogas production from coffee pulp and chicken feathers, and aims to compose kinetics using the modified Gompertz model. The results show that adjusting the percentage of TS at low-level speeds up the degradation process, which increases chemical oxygen demand (COD) reduction and biogas production. COD reduction and biogas production increase optimally at the 25 (g/g) C/N ratio. Pretreatment delignification aids microorganisms in substrate decomposition, resulting in faster COD reduction and biogas conversion. The 25% TS and 25 (g/g) C/N ratio with the delignification process achieved the best biogas production, with bi... [more]