Power converter technology has expanded into a wide range of low, medium, and high power applications due to the ability to manage electrical energy efficiently. In this regard, the modular multilevel converter has become a viable alternative to ensure an optimal harmonic profile with a sinusoidal voltage at the load side. Model predictive control (MPC) is a state-of-the-art technique that has been successfully used to control power electronic converters due to its ability to handle multiple control objectives. Nevertheless, in the classical MPC approach, the optimal vector is applied during the whole sampling period producing an output voltage. This solution causes an unbalanced switching frequency of the power semiconductor, which then causes unbalanced stress on the power devices. Modulation strategies have been combined with MPC to overcome these shortcomings. This paper introduces the experimental assessment of a 7-level converter combining a simple phase shift multicarrier pulse-... [more]

Best Estimate Plus Uncertainty (BEPU) approaches for nuclear reactor applications have been extensively developed in recent years. The challenge for BEPU approaches is to achieve multi-physics modeling with an acceptable computational cost while preserving a reasonable fidelity of the physics modeled. In this work, we present the core multi-physics computational framework developed for the efficient computation of uncertainties in Light Water Reactor (LWR) simulations. The subchannel thermal-hydraulic code CTF and the nodal expansion neutronic code PARCS are coupled for the multi-physics modeling (CTF-PARCS). The computational framework is discussed in detail from the Polaris lattice calculations up to the CTF-PARCS coupling approaches. Sampler is used to perturb the multi-group microscopic cross-sections, fission yields and manufacturing parameters, while Dakota is used to sample the CTF input parameters and the boundary conditions. Python scripts were developed to automatize and modu... [more]

Based on the square heat-generation body (HGB) with “arrow-shaped” high-thermal-conductivity channel (HTCC) model established in the previous literature, we performed multi-objective optimization (MOO) with maximum temperature difference (MTD) minimization and entropy-generation rate (EGR) minimization as optimization objectives for its performance. Pareto frontiers with optimal set were obtained based on NSGA-II. TOPSIS, LINMAP, and Shannon entropy decision methods were used to select the optimal results in Pareto frontiers, and the deviation index was used to compare and analyze advantages and disadvantages of the optimal results for each decision method. At the same time, multi-objective constructal designs of the “arrow-shaped” HTCC were carried out through optimization of single degree of freedom (DOF), two DOF, and three DOF, respectively, and the thermal performance of the square heat-generation body under optimizations of different DOF were compared. The results show that const... [more]

As a crucial factor in the improvement of energy efficiency for power-using electromechanical products, the flow, conversion and distribution of energy are closely related to design variables of products. Simultaneously, performance is the constraint of energy efficiency and is strongly affected by design variables. In order to improve a product’s energy efficiency without compromising performance, an energy flow model with a basic energy flow element (EFE) was built on a functional basis and its modelling procedure is presented in this paper. Containing function, design variable and characteristic energy in EFEs, as well as the interface parameters between EFEs and environment, the model contributes to logically clarifying the relationship between design variables and performance. With the refrigerator as an example, the effectiveness of the energy flow model is verified by a comparison between simulation, based on an energy flow model, and experimentation. Furthermore, five critical... [more]

This paper deals with the proposition of improvement in the performance of a heat source by modification of its structure and by deriving a dedicated control system. Traditional heat sources consist of a single heater of high nominal power, but slow dynamics, that is regulated by a single closed loop control system. In this paper, an existing heater serially-connected with a supplemental heater with low nominal power but fast dynamics is proposed. A dedicated control system was derived with two active disturbance rejection controllers (ADRC) implemented in the habituating control structure. The proposed solution was validated using a virtual commissioning procedure where the heating system was simulated in the SIEMENS® Simit v10.3 industrial software, and ADRC controllers were implemented in SIEMENS® PLCSIM Advanced using dedicated library function blocks. The results showed the superiority of the proposed approach in comparison with the traditional single closed loop solution. The pro... [more]

Biogas production is a process with great potential. It uses the biodegradable raw materials of animal, vegetable and municipal waste. The amount of municipal as well as agricultural waste is increasing every year. This waste is an unmanaged and nuisance waste, and using it in biogas plants reduces the amount of waste. Biogas production is part of the EU’s policy to reduce dependence on fossil fuels and use energy from renewable sources (diversification of energy sources). Its importance is certain to increase in the future as energy demand increases. This article deals with the economical use of biodegradable waste for biogas production in Poland and Germany. Both countries have a similar agricultural and municipal waste structure. An agricultural biogas plant is one way of obtaining energy based on renewable energy sources (RES). Energy production from agricultural biogas will allow Poland to meet the 32% obligation imposed by the EU and Germany to continue to be the market leader in... [more]

The brushless doubly fed induction machine (BDFIM) is being considered as a possible solution for low-speed wind energy generator applications. It has been proposed as an alternative to the doubly fed induction machine (DFIM) due to its robust rotor structure as well as low operational maintenance requirements. However, due to its complicated control philosophy, higher overall machine size due to the extra set of control windings in the stator, and slightly lower efficiency, it is yet to be adopted in commercial applications. In this paper, a simplified vector control scheme for the control winding of a cage+nested-loop (cage+NL) rotor BDFIM is proposed. Experimental results are compared with simulations to validate the effectiveness of the proposed control scheme.

Coal resources perform an important role in China’s energy structure. Hydraulic support is the main supporting equipment of fully mechanized mining face in coal mines. Because the hydraulic support frequently bears the impact pressure from the working face, it is very easy to cause failure of the balance jack. In order to solve the problem that the balance jack easily damaged by impact and improve the impact resistance of the hydraulic support, an improved fast response balance jack with multiple adaptive buffers was proposed in this paper. The energy dissipation characteristics of the balance jack were analyzed by establishing the mathematical model of the multiple buffering process of it. Based on ADAMS, the dynamic simulation model of the hydraulic support was constructed, and the mechanical response characteristics of the proposed balance jack and the traditional balance jack under different impact loads were compared and analyzed. By changing the equivalent stiffness of the novel... [more]

In Wireless Sensor Networks (WSNs), routing algorithms can provide energy efficiency. However, due to unbalanced energy consumption for all nodes, the network lifetime is still prone to degradation. Hence, energy efficient routing was developed in this article by selecting cluster heads (CH) with the help of adaptive whale optimization (AWOA) which was used to reduce time-consumption delays. The multi-objective function was developed for CH selection. The clusters were then created using the distance function. After establishing groupings, the supercluster head (SCH) was selected using the benefit of a fuzzy inference system (FIS) which was used to collect data for all CHs and send them to the base station (BS). Finally, for the data-transfer procedure, hop count routing was used. An Oppositional-based Whale optimization algorithm (OWOA) was developed for multi-constrained QoS routing with the help of AWOA. The performance of the proposed OWOA methodology was analyzed according to the... [more]

Lignocellulosic biomass is an abundant resource that can be valorized for the production of bioenergy. However, studies aiming to quantify the amount of biogas production potential per km forest road are scarce in the literature. In this study, fresh pine needles, pine needle litter, pine branches, and pine bark were digested in batch reactors under mesophilic conditions after a grinding/milling pre-treatment. All samples were collected from a low-altitude Mediterranean Pinus forest (North Greece) adjacent to a category G forest road with a gentle slope. The methane yield of fresh pine needles was between 115 and 164 NmL g−1 volatile solids (VS), depending on the Pinus tree size. Pine needle litter produced a significantly lower methane yield (between 58 and 77 NmL g−1 VS), followed by pine bark (85 NmL g−1 VS) and pine branches (138 NmL g−1 VS). Considering the quantity of pine needle litter accumulated on adjacent forest roads (600 ± 200 g m−2), it was possible to calculate the biome... [more]

The energy generated by a solar photovoltaic (PV) system depends on uncontrollable factors, including weather conditions and solar irradiation, which leads to uncertainty in the power output. Forecast PV power generation is vital to improve grid stability and balance the energy supply and demand. This study aims to predict hourly day-ahead PV power generation by applying Temporal Fusion Transformer (TFT), a new attention-based architecture that incorporates an interpretable explanation of temporal dynamics and high-performance forecasting over multiple horizons. The proposed forecasting model has been trained and tested using data from six different facilities located in Germany and Australia. The results have been compared with other algorithms like Auto Regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Multi-Layer Perceptron (MLP), and Extreme Gradient Boosting (XGBoost), using statistical error indicators. The use of TFT has been shown to be more accurate... [more]

Accurate photovoltaic (PV) power forecasting is indispensable to enhancing the stability of the power grid and expanding the absorptive photoelectric capacity of the power grid. As an excellent nonlinear regression model, the relevance vector machine (RVM) can be employed to forecast PV power. However, the optimization of the free parameters is still a key problem for improving the performance of the RVM. Taking advantage of the strong global search capability, good stability, and fast convergence rate of the sparrow search algorithm (SSA), this paper optimizes the parameters of the RVM by using the SSA to develop an excellent RVM (called SSA-RVM). Consequently, a novel hybrid PV power forecasting model via the SSA-RVM is proposed to perform ultra-short-term (4 h ahead) prediction. In addition, the effects of seasonal distribution and weather type on PV power are fully considered, and different seasonal prediction models are established separately to improve the prediction capability.... [more]

The automobile sector is a promising avenue for enhancing energy security, economic opportunity, and air quality in India. Before penetrating a large number of electric vehicles (EV) into the power grid, a thorough investigation and assessment of significant parameters are required, as additional nonlinear and EV loads are linked to the decentralized market. Many automobile companies have already invested in electric vehicle research; hence, a detailed analysis on range anxiety and grid connectivity concerns are the important factors affecting the future of the electric vehicle industry. In this paper, the initial review is about the decentralized market in India and sustainable aspects of electric mobility based on the Indian context, as it is a developing nation with an enormous resource and scope for EV markets. With recent literature from the last three years, the substantial constraints observed in benefits and challenges are reviewed. The financial stability aspects and the incen... [more]

Power converters for wireless power transfer (WPT) and, in general, for electrical vehicle charging are evolving in terms of nominal power and performance, bringing along non negligible emissions in the supraharmonic range (2 kHz to 150 kHz). The large installed power and the high concentration with a relatively short separation distance can be addressed by feeding the converters through a DC grid for better dynamic response and lower impedance. The prediction of conducted emissions in real supply conditions requires carrying out measurements with low impedance values, lower than those available in line impedance stabilization networks (LISNs) for AC grids. This work proposes an approach to extrapolate converter emissions in an ideal 0 Ω condition, that together with the input impedance curve (determined by a least mean square approach) form a Norton equivalent circuit of the converter. The interaction of the converters with the DC grid and superposition of emissions can be then thorou... [more]

Low-carbon development is a prerequisite and a fundamental element of sustainable development [...]

The proportion of renewable power generation in the world has been increasing in recent years. However, the fluctuations and uncertainties of renewable power generation bring a considerable challenge to future unit scheduling. Therefore, the generation flexibility in power systems becomes more critical as a large amount of renewable generation is integrated into power systems. The use of flexible generators with energy storage systems is one of the most efficient methods of improving power system flexibility. The primary purpose of this study is to explore the effect of generation flexibility on the cost of unit scheduling. A flexibility index is used to evaluate the generation flexibility in the Taiwan power system, and a multi-scenario analysis for renewable power integration is considered. This study also considers various system constraints, such as the unit commitment of actual hydro and thermal units, the scheduling of flexible internal combustion engines (ICEs) and energy storag... [more]

The liquid metal infiltration of carbon preformed with copper and its alloys is already an established and well-known process. It is extensively used by the electronic industry to produce heat sinks of power electronics and electric contacts and sliding electric contacts. The advantage of the process is its ability to produce near net shape components with high volume fractions of carbon at a relatively low price. The process is carried out in a vacuum and with low applied pressure. However, a strong dependence on the temperature of infiltration and its precise control is significant for the sound final product. For certain pair carbon matrix−copper alloys, different results could be obtained according to the infiltration temperature. If the temperature is too low, the solidification may occur prior to complete infiltration (high final porosity). When the temperature is too high, undesirable reactions may occur at the fiber−matrix interface (e.g., corrosive carbides). Therefore, there... [more]

The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new technologies and digitalization in a technocratic way. Therefore, the new industrial paradigm Industry 5.0 appeared very soon and automatically triggered a debate about the role of, and reasons for applying, the new paradigm. Industry 5.0 is complementing the existing Industry 4.0 paradigm with the orientation to the worker who has an important role in the production process, and that role has been emphasized during the COVID-19 pandemic. In this research, there is a brief discussion on main drivers and enablers for introduction of these new paradigms, then a literature-based analysis is carried out to highlight the differences between two paradigms from three important aspects—people, or... [more]

In recent decades, research on alternative fuel engines is becoming more and more popular. Compressed natural gas (CNG) has the advantages of abundant reserves and a lower cost. It can reduce vehicle emissions relatively quickly and has little impact on the entire transportation infrastructure. As the fourth generation of a gas fuel supply method, gas fuel direct injection (DI) technology can effectively avoid volumetric efficiency reduction and power reduction problems of the port fuel injection (PFI) method. However, the former’s mixing path and duration are shortened greatly, which often leads to poor mixing uniformity. In order to improve the in-cylinder mixing uniformity, the in-cylinder mixing process of the CNG-fueled engine is taken as the research object in this study. The computational fluid dynamics (CFDs) models of the mixing process for the PFI and DI modes are established, and their mixing uniformities are compared. Besides, based on the authors’ previous research, the in... [more]

Wind turbines, as any technical system, are expected to have an efficiency that declines in time [...]

In this paper, we propose a geometry-based channel model for multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communications in practical tunnel scenarios. In the proposed channel model, the waves transmitted from the transmitter experience line-of-sight (LoS) and non-LoS (NLoS) before arriving at the receiver. The time-varying parameters of the propagation paths and angles are derived to characterize the channel non-stationarity. Furthermore, we derive the correlation property functions of the proposed V2V channel model; they are space cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), frequency CCFs, as well as the Doppler power spectrum distributions (PSDs). Numerous simulation results of the propagation characteristic for different physical properties of the tunnel, as well as the different motion properties of the transmitter and receiver, are studied and discussed; they demonstrate that the proposed channel model is suitable for describi... [more]

This paper proposes a dynamic factor model to accurately characterize the dynamic dependence and risk spillovers between the crude oil and exchange rate returns of oil-trading countries from 2000−2020, conditional on the common factors. To this end, we first identify the common factors related to returns of crude oil prices and exchange rates from 14 typical oil-trading countries. Then, we use the AR-GARCH model to filter the respective idiosyncratic factors and conduct a comparative study of conditional dynamic dependence between the crude oil and exchange rate returns of oil importers and exporters. Finally, we combine the dynamic factor copula model with the CoVaR method to measure the conditional risk spillover effect between crude oil and exchange rate markets. The empirical study indicates that the classical factor analysis can be used to precisely identify the common factors related to both financial markets, with the similar trend of macro-economic indicators. Furthermore, the... [more]

To achieve net-zero iron and steel production by 2050, many iron and steel producers are turning to direct reduced iron (DRI)—electric arc furnace (EAF) steel production as an opportunity to achieve significant CO2 emissions reductions relative to current levels. However, additional innovations are required to close the gap between DRI and net-zero steel. Pressurized chemical looping-DRI (PCL-DRI) is a novel technology explored to meet this target, in which the reformer firebox and fired process gas heaters are replaced with PCL combustion units. Captured CO2 is conditioned and compressed for pipeline transportation and storage/utilization. The performance of two different PCL-DRI configurations relative to traditional DRI processes was explored via process simulation: a Midrex-type process and an Energiron-type process. The PCL-DRI processes were shown to have equivalent or lesser total fuel consumption (8% reduction) compared to the base cases, and greater process water production (1... [more]

This paper presents a detailed analysis of the safety of human bodies in the electromagnetic field generated by inductive power transfer (IPT) systems designed for kitchen appliances. Comparisons of basic and reference limit values of various safety standards are investigated through theoretical circuit analysis and extensive simulation studies. Simulation models of human bodies along with an IPT system for kitchen appliances are established to reveal the effect of the electromagnetic field on the human body. Corresponding experiments are conducted via constructing a configuration of the designed IPT system and simulating the standing position. Both experimental and analytical results indicate that it is easier to fulfill international safety standards by increasing the operating frequency of the IPT system for kitchen appliances, and hence, the safety of human bodies can be effectively improved.

Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to br... [more]