An Energy Management System (EMS) that uses a Model Predictive Control (MPC) to manage the flow of the microgrids is described in this work. The EMS integrates both wind speed and solar radiation predictors by using a time series to perform the primary grid forecasts. At each sampling data measurement, the power of the photovoltaic system and wind turbine are predicted. Then, the MPC algorithm uses those predictions to obtain the optimal power flows of the microgrid elements and the main network. In this work, three time-series predictors are analyzed. As the results will show, the MPC strategy becomes a powerful energy management tool when it is integrated with the Double Exponential Smoothing (DES) predictor. This new scheme of integrating the DES method with an MPC presents a good management response in real-time and overcomes the results provided by the Optimal Power Flow method, which was previously proposed in the literature. For the case studies, the test microgrid located in th... [more]

This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The resu... [more]

The tire pyrolysis oil is a waste-derived fuel with a lower cetane number and higher den-sity than diesel fuel, but this is a promising waste-based fuel for compression ignition en-gines. In the European Union, it is necessary to increase the bio-share of fuels, and the second-generation waste-derived blend components are essential for achieving the 2030 goals. The injection characteristics of tire pyrolysis oil and diesel oil were investigated on a Bosch solenoid type common rail (CR) injector. Six different premixed ratios were investi-gated, including in a low volume percentage 250 ppm and higher 10%, 20%, and 100% pyrolysis oil and 100% diesel oil. The simulation investigation was done in the AVL Fire software, the experimental investigations were done on a LDX CR injection test bench, and the videos were taken on an Olympus Ispeed 3 camera. The scope of the research was to record the flow pattern of the fuel mixture, flowing out of the high-pressure injector, from which the mixing... [more]

The operational reliability and high efficiency of modern electrical machines depend on the ability to transfer heat in the construction parts of the machine. Therefore, many authors study various thermal models and work on the development of effective heat dissipation. New insights and methods lead to improved techniques for the thermal design of electrical machines. This paper presents an experimentally validated thermal model of a permanent magnet synchronous motor (PMSM) with an improved slot winding model. It also deals with various approaches to homogenization and equivalent material properties of a tooth-coil winding sub-model. First, an algorithm for building a lumped-parameter thermal network (LPTN) of PMSM is described and its properties and problems are discussed. Subsequently, a sub-model of a slot with a winding based on the finite element method (FEM) is introduced. This sub-model is able to generate different conductor distributions based on probabilistic methods for a s... [more]

This paper analyzes the impact of the COVID-19 pandemic on economic growth and electricity consumption and investigates the hypothesis of the influence of this consumption on the gross domestic product (GDP) for Romania. Using time series on monthly electricity consumption and quarterly GDP and a multi-linear regression model, we performed an analysis of the evolution of these indicators for 2007−2020, a comparison between their behavior during the financial crisis vs. COVID-19 crisis, and empirically explore the relationships between GDP and electricity consumption or some of its components. The results of the analysis confirm that the shock of declining activity due to the COVID-19 pandemic had a severe negative impact on electric energy consumption and GDP in the first half of 2020, followed by a slight recovery. By using a linear regression model, long-term relationships between GDP and domestic and non-household electricity consumptions were found. The empirically estimated elasti... [more]

Intensive-stage fracturing in horizontal wells is a potentially new technology for reservoir stimulations of deep shale oil and gas. Due to a strong stress interaction among the dense fractures, the fracture geometry and stress field are very complicated, which are the bottlenecks of this technology. Aiming at simulating the intensive-stage fracturing, a coupled three-dimensional (3D) fracture model of multiple-fracture simultaneous propagation is proposed. The dynamic behavior of the fracture propagation and stress field was analyzed using this model. The perforation parameters were optimized for improving the fracture geometry equilibrium. The results showed that the exterior fractures of the multiple fractures penetrated by the horizontal well become the main fractures, while the interior fractures are drastically restrained. The exterior fracture widths increased with increasing injection time, while the interior fracture widths decreased with increasing injection time. An extruded... [more]

Since solid particles suspended in the fluid can cause wear in centrifugal pumps, intensive attention has been focused on the numerical prediction for the wear of flow parts in centrifugal pumps. However, most numerical studies have focused on only one wear model and a sphere particle model. The impact of particle shape on the wear of flow parts in centrifugal pumps is under-studied, particularly considering abrasive and impact wear simultaneously. In this work, the Computational Fluid Dynamics (CFD)-Discrete Element Method (DEM) coupling method with an abrasive and impact wear prediction model was adopted to study the wear characteristics of a centrifugal pump. Moreover, four regular polyhedron particles and a sphere particle with the same equivalent diameter but different sphericity were mainly analyzed. The results demonstrate that more particles move closer to the blade pressure side in the impeller passage, and particles tend to cluster in specific areas within the volute as spher... [more]

Here, we propose a new deep learning scheme to solve the energy time series prediction problem. The model implementation is based on the use of Long Short-Term Memory networks and Convolutional Neural Networks. These techniques are combined in such a fashion that inter-dependencies among several different time series can be exploited and used for forecasting purposes by filtering and joining their samples. The resulting learning scheme can be summarized as a superposition of network layers, resulting in a stacked deep neural architecture. We proved the accuracy and robustness of the proposed approach by testing it on real-world energy problems.

This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep neural networks to disaggregate appliances from low frequency data, i.e., data with sampling rates lower than the AC base frequency. The overall purpose of this review is, firstly, to gain an overview on the state of the research up to November 2020, and secondly, to identify worthwhile open research topics. Accordingly, we first review the many degrees of freedom of these approaches, what has already been done in the literature, and compile the main characteristics of the reviewed publications in an extensive overview table. The second part of the paper discusses selected aspects of the literature and corresponding research gaps. In particular, we do a performance comparison with respect to reported mean absolute error (MAE) and F1-scores and observe different recurring elements in the best performing approaches, namely data sampling intervals below 10 s, a large field of view, the usage of generative... [more]

Despite coal being one of the major contributors of CO2, it remains a cheap and stable source of electricity. However, several countries have turned to solar energy in their goal to “green” their energy generation. Solar energy has the potential to displace coal with support from natural gas. In this study, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. To ensure the results’ robustness, the study presents a straightforward weather-driven scenario analysis that utilizes historical weather and electricity demand to generate representative scenarios. This approach was tested in Japan’s southernmost region, since it represents a regional grid with high PV penetration and a fleet of coal plants older than 40 years. The results revealed that solar power could decommission 3.5 GW of the 7 GW coal capacity in Kyushu. It was discovered that beyond 12 GW, solar power... [more]

The brushless doubly fed reluctance machine (BDFRM) is receiving an increased amount of attention from the research community thanks to its potential as an alternative drive for variable speed applications, both as motor and generator. Currently, the sizing of the BDFRM in the literature is based on the model of an ideal axially laminated rotor (ALR) and discrepancies are hidden in compensation factors which are in turn tuned with a finite element analysis (FEA). This paper proposes an analytical framework to accurately model the air gap field modulation, and by extension the torque density, of the BDFRM with ducted segmental rotor (DSR) and salient pole rotor (SPR). The results are verified with FEA and validated on a BDFRM prototype.

Piezoelectric energy harvesters have attracted much attention because they are crucial in portable industrial applications. Here, we report on a high-power device based on a magneto-mechanical piezoelectric energy harvester to scavenge the AC magnetic field from a power-line cable for industrial applications. The electrical output performance of the harvester (×4 layers) reached an output voltage of 60.8 Vmax, an output power of 215 mWmax (98 mWrms), and a power density of 94.5 mWmax/cm3 (43.5 mWrms/cm3) at an impedance matching of 5 kΩ under a magnetic field of 80 μT. The multilayer energy harvester enables high-output performance, presenting an obvious advantage given this improved level of output power. Finite element simulations were also performed to support the experimental observations. The generator was successfully used to power a wireless sensor network (WSN) for use on an IoT device composed of a temperature sensor in a thermal power station. The result shows that the magnet... [more]

Rational decision-making requires assessing the advantages and disadvantages of options, including nonmarket effects (such as environmental effects). This also applies to strategic decision-making in the industrial sector to select alternative renewable energy source (RES). Often, a variety of criteria can be used to select a renewable energy source, whereas no ideal family of criteria for renewable energy selection for industry has been defined in the literature. It was concluded that there is a need to support the actions of industrial development based on RES, which will contribute significantly to overcoming the limitations of the negative effect on the environment in terms of greenhouse gas emissions. There is a clear need for a systematic and polyvalent multicriteria approach to planning in industry. Therefore, a method for choosing the preferred renewable source of electricity for industry has been developed, which considers key criteria of RES choice: Expert opinions, the costs... [more]

The transition towards the massive penetration of Renewable Energy Resources (RESs) into the electricity system requires the implementation of the Smart Grid (SG) paradigm with innovative control systems and equipment. In this new context, Distributed Energy Resources (DERs), including renewable sources and responsive loads, should be redesigned to enable aggregators to provide ancillary services. In fact, by using the Internet of Things (IoT) systems, aggregators can explore energy usage patterns from residential users, also known as prosumers and predict their services. This is undoubtedly important especially for SGs facing the presence of several RESs, where understanding the optimal match between demand and production is desirable from several points of view. However, revealing energy patterns and information can be of concern for privacy if the entire system is not properly designed. In this article, by assuming that the security of low-level communication protocols is guaranteed... [more]

A method for assessing the operation of analog filters installed in the measuring paths of current and voltage converters in the power supply system of a mining machine motor, using the example of the driving unit of a roadheader’s cutterhead, is presented. The suggested method is based on the identification of the fundamental harmonic of signals from the current and voltage sensors observed at the input and output of the tested filters, respectively. The identified parameters of the fundamental harmonic of signals before and after the filter allow the determination of points of the filter frequency’s characteristics and their comparison with the reference values. In the suggested method of assessing the operation of analog filters, the new approach consists of checking the frequency characteristics on the basis of identification of the basic harmonics of the signal at the input and output of the tested filter (installed in the measuring line of the electrical quantity) using data acqu... [more]

Electrification offers an opportunity to decarbonize the transport sector, but it might also increase the need for flexibility options in the energy system, as the uncoordinated charging process of battery electric vehicles (BEV) can lead to a demand with high simultaneity. However, coordinating BEV charging by means of smart charging control can also offer substantial flexibility potential. This potential is limited by restrictions resulting from individual mobility behavior and preferences. It cannot be assumed that storage capacity will be available at times when the impact of additional flexibility potential is highest from a systemic point of view. Hence, it is important to determine the flexibility available per vehicle in high temporal (and spatial) resolution. Therefore, in this paper a Markov-Chain Monte Carlo simulation is carried out based on a vast empirical data set to quantify mobility profiles as accurately as possible and to subsequently derive charging load profiles. A... [more]

The energy consumption problem has become a bottleneck hindering further development of data centers. However, the heterogeneity of servers, hybrid cooling modes, and extra energy caused by system state transitions increases the complexity of the energy optimization problem. To deal with such challenges, in this paper, an Energy Aware Task Scheduling strategy (EATS) utilizing marginal cost and task classification method is proposed that cooperatively improves the energy efficiency of servers and cooling systems. An energy consumption model for servers, cooling systems, and state transition is developed, and the energy optimization problem in data centers is formulated. The concept of marginal cost is introduced to guide the task scheduling process. The task classification method is incorporated with the idea of marginal cost to further improve resource utilization and reduce the total energy consumption of data centers. Experiments are conducted using real-world traces, and energy redu... [more]

For calculation of biological efficiency of a biogas plant (BP), it is required to determine the specific methane potential (SMP) of the substrate. A study comparing available methods for determination of SMP and the comparison with data of full-scale BPs is missing but necessary according to the differences in process conditions between both. Firstly, mass and mass associated energy balances of 33 full-scale BPs were calculated and evaluated. The results show plausible data for only 55% of the investigated BPs. Furthermore, conversion and yield efficiencies were calculated according to six different methods for SMP determination. The results show a correlation between the measured on-site specific methane yield and the calculated SMP by methods based on biological degradability. However, these methods underestimate the SMP. Calculated SMPs based on calorific values are higher, but less sensitive. A combination of biochemical and energetical methods is a promising approach to evaluate... [more]

Milling is one of the most energy consuming stages of the value production chain in many industries. To minimize the specific energy required, new and more efficient devices and circuits are designed and dedicated optimizing control strategies are applied. This research presents the results of innovative electromagnetic mill energy consumption reduction with dedicated supervisory on-line optimizing control algorithm. The paper describes an algorithm that uses the active power measurement and searches for the minimum on the active constraints of the optimization problem. The constraints follow from the product quality, mill supply voltage and magnetic induction requirements. Algorithm performance was tested in simulations, but the main validation was performed on a semi-industrial dry grinding and classification circuit equipped with an electromagnetic mill. The results of the experiments presented in this paper show that the application of the on-line optimization algorithm allows for... [more]

A beam containing a piezoelectric layer or layers is used for piezoelectric harvesting from various processes. The structure of the beam is made by gluing the piezoelectric material on one side (unimorph) or both sides (bimorph) of a carrying substrate. Two piezoelectric layers, glued on both sides of the substrate, may be electrically parallel or series connected. This paper presents an experimental analysis of the impact of parallel and series connections of two Macro Fiber Composite (MFC) MFC patches in a bimorph on the charging of a capacitor. In experiments, the effective charging process of the capacitor was obtained both for parallel and series connection of two MFC patches. The bimorph with a parallel connection generated a larger capacitor charging power than the bimorph with a series connection in the range of voltage across the capacitor from 1 to 18 V. However, the bimorph with a series connection was more effective than a parallel connection for voltage across the charged... [more]

Tire normal forces are difficult to measure, but information on the vehicle normal force can be used in many automotive engineering applications, e.g., rollover detection and vehicle and wheel stability. Previous papers use algebraic equations to estimate the tire normal force. In this article, the estimation of tire normal force is formulated as an input estimation problem. Two observers are proposed to solve this problem by using a quarter-car suspension model. First, the Youla Controller Output Observer framework is presented. It converts the estimation problem into a control problem and produces a Youla parameterized controller as observer. Second, a Kalman filter approach is taken and the input estimation problem is addressed with an Unbiased Minimum Variance Filter. Both methods use accelerometer and suspension deflection sensors to determine the vehicle normal force. The design of the observers is validated in simulation and a sensitivity analysis is performed to evaluate their... [more]

New semiconductor technology is enabling the design of more reliable and high-performance power converters. In particular, wide bandgap (WBG) silicon carbide (SiC) and gallium nitride (GaN) technologies provide faster switching times, higher operating temperature, and higher blocking voltage. Recently, high-voltage GaN devices have opened the design window to new applications with high performance and cost-effective implementation. However, one of the main drawbacks is that these devices require accurate base current control to ensure safe and efficient operation. As a consequence, the base drive circuit becomes more complex and the final efficiency is decreased. This paper presents an improved gate driver circuit for GaN devices based on the use of a constant current regulator (CCR). The proposed circuit achieves constant current regardless of the operating conditions, solving variations with temperature, aging and operating conditions that may degrade the converter performance. Besid... [more]

This paper proposes a new compact electrothermal model of the Insulated Gate Bipolar Transistors (IGBT) dedicated for SPICE (Simulation Program with Integrated Circuit Emphasis). This model makes it possible to compute the non-isothermal DC characteristics of the considered transistor and the waveforms of terminal voltages and currents of the investigated device and its internal temperature at transients. This model takes into account the nonlinearity of thermal phenomena in this device. The form of the formulated model is described and the problem of estimating its parameter values is discussed. The correctness of the proposed model was verified experimentally both at DC operation and at transients. The obtained results are compared to the results of computations performed with the use of the classical literature model. A very good agreement between the results of measurements and computations performed with the new model is obtained at different cooling conditions and in a wide range... [more]

Automatic generation control (AGC) is primarily responsible for ensuring the smooth and efficient operation of an electric power system. The main goal of AGC is to keep the operating frequency under prescribed limits and maintain the interchange power at the intended level. Therefore, an AGC system must be supplemented with modern and intelligent control techniques to provide adequate power supply. This paper provides a comprehensive overview of various AGC models in diverse configurations of the power system. Initially, the history of power system AGC models is explored and the basic operation of AGC in a multi-area interconnected power system is presented. An in-depth analysis of various control methods used to mitigate the AGC issues is provided. Application of fast-acting energy storage devices, high voltage direct current (HVDC) interconnections, and flexible AC transmission systems (FACTS) devices in the AGC systems are investigated. Furthermore, AGC systems employed in different... [more]

Electro-hydraulic compact drives (ECDs) are an emerging technology for linear actuation in a wide range of applications. Especially within the low power range of 5−10 kW, the plug-and-play capability, good energy efficiency and small space requirements of ECDs render this technology a promising alternative to replace conventional valve-controlled linear drive solutions. In this power range, ECDs generally rely on passive cooling to keep oil and system temperatures within the tolerated range. When expanding the application range to larger power classes, passive cooling may not be sufficient. Research investigating the thermal behaviour of ECDs is limited but indeed required for a successful expansion of the application range. In order to obtain valuable insights into the thermal behaviour of ECDs, thermo-hydraulic simulation is an important tool. This may enable system design engineers to simulate thermal behaviour and thus develop proper thermal designs during the early design phase, e... [more]