It is vital that the synchronous generator rotor angle be kept stable to avoid disastrous consequences such as the loss of synchronism amongst generators within a power system network. Once it is unstable, the time that is taken to remedy this is advised to be 5−10 s for smaller power systems and 15−20 s for larger ones. The instability that is caused by poorly damped Low-Frequency Electromechanical Oscillations (LFEOs) may result in inter-area oscillations, where a group of generators in one area oscillates against those in another area, thus affecting the stability of the entire network. This paper explores two control architectures, namely, a nonlinear Lyapunov-based trajectory tracking controller and a Model Reference Adaptive Controller (MRAC) as options to enhance the stability of the rotor angle. The performance of each of these controllers was assessed under steady-state conditions, and then, the synchronous generator was subjected to Gaussian noise and an impulse. While the fi... [more]

One of the most crucial control aspects in electric power networks is ensuring constant voltage levels throughout different circumstances. To overcome this problem, an automatic voltage regulator (AVR) is installed in the electrical power networks to preserve the voltage at its allowable range. In this paper, a fuzzy-based PID controller was used to enhance the AVR dynamic performance under several operating conditions. Moreover, an Equilibrium Optimizer (EO) algorithm was used to initialize the controller gains. The validation of the proposed controller was proven through three different systems. The first was a simple AVR system under fixed and dynamic references. The proposed fuzzy EO PID controller proved its superiority in this case through the reduction of voltage overshoot by around 3−28% compared with the reported methods in the literature. Then, the fault-ride through capability of the proposed controller was proven through the second system, which was the Kundur two-area syst... [more]

In this paper, an enhanced version of whale optimization algorithm (EWOA) is presented to be applied in adaptive control techniques as a parameter tuner. One weakness point in this control scheme is the low efficiency of its objective function. Balloon effect (BE) is a modification introduced to increase the efficiency of the objective function of the optimization method and the ability of the controller to deal with system problems increase consequently. Controlling of the temperature of electric furnaces is considered as one of the important issues in several industrial applications. Conventional controllers such as PID controller cannot deal efficiently with the problem of parameters variations and step disturbance. This paper proposes an adaptive controller, in which the gain of the temperature controller is tuned online using EWOA supported by balloon effect. System responses obtained by the proposed adaptive control scheme using EWOA + BE have been compared with an electric furna... [more]

The presented article concerns issues related to the diagnostics of the technical condition of the insulation of electrical machines. It discusses the importance of the operational supervision, maintenance and diagnostics of electrical machine insulation systems. The structure of the insulation system is presented and known solutions for making winding insulation are described. The negative impact of conditions and various exposures on the technical condition of the insulation system is described. Special attention is focused on the review of available diagnostic methods for insulating systems of electrical machines. These methods have been arranged in a systematic order according to the type of tests to be carried out.

Due to the flexibility, sustainability, affordability, and ease of installation of solar photovoltaic systems, their use has significantly increased over the past two decades. The performance of a solar PV system can be constrained by a variety of external conditions, including hotspots, partial shade, and other minor faults. This causes the PV system to permanently fail and power losses. The power output in a partially shaded solar system is improved in this work by the introduction of a fault classifier based on thermal image analysis with a reconfiguration algorithm. For that purpose, the entire PV array is divided into two parts, with one of these being the male part and the other being the female part. MOSFET switches are used to build the switching matrix circuit that connects these parts. The Flir T420bx thermal camera captures thermal pictures, and MATLAB/Simulink® is used to extract the image properties. The pairing reconfiguration pattern is found using an algorithm based on... [more]

The trend towards the decentralization and decarbonization of the energy sector stimulates the adoption of generation facilities based on renewable energy sources (RES) and distributed generation (DG) facilities that utilize secondary energy resources. Operation features of DG facilities, such as a high speed of electromechanical transient processes and significant deviations of power quality indicators from standard values, require improvement and an increase in the speed of automation devices. Modern electroautomatic devices must determine the operating regions (normal and emergency) and adapt the operation algorithms to the conditions of the current mode. The study presented proposes methods developed to use the Wald Sequential Probability Ratio Test (WSPRT) to improve the reliability and efficiency of the power system automation devices. The paper provides examples of using WSPRT in the devices of automatic frequency load shedding, automatic transformer disconnection, and power qua... [more]

Centralized control algorithm limits the hardware flexibility of a modular multilevel converter (MMC). Therefore, distributed control structure has recently started to be seen in the industry application. Even though distributed controller reduces a single point of failure risk compared to the centralized controller, the failure risk of the entire control systems increases due to the number of local controllers. However, the distributed controller can be programmed in such a way as to replace the faulty local controller and sustain the MMC operation. In this paper, the distributed modular fault-tolerant controller is implemented in a laboratory-scale MMC prototype. The controller is built to control four SMs per phase for the proof-of-concept. Therefore, the MMC prototype is also built by two SMs per arm. The controller capability is validated with experimental and the Opal-RT result-time simulator results in a control-hardware-in-loop (CHIL) environment.

To address the difficulty of early fault diagnosis of rolling bearings, this paper proposes a rolling bearing diagnosis method by combining the attention entropy and adaptive deep kernel extreme learning machine (ADKELM). Firstly, the wavelet threshold denoising method is employed to eliminate the noise in the vibration signal. Then, the empirical wavelet transform (EWT) is utilized to decompose the denoised signal, and extract the attention entropy of the intrinsic mode function (IMF) as the feature vector. Next, the hyperparameters of the deep kernel extreme learning machine (DKELM) are optimized using the marine predators algorithm (MPA), so as to achieve the adaptive changes in the DKELM parameters. By analyzing the fault diagnosis performances of the ADKELM model with different kernel functions and hidden layers, the optimal ADKELM model is determined. Compared with conventional machine learning models such as extreme learning machine (ELM), back propagation neural network (BPNN)... [more]

With the massive integration of renewable energy into the grid, grid inertia and its stability continue to decrease. To improve inertia and facilitate grid restoration, a control strategy for radial basis function virtual synchronous generators based on model predictive control (MPC-VSG-RBF) is proposed in this paper. In this method, virtual synchronous generator (VSG) control strategy is introduced into the model predictive control (MPC), so that the reference value of the inner loop current can vary with the grid voltage and frequency. Using the radial basis function (RBF) neural network to adjust the VSG virtual inertia online can solve the large fluctuation of frequency and power caused by excessive load fluctuation. The simulation model was built based on MATLAB and compared and analyzed with the MPC control method. The simulation results show that: when the output power of the inverter changes, the model predictive control of the adaptive virtual synchronous generator can increas... [more]

A hub motor is an effective drive system for Battery Electric Vehicles (BEVs). However, due to limitations on packaging and cost, there are few applications in which hub motors are taken as the only actuators for a brake vehicle. Most applications involve a Regenerative Braking System (RBS) combined with a Hydraulic Braking System (HBS). In this paper, a top hierarchy Advanced Emergency Braking System (AEBS) controller is designed in Matlab/Simulink and State-flow, including functionalities of basic emergency braking, brake force distribution between front and rear wheels, anti-lock braking and coordination between RBS and HBS based on Model Predictive Control (MPC); a Seven Degrees of Freedom (DOF) BEV chassis model is constructed and rear-end crash test scenarios are created in Carsim with a high and low road adhesion coefficient. A series of comparison tests show that not only are the stopping distances between the ego vehicle and target vehicle shorter, but also the braking torques... [more]

The direct matrix converter (DMC) is considered to be an exciting power converter topology option for electric motor drives in industrial applications (elevators, hoists and cranes) and applications where size and weight are critical (e.g., the aerospace industry). Several control techniques have been developed to exploit the DMC’s benefits and achieve the desired performance with classic control techniques, such as field-oriented control and direct torque control, and more sophisticated ones, such as model predictive control and sliding mode control (SMC). SMC is attractive due to its robustness and fast response. However, this control strategy suffers from a phenomenon called chattering. Thus, a solution based on the exponential reaching law (ERL) is implemented to resolve this issue. The proposed method was validated using simulation and experimental results from tests on a three-phase induction machine.

Induction motors are the horsepower in the industrial environment, and among them, 3-phase induction motors (3PIMs) stand out for their robustness and standard 3-phase power supply. In the literature, there are many approaches to diagnose faults for the nonlinear 3PIM model, and the vast majority focus on a single motor fault, although others address more faults but at the cost of greater computational complexity. In this sense, one of the methods with less computational load and early detection is the parity equation approach, which is based on analyzing the discrepancy between the input and output signals of a real process and a linear mathematical model to generate a residual signal, which contains important information about the fault and is obtained through a suitable selection of a weighting matrix W to isolate the faults as much as possible. The problem in this case study is that the 3PIM model is a nonlinear system. In this work, the fault detection method based on the parity e... [more]

Fan deltas of the Lower Cretaceous area in Saihantala sag, Erlian Basin have been identified as major petroleum exploration opportunities. The sedimentary evolution is, however, still debatable, which hinders insights into its controlling factors. This research employed new core observations, thin section observations, and grain size analyses of 28 wells in the Saidong sub-sag, together with numerous borehole and seismic data points, to explore lithofacies types, subfacies, and microfacies characteristics, thus leading to a further investigation of the sedimentary facies evolution of the sag and its controlling factors. The findings showed there are 3 categories, 12 sub-categories, and 20 fine lithofacies types in the Saidong sub-sag. Additionally, various sand-conglomerate lithofacies were characterized by lower composition and texture maturity. With dentate-shaped, box-bell-shaped, and other morphological well-logging responses, fan deltas were mostly developed in the A’ershan Format... [more]

Renewable energy is usually connected to the DC micro-grid by a large number of power electronic devices, which have the advantages of a fast system response, but the disadvantage to reduce the inertia of the system, which makes the stability of the system worse. It is necessary to increase the inertia of DC micro-grid so that it can recover and stabilize well when it receives a disturbance. In this paper, a small-signal model of DC micro-grid with constant power load (CPL) is established, and a flexible virtual inertial (FVI) control method based on DC bus voltage real-time variation is proposed, by controlling the DC/DC converter of the energy storage system, the problem of system oscillation caused by introducing voltage differential link to the system is solved. Compared with the droop control method, the FVI control method can increase the inertia of DC micro-grid system, reduce the influence of small disturbances, and improve the stability of the system. Finally, the validity of... [more]

The pore structure characteristics of shales are controlled by their mineral and organic matter compositions. However, the contributions of different components to the pore structure characteristics of lacustrine shales remain poorly understood. In this study, fifteen Chang 7 Member shales of the Yanchang Formation, Ordos Basin, were investigated through total organic carbon (TOC), X-ray diffraction (XRD), scanning electron microscopy (SEM), and low-pressure N2 and CO2 adsorption analyses to study the control of shale composition on the pore structure characteristics of lacustrine shales. The results show that the average TOC content of the Chang 7 Member shales is 9.63 wt.%. XRD analysis shows that minerals in the Chang 7 Member shales consist of quartz, feldspars, clay minerals, and pyrite. The clay minerals were dominated by illite, chlorite, and interstratified illite/smectite. The mesopore characteristics of the Chang 7 Member shales and micropore characteristics of organic-lean s... [more]

Due to its high functionality, the solid state transformer (SST) represents an emerging technology with huge potential to replace the conventional low-frequency transformer (LFT) in a wide range of applications, including railway traction, smart grids, and others. On the other hand, model predictive control (MPC) has proven to be a highly promising control approach for several power electronics systems, especially those based on multiple power converters. Considering these facts, over recent years, different MPC techniques have been proposed for different types of SSTs. In addition to that, numerous MPC strategies have also been investigated for various power converters topologies that can be used in SSTs. However, a paper summarizing and discussing MPC strategies in the framework of SSTs has not yet been proposed in the literature, being the main goal of this work. In this paper, all the existing MPC techniques in complete SST topologies will be presented and discussed. In addition, f... [more]

The shielding calculation of neutron streaming problems with ducts is characterized by the strong anisotropy of angular flux, which poses a challenge for the analysis of nuclear installations. The discrete ordinate method is one of the most commonly deterministic techniques to solve the neutron transport equation, in which the accuracy and efficiency neutron are crucial to ensure the reliability of the streaming shielding simulation. We implemented the goal-oriented multi-collision source algorithm in the 3D transport code ARES. This algorithm can determine the importance factor based on the adjoint transport calculation, obtain the response function to enable problem-dependent, goal-oriented spatial decomposition, and provide the error estimation as a driving force behind the dynamic quadrature to optimize the source iteration. This study focuses on verifying the goal-oriented multi-collision source algorithm under the neutron streaming problems, and the capabilities of the algorithm... [more]

Fault detection of the electric vehicle battery system is vital for safe driving, energy economy, and lifetime extension. This paper proposes a data-driven method to achieve early and accurate battery system fault detection to realize rapid early warning. The method first adopts the support vector data description model mapping the feature of unlabeled voltage and temperature into a minimum volume hypersphere in high-dimensional space. When the feature is located outside the hypersphere, it is judged to be faulty. Then, to overcome the problem of hyperparameters selection, Bayesian optimization and a small amount of label data are used to iteratively train the model. This step can greatly improve the fault detection ability of the model, which is conducive to mining early and minor faults. Finally, the proposed model is compared with three unsupervised fault detection models, principal component analysis, kernel principal component analysis, and support vector data description to valid... [more]

With increased interests in affordable energy resources, a cleaner environment, and sustainability, more objectives and operational obligations have been introduced to recent power plant control systems. This paper presents a verified load frequency model predictive control (MPC) that aims to satisfy the load demand of three practical generation technologies, which are wind energy systems, clean coal supercritical (SC) power plants, and dual-fuel gas turbines (GTs). Simplified state-space models for the two thermal units were constructed by concepts of subspace identification, whereas the individual wind turbine integration was implicated by the Hammerstein−Wiener (HW) model and then augmented from the output to simulate the effect of a wind farm, assuming similar power harvesting from all turbines in the farm. A practical strategy of control was then suggested, which was as follows: with a changing load demand, the available harvested wind energy must be fully admitted to the network... [more]

Previous studies have shown that the influence of deep dynamic pressure on the surrounding rock control of a coal roadway is one of the difficulties in mine roadway support. Based on the investigation of the headgate 11231 in a coal mine, this study analyzes the damage characteristics of coal roadway surrounding rock affected by deep dynamic pressure, expounds on the difficulties of controlling the roadway surrounding rock, and creatively proposes a cooperative control technology of external anchor−internal unloading for regulating large deformation of roadways. The vertical stress distribution and transfer law of surrounding rock with different hole-making depths, spacing, and lengths after roadway excavation were simulated and studied, and an appropriate parameter range of hole-making space in the stage without dynamic pressure influence was obtained. Considering the influence of mining dynamic pressure, the surrounding rock pressure relief effect of each optimized hole-making parame... [more]

For the last decade, there has been great interest in studying dynamic control for unmanned aerial vehicles, but drones—although a useful technology in different areas—are prone to several issues, such as instability, the high energy consumption of batteries, and the inaccuracy of tracking targets. Different approaches have been proposed for dealing with nonlinearity issues, which represent the most important features of this system. This paper focuses on the most common control strategy, known as model predictive control (MPC), with its two branches, linear (LMPC) and nonlinear (NLMPC). The aim is to develop a model based on sensors embedded in a Tello quad-rotor used for indoor purposes. The original controller of the Tello quad-rotor is supposed to be the slave, and the designed model predictive controller was created in MATLAB. The design was imported to another embedded system, considered the master. The objective of this model is to track the reference trajectory while maintainin... [more]

Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-quality data thanks to the application of data analysis to the energy management monitoring system of a building model in Viet Nam. The research results provide a good opportunity to improve the efficiency of building energy-management systems and support the development of low-cost smart buildings.

As the world’s largest carbon emitter, China is facing great pressure to reduce emissions. With the country’s proposed timeline for carbon peaking and carbon neutralization, a new goal has been established for China’s low-carbon development. Based on the improved equal proportion allocation method, this paper allocates the overall carbon emission control goal for 2025 among 30 provinces and cities, based on 2015 figures, and measures and studies the country’s carbon emission allocation efficiency on this basis. The results show that Beijing, Tianjin, Hebei, Shandong, Zhejiang, Shanghai, Jiangsu, Guangdong and Inner Mongolia need to increase their emission reduction capacity, while Jiangxi, Guizhou, Gansu, Qinghai, Hainan and Guangxi have relatively low emission reduction targets. Based on this allocation scheme, more provinces can reduce carbon emissions by increasing their efficiency with up-to-date technology, and a new vision for national allocation that is more easily accepted by a... [more]

This study proposes a novel logarithm curve and operating time (LCOT) control strategy for a self-driving electric mobile robot. This new LCOT control strategy enables the mobile robot to speed up and slow down mildly when running longitudinally, turning left, turning right, and encountering an obstacle based on the relationship between the logarithm curve and operating time. This novel control strategy can enhance the comfort and stability of the self-driving electric mobile robot and reduce its vibrations and instabilities in the operation process. The proposed LCOT control strategy and the fixed duty cycle method were verified experimentally. The results showed that the LCOT control strategy spent 300 s running on a 3000 cm road, whereas the fixed duty cycle method spent 450 s. Because this novel method controls the acceleration and deceleration of the self-driving electric mobile robot gently and flexibly, the proposed LCOT control strategy has better working efficiency than the fi... [more]

In this paper, an adaptive fuzzy sliding-mode control (AFSMC) system is investigated for an islanded inverter to achieve a high-performance power supply. A sliding mode control (SMC) law is designed initially to obtain both the voltage tracking error and the current tracking error of the inverter involved, to realize both the output-voltage regulation and the current protection with global stability. Moreover, to deal with uncertainties in the practical inverter system without the chattering phenomenon, an adaptive fuzzy system embedded with a self-adjustive translation width is developed to replace the switch term of the SMC. In addition, the adaptation laws, derived from the Lyapunov stability theorem, adjust the AFSMC parameters online to guarantee optimal and robust performance. Furthermore, the superior control performance of the proposed AFSMC is verified by a numerical simulation in MATLAB, producing experimental results on the prototype in comparison with the conventional SMC.