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The broad acceptance of sustainable and renewable energy sources as a means of integrating them into electrical power networks is essential to promote sustainable development. Microgrids using direct currents (DCs) are becoming more and more popular because of their great energy efficiency and straightforward design. In this work, we discuss the control of a PV-based renewable energy system and a battery- and supercapacitor-based energy storage system in a DC microgrid. We describe a hierarchical control approach based on sliding-mode controllers and the Lyapunov stability theory. To balance the load and generation, a fuzzy logic-based energy management system has been created. Using a neural network, maximum power defects for the PV system were determined. The global asymptotic stability of the framework has been verified using Lyapunov stability analysis. In order to simulate the proposed DC microgrid and controllers, MATLAB/SimulinkR (2019a) was utilized. The outcomes show that the system operates effectively with changing production and consumption.

The integration of variable renewable energy sources (RES) into power grids has resulted in a more complex operating environment for power system operators (SO), necessitating the need for increased grid flexibility. This is crucial for utilities, as the cost-effective utilization of existing infrastructure is necessary, given the prolonged construction period and high investment costs associated with building new power delivery facilities. Under the umbrella of smart grid, optimal transmission switching (OTS) is a cost-effective transmission technology that can alleviate concerns related to network congestion, limited transmission capacity, and high penetration of renewables. OTS is a concept that is integrated into the optimal power flow (OPF) problem such that it provides SO the choice to temporarily switch one or more lines out of service from the network. OTS is shown in the literature to have economic benefits, reduce operational cost, relieve network congestion, serve as a corrective mechanism for reducing voltage violations, improve system reliability, and minimize system loss. Despite the significant attention given to OTS by researchers over the past decade, no extensive review paper exists on the topic in the literature. Therefore, this paper provides a state-of-the-art overview of the OTS problem. The concept of OTS is explained by approximating the alternating current OPF problem into a linear direct current OPF problem. Various alternative models of the OTS problem proposed in the literature are discussed. The paper also analyzes the interaction between OTS and other flexibility options such as Dynamic thermal rating (DTR), Energy storage systems (ESS), and RES. Furthermore, the paper presents the general framework and impact of the short-term OTS problem on long-term expansion planning problems. Finally, an extensive literature review on the impact of OTS on system reliability is provided.

The regenerative braking in the tram allows the energy to be returned to the power grid through a power inverter. Since the inverter location between the tram and the power grid is not fixed, resulting in a wide variety of impedance networks at grid coupling points, posing a severe threat to the stable operation of the grid-tied inverter (GTI). By independently changing the loop characteristics of the GTI, the adaptive fuzzy PI controller (AFPIC) can adjust according to different impedance network parameters. It is challenging to fulfill the stability margin requirements of GTI under high network impedance since the PI controller has phase lag characteristics. A correction method of series virtual impedance is proposed, which connects the inductive link in a series configuration with the inverter output impedance, correcting the inverter equivalent output impedance from resistance-capacitance to resistance-inductance and improving the system stability margin. Feedforward control is adopted to improve the system's gain in the low-frequency band. Finally, the specific series impedance parameters are obtained by determining the maximum network impedance and setting the minimum phase margin of 45°. The realization of virtual impedance is simulated by conversion to an equivalent control block diagram, and the effectiveness and feasibility of the proposed method are verified by simulation and a 1 kW experimental prototype.

Exhaustive surveys have been previously done on the long-time behavior of illness systems with Lévy motion. All of these works have considered a Lévy–Itô decomposition associated with independent white noises and a specific Lévy measure. This setting is very particular and ignores an important class of dependent Lévy noises with a general infinite measure (finite or infinite). In this paper, we adopt this general framework and we treat a novel correlated stochastic $ SIR_p $ system. By presuming some assumptions, we demonstrate the ergodic characteristic of our system. To numerically probe the advantage of our proposed framework, we implement Rosinski's algorithm for tempered stable distributions. We conclude that tempered tails have a strong effect on the long-term dynamics of the system and abruptly alter its behavior.

Micro-Doppler signatures obtained from the Doppler radar are generally used for human activity classification. However, if the angle between the direction of motion and radar antenna broadside is greater than 60°, the micro-Doppler signatures generated by the radial motion of human body reduce significantly, thereby degrading the performance of the classification algorithm. For the accurate classification of different human activities irrespective of trajectory, we propose a new algorithm based on dual micro-motion signatures, namely, the micro-Doppler and interferometric micro-motion signatures, using an interferometric radar. First, the motion of different parts of the human body is simulated using motion capture (MOCAP) data, which is further utilized for radar echo signal generation. Second, time-varying Doppler and interferometric spectrograms obtained from time-frequency analysis of a single Doppler receiver and interferometric output data, respectively, are fed as input to the deep convolutional neural network (DCNN) for feature extraction and the training/testing process. The performance of the proposed algorithm is analyzed and compared with a micro-Doppler signatures-based classifier. Results show that a dual micro-motion-based DCNN classifier using an interferometric radar is capable of classifying different human activities with an accuracy level of 98%, where Doppler signatures diminish considerably, providing insufficient information for classification. Verification of the proposed classification algorithm based on dual micro-motion signatures is also performed using a real radar test dataset of different human walking patterns, and a classification accuracy level of approximately 90% is achieved.

This paper presents two new fault models for networked systems. These fault models are more realistic and generalized for networked systems in the sense that they can represent the effects of fault at the node and network levels. At the network layer, the uncertain effects of the network lines are modeled using a Markov chain with complex transition probabilities simultaneously with the stochastic behavior of the network using a Bernoulli process. A new output feedback-based controller, which is two-mode dependent and considers network uncertainties and output measurements for gain calculation, is presented. Using the tools of robust control and stochastic stability, linear matrix inequality-based sufficient conditions are derived. The proposed controller successfully maintains the system’s performance by tolerating the effects of simultaneous sensor and actuator faults, ensuring the stability of networked loops. Simulation results verify the applicability of the presented fault-tolerant control against multiple simultaneous faults.

The development of single-phase symmetrical bipolar voltage gain matrix converters (MC) is growing rapidly as they find their application in power systems for dynamic restoration of line voltages, high voltage AC–DC converters, and variable frequency controllers for many industrial processes. However, the existing trend in matrix converter technology is a buck–boost operation that has inherently serious issues of high voltage and current surges or stresses. This is a big source of the high voltage and current rating of semiconductor switching devices. There is also a problem of high ripples both for voltage as well for current, requiring large size of filtering capacitors and inductors. The non-symmetrical control of the voltage gain increases the control complication. A large count of operating transistors is critical regarding their cost, size, and power conversion losses, as the space and cost required by their gate control circuits are much larger than the size and cost of the switching transistors. Thus, in this research work, a new single-phase MC is introduced only employing six fully controlled switching devices, ensuring similar operation or outputs as is obtained from the existing topologies that require the use of eight or more fully controlled switching devices, and the reduction by two or more switching transistors helps to compact the overall size and lower the overall cost. The separation in its voltage buck and boost operation enables smooth control of the voltage gain through duty cycle control. The low values of the voltage and current surges reduce the power rating and losses of the switching devices. The flow of the current in the filtering inductor is kept unidirectional to avoid the current interruption and reversal problem once the operation of the converter is abruptly switched from inverting to non-inverting and vice versa. All these factors are comprehensively detailed through the circuit’s description and comparative analysis. Simulation and practical results are presented to confirm the effectiveness of the developed circuit topology.

Multi-target tracking (MTT) generally needs either a Doppler radar network with spatially separated receivers or a single radar equipped with costly phased array antennas. However, Doppler radar networks have high computational complexity, attributed to the multiple receivers in the network. Moreover, array signal processing techniques for phased array radar also increase the computational burden on the processing unit. To resolve this issue, this paper investigates the problem of the detection and tracking of multiple targets in a three-dimensional (3D) Cartesian space based on range and 3D velocity measurements extracted from dual-orthogonal baseline interferometric radar. The contribution of this paper is twofold. First, a nonlinear 3D velocity measurement function, defining the relationship between the state of the target and 3D velocity measurements, is derived. Based on this measurement function, the design of the proposed algorithm includes the global nearest neighbor (GNN) technique for data association, an interacting multiple model estimator with a square-root cubature Kalman filter (IMM-SCKF) for state estimation, and a rule-based M/N logic for track management. Second, Monte Carlo simulation results for different multi-target scenarios are presented to demonstrate the performance of the algorithm in terms of track accuracy, computational complexity, and IMM mean model probabilities.

Harmonics worsen the quality of electrical signals, hence, there is a need to eliminate them. The test objects under discussion are single-phase versions of cascaded H-bridge (CHB) multilevel inverters (MLIs) whose switching angles are optimized to eliminate specific harmonics. The Dragonfly Algorithm (DA) is used to eradicate low-order harmonics, and its statistical performance is compared to that of many other optimization techniques, including Particle Swarm Optimization (PSO), Accelerated Particle Swarm Optimization (APSO), Differential Evolution (DE), and Grey Wolf Optimization (GWO). Various scenarios of the algorithms’ search agent population for inverters with seven, nine, and eleven levels of output voltages are comprehensively addressed in this research. No algorithm shows total dominance in every scenario. The DA is least impacted by the change in dimensions of the narrated problem.

An automotive supply chain includes a range of activities from the concept of the product to its final transfer to a customer and subsequent vehicle maintenance. The three distinct stages of this chain are production, sales, and maintenance. In many countries, automobile records are not available to the public and anyone who has access to the central database or government systems can tamper with these records. In addition, used vehicle maintenance and transfer histories remain unavailable or inaccessible. These issues can be overcome by incorporating state-of-the-art blockchain technology into automotive supply chain management. Blockchain technology uses a chain of blocks for distributed transfer and storage of information, creating a decentralized data register that makes records of any digital asset tamper-proof and transparent. In this paper, we implement a permissioned blockchain-based framework for secure and efficient supply chain management of the automobile industry. We employed Hyperledger Fabric; an enterprise-grade distributed ledger platform for developing solutions. In our solution, the blockchain is customized and private in order to ensure system security. We evaluated our system in terms of memory cost, monetary cost, and speed of execution. Our results demonstrate that only 346 MB of extra memory space is required for storing the automotive data of 1 million users, thus rendering the memory cost negligible. The monetary cost is insignificant as all open source blockchain resources are employed, and the speed of record update is also fast. Our results also show that the decentralization of the automotive supply chain using blockchain can implement system security with minor modifications in the established configuration of the web application database.

Single-phase AC–AC converters with a direct power conversion approach are receiving rapid development as they have the ability to produce the regulated non-inverting and inverting form of the input voltage at the output. This feature enables them to correct the line voltage profile once they are used as dynamic voltage restorers if there is an issue of voltage sag or swell in the power distribution system. The regulated non-inverting and inverting form of the output voltage may also be used to obtain the step change in the output frequency, as it is required in many industrial drive systems. However, the realization of such existing circuits needs a large number of components and semiconductor devices, especially switching transistors. The operating control (on and off) of the transistors is directly associated with the use of gate control circuits. The count of such circuits is critical as their volume and cost are much greater than the operating transistors. The number of conducting semiconductor devices in the existing converters is also a big source of high conversion losses, thus leading to lower efficiency. This article introduces a new circuit topology realized only with the use of one full bridge of four IGBTs and a full bridge of four diodes. The use of four switching transistors only requires four gate control circuits that drastically reduce the overall volume and size. All the operating modes of the proposed topology require the conduction of fewer semiconductor devices, which helps to lower the conduction losses. Detailed analysis and description were carried out to validate the attractive features of the developed circuit once compared with the existing circuit topologies. For validation purposes, the computer simulation was carried out on Simulink software. The results obtained from this environment were compared with the real results gained from a practically developed laboratory test bench. The voltage regulation characteristics of the output voltage by employing pulse width modulation (PWM) were confirmed for two values of the non-inverting and inverting outputs.

The unconvertible portion of incident radiation on solar panels causes an increase in their temperature and a decrease in efficiency due to the negative temperature coefficient of the maximum power. This problem is dealt with through the use of cooling systems to lower the temperature of photovoltaic (PV) panels. However, the developments are focused on the loss of efficiency or extract the heat out of the solar panel, rather than optimizing the solution to produce a net gain in the electric power output. Therefore, this study proposes the analytical model for the cell temperature, irradiance and design of absorbers. Furthermore, the cooling systems for the hybrid solar panels were developed through analytical modeling of the solar cell temperature behavior and heat exchange between the fluid and back surface of the PV module in MATLAB. The design parameters such as mass flow rate, input power, solar cell temperature, velocity, height, number of passes and maximum power output were optimized through a multi-objective, multivariable optimization algorithm to produce a net gain in the electrical power. Three layouts of heat absorbers were considered—i.e., single-pass ducts, multi-pass ducts, and tube-type heat absorbers. Water was selected as a cooling medium in the three layouts. The optimized results were achieved for the multi-pass duct with 31 passes that delivered a maximum power output of 186.713 W at a mass flow rate of 0.14 kg/s. The maximum cell temperature achieved for this configuration was 38.810 °C at a velocity of 0.092 m/s. The results from the analytical modeling were validated through two-way fluid-solid interaction simulations using ANSYS fluent and thermal modules. Analyses revealed that the multi-pass heat absorber reduces the cell temperature with the least input power and lowest fluid mass flow rate to produce the highest power output in the hybrid PV system.

Power transmission line capacity is restricted with the maximum temperature that can withstand without inadmissible of line sag. Regardless of the carried current, the temperature of the transmission line conductors was affected by various weather variables. However, the maximum capacity of the line current known as static thermal rating was determined based on the conservative weather conditions for safe operation, but the restriction of the line capacity may be modified which results in the additional capacity of the line. As a result, real-time thermal rating technique was applied on thermal model of the transmission line. Generally, the information about weather conditions is considered uncertainty, however, the weather variables should be dealt with and studied statistically for determining the accurate rise in the conductor temperature. The real-time thermal rating technique is evaluated using weather variables. The most important parameter is the wind speed, which greatly influence s conductor temperature and implicitly affects power transmission line capacity. Thus, in this study, the real-time thermal rating technique is developed by weather variable model based on the variational mode decomposition technique that applied only on the wind speed for adapting wind speed measurements to produce conservative evaluation of convective cooling on the conductors of power transmission system without violating the maximum operating temperature inside the core of conductors. The developed real-time thermal rating is implemented on sections of the power transmission system of western Saudi Arabia. The developed technique is compared with other techniques to investigate its applicability. [ABSTRACT FROM AUTHOR]

In this paper, a composite Rayleigh-Gamma distribution is proposed for the urban wireless channel environment which represents small-scale fading with no Line of Sight (LoS) and shadowing. Moment Generation Function (MGF) and truncated MGF for the proposed model are derived. The spectral efficiency (SE) and the energy efficiency (EE) for a digital communication system are defined and introduced as efficiency metrics. The SE and EE are derived and evaluated in shadowing urban environment using MGF approach. Both efficiency metrics are also simulated for a particular M- QAM modulation technique. The obtained results show that the efficiency metrics are adversely affected by the urban channel environment. Thus, an energy efficient transmission technique which is based on employing a modulation level of M-QAM to provide a maximum EE in a specific region of the signal to noise ratio (SNR). With the aid of truncated MGF, the performance of adaptive M-QAM system is evaluated in terms of efficiency metrics, outage probability and average bit error probability. The proposed adaptive technique shows high potential for achieving significant improvement in SE and EE while maintaining acceptable bit error probability even under severe channel effects. [ABSTRACT FROM AUTHOR]