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The objective of the study is to investigate the thermal, electrical, and exergetic performance of a hybrid photovoltaic–thermal (PVT) system under the influence of copper oxide (CuO) nanofluid and phase change material (Vaseline (petroleum jelly)) as a heat storage medium. A mathematical model was developed with the help of various energy-balance equations over the layers of the hybrid system. The performance evaluation of the PVT system was performed using pure water, CuO-water nanofluid (0.2 and 0.4% weight fractions), and CuO-water nanofluid 0.4% weight fraction with Vaseline as a phase change material. The results of the overall analysis show that the performance of the PVT system is better using CuO-water nanofluid (0.4% wt. fraction) with PCM as compared to the water-cooled PVT system and CuO-water nanofluid. The results obtained from the study show indicate that the cell temperature of PVT was reduced by 4.45% using nanofluid cooling with PCM compared to a water-cooled PVT system. Moreover, the thermal, electrical, and overall efficiencies improved by 6.9%, 4.85%, and 7.24%, respectively, using 0.4% wt. fraction of CuO-water nanofluid with PCM as compared to PVT water-cooled systems. The performance of the PVT system was also investigated by changing the mass flow rate (MFR). The increase in mass flow rate (MFR) from 0.05 kg/s to 0.2 kg/s tends to enhance the electrical and overall efficiencies from 12.89% to 16.32% and 67.67% to 76.34%, respectively, using 0.4% wt. fraction of CuO-PCM as fluid.

The paper deals with the performance checking of an optimally designed LCL-filter connected along the grid-side converter (GSC) in a doubly fed induction generator (DFIG) based wind energy conversion system (WECS) in attenuating harmonics. A repetitive approach is required for designing the parameters of the LCL-filter. The reasons being the explicitness of design parameters and design requirements of the proposed filter like IEEE-519 Std. for harmonic current attenuation, maximum voltage difference allowed in between two sides of the filter to limit switching losses, and limit of reactive power compensation. The proposed filter is compared with the conventional LCL-filter. Based on the proposed method, a minimal inductance and optimal capacitance-based filter is obtained in this paper which is validated using a 2.2 kW DFIG based WECS. Comparative stability analysis of DFIG system with and without proposed filter is performed using small signal stability analysis. The system under study is simulated using MATLAB/Simulink and OPAL-RT 4510, simultaneously. Simulation results validates the effective use of proposed filter design method into DFIG system in terms of harmonic attenuation, total harmonic distortion and reactive power compensation.

A political leader, aiming to replace a repressive regime, wishes to establish her credibility with citizens whose participation in her movement affects its success. If her perceived ability is in an intermediate range of values, her optimal strategy is to masquerade as a no-threat before announcing a movement directly against the regime. In this range, for low costs of repression, the regime finds it optimal to exert force even against a movement that has purely non-political motives. Interestingly, if the average ability of the political leader is low (high) relative to the non-political type, then the range where the regime exerts force against a non-political movement, increases (decreases) with the leader’s likelihood of being non-political.

MRI image analysis and its segmentation for the accurate and automatic detection of brain tumors at an early stage is very much crucial for diagnosis the disorders and save human lives. Since most deep learning models have a large number of layers, they also take longer processing time, making them unsuitable for smaller image datasets. Hence, we have proposed, the detection of abnormality from brain MR images using a Less Layered and less complex U-Net model (LeU-Net) architecture. The principle of LeU-Net is inspired by the Le-Net and U-Net models, but completely different from both the design and architectural perspectives. The abnormality detection indicates the classification of the tumorous cell from overall Magnetic Resonance images. The Proposed deep learning model (LeU-Net) performance was compared with the existing basic CNN models Le-Net, U-Net, and VGG-16. The model performance was evaluated using evaluation metrics accuracy, precision, F-score, recall, and specificity. The experiment is performed on MR Dataset with uncropped images and cropped images (removed unwanted area) and compared the result with all three models. The LeU-Net model registers overall 98% accuracy on cropped images and 94% of accuracy on uncropped images. The LeU-Net model has much faster processing (simulation) time, it only takes 244.42 s and 252.36 s, respectively, to train the model with 100 epochs on the uncropped and cropped images. We have compared the performance of our proposed model with various state-of-the-art techniques, and it provides the best classification accuracy among all.

Automatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram (ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is also referred as a “Heart Attack”, which is the most fatal cardiovascular disease. In many cases, MI does not show any symptoms, hence it is also called a “silent heart attack”. In such cases, patients do not get time to prepare themselves. Hence this disease is more dangerous and fatal with a high mortality rate. Hence, we have proposed an automated detection system of MI using electrocardiogram (ECG) signals by a convolutional neural network (CNN), hybrid CNN- long short-term memory network (LSTM), and ensemble technique to choose the optimum performing model. In this work, we have used 123,998 ECG beats obtained from the “PTB diagnostic database (PTBDB)” and “MIT-BIH arrhythmia database (MITDB) to develop the model. The experiment is performed in two stages: (i) using original and unbalanced datasets and (ii) using a balanced dataset, obtained from synthetic minority oversampling technique (SMOTE) data sampling technique. We have obtained the highest classification accuracy of 99.82 %, 99.88 %, and 99.89 % using CNN, hybrid CNN-LSTM, and ensemble techniques, respectively. Hence the proposed novel data balancing technique (SMOTE-Tomek Link) not only solves the imbalanced data problem but also increases the minority class accuracy significantly. Now our developed model is ready for the clinical application that can be installed in hospitals for the detection of MI.

In this article, authors proposed a useful technique for order reduction of large-scale linear dynamic time-invariant systems using the dominant pole retention, Pole Spectrum Analysis, and Pade approximations. The denominator dynamics of the simplified system is obtained by using PSA and pole dominance algorithm; numerator dynamics of the same is obtained by using Pade approximation. The approximation is based on the principle that the mean of the poles (pole centroid) and centroid-based system stiffness are same for both large-scale and simplified systems. For a stable higher-order system, the method promises the stability of the simplified system. To validate the proposed technique, some numerical illustrations have been considered from the literature with the comparisons of performance in terms of a quality check through performance index and response matching between original higher-order and simplified systems.

In the upcoming decades, renewable energy will find enormous usage in power industries. Renewable energy while supplementing conventional energy may experience a huge problem during making of contr...

This paper presents a modified minimal realization technique to reduce single input single output (SISO) systems from higher-order SISO systems. The reduction process is based on restructuring the Hankel matrix, which consists of two major elements, i.e., Time Moments and Markov parameters. The system transformation is executed to reduce the order of the system by maintaining the desired system properties. The modified Hankel Matrix is proposed to obtain an expected reduce order model, i.e., kth order reduced model by selecting $$\left[ {k \times k} \right]$$ order square matrix and using Silverman’s algorithm. This paper presents a simple solution of model order reduction with the advantages of minimizing the steady-state error, fast convergence of steady-state behavior, better approximation in terms of rise time, peak time, and settling time at higher frequencies. Three different cases have been taken from the literature to validate the proposed technique with the comparisons of performance in terms of a quality check through performance indices and response matching between original and reduced-order models.

In recent decades, renewable energy has emerged as one of the most promising alternatives to traditional energy sources for long-term, uninterrupted power supply. Engineers face numerous challenges when replacing renewable energy with con ventional energy because the characteristics of solar and wind generation rapidly fluctuates with environmental conditions, resulting in large synchronizing imbal ances between different units with system delays or communication delays in large electrical grids. They want to leverage computation delay margin to build a control mechanism that can handle a wide range of time delays (MADB). The authors of this article concentrate on the effects of the fractional integral order (FOI) on the stable parameter space for the regulation of a hybrid renewable energy based dis tributed system (DGS) in three-area AGC configuration. By altering the fractional order range, the delay margin () can be expanded, which can help to expand the stability region of a time delayed system. The stable parameter spaces of the con troller are computed stability boundary based on the fractional integral order and time delay ( ) values, and the present authors have developed asymptotic bode plot of time delayed Fractional-order proportional integral (FOPI) controller and computing delay margin () using gain margin (GM) and phase margin (PM) for this purpose. Honey badger algorithm (HBA) has been devised for fine-tuning the above-mentioned controller parameters. The controller’s resilience is confirmed in the presence of random load perturbations, nonlinearities, and parameter fluctuation.

This article introduces grasshopper optimization algorithm (GOA) for getting an optimum and effective solution of an automatic generation control (AGC) problem in hybrid power systems under a dereg...

Potential challenge during a disaster is the wide range of disturbance caused to the power system network. The article attempts to develop a systematic procedure to progressively restore the network by recognizing the alive network. During disaster there is manpower shortage and poor road connectivity around the affected area. Hence, an autonomous priority-based restoration policy is required for critical load restoration. The main idea of the proposed article is to develop an autonomous system, which is decision-based restoration system by identifying the network component still available after disaster followed by reconfiguration confirming the proposed load pickup procedure. Because of the inherent capability of implementing the condition-based state transition of switches and parallel processing, a petri net (PN) based methodology has been used in the article to integrate alive parts, which further assists in identifying the best switching schedule of circuit breakers for autonomous load restoration. The primary contribution of the article is to develop an encapsulated algorithm using PN as a modeling platform of components as well as empowering the same by introducing the game-theory-based concept in the formulation of different microgrids integrated with distributed generators during extreme weather events. The verification of effective autonomous restoration is then realized by using the available delivery capability and design verification of the framed microgrids, and the comparison with different restoration strategies adopted by other authors. The studies are carried out with the IEEE 34, 37, and 123-bus feeder test systems for implementation and validation of the proposed article along with the comparison with other published works.

In this manuscript, an off-grid or isolated microgrid (IMG) model has been considered, which consists of renewable power generating sources (RPGS) like solar photovoltaic (PV), solar thermal, wind and fuel cell (FC) along with diesel engine generator (DEG) and battery energy storage system (BESS). The paper emphasizes the analytical study of the impact of RPGS in the frequency control of IMG system. In an IMG integrating distributed energy sources (DES), proper frequency regulation is important because some RPGS do not take part in the frequency control technique and depend on weather conditions like solar insolation and wind speed. For frequency control of the IMG system, a linear quadratic regulator with an integral controller (LQR-I) has been used for its robust characteristics. For designing the LQR-I controller, the IMG system has been represented as a state-space model. The effectiveness of the proposed LQR-I controller has been validated through the dynamic response of the IMG system for a small load perturbation. Robustness of the controller has been verified by sensitivity analysis of the system for varying IMG system parameters such as KWTG, KPV, KS, KT, KAE, KFC, KDEG, KBESS, TFC, KP, TP as well as randomly varying load, varying wind speed and seasonal variation of solar insolation level.

The paper presents design and development of a precision motion actuator, which can traverse required trajectory in the X–Y plane and can be used for micromachining applications using magnetic levitation based technology. A glass-reinforced epoxy laminate sheet with micromachined holes in the horizontal and vertical direction with copper wires placed vertically and horizontally was used for actuation of rare earth magnets wherein a pyrolytic graphite sheet was fixed over the copper wires. The diamagnetism of pyrolytic graphite sheet coupled with electromagnetic field generated because of the current passing through the copper wires led to levitation and actuation of the rare earth magnet over desired trajectory. COMSOL Multiphysics (COMSOL Inc., Burlington, Massachusetts, USA) simulation was conducted in order to simulate the forces generated by the developed actuator. Thereafter, the forces generated by the actuator with current flowing through the wires were measured using a dynamometer where the error was limited within 2%. An acrylic sheet was fixed over the actuator and laser micromachining was conducted with trajectories traversed by the actuator. Scanning electron microscope results of the machined samples confirmed that feature sizes in the range of 200–300 micron could be generated. This proves the potential of the developed actuator for micromachining applications.

This study analyses the dynamic behaviour of a doubly fed induction generator (DFIG)-based wind integrated power system (WIPS) resulting from a major disturbance. The effects of transient disturbance on WIPS are examined without and with a controller in terms of performance and stability of the system. To enhance the performance of WIPS after a sudden disturbance, an optimally designed linear quadratic regulator (LQR) controller is applied to the system. The wind energy system is described in state-space representation, whose states and outputs are taken as feedback to the controller for improving their dynamic response. An artificial bee colony (ABC)-based swarm optimisation technique is used to evaluate the optimal weighting matrices of the LQR controller in parallel with minimising the performance index and dynamic response characteristics of the system. The effectiveness of the proposed ABC–LQR controller in WIPS is verified by comparing their simulation and numerical results with standard proportional–integral and LQR controllers. It indicates that the proposed controller provides better enhancement of dynamic response as compared with other controllers in terms of performance index and dynamic response characteristics. Moreover, the robustness and stability of various system configurations are tested by the eigenvalue analysis.

We investigate intertemporal planning problems as a way of gaining understanding of the characteristics of individual decision-makers and the choice options presented to them. A frequent simplifying assumption that is made in studies of this sort is that choice of options that yield lower monetary payments than other available options is suboptimal, but consideration of subjective uncertainty in fulfilling requirements to obtain future payments easily disposes of this notion. For example, if one chooses an option in which one pays zero interest for a year on a purchase but then fails to pay the item off before high interest charges kick in, this would be considered suboptimal, compared with paying the item off up front, or in some other fashion. The important point is that what makes an action optimal or suboptimal is often contingent on information that is essentially unobservable, specifically, the probability that one will fail to pay the item off in time. In the experiment, we make inferences about subjective uncertainty based on the choices one makes.

With the increase of electrical energy consumption and associated power grid expansion the complexity in the grid network increases which tends to increase the fault occurrence possibilities. Low voltage ride-through capability helps the system to achieve the standard of grid code by remaining connected with the grid during fault occurrence. Direct current-based saturated core fault current limiter (DC-SCFCL) is a type of fault current limiter with superior influence in fault ride-through (FRT) capability. It has an arrangement of embedded alternating current coil and direct current (DC) coil across the side and centre of the core limb. However, being more effective in FRT, the ideal DC-SCFCL has some of its drawback such as development of high voltage across the DC coil and more current difference during fault occurrence. To limit these drawbacks a modified DC-SCFCL with shorted ring and also working with the coil below its critical temperature has been proposed in this study. The voltage profile, as well as the current profile, has been analysed which comprises its behaviour in all conditions. The proposed technique is applied to DFIG-based wind energy system to restrict the fault current and enhance the FRT capability.