Showing papers in "Iranian Journal of Science and Technology-Transactions of Electrical Engineering in 2020"

Multi-criteria COPRAS Method Based on Parametric Measures for Intuitionistic Fuzzy Sets: Application of Green Supplier Selection

Abstract: In this manuscript, we present complex proportional assessment (COPRAS) method to solve multi-criteria decision-making (MCDM) problems with intuitionistic fuzzy information, known as IF-COPRAS method. In this method, a new formula is developed to evaluate the criterion weights, in which the objective weights are calculated from divergence measure method. For this, new parametric divergence and entropy measures are investigated and some desirable properties are also discussed. Since the vagueness or uncertainty is an unavoidable characteristic of MCDM problems, the proposed approach can be a useful tool for decision making in an uncertain atmosphere. Further, a decision-making problem of green supplier selection is presented to demonstrate the usefulness of the proposed method. To illustrate the validity of the proposed method, comparison with existing methods is presented and the stability is also discussed through a sensitivity analysis with different values of criterion weights.

Image Segmentation Using Multilevel Thresholding: A Research Review

Abstract: Image segmentation is a basic problem in computer vision and various image processing applications. Over the years, commonly used image segmentation has become quite challenging because of its utilization in many applications. Image thresholding is one of the most exploited techniques to accomplish image segmentation. Multilevel thresholding is found to be most appropriate and well known among all the image segmentation techniques. The segmented image quality is based on the techniques incorporated to choose the threshold value. In this paper, an exhaustive survey has been carried out, considering both the general purpose and satellite images to cover the performance comparison of various image segmentation approaches based on meta-heuristics optimization algorithms, present in the literature for multilevel image thresholding. In addition, this paper also focuses on information theoretic approach-based objective criterion using different statistical properties such as between-class variance, entropy, moment and maximum likelihood for selecting multilevel thresholds. A list of 157 publications on the subject is also appended for quick reference.

Flexibility Planning of Distributed Battery Energy Storage Systems in Smart Distribution Networks

Abstract: The deployment of batteries in the distribution networks can provide an array of flexibility services to integrate renewable energy sources (RES) and improve grid operation in general. Hence, this paper presents the problem of optimal placement and sizing of distributed battery energy storage systems (DBESSs) from the viewpoint of distribution system operator to increase the network flexibility. The problem is formulated as an optimization framework wherein the objective function is to minimize the annualized sum of investment costs and operational costs of DBESSs while it is constrained to power flow, DBESS and RES constraints as well as distribution network operation limits. In addition, while the problem model is as nonlinear programming, this paper suggests an equivalent linear programming model for all constraints and quadratic formulation for the objective function to reach the global optimal solution with low error calculation. In the next step, the Benders decomposition approach is deployed to acquire better calculation speed. Finally, the proposed problem is applied to 19-bus LV CIGRE benchmark grid by GAMS software to investigate the capability of the model.

Photovoltaic Cells Parameter Estimation Using an Enhanced Teaching–Learning-Based Optimization Algorithm

Abstract: Solar cell is one of the important renewable energy resources, and it is considered a promising source for energy challenges in the future. The identification of solar cell model parameters is very important due to the control and the simulation of PV systems. In this paper, an enhanced teaching–learning-based optimization (ETLBO) algorithm is proposed and applied to estimate the photovoltaic cells parameter. The ETLBO is proposed to improve the performance of conventional TLBO and reduce its search space by adjusting the parameters which control the explorative and exploitative phases to achieve the suitable balancing. The proposed algorithm is validated using real dataset of photovoltaic single-diode and double-diode models. In addition, the proposed algorithm is tested on the dataset of two real PV panels (polycrystalline and monocrystalline). The results obtained by the proposed algorithm are compared with those obtained by other well-known optimization algorithms. All results prove the effectiveness and superiority of proposed algorithm compared with other optimization techniques.

Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm

Abstract: This paper proposed a new methodology based on nature-enthused meta-heuristic optimization algorithm named as whale optimization algorithm (WOA), which can significantly envisage problems for simultaneous allocation of distributed generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the radial distribution systems (RDS). In the proposed method, optimal locations and sizing of the DG and DSTATCOM can be determined by loss sensitivity factor and WOA, respectively. The objective function of the proposed method is to minimize the system’s total power losses and total operating cost of DG and DSTATCOM. The proposed method is applied to well-known IEEE 33-bus and large 136-bus RDS. The attained simulation results and comparison of different cases considered leads to allocation of DG and DSTATCOM combination resulting in significant power loss reduction with good voltage profile enhancement.

Dilated Deep Neural Network for Segmentation of Retinal Blood Vessels in Fundus Images

Abstract: Medical diagnosis is being assisted by numerous expert systems that have been developed to increase the accuracy of such diagnoses. The development of image processing techniques along with the rapid development in areas like machine learning and computer vision help in creating such expert systems that almost nearly match the accuracy of the expert human eye. The medical condition of diabetic retinopathy is diagnosed by analyzing the retinal blood vessels for damages, abnormal new growths and ruptures. Various techniques using convolutional neural networks have been used to segment retinal blood vessels from fundus images, but these techniques often do not segment the retinal blood vessels accurately and add additional noise due to the limited receptive field of the convolutional filters. The limited receptive field of the convolutional layer prevents the convolutional neural network from getting an accurate context of objects that extend beyond the size of the filter. The proposed architecture uses a dilated convolutional filter to obtain a larger receptive field which leads to a greater accuracy in segmenting the retinal blood vessels with near human accuracy. The convolutional neural networks were trained using the popular datasets. The proposed architecture produced an area under ROC curve (AUC) of 0.9794 and an accuracy of 95.61% and required very few iterations to train the network.

Progress and Challenges in Smart Grids: Distributed Generation, Smart Metering, Energy Storage and Smart Loads

Abstract: The future power system must provide electricity that is reliable and affordable. To meet this goal, both the electricity grid and the existing control system must become smarter. In this paper, some of the major issues and challenges of smart grid’s development are discussed, and ongoing and future trends are presented with the aim to provide a reader with an insight on the relevant research topics, challenges and actual engineering tasks in smart grids. The focus areas of this review study are distributed generation, microgrids, smart meters’ deployment, energy storage technologies, and the role of smart loads in primary frequency response provision. The exploration of smart grid technologies and distributed generation systems has been accomplished, and a general comparison of the conventional grid and a future smart model is included. The issue of increasing penetration of renewable energy sources to the power system and posers related to the integration of distributed generation are also presented.

Moth-Flame Algorithm for TCSC- and SMES-Based Controller Design in Automatic Generation Control of a Two-Area Multi-unit Hydro-power System

Abstract: An analysis on automatic generation control (AGC) performance of an interconnected two-area hydro–hydro-power system model is presented in this paper subjected to dynamic control of damped oscillations in the presence of thyristor-controlled series compensation (TCSC) and the superconducting magnetic energy storage (SMES) unit. In real time, the load profile characteristics are un-deterministic in nature. Therefore, the current article studies a diverse prospective of area load profiles [such as step load perturbation (SLP), random SLP and sinusoidal load perturbation] in view of AGC performance analysis. The present work is to improve the dynamic responses and to pursue their significances in damping oscillation after the addition of a fast-acting TCSC (as a damping controller) in area-1, whereas SMES unit is installed in area-2 (to provide large values of energy instantaneously). In the present prospect, a new control strategy based on Taylor theorem is implemented to modify the TCSC controller as well as the two-stage phase-compensating blocks are cascaded to both the TCSC and the SMES to improve the phase lag of the system. In this paper, a nature-inspired optimization paradigm [called moth-flame optimization (MFO) algorithm] is utilized to design the controller gains. Additionally, the robustness of the designed controller is investigated in the event of loaded condition and model parameter uncertainties through sensitivity analysis. Analytically, eigenvalues, performance indices values and transient details are presented in support of the designed MFO–TCSC–SMES controller. The obtained simulation results are compared to genetic algorithm (GA)-based designed GA–TCSC–SMES controller to show the optimizing performance of the MFO algorithm in the controller design. The simulation results showed that after the addition of a TCSC–SMES unit in the studied power system model, in addition to eliminating damped oscillations, the settling times of frequency and tie-line power flow are considerably reduced.

Topologies and Control Strategies Implicated in Dynamic Voltage Restorer (DVR) for Power Quality Improvement

Abstract: Controlled and improved power quality is one of the fundamental and essential needs in any industry driven by electric power for optimal exploitation of resources. However, in power quality, some crucial problems have been recognized as harmonic distortion, interruption, sag, swell and transient. Out of these, sag and swell are predominantly seen and cause stern impact on the electrical devices or machines and therefore require to be mitigated at an earliest to protect from any failure or mal-operation. As an ultimate key to crack these problems, some custom power devices such as distribution STATCOM (DSTATCOM), dynamic voltage restorer (DVR) and unified power quality conditioner are unanimously procured. A prominent custom power device DVR is apparently suggested in the literature for the mitigation of voltage sag and swells, with the benefit of active or/and reactive power control. The DVR is reported as being a high-performance solution to compensate voltage disturbances, since it provides both a cost-effective solution and very fast dynamics. In recent years, a bulk amount of the literature accounts for DVR on different configurations of its power circuit and various control techniques employed in it. This review article presents a detailed study on DVR with the different possible configurations of its power circuit and control techniques encircling major power quality issues. The informative object covered in the paper, articulate choice of control strategy and power circuit ensuring optimal recital of DVR in satisfying a required quality. This paper also furnishes the valued information for the investigator in this field.

An Analysis and Generation Toolbox for Chaotic Substitution Boxes: A Case Study Based on Chaotic Labyrinth Rene Thomas System

Abstract: One of the successful examples of chaos-based cryptology design proposals is s-box structures based on random selection. There are many s-box design proposals in the literature since chaotic systems are a powerful entropy source. This feature is one of the most important factors affecting successful designs. Another important factor affecting this success is that measurable test criteria for s-box analysis are clearly presented in the literature. This study has developed a toolbox that can analyze these measurable test criteria. This toolbox has shown that the performance measures of the seven previous proposals in the literature are incorrectly calculated. This analysis toolbox has been made free to use for researchers and aims to prevent inaccurate analyses in future studies. Another contribution of the study is the random selection-based s-box generator toolbox. This toolbox can use both classical random function and chaotic system classes as entropy source. Another important output of generator toolbox is the chaotic labyrinth Rene Thomas system, which can be selected as a continuous-time chaotic system. This system has been first used in the s-box generator. This study has been one of the first steps in addressing the analysis problems of the chaos-based cryptology literature. It is thought that along with such studies to be developed in the future will positively affect the success of the chaos-based cryptographic system proposals.

A Novel Salp Swarm Algorithm for Expansion Planning with Security Constraints

Abstract: Transmission expansion planning (TEP) is one of the critical issues of the deregulated electricity market. In view of this, a salp swarm algorithm (SSA) is being considered in the present work for the solution of TEP problem with the added security constraint. The features of SSA algorithm are its foraging behavior of salps swarming in the oceans. Under the TEP problem, the work considered here is to determine the cost-effective expansion planning in the deregulated electricity market. For this act, some of the important constraints such as power flow of the lines, right-of-way’s validity and maximum line addition are taken into consideration. The studied power system networks are IEEE 25-bus system, Brazilian 46-bus system and Columbian 93-bus system for the study of TEP problem. The results are compared to those offered by some other state-of-the-art algorithms. It showed that SSA is effective algorithm for the TEP problem.

Boosting the Performance of the BoVW Model Using SURF–CoHOG-Based Sparse Features with Relevance Feedback for CBIR

Abstract: The content-based image retrieval (CBIR) based on sparse visual features is a challenging research problem to categorize images into semantically meaningful classes Different robust feature representation methods have been proposed to address the semantic gap issue of CBIR In this article, we propose a novel robust image representation for CBIR, which is based on complementary visual words integration of speeded up robust features (SURF) and co-occurrence histograms of oriented gradients (CoHOG) The SURF is a local feature descriptor, while CoHOG is a global feature descriptor The local features give better performance for images belonging to different semantic classes and having close visual appearance among their visual contents, while global features give better performance to retrieval images at large scale To ensure image retrieval accuracy, the proposed method build two smaller size dictionaries, each containing visual words of SURF and CoHOG descriptors, which are assimilated to form one larger size dictionary In the CBIR system, a dictionary of smaller size produces better sensitivity, while a dictionary of larger sizes produces better specificity The dictionary of the larger sizes also yields an overfitting problem to affect CBIR performance, which is addressed by introducing a linear discriminant analysis (LDA) and relevance feedback with the proposed method The comparative performance analysis of the proposed method is performed with the competitor CBIR methods (ie, feature integration of SURF–CoHOG descriptors’ based on the bag-of-visual-words (BoVW), a single feature of SURF–BoVW and CoHOG–BoVW methods) The quantitative and qualitative analysis carried out on four standard image databases proves the robust performance of the proposed method as compared to its competitor and recent CBIR methods

Deregulated Automatic Generation Control using Novel Opposition-based Interactive Search Algorithm Cascade Controller Including Distributed Generation and Electric Vehicle

Abstract: This paper deals with the maiden application of opposition-based interactive search algorithm (OISA) for a multi-area, multi-source power system having thermal, hydro and gas generating units. For realistic approach, physical constraints like boiler dynamics (BD), governor dead band (GDB) and generation rate constraint (GRC) have been considered in the thermal system, while the effects of GRC and GDB are included in hydro and gas systems. Since modern power systems are focussing more towards renewable energy resources, for the purpose of analysis distributed generation (DG) and electric vehicle (EV) units are also incorporated in the system. A novel cascade combination of two-degree-of-freedom proportional–integral–derivative with a filter (PIDN) and fractional order integral–derivative (FOID) is used as the proposed controller for the system (2DOF-PIDN-FOID). The parameters of the proposed controller are optimised using the OISA algorithm. For analysis of the proposed system in deregulated environment, a step load perturbance (SLP) of 0.01 per unit is done in area-1. The effect of integration of distributed generation (DG) and electric vehicle (EV) on the system is analysed in both combined manner and separately. In both the cases, the system dynamics show marked improvement in comparison with previous cases. Analysis of system dynamics for various cases reveals the superiority of the proposed control scheme. Further, the superiority of the proposed algorithm is proven among other well-known evolutionary techniques like genetic algorithm (GA), particle swarm optimisation (PSO), interactive search algorithm (ISA) and whale optimisation algorithm (WOA) by comparison under same test conditions. Moreover, the robustness of the system is validated against system parameter variations. Finally, the superiority of the proposed control scheme is shown by comparison with published results in the literature under same test conditions.

Trajectory Tracking Control for Mobile Robots Using Reinforcement Learning and PID

Abstract: In this paper, a novel algorithm of trajectory tracking control for mobile robots using the reinforcement learning and PID is proposed. The Q-learning and PID are adopted for tracking the desired trajectory of the mobile robot. The proposed method can reduce the computational complexity of reward function for Q-learning and improve the tracking accuracy of mobile robot. The effectiveness of the proposed algorithm is demonstrated via simulation tests.

Design of Mobile Robot Control Infrastructure Based on Decision Trees and Adaptive Potential Area Methods

Abstract: There have been a great number of studies in the scope of mobile robot systems. The most critical tasks in these systems are control and path planning. The main goal of the control task is to develop a stable control system. On the other hand, the basic motivation in the path planning task is to find a safe path with an acceptable cost. In most researches, a moving robot is considered as a point mass object and only the simulation experiments are applied. In this study, a decision tree-based mobile robot control has been developed for a static indoor environment hosting obstacle(s). The camera has been hung vertically (eye-out-device configuration) to obtain the configuration area map and track the wheeled mobile robot (WMR). A suitable path plan has been extracted with the adaptive artificial potential field (APF) method on the image obtained from the camera. Virtual distance sensors are used to calculate the potentials for APF. A decision tree-based controller has been developed to model the motion characteristics of the robot. A trigonometry-based approach is used to calculate the controller inputs. The controller has steered the WMR on the path in real time. Both simulation and real-world experiments have been conducted on a WMR in different configuration spaces. It has been determined that the designed system is convenient for controlling the WMR. The data obtained are compared to show the difference between the desired and actual path planning results. The efficiency of the controller method has been greatly improved by using dynamic parameters in the control modules.

Technical and Economic Feasibility of Utility-Scale Solar Energy Conversion Systems in Saudi Arabia

Abstract: A move toward renewable energy sources has become a global trend due to the economic and the environmental inconveniences of fossil fuels. Solar energy receives a great share of research focus owing to its availability and eco-friendly characteristics. Different approaches are advised and implemented for converting solar energy into electricity. Photovoltaic (PV) and concentrated solar power (CSP) systems are the most promising technologies in this field. PV is simply direct conversion of solar energy into electricity. It gains the advantages of size/power versatility. Meanwhile, CSP converts solar energy to electricity indirectly via thermal energy. This article introduces a comprehensive comparison between PV and CSP types regarding technical and economic feasibility of utility-scale solar power plants. Kingdom of Saudi Arabia is taken as a case study. The different types of either CSP or PV have been tested under hourly climatic data of 10 locations throughout the Kingdom of Saudi Arabia by using system advisor model software from National Renewable Energy Laboratory in order to identify the appropriate type of these systems to Saudi Arabia. The article produces fairly accurate forecasting for utility-scale solar energy market in Saudi Arabia. Several significant conclusions are presented that could act as reference for solar energy projects. For example, solar PV and parabolic trough are preferred candidates in Saudi energy market due to the lowest levelized cost of electricity. The minimum cost of electricity was found to be 0.06$US/kWh that was generated by solar trough technology in the Solar Village site.

Integration of Optimal Time-of-Use Pricing in Stochastic Programming for Energy and Reserve Management in Smart Micro-grids

Abstract: In this paper, the optimal operation problem of smart micro-grids integrated with the pricing of Time-of-Use (TOU) demand response (DR) program is modeled as a two-stage stochastic programming problem with the aim of minimizing the cost of MG operation and running TOU in the presence of renewable resources and incentive-based DR programs. Here, TOU as the most common type of time-based DR programs is implemented using a linear function based on the concept of self- and cross-price elasticity of load demand. In the presented model, the forecasting errors of generation of renewable resources are modeled by probability density functions. The operator of MG decides on two stages for optimal management of its network; the first stage refers to the operation of base condition of MG and the second one is pertaining to after the realization of different scenarios for generation of renewable resources. The base condition of MG refers to the situation in which the active power productions of renewables are equal to the predicted values. The proposed model is solved by Particle Swarm Optimization algorithm. A typical MG is employed to investigate and analyze the different features of the method. By varying the demand response potential of MG consumers, TOU tariffs are determined, and their impact on the results of energy and reserve cost as well as voltage and load profiles of MG are analyzed. Numerical results show the efficiency of DR in reducing costs as well as covering the uncertainty resulting from renewables.

Hysteretic Dynamics, Space Magnetization and Offset Boosting in a Third-Order Memristive System

Abstract: In the present contribution, we investigate the dynamics of a third-order memristive system with only the origin as equilibrium point previously proposed in Kountchou et al. (Int J Bifurc Chaos 26(6):1650093, 2016). Here, the nonlinear component necessary for generating chaotic oscillations is designed using a memristor with fourth-degree polynomial function. Standard nonlinear analysis techniques are exploited to illustrate different chaos generation mechanisms in the system. One of the major results in this work is the finding of some windows in the parameters’ space in which the system experiences hysteretic dynamics; characterized by the coexistence of two and four different stable states for the same set of system parameters. Basins of attraction of various competing attractors are plotted showing complex basin boundaries. The magnetization of state space justifies jump between coexisting attractors. Furthermore, the model exhibits offset-boosting property with respect to a single variable. To the best of the authors’ knowledge, these interesting and striking behaviors (coexisting bifurcations and offset-boosting property) have not yet been reported in a third-order memristive system with only one equilibrium point in view of previously published systems with self-excited attractors. Some Pspice simulations are carried out to validate the theoretical analyses.

CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm

Abstract: Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power energy to balance energy supply and demand, mitigate climate change and improve energy efficiency of sustainable cities and green buildings. In this paper for the first time, self-regulating particle swarm optimization (SRPSO) algorithm is utilized for solving the CHPED problem by considering valve point effects and prohibited zones on fuel cost function of pure generation units and electrical power losses in transmission systems. The main advantage of SRPSO algorithm to PSO algorithm is the inertia weight flexibility with respect to search conditions. In this algorithm, unlike PSO algorithm that inertia weight reduces in each iteration, this value increases or reduces proportional to particles’ positions, which will lead particles to achieve optimal value with higher speed. The capability and effectiveness of the proposed algorithm are evaluated on a large-scale energy system using MATLAB environment. The results obtained by SRPSO algorithm are outperformed by other optimization methods from the economic, sustainable energy and time consumption point of view.

Economic Dispatch of Renewable Energy and CHP-Based Multi-zone Microgrids Under Limitations of Electrical Network

Abstract: In order to integrate renewable and non-renewable energy resources like combined heat and power (CHP) systems, microgrid seems to be a good idea. This paper has developed an optimization framework for economic dispatch of microgrids including CHP plants, boiler units, conventional power generators, photovoltaic units, wind turbines and battery storage system in a 10-bus test system. The main goal of proposed paper is to optimally dispatch the studied microgrid in the mentioned test system considering impacts of heat buffer tank and battery energy storage. It should be noted that the studied test system is composed of several zones in which microgrid system can be operated in connected/islanded mode. Optimal economic dispatch problem of microgrid is studied within a 24-h time horizon, and the obtained results are analyzed for comparison.

A Planar Integrated UWB/Reconfigurable Antenna with Continuous and Wide Frequency Tuning Range for Interweave Cognitive Radio Applications

Abstract: This paper presents a planar ultra-wide band (UWB) sensing antenna accompanied with a monopole narrow band communicating antenna for interweave cognitive radio (CR) applications. The UWB antenna bandwidth covers the entire band specified for UWB applications (3.1–10.6 GHz). In addition to the varactor diode, a PIN diode is attached to the communicating antenna to expand the continuous frequency tuning of the varactor diode up to 3 GHz along the frequency range (3.3–6.3 GHz) including WiMAX, personal area network, and the 5 GHz wireless local area network. The UWB sensing antenna shape and the ground plane size of the communicating antenna are modified to reduce the mutual coupling between the two antennas to values less than − 15 dB. The measurements are well agreed with the simulation, and they verify the antenna suitability for CR systems. Moreover, the results show an omnidirectional power pattern for both sensing and communicating antennas which is compatible to the portable CR devices.

Assessment of Battery Energy Storage System with Hybrid Renewable Energy Sources to Voltage Control of Islanded Microgrid Considering Demand-Side Management Capability

Abstract: To address the issue of voltage instability in the stand-alone microgrid structure, the paper presents control algorithm of energy storage system that can support the microgrid network at the time of sudden variation in load. The incorporation of battery module into the microgrid network strengthens the overall structure as it features high energy density. A control strategy is devised that establishes power delivery from the battery unit, and it also manages the status of state of charge (SOC) of battery. The delivery of power from battery structure is solely dependent on two variables: first the voltage established by the wind energy, PV and battery unit, i.e. the voltage Vdc. The second variable comprises the status of SOC of battery module. The paper also presents the process of demand-side management, and voltage customization control strategy is adopted to harness the power. The control mechanism of DC–AC microgrid incorporates voltage droop algorithm to retain the power. The demand-side management is the consequence of coordinated control strategy of battery module and stand-alone microgrid network. The microgrid topology and devised control framework of energy storage system are intertwined to establish the desired voltage and make the autonomous structure sturdy and robust in case of voltage perturbation. The standards of IEEE 1547 allow to employ conservative voltage regulation, and the proposed work of demand-side management fulfils the standard. The effectiveness of the devised control strategy is demonstrated through MATLAB simulation, and different cases are included to validate the proposed work.

Low-Loss and Dispersion-Flattened Octagonal Porous Core PCF for Terahertz Transmission Applications

Abstract: In order to make the direct transmission more effective, we have intended an octagonal shape cladding design in this paper. The minimum resultant effective material loss obtained from our proposed photonic crystal fiber is 0.007 cm−1 at 0.5 THz is very effective. The proposed design gives an ultra-high birefringence of 0.06 with an effective area of about 4 × 10−6 m2, a core power fraction of 70% for 290 µm core diameter with a core porosity of 80% at 1.6 THz frequency and closely zero flattened dispersion of variation of 0.3 ± 0.1 ps/THz/cm at a wide frequency range of 0.7–2.1 THz.

Quasi-oppositional Backtracking Search Algorithm to Solve Load Frequency Control Problem of Interconnected Power System

Abstract: This study addresses a powerful optimization technique with the notion of quasi-oppositional-based learning, namely quasi-oppositional backtracking search algorithm (QOBSA), for load frequency control (LFC) of power system. Two widely used power systems have been selected to establish the efficiency of QOBSA. Supplementary controllers in LFC are designed by taking frequency and tie-line power deviations of each area as an input, and QOBSA is applied for simultaneous optimization of the controller gains. Integral error-based performance criterions are formulated to claim the tuning optimality of QOBSA. Comparisons are also made with the existing results to establish the superiority of QOBSA in terms of convergence mobility and time response measurements. The effectiveness and competence of the applied method have been confirmed after penetration of renewable energy resources, and in the presence of power system nonlinearities. The robustness of the developed controller has been appraised with system uncertainty and random perturbation.

Robust Control of Islanded Microgrid Frequency Using Fractional-Order PID

Abstract: In this paper, a robust fractional-order PID (FOPID) controller is proposed to regulate islanded microgrid (MG) frequency. The considered MG is composed of a photovoltaic system, a wind turbine generation, a diesel generator, a battery energy storage system, the control unit, and loads. Some challenges in islanded MGs such as unpredictable variation in output power of renewable energy sources and model uncertainties, affect the system performance and lead to frequency deviations from the nominal value. For designing the proposed robust controller, the wind power and solar radiation are considered as disturbance inputs. Also, uncertainties are assumed in the inertia constant and the load damping coefficient parameters of the system. The FOPID parameters are determined by minimizing some constraints that guarantee robust stability and robust performance of the system. The performance of the proposed FOPID controller is compared with those of the classic PID and H∞ controllers. The effectiveness of the controller is illustrated through appropriate simulations.

Metastability-Induced TRNG Architecture on FPGA

Abstract: Due to the emerging high-speed digital infrastructure, the protection of data being shared throughout the open networks has been a challenging task. By large, the dependency on cryptographic primitives exists to encounter cyberspace challenges. Key generation is a core process of any cryptographic application which improvises the strength of the algorithm. Reconfigurable hardware-assisted true random number generators (TRNGs) play a crucial role in key generation to provide high-speed cryptographic solutions. In this work, metastability-influenced TRNG architecture on Altera Cyclone II EP2C20F484C7 FPGA has been proposed. The 256 units of SR latches with de-synchronisation technique were the prime source used to harvest the true randomness. TRNG design consumed 1851 logic elements with a dynamic power dissipation of 4.41 mW. Proposed architecture achieves a high throughput of 26.64065 Mbps using 27 MHz onboard sampling clock. This TRNG has been validated through entropy, correlation, NIST SP 800-22 batteries of test, linear complexity test, restart experiment and hamming distance analysis.

A Framework for $$H_{2} /H_\infty$$H2/H∞ Synthesis in Damping Power Network Oscillations with STATCOM

Abstract: The escalating in load demand prioritized the incorporation of additional renewable energy generation plants to the existing grid. In parallel, the necessity of reactive power balance and damping characteristics has advised the incorporation of flexible AC transmission system controllers to the existing power network. Hereby, the modern power system has been driven towards the much more composite system which in turn necessitates a healthy controller technique. The objective of this paper is to contribute recommendations to incorporate robust controller technique in the field of the electrical power system. Detailed design considerations for the $$H\infty$$ controller design of a modern power network have been specified, and the same has been demonstrated with mathematical modelling of power network with static synchronous compensator (STATCOM) connected in the middle of the transmission line and in a multi-machine power system. To comment on the suitability of the controller design, a deep stability analysis has been presented and compared with the traditional power system stabilizer, power system stabilizer optimized using particle swarm optimization with time-varying acceleration coefficients algorithm and whale optimization algorithm under adverse system operating conditions. The proposed controller framework has been presented by considering the case studies of single machine infinite bus system, two-machine system model and the benchmark two-area four-generator multi-machine systems connected with STATCOM. The controller performance analysis has been verified by considering eigenvalues analysis, singular value analysis and dynamic response of system states during perturbations for the first two case studies, and system analysis under faulty condition has been investigated for the multi-machine system.

A Novel 5D Chaotic System with Extreme Multi-stability and a Line of Equilibrium and Its Engineering Applications: Circuit Design and FPGA Implementation

Abstract: Extreme multi-stability is a newly introduced property observed in nonlinear dynamical systems. Such systems have very rich dynamical solutions depending on both parameters and initial conditions. On the other hand, designing dynamical systems with special features related to their equilibria is of great interest. In this paper, a novel chaotic system with extreme multi-stability and a line of equilibrium is presented. Such systems are so infrequent. It also should be noted that this designed chaotic system belongs to the category of dynamical systems with hidden attractors. Complete dynamical properties of this new system are investigated. Also, by the assistance of FPGA and electronic circuit implementation, this system is implemented.

Serpentine and Rectilinear Motion Generation in Snake Robot Using Central Pattern Generator with Gait Transition

Abstract: This paper contributes to the fabrication of a snake-like robot in which the motion can be achieved through active wheels. The robot is constructed in such a way that its size can be increased and decreased, as well as it can undulate into a sine wave-like shape. The snake robot with wheels consists of chain of links attached to each other with the help of the passive prismatic and revolute joints. A neural oscillator-based central pattern generator (CPG) algorithm is applied to the robot so that rhythmic serpentine as well as rectilinear motions can be generated in it. In addition, a novel smooth transition mechanics of robot motion, from stationary position to serpentine or rectilinear motion as well as transition between these two gaits, is also suggested in the paper. The working of the formulated CPG motion algorithm is realized through experimental setup equipped with a motion capture system as well as through simulations.

Impact of Solar Panel on the Transformer Performance: A Case Study

Abstract: Transformer is the most important part of any transmission system, so it is necessary to have the transformer in proper working order for uninterrupted power supply in the various locations in around the substations. Renewable energy replaces the conventional energy sources at the fast rate in various parts of the world. Due to high penetration of renewable energy, the installed transformers have observational impact on their insulation, leading to degradation of transformer life. This paper presents a case study of Gujarat solar power plant to find the impact of photovoltaic (PV) penetration on transformer performance in the time span of 1 year. A PV plant has various impacts on performance parameters of transformers. The working of on-load tap changer is also affected by the presence of PV. The main cause behind the altered performance of transformer in the presence of solar panel is its associated inverters that are used to supply linear loads. A higher temperature rise will occur in the windings and cores of the transformer due to voltage and current harmonics, resulting in extra losses. This paper presents the cumulative effect of solar plant on the transformer working during a period of 1 year and finds both negative and positive impact on transformer parameters.