×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerWind Energy Conversion Systems (WECSs) have experienced significant growth in recent years.Among various types of generators employed in WECSs,Permanent Magnet Synchronous Generators (PMSGs) are an attractive choice among the wide variety of wind generators due to several advantages.The growing penetration of PMSG-based WEGSs into the worldwide electrical grid raises the concern that the failure of wind turbine generators may potentially result in the collapse of the system.This prompted several countries to adopt the Low-Voltage Ride-Through (LVRT) for wind farms.LVRT is the capability to maintain the connection between the wind farm and the grid during certain periods of voltage sag.This paper presents an efficient LVRT control strategy for a 12.0MW (6*2MW) grid-connected PMSG-based Wind Farm (PMSG-WF).The proposed strategy aims to enhance the power quality and amount of injected power to achieve the grid code requirements by integrating a Braking Chopper (BC) and a Dynamic Voltage Restorer (DVR) with the conventional structure of PMSG-WF. The detailed mathematical models for a wind turbine, PMSG, power converters, DVR system, and grid model are utilized to analyze the dynamic behavior and operation of PMSG-WF.For DVR, a PI controller is used for voltage sag mitigation to inject reactive power during grid faults, while a hysteresis controller-based BC system is utilized to keep DC-link voltage within its permissible limits.The proposed system is exposed to three scenarios of symmetrical and asymmetrical grid fault conditions (single-phase, two-phase, and three-phase faults) at the point of common coupling to evaluate its dynamic response.MATLAB/SIMULINK environment is used to validate the effectiveness of the proposed strategy during the studied scenarios.The results show the superiority of DVR in improving the voltage stability of PMSG-WF and maintaining the uninterrupted operation of the grid during different grid faults.
Smart Microgrid (MG) effectively contributes to supporting the electrical power systems as a whole and reducing the burden on the utility grid by the use of unconventional energy generation resources, in addition to backup Diesel Generators (DGs) for reliability increasing. In this paper, potential had been done on day-ahead scheduling of diesel generators and reducing the energy cost reached to the consumers side to side with renewable energy resources, where economical energy and cost-effective MG has been used based on optimization agent called Energy Management System (EMS). Improved Particle Swarm Optimization (IPSO) technique has been used as an optimization method to reduce fuel consumption and obtain the lowest energy cost as well as achieving the best performance to the energy system. Three scenarios are adopted to prove the efficiency of the proposed method. The first scenario uses a 24 hour time horizon to investigate the performance of the model, the second scenario uses two DGs and the third scenario depends on a 48-hour time horizon to validating the performance. The superiority of the proposed method is illustrated by comparing it with PSO and simulation results show using the proposed method can reducing the fuel demand and the energy cost by satisfying the user’s preference.
As demand for sustainable energy continues to grow, wind energy especially provided by permanent magnet synchronous generators (PMSG) connected to wind turbines, has become an important research area. This article provides a comprehensive review of various converter topologies used in PMSG-based wind turbines. The transition from asynchronous to synchronous generators reflects the industry’s response to the evolving landscape of energy requirements. The review explores the advantages and disadvantages associated with different power converter topologies. Among these, the ”back-to-back” converter emerges as a common and favored topology due to its superior performance over Doubly Fed Induction Generators (DFIGs). The study delves into the intricate details of these converter topologies, shedding light on their operating intricacies and the impact on overall wind energy conversion efficiency. Furthermore, the analysis demonstrates recent developments and outcomes in power conversion topologies, including resonant converters, matrix converters, and multilevel converters. Tests have shown that the continuously clamped three-phase neutral diode topology (3L NPC-BTB) is superior to the BTB 2L-VSC parallel two-phase converter with DC coupling and multi-level converters. The proposed converter topology improves energy extraction and provides a gainful solution for generator on the side converters of high-power, variable speed PMSG wind turbines. This review provides a comprehensive guide to the power converter topologies of PMSG in wind turbines and contributes to ongoing discussions on advancing wind energy technology. Additionally, this review article is also useful for researchers, engineers, and professionals interested in renewable energy systems.
The paper presents a novel approach that merges the abilities of the biological environment with the concept of hierarchical trees to attack a specific stream cipher. The model being presented introduces a systematic method that targets a group of stream ciphers, such as the GCM family, these devices are composed of components that are suitable for the proposed method. A restricted set of binaries for the final key sequence is required to implement this technique as an input. The attacked algorithm comprises feedback shift registers, memories, delays, and so on. The stream ciphers are widely used in modern encryption to secure communication devices, so any attempt to analyze or attack it is of the utmost importance. The results of this method have been confirmed to lead to the destruction of the cipher’s security. Many novelties and contributions of the present work can be summarized as follows: firstly, the key generator’s components are attacked individually, disrupting the cohesion between them. This was not possible previously except in rare cases and under difficult conditions. Secondly, the method of verifying the correct initial values is unrelated to the generator’s operation. Thirdly, the technique applies biological concepts and processes to laboratory test tubes for genetic engineering, it can be said that the prepared model targets a broad class of stream key generators, rather than a single algorithm. The proposed technique requires a specific and deterministic number of final key sequence bits, which are easy to provide. The proposed technique creates a search E -tree in the style of hierarchical clusters, in which the first level containsE nodes. Then each successive level contains the square of E nodes of the number of nodes in the previous level, and the root is composed of the total solution space of the stream key generator and produces the nodes of each level from the intersection of the cluster contents in the test tubes for all clusters in the level above it. The contribution and novelty of the present work is cryptanalyzing and attacking shift register-based stream key generators involves fragmentation. The attacking principle entails disassembling generator components from registers and individually attacking them. DNA logic clustering aids in this process, as the strength of these generators relies on component cohesion. Because the components are cryptanalyzed individually, the time complexity of the attack is equal to O(C2N) , where N is the length of the largest component, and C is a constant.
This paper presents a novel approach, Equal Incremental fuel cost (λ-Concept) approach, for solving Multi Area Economic Dispatch (MAED) problem. It is a simple approach and developed from the basic observation of incremental fuel cost of an area. The proposed approach has been tested on 4-area system with four generators in each area and a large 2-area system consists of 120 generators. The suggested algorithm has been tested extensively by considering the different tie line power transfer limits and useful recommendations are provided. Further, the impact of tie line power transfer limits on total fuel cost is also discussed. It is found from the test cases that the proposed method is shown to be robust, very fast and extensible to include a large class of problems. The simulation results of the proposed method have been compared with the existing methods.
This paper presents a novel approach, Equal Incremental fuel cost (λ-Concept) approach, for solving Multi Area Economic Dispatch (MAED) problem. It is a simple approach and developed from the basic observation of incremental fuel cost of an area. The proposed approach has been tested on 4-area system with four generators in each area and a large 2-area system consists of 120 generators. The suggested algorithm has been tested extensively by considering the different tie line power transfer limits and useful recommendations are provided. Further, the impact of tie line power transfer limits on total fuel cost is also discussed. It is found from the test cases that the proposed method is shown to be robust, very fast and extensible to include a large class of problems. The simulation results of the proposed method have been compared with the existing methods.
Due to the nonlinear electrical properties of PV generators, the width and performance of these frames could be enhanced by carrying them to operate at ultimate energy mark tracking. In this study, a versatile maximum power point tracking (MPPT) model using a modified Flyback controller with artificial neural network (ANN) technique as our proposed system. The hybrid Flyback/ANN controller is based on teaching and training a neural network, where the dataset is utilized to adjust the levitation converter which is taken care of by a stand-alone photovoltaic generator (PVG) with a Flyback controller. It is assumed that the results will be obtained by the ANN-MPPT system with the Flyback controller which provides low motions and shows a great implementation around the maximum power point compared to the PVG used with traditional MPPT algorithms such as Perturbation and Observation (P & O).
Recently, researchers have focused their efforts to generate electricity on renewable energy sources. Wind power systems are considered good alternative sources of clean energy. Induction generators are the best choice for generating this energy due to their simplicity, robustness, and low maintenance requirements. However, their main drawback is their need for leading reactive power to build the terminal voltage and generate electrical power. This drawback can be overcome using a terminal capacitor across the generator terminals to generate this leading reactive power. This research focuses on: 1-Provides a methodology for selecting an accurate and reliable value of the excitation capacitance required for self-excited induction generators (SEIG), which can be used in pumps operating as turbines (PATs + SEIG). When operating at different speeds and loads. For these systems, the choice of capacitance for the SEIG is of utmost importance. 2- A simplified and understandable method derived from nodal analysis is presented for calculating the exact excitation capacitance of a self-excited induction generator (SEIG) under various conditions. 3-A new analysis and model of (SEIG) is presented. The proposed model consists of an induction generator, a self-excited capacitor, and a RL load. It is used to study the performance of SEIG under different faults and excitation (sudden short circuit, unbalanced excitation, sudden load surge, sudden disconnection of excitation capacitance, and load disturbance). Simulations are created using MATLAB-SIMULINK to validate the proposed model.
The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a second- order two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable.
In electrical power plants, the excitation control system is an important part of controlling the output voltage of the synchronous generators. The purpose of this paper is to utilize various methods of excitation control, such as Proportional-Integral-Derivative (PID), Simulated Annealing (SA), and Neural Network (NN) controllers. Each method is examined in terms of its effectiveness in enhancing system stability, reliability, and adaptability to varying operational conditions. The study simulates and optimizes a 2 MVA/400 V synchronous generator driven by a three-phase diesel engine with mechanical coupling and an exciter system. MATLAB 2021 is used to implement the Simulink model. The dynamic responses of field voltage and field current to load changes were analyzed for each control technique. Additionally, the performance of three-phase voltage and current for synchronous generator were examined over a 10-second timeframe. Our findings indicate that the PID controller offers straightforward implementation and reliable performance under varying conditions. The NN controller implementation is more similar to the PID response, and the SA controller demonstrates superior adaptability. The research underscores the potential of integrating these advanced control techniques in synchronous generators, paving the way for enhanced stability and reliability in modern electric power systems, with further implications for renewable energy integration.
In developing nations, such as Iraq, supplying power to isolated and rural border areas that are not connected to the grid continues to be a problem. At present, fossil fuels, which are significant causes of pollution, supply around 80% of the world’s energy demands. Nonetheless, drastically reducing reliance on fossil fuels has many reasons, including depleting global fossil fuel supplies, increasing costs and growing energy needs. The present study examines the electrical requirements of the Al-Teeb area, a city situated in the eastern region of Iraq, close to the Iranian border. This region has not been researched despite its tourism and oil significance. Despite the unpredictable expansion of many isolated locations in Iraq in recent years, the number of generation stations has not changed. Supplying energy to these places will require considerable time and money. Photovoltaics (PV), wind turbines (WTs), diesel generators (DGs), batteries and converters combined on the basis of their compatibility under three distinct scenarios comprise the system’s components. Considering the lowest net present cost (NPC) and cost of energy (COE) of all the examined scenarios, PV, WTs, batteries and DGs are the most economical solutions for the Al-Teeb area. Number of PV (1,215), number of WTs (59), number of DGs (13), number of batteries (3,138), number of converters (47), COE (0.155 US$/kWh), NPC (14.2 million US$) and initial capital cost (4.91 million US$) are revealed by the results. Finally, the results are confirmed using another global optimization method, namely, modified particle swarm optimization.
In this research we study the elevations of cities and the water resources specially at the dams reservoirs and the distance between them(dams & cities), we use the Google Earth program to determine these elevations and calculate the difference between the average level (elevation) of water at the dam and the average level of cities, which we want to supply it by water, in order to save electrical power by using the energy of supplied water through pipe line from dams to the cities, the pressure of supplied water must be calculated from the difference in elevations(head). The saving of energy can be achieved by two ways. The first is the energy saving by reduce the consumed power in the pumping water from river, which is used for different purposes. The second is the hydroelectric power generated by establishing a micro hydroelectric generator on the pipe line of the water supplied.
Among all control methods for induction motor drives, Direct Torque Control (DTC) seems to be particularly interesting being independent of machine rotor parameters and requiring no speed or position sensors. The DTC scheme is characterized by the absence of PI regulators, coordinate transformations, current regulators and PWM signals generators. In spite of its simplicity, DTC allows a good torque control in steady state and transient operating conditions to be obtained. However, the presence of hysterics controllers for flux and torque could determine torque and current ripple and variable switching frequency operation for the voltage source inverter. This paper is aimed to analyze DTC principles, and the problems related to its implementation, especially the torque ripple and the possible improvements to reduce this torque ripple by using a proposed fuzzy based duty cycle controller. The effectiveness of the duty ratio method was verified by simulation using Matlab/Simulink software package. The results are compared with that of the traditional DTC models.
Some engineering applications requires constant engine speed such as power generators, production lines ..etc. The current paper focuses on adding a new closed loop based on engine torque. Load cells can be used to measure the torque of load applied , the electrical signal is properly handled to manipulate a special fuel actuator to compensate for the reduction in engine speed. The speed loop still acts as the most outer closed loop. This method leads to rapid speed compensation and lead control action.
This review article puts forward the phenomena of chaotic oscillation in electrical power systems. The aim is to present some short summaries written by distinguished researchers in the field of chaotic oscillation in power systems. The reviewed papers are classified according to the phenomena that cause the chaotic oscillations in electrical power systems. Modern electrical power systems are evolving day by day from small networks toward large-scale grids. Electrical power systems are constituted of multiple inter-linked together elements, such as synchronous generators, transformers, transmission lines, linear and nonlinear loads, and many other devices. Most of these components are inherently nonlinear in nature rendering the whole electrical power system as a complex nonlinear network. Nonlinear systems can evolve very complex dynamics such as static and dynamic bifurcations and may also behave chaotically. Chaos in electrical power systems is very unwanted as it can drive system bus voltage to instability and can lead to voltage collapse and ultimately cause a general blackout.
This paper presents a novel linear variable structure secondary controller for islanded Microgrid driven by voltage source inverters. The main control stretchy depends on a low pass filter based frequency restoration. The proposed control strategy solves the problem of trade of between accurate frequency restoration and active power sharing accuracy by using variable structure controller. A bank of low pass filters with different parameter values are used instead of single fixed parameter controller. An efficient algorithm is designed to switch between the compensators in the bank to achieve the two objectives, namely accurate frequency restoration and fast power sharing. The switching algorithm uses event driven protocol to trigger its activation until reaching steady state and then staying stand by for the next event where the event is active power change. Simulation results shows an excellent result.
Nonlinear stream ciphers have become a viable alternative to traditional cryptosystems in response to the growing need for secure communication. These ciphers generate a keystream via feedback mechanisms and nonlinear functions, which are then utilized for encryption. Geffe generator system is one of the most keystream generators. Also, these systems have many benefits, like being fast, flexible, and able to create unpredictable and non-repeating keystreams, these systems are susceptible to cryptanalysis attacks, which have the potential to compromise their security. This paper presents the first study of applying chicken swarm optimization (CSO) algorithm in the field of cryptanalysis based on cipher only attack. The standard CSO algorithm and an adaptive multi points CSO (AMPCSO) algorithm are proposed to cryptanalysis nonlinear stream cipher based on Geffe keystream generator. Firstly, the traditional CSO is used to reveal the secret initial values of the Geffe generator. Secondly, an adaptive multi points chicken swarm optimization (AMPCSO) has been proposed to enhance the traditional CSO algorithm to attack Geffe generator systems. The AMPCSO is a new idea to advance the CSO search abilities and improve the foraging behavior of hens and chicks by allowing hens to be influenced by other individuals within the same or different groups and affected by the best individual in the population and enable chicks to learn from four reference points rather than learn from their respective mothers only. Lastly, a new criterion is used to estimate the value of fitness by utilizing a multi-objective fitness function (MOFF), which is grounded on Pareto dominance. The experimental results showed that the CSO and AMPCSO are very effective tools in terms of accuracy, information required, and CPU times when applied to the analysis of nonlinear stream cipher. The AMPCSO required a few characters from ciphertext to attack systems with total LFSRs length up to 59 bits with an appropriate CPU time.