جستجوی مقالات مرتبط با کلیدواژه « پایداری » در نشریات گروه « برق »

The system under study in this paper is an AC microgrid, consisting of parallel inverters and feeding an independent load. This paper includes two main parts. In the first part, the control method based on the conventional droop control method is modified to achieve accurate reactive power sharing between parallel inverters even under unequal transmission lines impedances. Then, in the second part, according to the widely use of active loads in existing microgrids, the response of the AC microgrid in presence of active loads is investigated, and effects of the factors such as the bandwidth of the DC bus voltage control loop of the active load and amount of the active load power on the system stability are studied. Next, the stability of the whole system is improved by modifying the control loops of parallel inverters on the source-side. At the end, simulation results are given in the Matlab-Simulink enviroment to evaluate the AC microgrid responses.

In this paper, the problem of improving the stability of the power system with DFIG and in the presence of SSSC using nonlinear method is discussed. The nonlinear controller is designed by the multi-input backstepping method with a sliding mode observer. This controller is applied simultaneously to the excitation system of synchronous generators and the rotor side converter in DFIG and SSSC in a way that improves the stability of the power system compared to the linear and nonlinear methods described in this paper. The control coefficient matrices are adjusted using intelligent algorithms in such a way that the stability of the system is more optimized. Practical constraints on the system are considered in selecting the control inputs. The designed controller is robust to changes in the operating point and the location of the disturbance. The performance of the designed controller in a 39-bus, 10 machines NEW ENGLAND network including DFIG generators and in the presence of SSSC is simulated and investigated using MATLAB software.

Data clustering is one of the main tasks of data mining, which is responsible for exploring hidden patterns in unlabeled data. Due to the complexity of the problem and the weakness of the basic clustering methods, today most of the studies are directed towards clustering ensemble methods. Although for most datasets, there are individual clustering algorithms that provide acceptable results, but the ability of a single clustering algorithm is limited. In fact, the main purpose of clustering ensemble is to search for better and more stable results, using the combination of information and results obtained from several initial clustering. In this paper, a clustering ensemble-based method will be proposed, which, like most evidence accumulation methods, has two steps: 1- building a simultaneous participation matrix and 2- determining the final output from the proposed participation matrix. In the proposed method, some other information will be used in addition to the clustering of the samples to construct the simultaneous participation matrix. This information can be related to the degree of similarity of the samples, the size of the initial clusters, the degree of stability of the initial clusters, etc. In this paper, the clustering problem is defined as an explicit optimization problem by the mixed Gaussian model and is solved using the simulated annealing algorithm. Also, an evolutionary method based on simulated annealing will be presented to determine the final output from the proposed simultaneous participation matrix. The most important part of the evolutionary method is to determine the objective function that guarantees the final output will be of high quality. The experimental results show that the proposed method is better than other similar methods in terms of different clustering quality evaluation criteria.

Wind power generation is making an increasingly significant contribution to global electricity production. The high penetration of wind power poses many operational and control challenges that affects the reliability and stability of power systems. In this Paper, the reported technical challenges caused by the grid integration of wind energy conversion system (WECS) and the proposed solutions methodologies represents. The wind-generating system components and architecture are investigated at the beginning of this article for analysis and stability studies purposes, then are addressed various technical challenges; each challenge is discussed individually, focusing on the bulk integration of wind energy into the power systems. Some solutions, including grids code, energy storage technologies, appropriate control strategies, and other methodologies employed to mitigate the effects of the integration, are also included. This review is ready-reckoner of essential topics for further research of wind energy and available technologies in this field. This review provides ready-reckoner of essential topics for grid integration of wind energy and available technologies in direction of overcome the related difficulties.

The microgrid inertia as a result of tiny structure and barely tolerance variations, is fairly low. Thus, the maintenance of voltage stability and frequency specifically in islanded mode is extremely demanding. Even if these products have efficient control system, they can’t retain microgrid stability due to the low speed of response in primary sources of energy and communication delays of the links between outer unit and control system in distributed generation. Introducing a structure of fuzzy control arranged with neural network to balance between generation part and consumption part in micro grid is the main purpose of this paper. Using the fuzzy logic, this controller enables flexible operation of microgrids in both network and islanded modes. In the proposed control system, a trainable neural network in different operating conditions is responsible for fine tuning of the fuzzy logic system. Because of the sensitivity of the loads in the microgrid the proposed structure is designed to interact with the storage source in order to increase the response speed to the imbalance between production and consumption. This might prevent excessive voltage and frequency deviation, especially in the severe situations. With this controller, fluctuations in the production of renewable resources quickly compensated without a negative impact on resilience and instability of the microgrid, especially while disconnecting from the main network

Conventional droop-based techniques have widely been used in controlling Voltage Source Inverter (VSI) based on distributed generation units within a Micro-Grid (MG). Despite the simplicity and high reliability of the controller, the low-inertia nature of VSIs threatens the system stability against probable disturbances. Thus, from the stability viewpoint, it is essential to carefully monitor the system operating point to determine the stable region of the parameters affecting the micro-grid stability. To this end, a complete dynamic model for an inverter-based micro-grid has been derived. According to this model, states affecting the dominant eigenvalues of the system are identified using eigenvalues analysis and modal analysis. Then, bifurcation theory is used to predict the parameter stability margin and identify the type of bifurcation. In this paper, by introducing a bifurcation index, the appropriate virtual impedance X/R ratio is selected from the viewpoint of both small-signal analysis and bifurcation analysis. Finally, a multi-objective optimization framework is presented to prevent such a problem in parallel to other operational goals.

There are two main challenges in control of hybrid systems which are to guarantee the closed-loop stability and reduce computational complexity. In this paper, we propose the exponential stability conditions of hybrid systems which are described in the Mixed Logical Dynamical (MLD) form in closed-loop with Model Predictive Control (MPC). To do this, it is proposed to use the decreasing condition of infinity norm based Lyapunov function instead of imposing the terminal equality constraint in the MPC formulation of MLD system. The exponential stability conditions have a better performance from both implementation and computational points of view. In addition, the exponential stability conditions of the equilibrium point of the MLD system do not depend on the prediction horizon of MPC problem which is the main advantage of the proposed method. On the other hand, by using the decreasing condition of the Lyapunov function in the MPC setup, the suboptimal version of the control signal with reduced complexity is obtained. In order to show the capabilities of the proposed method, the stabilization problem of the car suspension system is studied.

Sustainable diets are important because of their less environmental impact, as well as having the micro-nutrients needed for healthy living in the present and future generations. Athletes always need special food programs to maintain their level of activity. Therefore, in this research, a mathematical model with three objective functions for the athlete's diet plan, consumed to taking into account the principles of sustainability, includes the objectives of 1- minimizing the cost of purchasing food, the cost of water consumption and the cost of producing carbon dioxide for food, 2- Maximizing the amount of protein intake and 3- Minimizing the amount of sugar and fat. For model validation, real information about nutrients and supplements required by the athletes' body has been used. The model was formulated in The GAMS computational software and solved by Cplex solver. The outputs of the model represent the performance of the model in the actual example.

In this paper, a new method for designing autopilot for an air vehicle with polynomial nonlinear model is presented. Moreover the method is developed to fault tolerant control autopilot using combined projection and redesign methods. The nominal autopilot has been designed based on regulator controller for the polynomial nonlinear model and sum of square optimization theory. Previous theoretical methods have been extended from the regulator type to the tracking. Stability of the closed loop system is guaranteed by introducing a polynomial Lyapunov function that is derived using sum of squares optimization method. Then, the feasibility problem has been changed to the optimization problem. The proposed method has been used on an air vehicle supersonic with nonlinear polynomial model. The results showed proper operation in normal and faulty situations.

In this paper, modeling, analyzing and controlling nonlinear systems using Polytopic linear models is considered. First, the output tracking problem is investigated for the state of the system as compared to the affine input, and then the problem is solved for the non-affine state. In the state of determining the parameters of each region to increase the problem solving speed we determine the weighted function in a specific manner that prevents interference between the regions and by solving an linear inequality matrix of controller design , in contrast to the past, it is not necessary to solve a bilinear matrix inequality and only by solving a linear one, the controller will be designed. To stability and design of the controller, a method is used to ensure both the stability of the approximate model (polytopic) and the stability of the main model (nonlinear). Finally, the results are taken and the methods proposed are used to  design of an elastic missile  system.

To improve the stability of the power system, the design of a PSS and STATCOM controller parameters using ABC is presented as an optimization problem in this paper. The ABC is a collective intelligence based on the optimization algorithm and inspired by the bee feeding behavior in finding food. Fast convergence and high accuracy are the capabilities of this algorithm. The effectiveness and robustness of the bee colony algorithm are shown by nonlinear simulation of a two-area power system consisting of four machines and compared with the particle swarm optimization method. Simultaneous design of power system controller and stabilizer parameters with bee cloning algorithm over non-optimized mode increases oscillation damping speed and improves power system stability. The simulation results are presented using MATLAB software for different system conditions.

In this paper, an algorithm is proposed to improve the design of constrained PID controller based on convex-concave optimization. This design method is based on the optimization of a performance cost function, taking into account the stability and efficiency constraints with frequency domain analysis in which the concepts of sensitivity and complementary sensitivity has been used. It is shown, using a counter example that the previous methods are not effective for some systems, the optimization problem becomes unbounded and interrupts. To solve this problem, attentions are paid to conditions that the optimization problem fails to have any response, and then previous limitations are eliminated by representing a new designing method. The performance of the proposed method is shown by applying it to the counter example. In the end, the controller is designed for an unstable system.

Increasing penetration level of modern generating units, in response to growing need for electrical energy and environmental issues, besides changing inherent of distribution systems and loads introduces new uncertainties into the power systems. In order to deal with such uncertainties, measurement-based control schemes are introduced in modern power systems. An attempt is made in this paper to propose a new measurement-based approach for tuning of excitation system parameters in large-scale power systems. For this purpose, Center of Gravity (COG) concept in corporation with fault propagation paradigm are introduced to reduce power system dimensions. In this framework, the power system dynamic behavior is represented by an equivalent model in which the geographical areas interact with the COG through unique fictitious interconnectors. Then, a new control scheme proposes in which utilizes post-fault system dynamics in the rotor angle-terminal voltage deviations portrait to design a coordinated Automatic Voltage Regulator (AVR)-Power System Stabilizer (PSS). Basic power system equations are employed to derive a case-independent algorithm. Effectiveness of the proposed method is examined for different fault scenarios on the 16 machines IEEE benchmark system.

Induction motors with nonlinear dynamics are superior in terms of size, weight, motor inertia, maximum speed, efficiency, and cost than direct current machines, and hence their control is of great important. The main objective of this paper is to design a fuzzy sliding mode controller in order to control the position of the induction motor including parametric and non-parametric uncertainties by considering the stability issue. In fact, in this method, in order to increase the performance of the control system and to improve the tracking performance, a moving sliding surface is considered, in which it is adapted in accordance with the variations of the sliding surface. As a result, during the reaching phase, the system is not sensitive to parameter variations and external disturbances. Simulation results show that the proposed control method has good performance in the face of parametric and non-parametric uncertainties.

AAbstract: Transfer function of the InGaAs/GaAs SAQD laser is calculated using its rate equations. Using the calculated transfer function, time and frequency analysis can be implemented completely. In the time domain, the calculated transfer function can show the transient and steady state response of the laser. Also this transfer function can be used in circuit simulator such as SPICE in order for analyzing the electro-optical VLSI circuits. After the calculation of the transfer function, time domain together with Nyquist responses has been calculated. The effect of carrier dynamics on the output response of the laser is analyzed in this case. Nyquist diagram is selected in this analysis because one can predict the closed loop system using the open loop system. Unlike the systems such as interconnects and transistors that are analyzed before, the results reveal that in SAQDLs, the ratio of the transient peak overshoot in the output power to stable output power is very large. Accordingly in integrated circuits that use SAQDLs, amplification of each overshoots in output power of the laser can deteriorate the input of the next circuit module on the chip or shock to it. This increases the importance of the stability analysis in SAQDLs for more reliability.

One of main problems of power systems with doubly fed induction generators (DFIG)-based wind farms is their capability of fault ride through (FRT) and output power fluctuations. If these generators provide considerable amounts of power, their outage can lead to system instability. According to the new needs of network codes, wind farms should remain in the network when a fault causes the voltage drop across the generator terminals. To solve this problem, the superconducting fault current limiter (SFCL) is used for limiting the fault current and superconducting magnetic energy storage (SMES) is used for injecting/withdrawing power to reduce power fluctuations. This article carries out the coordinated control of DFIG, SFCL, and SMES by employing the HBB-BC optimization algorithm. Its objective functions include minimization of the required storage core capacity, energy reduction, improvement of generators bus voltage, fault current limiting, reducing power fluctuations, and the generators angular velocity. Simulation results show the ability of this optimal controller in achieving the above indicated objectives.

The capabilities of air defense systems require that they always operate under an integrated, robust, and "survival" command and control network. Survivability is one of the most important features of air defense systems, especially command and control systems. Survivability expresses the durability, endurance, and survival of the system on the battlefield. Survivability is affected by three factors: susceptibility, vulnerability and recoverability. In this research, the survivability of the air defense command and control network has been studied and a solution has been proposed to promote it. The research is applied and developmental and its method is descriptive with mixed approach. To collect data, library studies and field studies have been used by using a questionnaire. The statistical population of this study was 120 people, sample size 92 and purposeful sampling has been used. Cronbach's alpha coefficient was used to measure the reliability of the questionnaire. For data analysis, linear regression test was used by SPSS software. Fischer and T-Student tests have been used to assess the accuracy of the coefficients of the line equation. The results of the research shows that, although decentralization approach in command and control and implementation is used as a common method in most air defense command and control networks, nonetheless this approach challenges the survivability of air defense command and control networks despite advanced air threats. Instead decentralization in command and control and implementation is the only approach that can reduce the susceptibility and vulnerability and improve the recoverability of air defense command and control networks and ensure the durability and survivability of other air defense systems.

Nowadays with the advancement of technology, the requirement for high speed circuits and memories with low leakage power consumption by keeping stability has been increased. In this paper, a stable 9T SRAM cell which is improved for high speed applications with low leakage power consumption has been suggested. In this scheme, two techniques including the isolation of read and write paths and the “stack effect” technique are used simultaneously to improve read and write performance. The results of simulations in 32 nm CMOS technology indicate that the proposed cell is in the category of high speed cells. Meanwhile, the leakage power of the proposed cell has been reduced 16% to 48% compared with high speed cells. It should be noted that the read stability of the proposed cell has nearly become two times greater than the conventional 6T SRAM cell.

As to the importance of power system performance in terms of quality, and stability, through flexible AC transmission system (FACTS) devices in power networks and coordinating these devices through power system stabilizers (PSSs) has gained a great acceptance. Accordingly, the problem of coordinated design of PSS and static var compensator (SVC) parameters in multi-machine power systems is introduced and solved through the improved quantum method. In previous studies PSS is designed for damping small-signal oscillations of the power system. To damp large-signal oscillations, PSS should be designed in accordance with other devices like SVC. Therefore to reach overall stability of power system, the Quantum-inspired Evolutionary Algorithm is applied here to determine PSS parameters and SVC in a coordinated manner. This proposed method is applied in determining PSS parameters and SVC of Kundur’s four-machine power systems and the New England 39-bus system. Simulation results reveal the effective performance of this proposed method in comparison with Particle Swarm Optimization (PSO) and Bacteria Foraging Optimization (BFO) methods.