共查询到20条相似文献，搜索用时 15 毫秒
1.
Yogendra Arya 《Journal of The Franklin Institute》2018,355(11):4583-4617
The incessant swell in size, complexity, nonlinearity and structural variations in modern electric power systems, as well as rise in power demand has entailed the use of intelligent control strategies for the real-time satisfactory operation of power system. Hence, in this paper, a novel fuzzy PID with filter plus double integral (FPIDF-II) controller is proposed for automatic generation control (AGC) of two-area interconnected power systems. Initially, a well accepted two-area non-reheat thermal system is considered and the output scaling factors (SF) of FPIDF-II controller are optimized using imperialist competitive algorithm (ICA) employing an integral squared error (ISE) criterion. The supremacy of the proposed approach is demonstrated by contrasting the results with recently published optimal and various modern heuristic optimization techniques based controllers. To demonstrate the efficacy and scalability of the approach over other prevalent intelligent control techniques, the study is further extended to two-area non-reheat thermal system with governor deadband nonlinearity, two-area reheat thermal system, recently appeared two-area photovoltaic (PV)-reheat thermal system and two-area multi-source hydrothermal system. Finally, a sensitivity analysis is carried out to demonstrate the robustness of the proposed controller under broad variations in the system parameters from their nominal values. 相似文献
2.
Raghuraman Sivalingam Subramani Chinnamuthu Subhransu Sekhar Dash 《Journal of The Franklin Institute》2017,354(12):4762-4783
This paper proposes to use a hybrid Stochastic Fractal Search (SFS) and Local Unimodal Sampling (LUS) based multistage Proportional Integral Derivative (PID) controller consisting of Proportional Derivative controller with derivative Filter (PDF) plus (1 + Proportional Integral) for Automatic Generation Control (AGC) of power systems. Initially, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral (I) controller is optimized by Stochastic Fractal Search (SFS) algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO) is demonstrated. To improve the system performance further, LUS is subsequently employed. The study is further extended for different controllers like PID, and proposed multistage PID controller and the superiority of multistage PID controller over conventional PID controller structure is demonstrated. The study is further extended to a two-area six unit multi-source interconnected power system and the superiority of proposed approach over, TLBO and optimal control is demonstrated. Finally the study is extended to a three unequal area system power system with appropriate nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB) and time delay. From the analysis, it is found that hybrid SFS–LUS algorithm is superior to the original SFS algorithm and substantial improvement in system performance are realized with proposed multistage PID controller over conventional PID controller structure. 相似文献
3.
《Journal of The Franklin Institute》2019,356(11):5611-5629
In the rapidly expanding size and complexity of the electricity network, automatic generation control (AGC) is contemplated to be the most remarkable option for offering good quality electric power supply to the end users. An AGC system entails highly vigorous, competent and intelligent control technique to deliver a healthy power under stochastic nature of consumers’ power demand. Hence, in this paper, a hybrid fuzzy fractional order proportional integral-fractional order proportional derivative (FFOPI-FOPD) controller is proposed as a new expert control technique to tackle AGC profitably in isolated and interconnected multi-area power systems. A recently developed imperialist competitive algorithm (ICA) is utilized for the optimization of the output gains (KP/KP1/KI/KD) and other parameters such as order of integrator (λ) and differentiator (μ) of FFOPI-FOPD controller exercising integral of squared error criterion. The proposed technique is firstly implemented on 1-area thermal system, then to express its potential and extensibility, the work is extended to 2-area hydro-thermal and 3-area thermal power systems widespread in the literature. The eminence of the method is betokened by comparing the results with the various newly published control methodologies and FPI/FFOPI controller designed in the study via ICA in terms of minimum values of various error criteria and undershoots/overshoots/settling times of frequency and tie-line power deviations following a sudden load demand in an area. The sensitivity analysis substantiates that the suggested controller is robust and performs staunchly under the wide variations in the system parameters, random load pattern and in the company of physical constraints to produce more clean electricity. 相似文献
4.
Omar Shaheen Ahmad M. El-Nagar Mohammad El-Bardini Nabila M. El-Rabaie 《Journal of The Franklin Institute》2018,355(3):1088-1106
This paper proposes a probabilistic fuzzy proportional - integral (PFPI) controller for controlling uncertain nonlinear systems. Firstly, the probabilistic fuzzy logic system (PFLS) improves the capability of the ordinary fuzzy logic system (FLS) to overcome various uncertainties in the controlled dynamical systems by integrating the probability method into the fuzzy logic system. Moreover, the input/output relationship for the proposed PFPI controller is derived. The resulting structure is equivalent to nonlinear PI controller and the equivalent gains for the proposed PFPI controller are a nonlinear function of input variables. These gains are changed as the input variables changed. The sufficient conditions for the proposed PFPI controller, which achieve the bounded-input bounded-output (BIBO) stability are obtained based on the small gain theorem. Finally, the obtained results indicate that the PFPI controller is able to reduce the effect of the system uncertainties compared with the fuzzy PI (FPI) controller. 相似文献
5.
This article presents a novel tuning design of Proportional-Integral-Derivative (PID) controller in the Automatic Voltage Regulator (AVR) system by using Cuckoo Search (CS) algorithm with a new time domain performance criterion. This performance criterion was chosen to minimize the maximum overshoot, rise time, settling time and steady state error of the terminal voltage. In order to compare CS with other evolutionary algorithms, the proposed objective function was used in Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms for PID design of the AVR system. The performance of the proposed CS based PID controller was compared to the PID controllers tuned by the different evolutionary algorithms using various objective functions proposed in the literature. Dynamic response and a frequency response of the proposed CS based PID controller were examined in detail. Moreover, the disturbance rejection and robustness performance of the tuned controller against parametric uncertainties were obtained, separately. Energy consumptions of the proposed PID controller and the PID controllers tuned by the PSO and ABC algorithms were analyzed thoroughly. Extensive simulation results demonstrate that the CS based PID controller has better control performance in comparison with other PID controllers tuned by the PSO and ABC algorithms. Furthermore, the proposed objective function remarkably improves the PID tuning optimization technique. 相似文献
6.
This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of ?50% to +50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population based optimization algorithms. 相似文献
7.
Since Proportional?+?Integral?+?Derivative (PID) controller is still the workhorse in taking over the workload of process control systems, this article introduces a new design methodology toward improving the performance of such controller. After a PI control law with windup protection is given, it is combined with a derivative path employing a first-order low pass filter in an innovative way to develop a performant controller called PI?+?DF controller. In attempting to attain a high level of control performance, gains of this controller including proportional, integral, derivative and filter gains are tuned choosing the recently introduced Stochastic Fractal Search (SFS) algorithm owing to its superiority to many state-of-the-art algorithms considering convergence, accuracy and robustness. To evaluate the efficacy of SFS, Particle Swarm Optimization (PSO) is also applied to the case study. Furthermore, the presented SFS optimized PI?+?DF controller is compared to a recently reported control scheme through simulation and experimental tests on an identical DC servo system. After providing the stability proof, SFS tuned PI?+?DF controller is found to be the pioneer in exhibiting the most accurate speed response profile under complicated scenarios, which is followed by PSO tuned PI?+?DF controller and the existing control approach, respectively. 相似文献
8.
The optimal location of a static synchronous compensator (STATCOM) and its coordinated design with power system stabilizers (PSSs) for power system stability improvement are presented in this paper. First, the location of STATCOM to improve transient stability is formulated as an optimization problem and particle swarm optimization (PSO) is employed to search for its optimal location. Then, coordinated design problem of STATCOM-based controller with multiple PSS is formulated as an optimization problem and optimal controller parameters are obtained using PSO. A two-area test system is used to show the effectiveness of the proposed approach for determining the optimal location and controller parameters for power system stability improvement. The nonlinear simulation results show that optimally located STATCOM improves the transient stability and coordinated design of STATCOM-based controller and PSSs improve greatly the system damping. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed PSO-optimized controllers. 相似文献
9.
Amir-R. Khorsand 《Journal of The Franklin Institute》2007,344(5):595-612
Evolutionary structural design has been the topic of much recent research; however, such designs are usually hampered by the time-consuming stage of prototype evaluations using standard finite element analysis (FEA). Replacing the time-consuming FEA by neural network approximations may be a computationally efficient alternative, but the error in such approximation may misguide the optimization procedure. In this paper, a multi-objective meta-level (MOML) soft computing-based evolutionary scheme is proposed that aims to strike a balance between accuracy vs. computational efficiency and exploration vs. exploitation. The neural network (NN) is used here as a pre-filter when fitness is estimated to be of lesser significance while the standard FEA is used for solutions that may be optimal in their current population. Furthermore, a fuzzy controller updates parameters of the genetic algorithm (GA) in order to balance exploitation vs. exploration in the search process, and the multi-objective GA optimizes parameters of the membership functions in the fuzzy controller. The algorithm is first optimized on two benchmark problems, i.e. a 2-D Truss frame and an airplane wing. General applicability of the resulting optimization algorithm is then tested on two other benchmark problems, i.e. a 3-layer composite beam and a piezoelectric bimorph beam. Performance of the proposed algorithm is compared with several other competing algorithms, i.e. a fuzzy-GA-NN, a GA-NN, as well as a simple GA that only uses only FEA, in terms of both computational efficiency and accuracy. Statistical analysis indicates the superiority as well as robustness of the above approach as compared with the other optimization algorithms. Specifically, the proposed approach finds better structural designs more consistently while being computationally more efficient. 相似文献
10.
针对PID控制器在不同的应用系统,需要动态调整PID控制参数的问题,提出了基于遗传算法的PID自适应参数优化方案。该方案通过将PID控制器产生的误差作为目标函数,利用遗传算法实现对PID控制器参数的自动调整。为了提高参数的优化效率,文章通过对交叉算子和变异算子的自适应处理,提高了PID控制器的性能。实验测试表明,文章设计的PID参数优化策略比普通的基于遗传算法优化策略效率平均高14.7%。 相似文献
11.
《Journal of The Franklin Institute》2023,360(14):10536-10563
A new framework of optimal fractional order proportional-derivative-integral (FOPID) controller series with fuzzy proportional-derivative (PD) controller, namely OFPD-FOPID controller, is proposed in this study for seismic control of structures equipped with active tuned mass damper (ATMD). Three controllers including optimal PID, optimal FOPID, and fuzzy PID (FPID) controllers are also implemented for comparison purposes. Simulation results carried out on a 15-story building show the FOPID controller than the PID and FPID controllers can remarkably reduce the maximum floor displacement, but they represent a poor performance in mitigation of the maximum floor acceleration in different soil conditions, while the proposed OFPD-FOPID controller tracking the amount of the maximum floor acceleration to estimate the optimal control force of the actuator can provide superior performance. An average reduction of 41%, 45%, and 33% in the maximum floor displacement; 36%, 33%, and 20% in the maximum inter-story drift are given by FOPID in the dense, medium, and soft soils, while it results in an increase of 45%, 52% and 24% in the maximum floor acceleration. Similarly, the proposed OFPD-FOPID controller represents an average reduction of 52%, 55%, and 45% in the maximum floor displacement; 42%, 44%, and 28% in the maximum inter-story drift in the dense, medium, and soft soils, while it also slightly reduces the maximum floor acceleration of the studied structure located on different soil conditions. 相似文献
12.
This paper proposes a novel application of Nonlinear Proportional-Integral-Derivative (NPID) controller to effectively attain Maximum Power Point Tracking (MPPT) in Photovoltaic (PV) systems. The proposed controller is based on the basic structure of the PID controller wherein, its integral term gain is varied at run time according to instantaneous error. The performance of the NPID controller is assessed in terms of undershoot, settling time and ripple which have been evaluated under varying realistic irradiation and temperature profiles. The Teaching Learning Based Optimization (TLBO) tuned NPID controller is found to be superior to TLBO tuned PID, Perturb and Observe and Incremental Conductance classical MPPT methods for all the considered environmental profiles. Therefore, based on the presented comprehensive investigations, it is concluded that the proposed NPID controller is a promising MPPT technique. 相似文献
13.
通过对广义预测控制性能指标函数中控制加权序列Qj（z-1）的配置给定,导出了具有PID算法结构的广义预测控制律,借助广义预测控制算法参数的递推关系链,自动优化整定PID调节参数,并在冶金实验炉温控制中实现了广义预测PID控制。 相似文献
14.
《Journal of The Franklin Institute》2021,358(15):7394-7412
Today, the quality of accessible power and the response of the system involved are most significant. Many controllers have been used by researchers dealing with issues pertaining to power. Controllers play a significant role in the renewable energy sector in terms of improving the quality of power and offering a speedy system response. This research analyzes the speed of response and harmonics and enhances system performance overall. The existing system consists of a photovoltaic panel, boost converter, multi-level inverter, classic proportional-integral (PI) controller, and three-phase induction motor. The proposed system comprises a photovoltaic-based multi-level inverter, fuzzy logic controller, buck-boost converter, and three-phase induction motor. The output of the photovoltaic panel is connected to a buck-boost converter, and that of the converter to an inverter, while the output of the seven-level multi-level inverter is connected to a three-phase induction motor. Motor speed is controlled by a fuzzy logic controller (FLC). The output of the proportional-integral (PI) controller is compared to that of the fuzzy logic controller. The behavior and performance of the existing system are verified with experimental setup and proposed system are verified by MATLAB and Simulink, and the results recorded. 相似文献
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16.
Sidhartha Panda 《Journal of The Franklin Institute》2011,348(8):1903-1926
Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite-bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. Simulation results are presented and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach. The performances of the proposed controllers are also evaluated under N−2 contingency situation. 相似文献
17.
Min-Rong Chen Guo-Qiang Zeng Xiao-Qing Xie 《Journal of The Franklin Institute》2018,355(17):8266-8295
How to design a set of optimal distributed load frequency controllers for a multi-area interconnected power system is an important but still challenging issue in the field of modern electric power systems. This paper presents an adaptive population extremal optimization-based extended distributed model predictive load frequency control method called PEO-EDMPC for a multi-area interconnected power system. The key idea behind the proposed method is formulating the dynamic load frequency control issue of each area power system as an extended distributed discrete-time state-space model based on an extended state vector, obtaining a distributed dynamic extended predictive model, and rolling optimization of real-time control output signal by adopting an adaptive population extremal optimization algorithm, where the fitness is evaluated by the weighted sum of square predicted errors and square future control values. The superiority of the proposed PEO-EDMPC method to a traditional distributed model predictive control method, a population extremal optimization-based distributed proportional-integral control algorithm and a traditional distributed integral control method is demonstrated by the simulation studies on two-area and three-area interconnected power systems in cases of normal, perturbed system parameters and dynamical load disturbances. 相似文献
18.
电网故障诊断的基本思想是根据保护动作原理将故障诊断问题表示为0-1规划问题。为了保证电网故障诊断的准确性和实时性,提出了一种改进的人工鱼群算法——二进制人工鱼群算法。分析了人工鱼群群聚行为和追尾行为最优方向的前进速度。并在此基础上与遗传算法、粒子群算法和量子免疫算法作了对比分析。结果表明:追尾行为最优方向的前进速度优于群聚行为,二进制人工鱼群算法综合性能优于遗传算法、粒子群算法和量子免疫算法。研究表明二进制人工鱼群算法具有收敛速度快、种群规模小和搜索能力强的特点。 相似文献
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The problem of designing optimal process-specific rules for non-parametric tuning is undertaken in the paper. It is shown that producing non-parametric process-specific optimal tuning rules for PID controllers leads to the problem that can be characterized as optimization under uncertainty. This happens due to the fact that tuning rules, unlike tuning constants, are produced not for a particular process or plant model but for a set of models from a certain domain. The novelty of the proposed approach is that the problem of obtaining optimal tuning rules for a flow process is formulated and solved as a problem of optimization of an integral performance criterion parametrized through values that define the domain of available process models. The considered non-parametric tuning assumes the use of the modified relay feedback test (MRFT) recently proposed in the literature. It allows one to tune the PID controller satisfying the requirements to gain or phase margins that is achieved through coordinated selection of tuning rules and test parameters. This approach constitutes a holistic approach to tuning. In the present paper, optimal tuning rules coupled with MRFT, for flow loops, are proposed. Final results are presented in the form of tables containing coefficients of optimal tuning rules for the PI controller, obtained for a number of specified gain margins. The produced non-parametric tuning rules well agree with the practice of loop tuning. 相似文献