A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems

In this paper, a novel hybrid Firefly Algorithm and Pattern Search (hFA–PS) technique is proposed for Automatic Generation Control (AGC) of multi-area power systems with the consideration of Generation Rate Constraint (GRC). Initially a two area non-reheat thermal system with Proportional Integral Derivative (PID) controller is considered and the parameters of PID controllers are optimized by Firefly Algorithm (FA) employing an Integral Time multiply Absolute Error (ITAE) objective function. Pattern Search (PS) is then employed to fine tune the best solution provided by FA. The superiority of the proposed hFA–PS based PID controller has been demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and conventional Ziegler Nichols (ZN) based PI/PID controllers for the same interconnected power system. Furthermore, sensitivity analysis is performed to show the robustness of the optimized controller parameters by varying the system parameters and operating load conditions from their nominal values. Finally, the proposed approach is extended to multi area multi source hydro thermal power system with/without considering the effect of physical constraints such as time delay, reheat turbine, GRC, and Governor Dead Band (GDB) nonlinearity. The controller parameters of each area are optimized under normal and varied conditions using proposed hFA–PS technique. It is observed that the proposed technique is able to handle nonlinearity and physical constraints in the system model.     

Super-capacitor based energy storage system for improved load frequency control

A fuzzy-logic controlled super-capacitor bank (SCB) for improved load frequency control (LFC) of an interconnected power system is proposed, in this paper. The super-capacitor bank in each control area is interfaced with the area control bus through a power conversion system (PCS) comprising of a voltage source converter (VSC) and a buck-boost chopper. The fuzzy controller for SCB is designed in such a way that the effects of load disturbances are rejected on a continuous basis. Necessary models are developed and control and implementation aspects are presented in a detailed manner. Time domain simulations are carried out to demonstrate the effectiveness of the proposed scheme. The performance of the resulting power system under realistic situation is investigated by including the effects of generation rate constraint (GRC) and governor dead band (DB) in the simulation studies.     

Load frequency control of power system under deregulated environment using optimal firefly algorithm

In this paper, a novel Firefly Algorithm (FA) optimized hybrid fuzzy PID controller with derivative Filter (PIDF) is proposed for Load Frequency Control (LFC) of multi area multi source system under deregulated environment by considering the physical constraints such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB) nonlinearity. As the effectiveness of FA depends on algorithm control parameters such as randomization, attractiveness, absorption coefficient and number of fireflies are systematically investigated, the control parameters of FA are tuned by carrying out multiple runs of algorithm for each control parameter variation then the best FA control parameters are suggested. Additionally, the superiority of the FA is demonstrated by comparing the results with tuned Genetic Algorithm (GA). To investigate the effectiveness of the proposed approach, time domain simulations are carried out considering different contracted scenarios and the comparative results are presented. Further, sensitivity analysis is performed by varying the system parameters and operating load conditions. It is observed from the simulation results that the designed controllers are robust and the optimum gains of proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Finally, the effectiveness of the proposed control scheme is evaluated under random step load disturbance.     

Application of modular multilevel converter for AGC in an interconnected power system

This article demonstrates the maiden application of a new Modular Multi level Converter based Series Compensation (MMCS) technique for multi area Automatic Generation Control (AGC) interconnected system. Primarily MMCS has been modeled in state space form and proposes an appropriate location in AGC to obtain the better dynamic responses in frequency, tie-line power and individual generating power; further to quench the oscillation for sudden changes in load. The system has been studied the operation of MMCS and investigated with Generation Rate Constraints (GRC) of reheat turbines used in system. Further, selection of suitable integral and proportional–integral controller gain has been investigated with Integral Square Error (ISE) technique and Particle Swarm Optimization (PSO) technique for step load perturbation (SLP) in area-1 with performance index as its objective function by making control parameters as variables. System with MMCS is compared with out MMCS and observed performance has been increased and results are explored.     

含抽水蓄能电站的互联电网负荷频率自抗扰优化控制研究

针对发电能源结构的多元化发展给互联电网负荷频率的稳定性控制带来较大的挑战,建立含抽水蓄能电站的两区域互联电网多元混合发电的负荷频率控制模型,提出一种基于粒子群优化算法的负荷频率线性自抗扰控制器参数整定优化策略,通过粒子群算法的迭代寻优计算获得最优的线性自抗扰控制器参数。考虑互联电网各区域发生不同的负荷扰动,在抽水蓄能电站的抽水和发电2种工况下,对所提出的控制方法进行系统仿真。仿真结果表明,通过粒子群算法优化的负荷频率线性自抗扰控制器,与传统PI控制器对比,前者具有更强的抗扰动能力和适应性,系统动态稳定性更好。     

Application of firefly algorithm with online wavelet filter in automatic generation control of an interconnected reheat thermal power system

This paper presents the implementation of the Firefly Algorithm (FA) with an online wavelet filter on the automatic generation control (AGC) model for a three unequal area interconnected reheat thermal power system. The model includes time delay, dead zone, boiler, Generation Rate Constraint (GRC), and high frequency noise components. A novel filtering technique based on wavelet transform is introduced for the purpose of removing noise(s) from the ACE signal. The performance of the filter is measured by formulating a signal integrity index. The simulation results show that the FA is able to outperform the Particle Swarm Optimization (PSO) in obtaining the minimum objective function based on Integral of Time Weighted Squared Error (ITSE). The results also shows that the proposed online wavelet filter performs with a higher degree of efficiency compared to the conventional low pass filter when the practical model of the AGC is analyzed. Further investigation by varying the GRC and time delay parameter confirms the robustness of the FA tuned controller with the online wavelet filter.     

Hybrid Neuro Fuzzy approach for automatic generation control in restructured power system

In this paper, a hybrid combination of Neuro and Fuzzy is proposed as a controller to solve the Automatic Generation Control (AGC) problem in a restructured power system that operates under deregulation pedestal on the bilateral policy. In each control area, the effects of the possible contracts are treated as a set of new input signal in a modified traditional dynamical model. The prominent advantage of this strategy is its high insensitivity to large load changes and disturbances in the presence of plant parameter discrepancy and system nonlinearities. This newly developed strategy leads to a flexible controller with a simple structure that is easy to implement and consequently it can be constructive for the real world power system. The proposed method is tested on a three-area hydro-thermal power system in consideration with Generation Rate Constraint (GRC) for different contracted scenarios under diverse operating conditions. The results of the proposed controller are evaluated with the Hybrid Particle Swarm Optimisation (HCPSO), Real Coded Genetic Algorithm (RCGA) and Artificial Neural Network (ANN) controllers to illustrate its robust performance.     

基于变论域模糊逻辑的互联电力系统负荷频率控制

随着风电在电力系统中的渗透率不断提高,其出力不确定性对系统频率稳定造成威胁。针对风电接入系统后的频率波动问题,提出变论域模糊PI负荷频率控制策略。为克服传统模糊控制器由于论域固定导致自适应能力有限的缺点,设计的变论域模糊PI负荷频率控制器通过变论域方法实现输入、输出论域的动态调整。为满足风电接入系统后复杂的论域调整需求,基于模糊推理设计新型变论域伸缩因子。典型两区域互联系统仿真实验表明,在不同形式的扰动下,该新型控制器较PI控制器、模糊PI控制器有更好的控制表现,能更好地处理风电出力不确定性对互联电力系统频率稳定的影响。     

Bat inspired algorithm based optimal design of model predictive load frequency control

Bat inspired algorithm (BIA) has recently been explored to develop a novel algorithm for distributed optimization and control. In this paper, BIA-based design of model predictive controllers (MPCs) is proposed for load frequency control (LFC) to enhance the damping of oscillations in power systems. The proposed model predictive load frequency controllers are termed as MPLFCs. Two-area hydro-thermal system, equipped with MPLFCs, is considered to accomplish this study. The suggested power system model considers generation rate constraint (GRC) and governor dead band (GDB). Time delays imposed to the power system by governor-turbine, thermodynamic process, and communication channels are accounted for as well. BIA is utilized to search for optimal controller parameters by minimizing a candidate time-domain based objective function. The performance of the proposed controller has been compared to those of the conventional PI controller based on integral square error (ISE) technique and the PI controller optimized by genetic algorithms (GA), in order to demonstrate the superior efficiency of the BIA-based MPLFCs. Simulation results emphasis on the better performance of the proposed MPLFCs compared to conventional and GA-based PI controllers over a wide range of operating conditions and system parameters uncertainties.     

A fuzzy logic controlled superconducting magnetic energy storage,SMES frequency stabilizer

This paper presents application of fuzzy logic controlled superconducting magnetic energy storage device, SMES to damp the frequency oscillations of interconnected two-area power systems due to load excursions. The system frequency oscillations appear due to load disturbance. To stabilize the system frequency oscillations, the active power can be controlled via superconducting magnetic energy storage device, SMES. The error in the area control and its rate of change is used as controller input signals to the proposed fuzzy logic controller. In order to judge the effect of the proposed fuzzy logic controlled SMES, a comparative study is made between its effect and the effect of the conventional proportional plus integral (PI) controlled SMES. The studied system consists of two-area (thermal–thermal) power system each one equipped with SMES unit. The time simulation results indicate the superiority of the proposed fuzzy logic controlled SMES over the conventional PI SMES in damping the system oscillations and reach quickly to zero frequency deviation. The system is modeled and solved by using MATLAB software.     

基于交替方向乘子法的分布式负荷频率控制策略

负荷频率控制(load frequency control, LFC)是维持电力系统安全稳定运行的基础。对于多区域互联电力系统,由于描述动态过程的微分方程组相当复杂,这给负荷频率控制器的设计带来了困难。在此背景下,针对多区域互联电力系统,提出基于交替方向乘子法 (alternating direction method of multiplier, ADMM) 的分布式最优负荷频率控制器设计方法,以取得良好的控制性能,同时具备较高的计算效率。首先,介绍了负荷频率控制问题的微分方程模型。之后,基于二次多项式和矩阵稀疏化构建了分布式最优LFC策略的数学模型,并采用ADMM求解。最后,以三区域互联电力系统为例对所提方法进行了验证。仿真结果表明,针对负荷扰动和时变参数,所提方法能够把各区域的频率偏差和区域间联络线上的功率偏差控制到0。     

基于MVO算法与改进目标函数的电力系统负荷频率控制

针对风电并网时的随机波动功率、负荷频率控制(load frequency control, LFC)系统参数变化所引起的电力系统频率稳定问题,提出了一种基于智能优化算法与改进目标函数的互联电网LFC系统最优PID控制器设计方法。首先,分析了基于PID控制的含风电互联电力系统LFC闭环模型。其次,在时间乘误差绝对值积分(integral of time multiplied absolute error, ITAE)性能指标的目标函数中考虑了区域控制器的输出信号偏差,对优化目标函数进行改进。采用性能优良的多元宇宙优化(multi-verse optimizer, MVO)算法先计算后验证的思路,寻优获得最优PID控制器参数。最后,以两区域4机组互联电力LFC系统为例,仿真验证了基于MVO算法结合改进目标函数所获得的PID控制器,比基于MVO算法所获得的PID控制器,对阶跃负荷扰动、随机负荷扰动、风电功率偏差扰动以及系统的参数变化,具有相对较好的鲁棒性能。并且,对控制器参数也具有相对较好的非脆弱性指标。     

Sliding mode based load-frequency control in power systems

The paper presents a new discrete-time sliding mode controller for load-frequency control (LFC) in control areas (CAs) of a power system. As it uses full-state feedback it can be applied for LFC not only in CAs with thermal power plants but also in CAs with hydro power plants, in spite of their non-minimum phase behaviors. To enable full-state feedback we have proposed a state estimation method based on fast sampling of measured output variables, which are frequency, active power flow interchange and generated power from power plants engaged in LFC in the CA. The same estimation method is also used for the estimation of external disturbances in the CA, what additionally improves the overall system behavior. Design of the discrete-time sliding mode controller for LFC with desired behavior is accomplished by using a genetic algorithm. To the best of our knowledge, proposed controller outperforms any of the existing controllers in fulfilling the requirements of LFC. It was thoroughly compared to the commonly used PI controller by extensive simulation experiments on a power system with four interconnected CAs. These experiments show that the proposed controller ensures better disturbance rejection, maintains required control quality in the wider operating range, shortens the frequency’s transient response avoiding the overshoot and is more robust to uncertainties in the system.     

A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems

In this paper, a novel hybrid Particle Swarm Optimization (PSO) and Pattern Search (PS) optimized fuzzy PI controller is proposed for Automatic Generation Control (AGC) of multi area power systems. Initially a two area non-reheat thermal system is used and the gains of the fuzzy PI controller are optimized employing a hybrid PSO and PS (hPSO-PS) optimization technique. The superiority of the proposed fuzzy PI controller has been shown by comparing the results with Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA), conventional Ziegler Nichols (ZN), Differential Evolution (DE) and hybrid BFOA and PSO based PI controllers for the same interconnected power system. Additionally, the proposed approach is further extended to multi source multi area hydro thermal power system with/without HVDC link. The superiority of the proposed approach is shown by comparing the results with some recently published approaches such as ZN tuned PI, Variable Structure System (VSS) based ZN tuned PI, GA tuned PI, VSS based GA tuned PI, Fuzzy Gain Scheduling (FGS) and VSS based FGS for the identical power systems. Further, sensitivity analysis is carried out which demonstrates the ability of the proposed approach to wide changes in system parameters, size and position of step load perturbation The proposed approach is also extended to a non-linear power system model by considering the effect of governor dead band non-linearity and the superiority of the proposed approach is shown by comparing the results of hybrid BFO-PSO and craziness based PSO approach for the identical interconnected power system. Finally, the study is extended to a three area system considering both thermal and hydro units with different controllers in each area and the results are compared with hybrid BFO-PSO and ANFIS approaches.     

Adaptive fuzzy logic load frequency control of multi-area power system

Based on indirect adaptive fuzzy control technique, a new load frequency control (LFC) scheme for multi-area power system is proposed. The power systems under study have the characterization of unknown parameters. Local load frequency controller is designed using the frequency and tie-line power deviations of each area. In the controller design, the approximation capabilities of fuzzy systems are employed to identify the unknown functions, formulate suitable adaptive control law and updating algorithms for the controller parameters. It is proved that the proposed controller ensures the boundedness of all variables of the closed-loop system and the tracking error. Moreover, in the proposed controller an auxiliary control signal is introduced to attenuate the effect of fuzzy approximation error and to mitigate the effect of external disturbance on the tracking performance. Simulation results of a three-area power system are presented to validate the effectiveness of the proposed LFC and show its superiority over a classical PID controller.     

Robust analysis and design of power system load frequency control using the Kharitonov's theorem

This paper presents a robust decentralized proportional-integral (PI) control design as a solution of the load frequency control (LFC) in a multi-area power system. In the proposed methodology, the system robustness margin and transient performance are optimized simultaneously to achieve the optimum PI controller parameters. The Kharitonov’s theorem is used to determine the robustness margin, i.e., the maximal uncertainty bounds under which the stable performance of the power system is guaranteed. The integral time square error (ITSE) is applied to quantify the transient performance of the LFC system. In order to tune the PI gains, the control objective function is optimized using the genetic algorithm (GA). To validate the effectiveness of the proposed approach, some time based simulations are performed on a three-area power system and the results are then compared with an optimal PI controller. The comparisons show that the proposed control strategy provides the satisfactory robust performance for the wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other methods.     

微粒群优化负荷频率控制

针对两区域电力系统运用微粒群优化算法进行负荷频率控制,将模糊控制和微粒群优化算法相结合,利用微粒群算法优化模糊控制规则和PI控制器参数,以实现对控制规则的自调整,并在负荷频率控制中引入模糊决策控制,以减弱由时延引起的系统振荡。对两区域的负荷频率控制系统用MATLAB软件进行仿真,并将其与传统的积分控制和模糊自调整PI控制进行比较,仿真结果表明该方法的有效性,对复杂的非线性电力系统能取得良好的控制效果。     

负荷频率系统的LFC模糊监控器设计

应用在LFC控制中常规的模糊调整增益PI控制器和I控制器,只针对单一区域的负荷频率进行控制,并不考虑实际模型中的互相扰动.其中最突出的问题是由于不限制联络线上的功率流动,电能总是从频率高区域流向频率低区域,加剧了频率高区域的控制负担,再加上各区域控制动作的不协调,使得当扰动在不同的时间和幅值时引起系统调节过程的急剧恶化,导致整个系统不稳定.提出一种基于模糊MAMDANI推理算法的模糊监督控制器,采用各个区域的频率偏差作为控制器的输入,监督控制器作为一种前馈补偿,设计输出为一个ACE的倍数,加快调节过程,到达稳态.经过实验仿真数据对比,说明提出的监督控制器能有效提高系统的稳定性.     

A new intelligent online fuzzy tuning approach for multi-area load frequency control: Self Adaptive Modified Bat Algorithm

The primary aim of the Automatic Generation Control (AGC) is to maintain system frequency and tie-line interchanges in a predestine limits by regulating the power generation of electrical generators, in case of fluctuations in the system frequency and tie-line loadings. This paper proposes a new online intelligent strategy to realize the control of multi-area load frequency systems. The proposed intelligent strategy is based on a combination of a novel heuristic algorithm named Self-Adaptive Modified Bat Algorithm (SAMBA) and the Fuzzy Logic (FL) which is used to optimally tune parameters of Proportional–Integral (PI) controllers which are the most popular methods in this context. The proposed controller guaranties stability and robustness against uncertainties caused by external disturbances and impermanent dynamics that power systems face. To achieve an optimal performance, the SAMBA simultaneously optimizes the parameters of the proposed controller as well as the input and output membership functions. The control design methodology is applied on four-area interconnected power system, which represents a large-scale power system. To evaluate the efficiency of the proposed controller, the obtained results are compared with those of Proportional Integral Derivative (PID) controller and Optimal Fuzzy PID (OFPID) controller, which are the most recent researches applied to the present problem. Simulation results demonstrate the successfulness and effectiveness of the Online-SAMBA Fuzzy PI (MBFPI) controller and its superiority over conventional approaches.     

Quasi oppositional harmony search algorithm based controller tuning for load frequency control of multi-source multi-area power system

This paper deals with the load frequency control (LFC) study of single-area and interconnected two-area power system having diversified power sources. The two areas considered in the present study are identical. Each area is having thermal, hydro and gas based power plants. Split-shaft model of gas turbine is used in the present work as one of the diversified generating unit for the purpose of LFC study. Optimal gains of the classical controllers (like integral controller, proportional–integral controller and proportional–integral–derivative (PID) controller, one installed at a time in the studied models) are obtained by using a novel music-inspired metaheuristic harmony search algorithm (HSA) which incorporates quasi opposition based learning technique for memory initialization and also for generation jumping. Single-area power system with diverse power sources is considered and its optimal transient performances are obtained and compared for step load perturbation. The same approach is further extended to two-area interconnected power system consisting of diverse power sources with nominal values of area input parameters. The performance of PID controller is found to be the best one for the studied power system models. It is also revealed that the performance of the interconnected two-area power system with AC–DC tie line is better in comparison to AC tie line.