Design of biogeography optimization based dual mode gain scheduling of fractional order PI load frequency controllers for multi source interconnected power systems

This paper presents the effect on application of biogeography optimization (BBODMFOPI) based dual mode gain scheduling of fractional order proportional integral controllers for load frequency control (LFC) of a multi source multi area interconnected power systems. This controller has three parameters to be tuned. Thus, it provided one more degree of freedom in comparison with the conventional proportional integral (PI) controller. For proper tuning of the controller parameters, Biogeography-Based Optimization (BBO) was applied. BBO is a novel evolutionary algorithm which involves the methodology of making the system effectively by using mathematical techniques. The dual mode concept is also incorporated in this work, because it can improve the system performance. In this work, simulation investigations were taken out on a two-area power system with different generating units. The simulation results show that the proposed biogeography optimization based dual mode gain scheduling of fractional order PI controllers, provide better transient as well as steady state response. It is also found that the proposed controller is less sensitive to the changes in system parameters and robust under different operating condition of the power systems.     

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.     

三相电压型PWM整流器的级联式非线性PI控制

该文以同步旋转坐标系模型为基础，设计了三相电压型PWM整流器的级联式非线性PI控制器。采用双环结构，用三个非线性PI环节实现了对整流器直流电压与功率因数的高性能控制。以误差的非线性函数与传统PI环节构成的级联式控制器，既提高了系统响应的快速性，又增强了抗扰能力，同时计算简单易于实现。与传统PI控制器的仿真对比表明该方法能够明显改善系统的动态性能，而实验结果也验证了非线性PI控制器的优良性能。     

Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units

This paper investigates a renewable energy resource’s application to the Load–Frequency Control of interconnected power system. The Proportional-Integral (PI) controllers are replaced with Proportional-Integral Plus (PI+) controllers in a two area interconnected thermal power system without/with the fast acting energy storage devices and are designed based on Control Performance Standards (CPS) using conventional/Beta Wavelet Neural Network (BWNN) approaches. The energy storing devices Hydrogen generative Aqua Electroliser (HAE) with Fuel cell and Redox Flow Battery (RFB) are incorporated to the two area interconnected thermal power system to efficiently damp out the electromechanical oscillations in the power system because of their inherent efficient storage capacity in addition to the kinetic energy of the generator rotor, which can share the sudden changes in power requirements. The system was simulated and the frequency deviations in area 1 and area 2 and tie-line power deviations for 5% step- load disturbance in area 1 are obtained. The comparison of frequency deviations and tie-line power deviations of the two area interconnected thermal power system with HAE and RFB designed with BWNN controller reveals that the PI+ controller designed using BWNN approach is found to be superior than that of output response obtained using PI+ controller. Moreover the BWNN based PI+ controller exhibits a better transient and steady state response for the interconnected power system with Hydrogen generative Aqua Electroliser (AE) unit than that of the system with Redox Flow Battery (RFB) unit.     

基于免疫优化的机炉协调系统模糊增益调度H∞鲁棒控制

针对非线性锅炉-汽轮机系统在负荷点大范围变动情况下的协调控制,提出了一种新的免疫优化模糊增益调度 鲁棒控制方法。该方法首先利用 /混合灵敏度方法设计出多个 局部鲁棒控制器以覆盖机炉系统的负荷变化区间;然后采用模糊推理生成增益调度准则以实现各局部控制器间的软切换;最后利用免疫遗传算法对模糊增益调度准则的结构参数进行优化设计,从而保证闭环系统具有良好的全局控制性能。仿真研究表明：基于该方法设计出的协调控制系统在大工况范围内具有优良的调节品质。     

Bacteria foraging optimization algorithm based load frequency controller for interconnected power system

Social foraging behavior of Escherichia coli bacteria has recently been explored to develop a novel algorithm for distributed optimization and control. The Bacterial Foraging Optimization Algorithm (BFOA), as it is called now, is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real world optimization problems. This paper proposes BFOA based Load Frequency Control (LFC) for the suppression of oscillations in power system. A two area non-reheat thermal system is considered to be equipped with proportional plus integral (PI) controllers. BFOA is employed to search for optimal controller parameters by minimizing the time domain objective function. The performance of the proposed controller has been evaluated with the performance of the conventional PI controller and PI controller tuned by genetic algorithm (GA) in order to demonstrate the superior efficiency of the proposed BFOA in tuning PI controller. Simulation results emphasis on the better performance of the optimized PI controller based on BFOA in compare to optimized PI controller based on GA and conventional one over wide range of operating conditions, and system parameters variations.     

Cuckoo Search algorithm based load frequency controller design for nonlinear interconnected power system

A new optimization technique called Cuckoo Search (CS) algorithm for optimum tuning of PI controllers for Load Frequency Control (LFC) is suggested in this paper. A time domain based-objective function is established to robustly tune the parameters of PI-based LFC which is solved by the CS algorithm to attain the most optimistic results. A three-area interconnected system is investigated as a test system under various loading conditions where system nonlinearities are taken into account to confirm the effectiveness of the suggested algorithm. Simulation results are introduced to show the enhanced performance of the developed CS based controllers in comparison with Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and conventional integral controller. These results denote that the proposed controllers offer better performance over others in terms of settling times and various indices.     

Adaptive fuzzy gain scheduling for load frequency control

An adaptive fuzzy gain scheduling scheme for conventional PI and optimal load frequency controllers has been proposed. A Sugeno type fuzzy inference system is used in the proposed controller. The Sugeno type fuzzy inference system is extremely well suited to the task of smoothly interpolating linear gains across the input space when a very nonlinear system moves around in its operating space. The proposed adaptive controller requires much less training patterns than a neural net based adaptive scheme does and hence avoiding excessive training time. Results of simulation show that the proposed adaptive fuzzy controller offers better performance than fixed gain controllers at different operating conditions     

Load frequency control of an autonomous hybrid power system by quasi-oppositional harmony search algorithm

This paper deals with a novel quasi-oppositional harmony search algorithm (QOHSA) based design of load frequency controller for an autonomous hybrid power system model (HPSM) consisting of multiple power generating units and energy storage units. QOHSA is a novel improved version of music inspired harmony search algorithm for obtaining the best solution vectors and faster convergence rate. In this paper, the efficacy of the proposed QOHSA is adjudged for optimized load frequency control (LFC) of an autonomous HPSM. The studied HPSM consists of renewable/non-renewable energy based generating units such as wind turbine generator, solar photovoltaic, solar thermal power generator, diesel engine generator, fuel cell with aqua-electrolyzer while energy storage units consists of battery energy storage system, flywheel energy storage system and ultra-capacitor. Gains of the conventional controllers such as integral (I) controller, proportional–integral (PI) controller and proportional–integral–derivative (PID) controller (installed as frequency controller one at a time in the proposed HPSM) is optimized using QOHSA to mitigate any frequency deviation owing to sudden generation/load change. In order to corroborate the efficacy of QOHSA, performance of QOHSA to design optimal LFC is compared with that of other well-established technique such as teaching learning based optimization algorithm (TLBOA). The comparative performances of the HPSM under the action of QOHSA/TLBOA based optimized conventional controllers (I or PI or PID) are investigated and compared in the present work. It is found that the QOHSA tuned frequency controllers improves the overall dynamic response in terms of settling time, overshoot and undershoot in the profile of frequency deviation and power deviation of the studied HPSM.     

并联有源电力滤波器典型重复控制策略的分析与改进

目前并联有源电力滤波器采用的典型重复控制通常由PI控制与重复控制并联构成,存在中频段开环增益不足的缺点,且PI控制器同时存在于前向通道与反馈通道中,动态补偿效果不佳。提出了改进的重复控制策略,利用PI控制构成电流内环,对控制对象的中低频段特性进行校正,提高控制系统鲁棒性。利用前向通道中的重复控制器提供对谐波信号的高增益,提高了有源电力滤波器的中频段带宽。同时利用参考电流信号前馈至PI控制电流内环,充分保证控制系统的动态性能。仿真和实验结果验证了所提出控制策略的正确性和有效性。     

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.     

大型双馈异步风力发电机组变桨控制算法研究

变桨控制系统[1]是变速恒频风力发电机组的重要组成本分,它不仅关系到大型MW级风机的安全运行,而且对风能的吸收具有较好的控制作用。其中变桨控制算法是其控制系统的核心部分,为减小整机机械载荷、风机功率的稳定输出做出重要贡献。基于2.0 MW双馈风力发电系统的基础上,提出了具有转速二阶陷波滤波器的增益调度-双PI(notch filter gain-schedule double PI)控制算法,对风机运行于额定风速以上的变桨控制策略[2],使风机能够以最佳的速率变桨到最佳桨距角位置,从而输出稳定的功率,减小整机的振动,减小风机在3P、6P处产生过大的振动。最后对2.0 MW双馈异步风机变桨控制进行仿真和实际监控图分析,结果表明,其控制算法具有良好控制效果。     

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.     

Robust Frequency Control in an Autonomous Microgrid: A Two-Stage Adaptive Fuzzy Approach

Highly intermittent power from renewable energy sources (RES) along with load and system perturbations in an autonomous microgrid (MG), results in large frequency fluctuations. Conventional controllers like PI controllers to be unable to provide acceptable performance over a wide range of operating conditions. To overcome this problem, present paper introduces a novel two-stage adaptive fuzzy logic based PI controller for frequency control of MG. In this proposed controller, particle swarm optimization (PSO) and grey wolf optimization (GWO) are used to optimize the membership functions (MFs) and rule base of fuzzy logic based PI controller. The proposed controller is examined on an MG test system, the robustness and performance of the proposed controller is tested in presence of different disturbance scenarios and parametric uncertainties. Finally, the superiority of the proposed controller is shown by comparing the results with various controllers available in literature like PSO tuned fuzzy logic based PI controller, fuzzy logic-based PI controller and also with the conventional PI controller.     

多馈入交直流输电系统的模糊控制器协调优化算法

设计了一套阻尼区域间功率振荡的模糊控制器。在多馈入交直流输电系统的直流功率控制系统和发电机励磁系统中同时采用了该模糊控制器,并对影响其性能的关键参数进行了协调优化。为了解决优化结果容易限于局部最优的问题,采用了遗传算法进行全局并行寻优,同时引入序优化理论在概率意义上保证优化解的质量。仿真结果表明:与常规阻尼控制器相比,模糊控制器能更好地提高交直流互联系统的动态稳定性且具有鲁棒性。序优化遗传算法比传统遗传算法具有更稳定的性能,可作为多馈入交直流输电系统的模糊控制器参数协调优化的一种有效方法。     

Alleviation of power fluctuation in a microgrid by electrolyzer based on optimal fuzzy gain scheduling PID control

This paper presents an application of the electrolyzer (EZ) to alleviate the power fluctuation in a microgrid with hybrid power generations from wind, photovoltaic array, fuel cell, and diesel engine. In this microgrid, the intermittent power generations from wind and photovoltaic arrays cause severe power fluctuation. With the fast response of EZ, the power absorbed by EZ can be controlled to compensate for the power fluctuation, in addition to the hydrogen production for fuel cell. The structure of the active and reactive power controllers of EZ is the fuzzy gain scheduling of a proportional‐integral‐derivative (FGS‐PID) controller. Without trial and error, the scale factors, membership functions, and control rules of the FGS‐PID controller are automatically optimized by bee colony optimization. A simulation study confirms that the proposed EZ with optimal FGS‐PID controller is much superior to the optimal PID controller in terms of damping effect, robustness against disturbances, and hydrogen production. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于串级PI-(1+PD)算法的含飞轮储能互联电网AGC控制器设计

针对传统控制器存在的响应速度较慢、超调较大及鲁棒性较差等问题,提出一种基于串级PI-(1+PD)算法的含飞轮储能互联电网AGC控制器设计方法。首先,建立含飞轮储能的两区域互联电网AGC系统模型,模拟飞轮储能联合火电机组参与AGC的过程。然后,设计一种基于串级PI-(1+PD)算法的AGC控制器。外环采用PI控制,内环采用带滤波系数的(1+PD)控制。在保证系统稳态性能的前提下,提高动态响应速度和抗扰能力,并通过粒子群算法的迭代寻优获得最优的控制器参数。最后,基于Matlab/Simulink进行算例仿真分析。结果表明：与传统PID控制和PI-PD控制相比,所提方法不仅具有更快的响应速度与更小的超调量,而且增强了系统抵御内部参数摄动的鲁棒性。     

BUCK型开关变换器最优PID控制器设计

针对开关电源的复杂性和时变性,传统PID控制器整定方法无法很好满足其控制性能要求的问题,提出一种面向性能指标的最优PID控制器参数整定方法。基于DP算法,计算保证闭环系统稳定的PID控制器参数范围;利用具有全局寻优能力的遗传算法,按照ITAE性能指标在该范围内进行参数寻优。以BUCK变换器为利的仿真研究表明,该方法在指定的性能指标上取得了满意的控制效果,在负载发生摄动时,较传统PID控制器,具有较好的鲁棒性,且计算相对简单、实用性强,可推广到非线性PID控制器的参数整定和相关工程实践中。     

蚁群优化PI控制器在静止无功补偿器电压控制中的应用

静止无功补偿器(static var compensator,SVC)通常用来进行负荷补偿或系统补偿,在系统补偿时往往用于电压稳定控制,针对电压稳定控制的工况,文中提出一种采用蚁群算法优化PI控制器参数的方法,克服了常规PI控制对被控对象数学模型的依赖性,简单易于实现。蚁群优化算法中,以时间与误差绝对值乘积积分(integral of time-weighted absolute error,ITAE)准则作为寻优目标函数,对PI控制器的比例、积分参数进行调整、寻优,使SVC系统的响应过程达到最优。仿真和实验结果表明,该最优PI控制器能快速跟踪SVC系统的电压设定值,基于该PI控制器的SVC能迅速进行无功补偿,具有较强的适应性和较高的补偿精度。     

Load Frequency Control of Multi-source Multi-area Hydro Thermal System Using Flexible Alternating Current Transmission System Devices

This article describes the load frequency control of a multi-area system. Each control area contains both a hydro and thermal power plant to form a multi-source multi-area hydro thermal system. The secondary proportional-integral controller has been tuned using Ziegler–Nichols, genetic algorithm, and fuzzy gain scheduling methods. On comparing the controller performance based on various performance indices, it is found that a fuzzy gain scheduling tuned proportional-integral controller is suitable for a multi-source multi-area hydro thermal system. Further improvement on the load frequency dynamics has been achieved by connecting superconducting magnetic energy storage unit in each control area and a static synchronous series compensator unit on a tie-line.