水轮机尼科尔斯比例–积分–微分调速器设计

根据闭环系统谐振峰值 Mr 与系统响应最大峰值 Mp之间的关系,构建一个与系统参数及控制器参数都相关的优化问题,通过该问题的求解获得控制器参数与系统参数之间的数学关系.针对线性水轮机模型,设计了基于尼科尔斯曲线的 PID 控制器.系统负荷干扰及参数摄动的仿真结果表明:所设计的 PID 控制器对系统参数摄动及外部有界干扰信号具有很好的鲁棒性能,系统过渡过程性能明显优于传统PID 调节器结果.     

基于粒子群算法的含大规模风电互联系统的负荷频率控制

以含大规模风电的互联电力系统为研究对象,以抑制风电并网时所引起的系统频率不稳定为目的,提出了基于PSO的负荷频率控制器。传统的负荷频率控制器根据区域控制偏差来调整机组的出力,使区域控制偏差ACE趋于零,从而保证全系统发出的出力和负荷功率相匹配。把风电输出当作一个负的负荷作为等效负荷,在传统的比例积分控制器中引入PSO智能控制,可以进一步提高对等效负荷的控制效果。通过在Matlab/Simulink中构建的含风电的两区域互联电力系统的仿真结果表明,无论是互联电网的频率偏差还是联络线的交换功率,控制指标更优。     

基于PID的互联电力系统LFC的优化研究

针对两区域互联电力系统在受到外界负荷扰动后系统负荷频率的变化规律,基于TBC—TBC联络线频率偏差的控制模式,先后利用经典的PID控制技术和前馈补偿控制技术,对两区域互联电力系统负荷频率的控制算法进行优化研究,使两区域的电力系统在突然遭受负荷扰动时能迅速可靠地减少频率偏差和联络线交换功率偏差,恢复系统的安全稳定运行。在MATLAB7.8.0/Simulink软件的仿真下,其结果表明,经过前馈补偿后的PID控制比经典PID控制具有更佳的控制效果和鲁棒性。     

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。     

基于智能优化算法的互联电网负荷频率控制器设计及其控制性能分析

互联电网负荷频率控制对保障电网安全可靠运行具有重要作用,适宜的控制器参数整定使得电网在各种随机扰动下维持系统频率稳定和联络线功率交换值恒定。针对两区域互联电网的负荷频率控制器参数优化整定问题,提出一种基于智能优化算法的控制器参数整定设计方案。该方案采用最小化时间乘误差绝对值积分作为目标函数,运用灰狼优化算法搜索获得最优化的负荷频率控制器参数。灰狼优化算法模拟了狼群的社会分层机制和群体狩猎行为,使得控制器参数优化整定过程具有快速、高效、自适应和精度高等优点。此外,重点考虑了控制器参数不确定性可能导致的控制器性能衰减,讨论了控制器的脆弱性问题。建立了两区域互联电网负荷频率控制系统仿真模型,采用所提优化算法获取PI/PID型负荷频率控制器参数,仿真结果显示所提算法设计PI/PID控制器相比于传统方法和其他的智能优化算法具有更好的寻优能力和控制性能,并且优化获得的控制器在系统参数和控制器参数不确定性下具有鲁棒性和非脆弱性。     

互联电网联络线随机功率波动统计特性与评价标准分析

正常运行时互联电网交流联络线上存在随机功率波动的现象。基于实际2大区互联电网的历史数据,分析了联络线功率偏差、频率偏差以及2大区电网区域控制偏差(area control error,ACE)的统计特性,结果显示：联络线功率偏差表现出良好的正态分布特性;系统频率偏差和正态分布存在较大差别,原因是电网的频率控制使得频率偏差大于0.03 Hz的概率减小;各控制区的ACE基本服从正态分布。文章认为联络线功率偏差由两端电网的ACE引起,可以通过两端电网ACE的均方根值和相关系数计算出联络线功率偏差的均方根值,从而得到对联络线功率偏差大小分布的估计。对目前采用的 T 标准进行了分析,得出结论：为实现联络线功率控制的目标,两端电网责任度阈值之和为2即可,不一定要求两端电网责任度的阈值都是1;两端电网责任度阈值的分配还需要综合考虑各种因素进行详细研究,以得到公平合理的方案。     

含风光水火储的多区域互联电力系统协同优化负荷频率控制

针对现代电力系统中呈现出的互联和多源的特点,首先提出了一种启发式智能优化算法辅助含风光水火储的多区域互联电力系统协同优化负荷频率控制方法,该方法以每个区域的区域控制偏差为目标函数;然后利用鲸鱼智能优化算法鲁棒性强、求解精度高及收敛快速度等优点,对各区域的PID负荷频率控制器参数进行协同优化,使得系统在各种随机扰动下,都能够维持频率稳定和长期安全运行;最后建立含风光水火储的三区域互联电力系统模型,对比不同优化整定方法下的互联电力系统频率和联络线功率偏差,测试系统在不同扰动时各区域的稳定性及所提方法的有效性。实验结果表明,所采取的多区域互联负荷频率控制器协同优化整定方法有效地改善了系统的稳定性,具有良好的鲁棒性和实用性。     

基于IPC模糊控制的互联电网联络线潮流控制研究

为了提高互联电网问联络线负荷的稳定性,提出了一种联络线传输功率和频率协调模糊控制方案。通过调节联络线两端发电机组对两侧电网频率差进行调整,调节相间功率控制器(IPC)元件参数调整联络线传输功率,对调节参数采用模糊逻辑控制。模拟通过IPC互联的东北-华北电网,对不同控制区域进行控制仿真。结果表明,在一侧发生小扰动时,另一侧电网和联络线功率几乎不受影响,在大扰动时,两侧系统能可靠实现同步运行。     

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PSO-GSA算法的含DFIG互联系统AGC优化控制研究

传统双馈感应风力发电机(DFIG)的解耦控制使其无法响应电网的频率变化。随着风电渗透率的不断提高,电网调频压力不断增大,有必要对含DFIG互联系统AGC优化控制进行研究。首先建立了将风电作为"负的负荷"的两区域AGC模型,通过引入改进的虚拟惯性控制使DFIG具有更好的频率响应的能力。同时以快速消除系统区域控制偏差和风机转速偏差为目的,采用PSO-GSA算法对控制区PID控制器和DFIG转速控制单元PI控制器参数进行优化。仿真结果表明,单个区域受负荷扰动时,风电参与调频时能提供更多的有功功率支撑以减小同步机调频出力,能有效缓解同步机调频压力。PSO-GSA算法较PSO和GSA迭代速度快且适应度值更好,基于PSO-GSA参数优化后的控制器对系统区域频率偏差、联络线功率变化和区域控制偏差信号的超调量和调节时间都有明显改善,增强了系统的稳定性。     

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.     

Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems

This paper presents a new population based parameter free optimization algorithm as teaching learning based optimization (TLBO) and its application to automatic load frequency control (ALFC) of multi-source power system having thermal, hydro and gas power plants. The proposed method is based on the effect of the influence of teacher on the output of learners and the learners can enhance their knowledge by interactions among themselves in a class. In this extensive study, the algorithm is applied in multi area and multi-source realistic power system without and with DC link between two areas in order to tune the PID controller which is used for automatic generation control (AGC). The potential and effectiveness of the proposed algorithm is compared with that of differential evolution algorithm (DE) and optimal output feedback controller tuning performance for the same power systems. The dynamic performance of proposed controller is investigated by different cost functions like integral of absolute error (IAE), integral of squared error (ISE), integral of time weighted squared error (ITSE) and integral of time multiplied absolute error (ITAE) and the robustness of the optimized controller is verified by its response toward changing in load and system parameters. It is found that the dynamic performance of the proposed controller is better than that of recently published DE optimized controller and optimal output feedback controller and also the proposed system is more robust and stable to wide changes in system loading, parameters, size and locations of step load perturbation and different cost functions.     

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.     

磁控开关型故障限流器偏置电流模糊PID控制

为提高偏置电流系统的控制精度,设计了一种运用模糊PID在线修改控制器参数的新型偏置电流控制系统。该系统集PID控制及模糊控制的优点于一体,具有不需要精确的数学模型就能够快速、精确控制偏置电流的特点。试验证明,利用该控制系统对限流器偏置电流进行控制,限流器的响应速度和限流效果可以得到保证。     

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.     

Simulated annealing based optimal frequency and terminal voltage control of multi source multi area system

The article proposes optimal secondary controller for combined Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) of multi source multi area system using simulated annealing technique. When subjected to load disturbance, frequency, tie-line power and voltage fluctuations results higher oscillations. Speed governor of the system helps to match generation with the demand. But, fine tuning of frequency, tie-line power and voltage when subjected to load disturbance in multi source multi area system is achieved by secondary Proportional Integral Derivative (PID) controller. As a conventional benchmark PID controller is tuned using Zeigler Nichol’s (ZN) method and further optimized using Simulated Annealing (SA) technique. The performance of the system is validated and judged using performance indices.     

Application of Hybrid Differential Evolution–Grey Wolf Optimization Algorithm for Automatic Generation Control of a Multi-Source Interconnected Power System Using Optimal Fuzzy–PID Controller

This paper deals with an optimal hybrid fuzzy-Proportional Integral Derivative (fuzzy-PID) controller optimized by hybrid differential evolution–Grey Wolf optimization algorithm for automatic generation control of an interconnected multi-source power system. Here a two area system is considered; each area is provided with three types of sources namely a thermal unit with reheat turbine, a hydro unit and a gas unit. The dynamic performance of the system is analyzed under two cases: with AC tie-line and with AC-DC tie-line. The efficiency and effectiveness of the proposed controller is substantiated equally in the two cases. The sturdiness of the system is proved by varying the values of the system parameters. The supremacy of the recommended work is additionally ascertained by comparison with the recently published results like differential evolution optimized PID Controller and hybrid Local Unimodal Sampling-Teaching Learning based Optimization (LUS-TLBO) optimized fuzzy-PID controller. The dynamic performance of the system is observed in terms of settling time, peak overshoot and peak undershoot. Finally the analysis is extended by applying the proposed control technique in two different models namely (i) A three area unequal thermal system considering proper generation rate constraints (GRC) and (ii) A three area hydro-thermal system with mechanical hydro governor. These test results reveal the adaptability of the proposed method in multi-area interconnected power system.     

Sliding mode controller design for frequency regulation in an interconnected power system

In this paper, a Sliding mode controller design method for frequency regulation in an interconnected power system is presented. A sliding surface having four parameters has been selected for the load frequency control (LFC) system model. In order to achieve an optimal result, the parameter of the controller is obtained by grey wolf optimization (GWO) and particle swarm optimization (PSO) techniques. The objective function for optimization has been considered as the integral of square of error of deviation in frequency and tie-line power exchange. The method has been validated through simulation of a single area as well as a multi-area power system. The performance of the Sliding mode controller has also been analyzed for parametric variation and random loading patterns. The performance of the proposed method is better than recently reported methods. The performance of the proposed Sliding mode controller via GWO has 88.91% improvement in peak value of frequency deviation over the method of Anwar and Pan in case study 1 and similar improvement has been observed over different case studies taken from the literature.