互联电力系统分散负荷—频率控制

本文提出了一个数值方法来解决由互联区域组成的电力系统负荷－频率控制问题，分析了控制律的两种结构，分解反馈控制和输出反馈控制。此方法在于经典黎卡提（Riccati)方程的特性：闭环渐近稳定性和次最优度，文中给出了将此方法应用于两互联区域电力系统的示例，并对闭环系统的性能做了分析。     

互联电力系统负荷频率分散变换控制

本文研究了一种适于离散系统的新型次最优控制方法——变换控制法。它比其他次最优控制及最优控制有更鲜明的特点及优越性,特别适于互联电力系统负荷频率分散控制的设计。     

基于滑模控制的含风储多域电力系统负荷频率控制

建立含风储多域互联电力系统负荷频率控制(LFC)模型,同时考虑系统参数不确定性、储能系统和传统机组控制信道延时问题.为提高系统鲁棒性,降低储能系统的容量配置,针对含风储的LFC模型,设计滑模负荷频率控制器,并提出滑模负荷频率控制器和储能协调的控制策略.算例分析表明,所提出的协调控制策略在新能源大规模渗透和系统负荷波动情况下能够有效减小系统频率偏差和区域控制偏差,同时降低储能系统的配置容量,提高电力系统安全稳定运行的经济性.     

改进多区域互联电力系统负荷频率滑模控制

提出了一种基于辅助反馈多区域互联电力系统负荷频率改进的PI切换面滑模控制器的设计方法,实现对多区域互联电力系统负荷频率的优化控制.该方法对滑模控制算法中的比例积分切换面进行改进,得到新的控制规律,从而能够在多区域互联电力系统存在区域负荷干扰和参数变化的情况下,实现负荷频率在规定范围内最小化波动.以两区域电力系统参数为模...     

多区域互联电力系统的自适应滑模负载频率控制

本文研究了一类计及电动汽车的电力系统中的负荷频率控制问题, 首先, 将电动汽车模型与传统的负载频率控制模型相结合,在未知扰动波动范围的条件下设计了自适应滑模控制律. 其次, 分别考虑了电网调频中的匹配扰动和不匹配扰动问题, 并利用李亚普诺夫稳定性理论导出了匹配和不匹配条件下的系统稳定的充分条件. 最后, 两个区域电力系统的仿真结果表明, 电动汽车作为电源和负载都可以提高电网的频率稳定性, 所设计的控制器可以有效地调节电网的频率波动.     

基于事件触发的互联电力系统分布式负荷频率预测控制

针对具有约束和扰动的多区域互联电力系统负荷频率控制(load frequency control, LFC)问题,本文提出了一种事件触发分布式模型预测控制(event-triggered distributed model predictive control,ET-DMPC)策略.将大规模互联电力系统分解成多个动态耦合的子系统,考虑发电机变化率约束(generation rate constraint, GRC)和调速器阀门位置限制,建立分布式预测控制优化问题.为了降低系统计算负担,减少计算资源的消耗和浪费,基于预测值和系统实际状态的误差构造事件触发条件.在事件触发机制下,只有子系统满足相应的事件触发条件时,控制器才传输状态信息和求解优化问题,并与邻域子系统交互最优解作用下的关联信息.仿真结果表明,本文提出的控制策略在负荷扰动和系统参数不确定的情况下具有良好的鲁棒性,同时极大地降低了系统的计算负担.     

基于滑模控制的多区域V2G系统的负荷频率控制

新能源背景下,电动汽车(EV)作为可调度的储能装置能够辅助参与电力系统的负荷频率控制。以含风电及电动汽车的多区域互联电力系统作为对象,对多系统的负荷频率控制问题展开研究。首先,针对风电与电动汽车并网(V2G)引起的系统状态难以准确监测的问题,设计状态观测器对系统状态进行估计;然后,设计了基于观测器的积分滑模控制器,并利用线性矩阵不等式求解控制器参数;最后,以两个区域的电力系统为例进行仿真实验,仿真结果表明所设计的控制器能够有效克服负荷需求扰动对系统造成的影响,验证了电动汽车参与辅助调频的有效性。     

基于滑模控制的单域电力系统负荷频率控制

针对一类包含非匹配参数不确定和负荷干扰的电力系统,提出一种负荷频率滑模控制器的设计方法.所设计的积分型切换面有效地改善了系统到达阶段的动态性能,提高了系统的鲁棒性;基于趋近律方法设计了滑模控制器,以保证系统运动轨线在有限时间内到达滑动模态;给出了单区域电力系统仿真模型,分别考虑了不同参数不确定条件下的仿真问题.仿真结果表明了所设计的控制器的有效性和鲁棒性.     

风电介入下的多区域互联电力系统分布式经济模型预测负荷频率控制

针对风电介入下的多区域互联电力系统,提出一种分布式经济模型预测负荷频率控制策略.通过将大规模互联电力系统分解成若干个动态耦合的子系统,这些子系统能够利用网络交流并共享信息,使得各区域的控制器实现各自优化问题的求解.同时,在满足状态约束和控制输入约束的前提下,遵循传统火力发电优先、风力发电配合的原则,通过在线求解优化问题,实现风电介入下的多区域互联电力系统的负荷频率控制.为了提高系统整体运行经济性,所提出的分布式经济模型预测控制器将负荷调频成本、燃料消耗成本以及风力发电成本等经济性指标考虑在内.仿真结果表明,在阶跃负荷扰动下,所设计的控制器不仅可以满足调频要求,在降低计算负担和提高经济性能方面也具有一定优势.     

Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity

This work presents an application of bio-inspired flower pollination algorithm (FPA) for tuning proportional–integral–derivative (PID) controller in load frequency control (LFC) of multi-area interconnected power system. The investigated power system comprises of three equal thermal power systems with appropriate PID controller. The controller gain [proportional gain (K _p), integral gain (K _i) and derivative gain (K _d)] values are tuned by using the FPA algorithm with one percent step load perturbation in area 1 (1 % SLP). The integral square error (ISE) is considered the objective function for the FPA. The supremacy performance of proposed algorithm for optimized PID controller is proved by comparing the results with genetic algorithm (GA) and particle swarm optimization (PSO)-based PID controller under the same investigated power system. In addition, the controller robustness is studied by considering appropriate generate rate constraint with nonlinearity in all areas. The result cumulative performance comparisons established that FPA-PID controller exhibit better performance compared to performances of GA-PID and PSO-PID controller-based power system with and without nonlinearity effect.

     

A novel hybrid DEPS optimized fuzzy PI/PID controller for load frequency control of multi-area interconnected power systems

In this paper, a novel hybrid Differential Evolution (DE) and Pattern Search (PS) optimized fuzzy PI/PID controller is proposed for Load Frequency Control (LFC) of multi-area power system. Initially a two-area non-reheat thermal system is considered and the optimum gains of the fuzzy PI/PID controller are optimized employing a hybrid DE and PS (hDEPS) optimization technique. The superiority of the proposed controller is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as DE, Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and conventional Ziegler Nichols (ZN) based PI controllers for the same interconnected power system. Furthermore, robustness analysis is performed by varying the system parameters and operating load conditions from their nominal values. It is observed that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Additionally, the proposed approach is further extended to multi-area multi-source power system with/without HVDC link and the gains of fuzzy PID controllers are optimized using hDEPS algorithm. The superiority of the proposed approach is shown by comparing the results with recently published DE optimized PID controller and conventional optimal output feedback controller for the same power systems. Finally, Reheat turbine, Generation Rate Constraint (GRC) and time delay are included in the system model to demonstrate the ability of the proposed approach to handle nonlinearity and physical constraints in the system model.     

Decentralized load frequency control for two-area interconnected power system

This paper proposes a decentralized output feedback control scheme applied to two-area interconnected power system. The controller synthesis problem is formulated as the scaled H∞control problem and a new LMI-based algorithm is proposed to compute the decentralized controller. The proposed controller provides robustness with regard to parametric uncertainties and also attenuates bounded exogenous disturbances in the sense of L2-gain. Simulation results clearly show the effectiveness of developed decentralized output feedback control scheme.     

Non-linear sliding mode load frequency control in multi-area power system

This paper addresses non-linear sliding mode controller (SMC) with matched and unmatched uncertainties for load frequency control (LFC) application in three-area interconnected power system. In conventional LFC scheme, as the nominal operating point varies due to system uncertainties, frequency deviations cannot be minimized. These lead to degradation in the dynamic performance or even system instability. In this paper, an effective control law is proposed against matched and unmatched uncertainties.. The proposed controller has ability to vary closed-loop system damping characteristics according to uncertainties and load disturbances present in the system. The frequency deviation converges to zero with minimum undershoot/overshoot, fast settling time, significantly reduced chattering and ensures asymptotic stability. In addition, the controller is robust in the presence of parameter uncertainties and different disturbance patterns. It also guarantees high dynamic performance in the presence of governor dead band (GDB) and generation rate constraint (GRC). Simulations are performed to compare the proposed controller with linear SMC. Using proposed control strategy, undershoot/overshoot and settling time gets reduced by approximately 30% with respect to linear SMC. The computed performance indices and qualitative results establish the superiority as well as applicability of the proposed design for the LFC problem. Further, the proposed controller scheme is validated on IEEE 39 bus large power system.     

Simulation based neuro-fuzzy hybrid intelligent PI control approach in four-area load frequency control of interconnected power system

This paper presents a novel control approach of hybrid neuro-fuzzy (HNF) for load frequency control (LFC) of four-area power system. The advantage of this controller is that it can handle the non-linearities, and at the same time it is faster than other existing controllers. The effectiveness of proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in four area interconnected power system. Area-1 and area-2 consist of thermal reheat power plant whereas area-3 and area-4 consist of hydro power plant. Performance evaluation is carried out by using fuzzy, ANN, ANFIS and conventional PI and PID control approaches. The performances of the controllers are simulated using MATLAB/Simulink package. The result shows that intelligent HNF controller is having improved dynamic response and at the same time faster than ANN, fuzzy and conventional PI and PID controllers.     

计及时滞的互联电网负荷频率控制最优分数阶PID控制器设计

分数阶PID控制器相比于传统整数阶PID控制器,具有控制性能好、鲁棒性强等诸多优势,可应用于电网的负荷频率控制(load frequency control,LFC)中.针对网络化时滞互联电网的LFC问题,提出了一种基于计算智能的分数阶PID控制器参数优化整定方案.该方案选择时滞LFC系统时域输出响应构建优化目标函数,采用最近提出的灰狼优化算法获得最优的分数阶PID控制器参数,所设计的控制器能确保一定时滞区间内LFC系统的稳定性.仿真算例表明,所设计的LFC最优分数阶PID控制器比传统整数阶PID控制器的控制性能更优,时滞鲁棒性更强.     

Performance investigation of ABC algorithm in multi-area power system with multiple interconnected generators

This paper presents an extensive study on the application of Artificial Bee Colony (ABC) algorithm for load frequency control (LFC) in multi-area power system with multiple interconnected generators. The LFC model incorporates various possible physical constraints and non-linearities such as generation rate constraint, time delay, dead zone and boiler. The ABC algorithm is used to find the optimum PID controller parameters. The tuning performance of the algorithm is comparatively investigated against different optimization technique such as evolutionary programming (EP), genetic algorithm (GA), gravitational search algorithm (GSA) and particle swarm optimization (PSO). The robustness analysis of the system is also evaluated by investigating the dynamic response of the controller with load demand at varying time step, tuning based on different performance criterion and by varying the load demand. The performance of the system is evaluated based on the settling time and maximum overshoot value of the frequency deviation response. The performance of ABC is also verified against an exhaustive search based on interval halving method. Despite employing a single controller for multiple interconnected generators, the optimized controller is able to successfully damp oscillations in the system response and regulate the area control error back to zero in minimal amount of time. The results indicate the superiority of the ABC algorithm’s search mechanism in finding the optimum set of PID controller’s gain.