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.     

互联电力系统鲁棒分布式模型预测负荷频率控制

负荷频率控制是现代互联电力系统运行的重要保障.本文针对含有不确定因素和负荷扰动的多区域互联电力系统提出了一种基于线性矩阵不等式参数可调节的鲁棒分布式预测控制算法.设计各个区域控制器目标函数引入相邻区域的状态变量和输入变量,同时考虑发电机变化速率约束和阀门位置约束,将求解一组凸优化问题转化成线性矩阵不等式求解,得到各个区域的控制律,在线性矩阵不等式中引入一组可调参数,将优化一个上限值转化成优化吸引区,降低算法的保守性.仿真结果验证了该算法在负荷扰动、系统参数不确定和结构不确定性情况下具有鲁棒性.     

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。     

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...     

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.     

通讯信息约束下具有全局稳定性的分布式系统预测控制

本文针对一类由状态相互耦合的子系统组成的分布式系统, 提出了一种可以处理输入约束的保证稳定性的非 迭代协调分布式预测控制方法(distributed model predictive control, DMPC). 该方法中, 每个控制器在求解控制率时只与 其它控制器通信一次来满足系统对通信负荷限制; 同时, 通过优化全局性能指标来提高优化性能. 另外, 该方法在优化 问题中加入了一致性约束来限制关联子系统的估计状态与当前时刻更新的状态之间的偏差, 进而保证各子系统优化问 题初始可行时, 后续时刻相继可行. 在此基础上, 通过加入终端约束来保证闭环系统渐进稳定. 该方法能够在使用较少 的通信和计算负荷情况下, 提高系统优化性能. 即使对于强耦合系统同样能够保证优化问题的递推可行性和闭环系统的 渐进稳定性. 仿真结果验证了本文所提出方法的有效性.     

计及温控负荷响应的二维云模型分布式频率控制

为改善电力系统频率稳定性,充分调用需求侧可控负荷资源,本文提出一种计及温控负荷响应的二维云模型分布式频率控制方法。建立了多区域互联电力系统负荷频率控制模型,设计了基于福克普朗克方程的温控负荷分布式控制策略,同时采用云模型算法与分数阶微积分理论,设计了二维云模型分数阶PID分布式频率控制器。最后通过控制仿真比较与分析,验证了在不同运行场景下所提出的综合控制方法具有较优的动稳态性能。结果表明该控制方法是可行和有效的。     

电力市场条件下互联电力系统的分散H_∞控制

根据分散的自动发电控制AGC(AutomaticGenerationControl)的控制要求和电力市场的条件,研究了互联电力系统分散的鲁棒控制问题。采用虚拟控制区域的概念修正原互联电力系统的状态空间模型;利用大系统包含原理的约束和聚集条件将修正后的互联电力系统模型分解为各个子系统;根据LMI算法来设计可随时满足区域间功率交换合同的分散H∞自动发电控制器。此方法应用到受负载阶跃扰动的两区域互联电力系统中,结果表明了该方法的有效性,并且满足了电力市场条件下自动发电控制的要求。     

改进的差分进化算法优化负荷频率控制北大核心CSCD

负荷频率控制(LFC)是保证供电质量及电力系统安全、可靠与经济运行的一种重要的手段。针对互联电力系统中负荷频率控制的特性,对控制参数保持不变的常规差分进化算法进行了改进,提出了一种根据进化代数的变化控制参数中的缩放因子和交叉概率因子也相应的进行变化,保证了进化初期对种群的多样性要求高以提高算法全局搜索能力以及进化后期对局部搜索能力要求较高以提高算法的精度和加快收敛速度。最后推导出两区域互联电力系统负荷频率控制的控制模型,将改进的差分进化算法用于优化其PI控制器参数,仿真结果表明改进后的优化算法在优化PI控制器参数性能上要优于传统的优化算法,即保证系统具有良好的动态性能下仍具有很好的鲁棒特性。     

改进的差分进化算法优化负荷频率控制

负荷频率控制(LFC)是保证供电质量及电力系统安全、可靠与经济运行的一种重要的手段。针对互联电力系统中负荷频率控制的特性,对控制参数保持不变的常规差分进化算法进行了改进,提出了一种根据进化代数的变化控制参数中的缩放因子和交叉概率因子也相应的进行变化,保证了进化初期对种群的多样性要求高以提高算法全局搜索能力以及进化后期对局部搜索能力要求较高以提高算法的精度和加快收敛速度。最后推导出两区域互联电力系统负荷频率控制的控制模型,将改进的差分进化算法用于优化其PI控制器参数,仿真结果表明改进后的优化算法在优化PI控制器参数性能上要优于传统的优化算法,即保证系统具有良好的动态性能下仍具有很好的鲁棒特性。     

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Reliable load frequency control (LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC) based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints (GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints.      

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.     

Grasshopper optimization algorithm for optimal load frequency control considering Predictive Functional Modified PID controller in restructured multi-resource multi-area power system with Redox Flow Battery units

Load frequency control (LFC) is a well-established issue in design and operation of power systems considering to the extension, restructuring, and complexity of the interconnected power systems and also the emergence utilization of renewable energy resources. This paper studies the frequency control of multi-area multi-source power system based on the importance of the LFC in the stability of the power system which includes various generation units of thermal, hydroelectric, wind, natural gas and diesel under the restructured environment. In this system, non-linear physical constraints, governor dead band (GDB) and generation rate constraint (GRC) are considered. In this paper, a new Predictive Functional Modified PID (PFMPID) controller is proposed that the effectiveness of this controller is verified compared to the traditional one. In order to optimize and demonstrate the superiority of the proposed control method, Grasshopper Optimization Algorithm (GOA) is proposed as a suitable solution. To further improve the performance of the under study system, the use of the Redox Flow Battery (RFB) energy storage unit has also been proposed. Since the operation evaluation of the proposed process is necessary in different system conditions, the performance of the proposed method is studied under various disturbances and simulation results are presented.     

A self-interested distributed economic model predictive control approach to battery energy storage networks

In this work, a dissipativity based distributed economic model predictive control (DEMPC) approach is developed for the operation of battery energy storage (BES) networks in residential microgrids. With the presence of a microgrid power market (MPM), control of the BES systems is formulated as a self-interested distributed control problem, as individual DEMPC controllers minimize their local economic cost functions based on the price prediction of MPM. Due to the intermittent nature of photovoltaic (PV) power generations and load demands, the DEMPC without proper coordination or constraints may lead to excessive energy trading and price oscillations in MPM. To solve this problem, dissipativity theory with dynamic supply rates is adopted in this paper to deal with the interactions between individual users and the MPM. The microgrid-wide performance requirement of attenuation of the net power fluctuations with respect to time-varying PV generation and demands, is converted into the dissipative trajectory constraints imposed on individual DEMPC controllers. The proposed approach is scalable as it does not require online iterative optimizations across the controller network. A case study is presented to illustrate the proposed method.     

Observer based robust integral sliding mode load frequency control for wind power systems

This paper investigates the load frequency control (LFC) for wind power systems with modeling uncertainties and variant loads. Since the system state is difficult to be accurately measured due to perturbation of nonlinear load, an observer is designed for reconstructing a substitution system state. Afterwards, an integral sliding surface is designed and a sliding mode LFC (SMLFC) strategy is proposed for reducing frequency deviations of the overall power system. Remarkably, it has been pointed out that a larger convergence rate of the observer error system has positive influences on the SMLFC performances, while the larger observer gain deteriorates the dynamic behavior. For seeking an acceptable balance so as to determine the optimal controller parameters, a collaborative design algorithm is proposed. The proposed method not only guarantees the asymptotical stability of overall power systems but also capable of improving the system robustness. Numerical examples are provided to demonstrate the effectiveness of the proposed methods.     

考虑通信时滞和采样周期的电力系统负荷频率控制

针对电力系统负荷频率稳定控制问题,本文提出了一种时滞/采样相关的离散负荷频率控制(LFC)方案.首先,考虑通信网络传输时滞和反馈信号采样周期对系统的影响,建立闭环电力系统LFC模型.然后,基于建立的LFC模型,利用双边闭环Lyapunov泛函和LMI技术,提出了低保守性的时滞/采样相关稳定准则和控制器设计方法,确保所提控制方案能在一个较大的通信时滞和采样周期条件下保持电力系统稳定运行.最后,通过单区域和三区域电力系统验证所提方法的有效性.仿真结果表明,所设计LFC方案比现有其他LFC方案的控制性能更佳,鲁棒性更强,并且能在一定大小的通信时滞条件下提升电力系统的动态性能.     

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.     

A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system

In this paper, a hybrid gravitational search algorithm (GSA) and pattern search (PS) technique is proposed for load frequency control (LFC) of multi-area power system. Initially, various conventional error criterions are considered, the PI controller parameters for a two-area power system are optimized employing GSA and the effect of objective function on system performance is analyzed. Then GSA control parameters are tuned by carrying out multiple runs of algorithm for each control parameter variation. After that PS is employed to fine tune the best solution provided by GSA. Further, modifications in the objective function and controller structure are introduced and the controller parameters are optimized employing the proposed hybrid GSA and PS (hGSA-PS) approach. The superiority of the proposed approach is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as firefly algorithm (FA), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), particle swarm optimization (PSO), hybrid BFOA-PSO, NSGA-II and genetic algorithm (GA) for the same interconnected power system. Additionally, sensitivity analysis is performed by varying the system parameters and operating load conditions from their nominal values. Also, the proposed approach is extended to two-area reheat thermal power system by considering the physical constraints such as reheat turbine, generation rate constraint (GRC) and governor dead band (GDB) nonlinearity. Finally, to demonstrate the ability of the proposed algorithm to cope with nonlinear and unequal interconnected areas with different controller coefficients, the study is extended to a nonlinear three unequal area power system and the controller parameters of each area are optimized using proposed hGSA-PS technique.     

Load Frequency Control of Multi-interconnected Renewable Energy Plants Using Multi-Verse Optimizer

A reliable approach based on a multi-verse optimization algorithm (MVO) for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic (PV) plants is presented in this paper. It has been applied for optimizing the control parameters of the load frequency controller (LFC) of the multi-source power system (MSPS). The MSPS includes thermal, gas, and hydro power plants for energy generation. Moreover, the MSPS is integrated with renewable energy sources (RES). The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES. HVDC link is utilized in shunt with AC multi-areas interconnection tie line. The proposed scheme has achieved robust performance against the disturbance in loading conditions, variation of system parameters, and size of step load perturbation (SLP). Meanwhile, the simulation outcomes showed a good dynamic performance of the proposed controller.