A Control Strategy for Smoothing Active Power Fluctuation of Wind Farm with Flywheel Energy Storage System Based on Improved Wind Power Prediction Algorithm

The fluctuation of active power output of wind farm has many negative impacts on large-scale wind power integration into power grid. In this paper, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm to realize smooth control of wind power output. Based on improved wind power prediction algorithm and wind speed-power curve modeling, a new smooth control strategy with the FESS was proposed. The requirement of power system dispatch for wind power prediction and flywheel rotor speed limit were taken into consideration during the process. While smoothing the wind power fluctuation, FESS can track short-term planned output of wind farm. It was demonstrated by quantitative analysis of simulation results that the proposed control strategy can smooth the active power fluctuation of wind farm effectively and thereby improve power quality of the power grid.

A PV powered shunt active power filter for power quality improvement

This paper deals with power quality improvement using a three-phase active power filter(APF) connected to a PV power system. A direct power control(DPC) approach is proposed to eliminate harmonic current caused by any nonlinear loads and at the same time guarantees the delivery of a part of the load request from the same PV source. A boost converter is used for maximum power point(MPP) tracking purposes under various climate conditions through a fuzzy logic technique. The suggested study is tested under a MATLAB/Simulink environment. The obtained results depict the efficacy of the proposed procedures to meet the IEEE 519-1992 standard recommendation on harmonic levels.

Design and Application of Wind Power Peak Control Technology

Wind power control technology is an important part of intelligent control in wind farms. By the automatic calculation and implementation of control strategy, problems such as imprecise of manual control scheduling, slow adjust rate, heavy workload, etc. have been solved. It can improve the capacity of wind power grid, and it also has the important meaning to the safe and stable operation of power grid. This paper introduces wind power control system from certain aspects such as control mode, control principle, and so on.

Fuzzy Logic Controlled Dual Active Bridge Series Resonant Converter for DC Smart Grid Application

Over the last few years, smart grids have become a topic of intensive research, development and deployment across the world. This is due to the fact that, through the smart grid, stable and reliable power systems can be achieved. This paper presents a fuzzy logic control for dual active bridge series resonant converters for DC smart grid application. The DC smart grid consists of wind turbine and photovoltaic generators, controllable and DC loads, and power converters. The proposed control method has been applied to the controllable load＇s and the grid side＇s dual active bridge series resonant converters for attaining control of the power system. It has been used for management of controllable load＇s state of charge, DC feeder＇s voltage stability during the loads and power variations from wind energy and photovoltaic generation and power flow management between the grid side and the DC smart grid. The effectiveness of the proposed DC smart grid operation has been verified by simulation results obtained by using MATLAB and PLECS cards.

Hierarchical Cluster Coordination Control Strategy for Large-scale Wind Power Based on Model Predictive Control and Improved Multi-time-scale Active Power Dispatching

The grid-connection of large-scale and high-penetration wind power poses challenges to the friendly dispatching control of the power system.To coordinate the complicated optimal dispatching and rapid real-time control,this paper proposes a hierarchical cluster coordination control(HCCC)strategy based on model predictive control(MPC)technique.Considering the time-varying characteristics of wind power generation,the proposed HCCC strategy constructs an improved multitime-scale active power dispatching model,which consists of five parts:formulation of cluster dispatching plan,rolling modification of intra-cluster plan,optimization allocation of wind farm(WF),grouping coordinated control of wind turbine group(WTG),and real-time adjustment of single-machine power.The time resolutions are sequentially given as 1 hour,30 min,15 min,5 min,and 1 min.In addition,a combined predictive model based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),wavelet thresholding(WT),and least squares support vector machine(LSSVM)is established.The fast predictive feature of this model cooperates with the HCCC strategy that effectively improves the predictive control precision.Simulation results show that the proposed HCCC strategy enables rapid response to active power control(APC),and significantly improves dispatching control accuracy and wind power accommodation capabilities.

Coordinated voltage control of renewable energy power plants in weak sending-end power grid

The utilization of renewable energy in sending-end power grids is increasing rapidly,which brings difficulties to voltage control.This paper proposes a coordinated voltage control strategy based on model predictive control(MPC)for the renewable energy power plants of wind and solar power connected to a weak sending-end power grid(WSPG).Wind turbine generators(WTGs),photovoltaic arrays(PVAs),and a static synchronous compensator are coordinated to maintain voltage within a feasible range during operation.This results in the full use of the reactive power capability of WTGs and PVAs.In addition,the impact of the active power outputs of WTGs and PVAs on voltage control are considered because of the high R/X ratio of a collector system.An analytical method is used for calculating sensitivity coefficients to improve computation efficiency.A renewable energy power plant with 80 WTGs and 20 PVAs connected to a WSPG is used to verify the proposed voltage control strategy.Case studies show that the coordinated voltage control strategy can achieve good voltage control performance,which improves the voltage quality of the entire power plant.

Jointly improving energy efficiency and smoothing power oscillations of integrated offshore wind and photovoltaic power: a deep reinforcement learning approach

This paper proposes a novel deep reinforcement learning(DRL)control strategy for an integrated offshore wind and photovoltaic(PV)power system for improving power generation efficiency while simultaneously damping oscilla-tions.A variable-speed offshore wind turbine(OWT)with electrical torque control is used in the integrated offshore power system whose dynamic models are detailed.By considering the control system as a partially-observable Markov decision process,an actor-critic architecture model-free DRL algorithm,namely,deep deterministic policy gradient,is adopted and implemented to explore and learn the optimal multi-objective control policy.The potential and effectiveness of the integrated power system are evaluated.The results imply that an OWT can respond quickly to sudden changes of the inflow wind conditions to maximize total power generation.Significant oscillations in the overall power output can also be well suppressed by regulating the generator torque,which further indicates that complementary operation of offshore wind and PV power can be achieved.

UPFC setting to avoid active power flow loop considering wind power uncertainty

The active power loop flow(APLF)may be caused by impropriate network configuration,impropriate parameter settings,and/or stochastic bus powers.The power flow controllers,e.g.,the unified power flow controller(UPFC),may be the reason and the solution to the loop flows.In this paper,the critical existence condition of the APLF is newly integrated into the simultaneous power flow model for the system and UPFC.Compared with the existing method of alternatively solving the simultaneous power flow and sensitivity-based approaching to the critical existing condition,the integrated power flow needs less iterations and calculation time.Besides,with wind power fluctuation,the interval power flow(IPF)is introduced into the integrated power flow,and solved with the affine Krawcyzk iteration to make sure that the range of active power setting of the UPFC not yielding the APLF.Compared with Monte Carlo simulation,the IPF has the similar accuracy but less time.

基于主动尾流控制的风电机群协同优化调度

针对机组间尾流效应严重影响风电机组发电效率的问题,提出了风电机组安全偏航约束计算方法、尾流特性混合半机理建模方法以及风电机群多目标协同优化调度方法。基于FAST.FARM平台完善了多自由度可控机组与尾流的动态交互集成仿真环境,对比分析了2台机组串列式排布以及华东地区某海上风电场7台机组实际排布下的协同运行优化性能。结果表明:所建立的集成仿真模型能够合理表征风电机群与空气流场的多领域动态交互特性,所提方法能够有效提升风电机群发电效能,促进经济效益、资源利用和成本控制的均衡优化。

新能源场站快速有功控制及频率支撑技术综述

以光伏/风电为代表的新能源高比例并网降低了电力系统的惯量水平和频率支撑能力,频率稳定问题成为当前电网安全稳定和新能源高效消纳的核心问题之一。发展新能源发电并网机组单元和场站的快速有功频率响应和主动支撑能力是当前的研究热点。该文以“单机快速有功控制-场站快速有功控制-场站快速频率支撑”为主线,梳理光伏/风电的快速有功控制及频率支撑发展现状,分析频率检测、通信延时和控制响应模式等因素对光伏/风电场站频率响应快速性的影响,指出风电机组的机械载荷约束、风电场百毫秒级有功控制、场站的调频响应模式选择和优化、暂态有功无功协同控制是提升新能源发电单元和场站的快速有功频率响应能力的4个关键问题,最后对未来的重点研究方向进行展望和讨论。

基于D-分割法的直流变换器遗传自抗扰控制器设计

针对光伏发电系统中DC-DC变换器由于负载和工作环境条件变化等扰动引起的输出波动问题,提出一种基于D-分割法的直流变换器遗传自抗扰控制器(ADRC)设计方法。该方法适用于设计光伏发电领域中的双向DC-DC变换器,采用D-分割法获得满足闭环系统鲁棒稳定的ADRC控制器参数范围;利用具有全局寻优能力的遗传算法,按综合性能指标在该范围内进行参数寻优。实验结果表明,所提基于D-分割法的直流变换器遗传自抗扰控制器设计方法能有效抑制微网母线侧的电压波动和负载突变,提高控制器的鲁棒性,增强光伏发电系统的动态响应性能和抗干扰能力。

双绕组感应发电机交直流集成发电系统的自抗扰控制策略

针对双绕组感应发电机交直流集成发电系统,为实现简单易调、性能优越、负载适应力强的发电控制,该文提出一种基于线性自抗扰控制器的交直流电压控制策略,通过交流电压和直流电压与控制绕组和功率绕组的传递函数模型,构建交直流电压的线性扩张状态观测器,同时对交流电压有效值、直流电压和电压扰动进行观测,并利用电压和扰动观测值设计线性误差反馈控制律,对交直流电压进行控制。最后,通过仿真和实验验证该控制策略提高电压扰动抑制能力和负载适应性,同时各模块参数可独立设计、控制器结构简单,避免需要较多传感器及降低调参难度。

基于改进信息最大化生成对抗网络的风光出力场景可控生成方法

基于深度学习的场景生成方法能够自适应挖掘历史数据中高维非线性特征,在风光出力的不确定性建模中得到了广泛应用。然而,基于深度学习的场景生成方法多为黑盒模型,存在可解释性差、生成不可控等问题。为此,提出了一种基于改进信息最大化生成对抗网络(information maximizing generative adversarial nets,Info GAN)的风光出力场景生成方法。该方法在目标函数中增加了基于互信息的正则化项,最大化控制编码与生成场景之间的互信息,无监督学习控制编码与生成场景统计特征的映射关系,并引入Gumbel-Softmax分布提高了生成场景的质量。结合风电场和光伏电站的真实数据进行了算例分析,算例结果表明,所提方法不仅能准确描述风光出力不确定性,而且具有可解释性,能够可控生成指定风光出力场景。

基于虚拟同步机的风-光-储并网系统自适应功频控制策略

风-光-储系统通过虚拟同步发电机(virtual synchronous generator,VSG)并网时,其运行工况变化将引起系统功频波动。针对这一问题,提出一种VSG自适应惯量阻尼功频控制策略。首先,建立VSG的数学模型及功率小信号模型,分析虚拟参数变化对系统稳定性的影响;然后,依据系统受扰时的功角曲线分析惯量阻尼的动态特性,设计了一种分段线性调整函数,并给出参数选取原则;最后,在Matlab/simulink平台中搭建仿真模型验证。结果表明,在工况变化情况下,采用VSG自适应控制的风光储并网系统功频响应得到了改善,相比传统VSG控制具有更好的动态调节性能。

基于卡尔曼滤波的改进ADRC风电制动器控制策略研究

为了提高风电制动器的抗干扰能力和控制精度,在传统三闭环系统的基础上,提出改进自抗扰控制并融合卡尔曼滤波算法.在扩张状态观测器中引入速度跟踪情况,将传统的“大带宽、小误差”改进为“小带宽、小误差”,提高观测器的观测效率.在误差反馈控制率中引入新型指数趋近律的滑模控制,增强控制效果.在电流环中引入卡尔曼滤波算法,降低电流噪声.通过MATLAB/Simulink建立风电制动系统的数学模型,与传统自抗扰控制策略和PID控制策略进行对比分析.结果表明:改进后的控制策略提高了响应速度,降低了启动转矩和电流噪声;制动器在不同工况下均展现出来良好的控制效果和抗干扰能力,提升了系统的鲁棒性和动态性能.

基于自抗扰的直驱风电机组强迫振荡抑制研究

风剪切和塔影效应会导致直驱式风电机组产生强迫功率振荡,影响系统的安全稳定运行。因此,提出了一种基于自抗扰控制的虚拟惯量控制方法,该方法通过扩张状态观测器观测估计系统扰动量,同时利用跟踪微分器调整系统频率的参考值,优化风电机组控制功率。仿真结果表明,相比传统的虚拟惯量控制,所提方法具有更好的抗干扰性,能更有效地对扰动进行观测估计并补偿,达到抑制直驱式风电并网系统强迫振荡的目的。

Performance of PI controller for control of active and reactive power in DFIG operating in a grid-connected variable speed wind energy conversion system

Due to several factors, wind energy becomes an essential type of electricity generation. The share of this type of energy in the network is becoming increasingly important. The objective of this work is to present the modeling and control strategy of a grid connected wind power generation scheme using a doubly fed induction generator （DFIG） driven by the rotor. This paper is to present the complete modeling and simulation of a wind turbine driven DFIG in the second mode of operating （the wind turbine pitch control is deactivated）. It will introduce the vector control, which makes it possible to control independently the active and reactive power exchanged between the stator of the generator and the grid, based on vector control concept （with stator flux or voltage orientation） with classical PI controllers. Various simula- tion tests are conducted to observe the system behavior and evaluate the performance of the control for some optimization criteria （energy efficiency and the robustness of the control）. It is also interesting to play on the quality of electric power by controlling the reactive power exchanged with the grid, which will facilitate making a local correction of power factor.

基于LADRC和准PR控制的风电并网逆变器控制策略

为了稳定风电并网逆变器直流母线电压的波动,提高其动态响应速度并减少并网电流中的谐波含量,本文提出了LADRC+准PR双环控制策略.首先根据两电平风电并网逆变器的拓扑结构建立其数学模型;然后,根据数学模型设计电压外环二阶LADRC控制器和电流内环准PR控制器代替传统的PI控制器,同时对两种控制器的参数进行了设计并整定;最后,在Matlab软件中构建仿真模型,进行了仿真分析和波形对比.结果表明:相较于传统的双闭环PI控制策略,新型控制策略不仅能够快速地稳定直流母线电压,而且交流侧电流的总谐波失真小;并且在电网电压发生扰动的工况下,仍有较好的控制性能.综上所述,基于LADRC和准PR控制的风电并网逆变器控制策略具有较好的抗扰性和优越的鲁棒性.

ADMM-based Distributed Active and Reactive Power Control for Regional AC Power Grid with Wind Farms

A distributed active and reactive power control(DARPC)strategy based on the alternating direction method of multipliers(ADMM)is proposed for regional AC transmission system(TS)with wind farms(WFs).The proposed DARPC strategy optimizes the power distribution among the WFs to minimize the power losses of the AC TS while tracking the active power reference from the transmission system operator(TSO),and minimizes the voltage deviation of the buses inside the WF from the rated voltage as well as the power losses of the WF collection system.The optimal power flow(OPF)of the TS is relaxed by using the semidefinite programming(SDP)relaxation while the branch flow model is used to model the WF collection system.In the DARPC strategy,the large-scale strongly-coupled optimization problem is decomposed by using the ADMM,which is solved in the regional TS controller and WF controllers in parallel without loss of the global optimality.The boundary information is exchanged between the regional TS controller and WF controllers.Compared with the conventional OPF method of the TS with WFs,the optimality and accuracy of the system operation can be improved.Moreover,the proposed strategy efficiently reduces the computation burden of the TS controller and eliminates the need of a central controller.The protection of the information privacy can be enhanced.A modified IEEE 9-bus system with two WFs consisting of 64 wind turbines(WTs)is used to validate the proposed DARPC strategy.

面向电网最大频率偏差的风电机组短时频率支撑最优策略与机理

当电网出现有功缺额并导致频率跌落时,风电机组可以通过释放自身轴系动能为电网提供短时频率支撑(short-term frequency support,STFS)。如何利用有限的风电机组轴系动能最大限度地支撑电网频率,是当前研究的热点问题。针对风电机组可释放动能和电网频率变化率约束下的电网最大频率偏差最小化问题,该文提出一种基于有功功率互补控制(active-power complementation control,ACC)的风电机组STFS策略,揭示STFS过程中风电机组的最小动能释放机理,并证明采用ACC释放全部轴系动能的STFS策略为上述问题的最优解。最后,基于含风电的电网动模实验平台的实验结果验证该文提出STFS策略的可行性与频率支撑效果。