Dynamic grouping control of electric vehicles based on improved k-means algorithm for wind power fluctuations suppression

To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.

Research and Application of Probability Distribution of Wind Power Fluctuation Characteristics

The fluctuation characteristics is the inherent property of wind power.Through analysis of a large number of wind t＇anns based on measured data,we find it describes the best probability distribution of wind power fluctuation for the mixed Gauss distribution of two components,and try to carry out the physical interpretation of two components.Further discussion is between the probability distribution of fluctuating wind power time difference and whole relationship.It is found that the two have basic similarity.Through comparing the different time level data quantified losses the information of wind power fluctuation,quantitative determination of the degree of impact prediction.We can summarize and understand of wind power fluctuation,constructing instance from the wind farm construction and monitoring prediction two aspect recommendations to overcome the adverse effects of wind power fluctuations on the power grid operation.

Probability distribution of wind power volatility based on the moving average method and improved nonparametric kernel density estimation

In the process of large-scale,grid-connected wind power operations,it is important to establish an accurate probability distribution model for wind farm fluctuations.In this study,a wind power fluctuation modeling method is proposed based on the method of moving average and adaptive nonparametric kernel density estimation(NPKDE)method.Firstly,the method of moving average is used to reduce the fluctuation of the sampling wind power component,and the probability characteristics of the modeling are then determined based on the NPKDE.Secondly,the model is improved adaptively,and is then solved by using constraint-order optimization.The simulation results show that this method has a better accuracy and applicability compared with the modeling method based on traditional parameter estimation,and solves the local adaptation problem of traditional NPKDE.

Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density to assess wind resource.The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China.The air density at 100 m height is accurately calculated by using air temperature,pressure,and humidity.The spatial-temporal variation features of air density are firstly analyzed.Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,respectively.Usingρstoverestimates the annual wind energy production(AEP)in 93.6%of the study area.Humidity significantly affects AEP in central and southern China areas.In more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated.Usingρsitesignificantly reduces the estimation error in AEP.But AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in winter.Except for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρsite.Usingρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as well.The impacts of air density on assessing wind resource are almost independent of the wind turbine types.

Analysis on the Characteristics of Wind Power Output in Hainan Power Grid

It is of great importance to study the characteristics of wind power output for the healthy and secure & stable of power grid. Based on the actual operating data, the probability distribution of the power fluctuations of the wind farm in Hainanand the variation of wind power annual, seasonal, daily active output is analyzed. The study showed thatHainanProvincehas obvious seasonal variation of wind power output characteristics, higher levels of output of the year generally in winter or summer, spring and autumn to contribute small. The average wind power output will contribute to “low day and high night”, with certain peaking capacity. Shorter time scales, changes in the wind power to smaller amount, not to bring too much impact on system operation, while a long time fluctuations affect the scheduling and running on the grid.

Coordinated control strategy for wind power accommodation based on electric heat storage and pumped storage

To solve the severe problem of wind power curtailment in the winter heating period caused by ＂power determined by heat＂ operation constraint of cogeneration units, this paper analyzes thermoelectric load, wind power output distribution and fluctuation characteristics at different time scales, and finally proposes a two level coordinated control strategy based on electric heat storage and pumped storage. The optimization target of the first level coordinated control is the lowest operation cost and the largest wind power utilization rate. Based on prediction of thermoelectric load and wind power, the operation economy of the system and wind power accommodation level are improved with the cooperation of electric heat storage and pumped storage in regulation capacity. The second level coordinated control stabilizes wind power real time fluctuations by cooperating electric heat storage and pumped storage in control speed. The example results of actual wind farms in Jiuquan, Gansu verifies the feasibility and effectiveness of the proposed coordinated control strategy.

Analysis of Cooperation between Wind Power and Load Side Resources

Development of the intermittent energy is greatly promoted by change in energy, while consumption of large-scale intermittent energy is becoming a problem. With the development of smart grid technology, controllability of load side resources is becoming more and more important. Based on the wave characteristics of wind power, this paper indicates that wind energy has continuous output characteristics on the hour-time scale. Through analysis on loads characteristic of industry, public facility and resident, this paper gets comprehensive response of load side resources. Considering characteristics of wind power output, combined with different load side resources and DR program, this paper suggests cooperation between wind power and load side resources on different time scales.

计及SOC自恢复的混合储能平抑风电功率波动控制

混合储能系统能够较好地应对复杂的风电波动,有效地提高电网的稳定性和安全性。在混合储能平抑风电功率波动的典型应用场景下,该文首先提出一种计及荷电状态(SOC)自恢复的混合储能平抑风电功率波动控制方法,在满足风电平抑需求的情况下,通过模型预测控制快速调节储能在平抑功率过程中的荷电状态,提高储能持续稳定运行能力;然后,为提高混合储能系统协调运行能力,设计了加权滑动平均(WMA)-模糊控制策略对超级电容和蓄电池功率进行动态分配;最后,结合实际风电功率数据,通过仿真验证了所提策略能有效平衡储能寿命和平抑风电波动的矛盾,能充分考虑两种储能设备的特性差异并提高功率分配的合理性。

基于二维动态减载和双层MPC的风储联合调频与功率优化分配

风机可以通过减载控制提供调频备用功率,但存在弃风量大的问题。为此,结合储能装置,设计了考虑风速分区与储能荷电状态(SOC)的二维动态减载策略,在提供充足调频备用功率的同时减小了弃风功率。在此基础上,结合双层模型预测控制(MPC)架构,提出了计及机组转矩波动的风储联合调频控制策略,上层MPC将风电场视作整体,通过协调风储出力提升调频效果;下层MPC通过风电场内的功率优化分配以抑制机组的转矩波动,保证调频性能的同时提高了机组运行稳定性。通过仿真分析验证了所提策略的有效性,结果表明该减载策略具有更高的风能利用率,且在调频过程中通过机组的功率优化分配减小了机组的转矩波动,提高了机组运行稳定性。

基于减载风电和储能的双层模型预测控制风电波动平抑策略

储能在平抑风电功率快速波动过程中频繁地充放电和过高地放电将深度影响储能寿命。为此,提出一种减载风电和储能协同平抑风电功率的方法,利用减载风电出力来减小储能充放电切换次数和放电深度。建立风储系统模型,利用双层模型预测控制优化方法:上层控制基于风功率预测数据进行滚动优化,在满足风电并网波动要求基础上,以储能和减载风电总出力最小为目标函数,通过模型预测控制方法求得储能和减载风电总功率;下层控制以储能功率变化率最小和出力能力最大为目标函数,通过模型预测控制方法分配储能和减载风电出力。最后对某风电场进行仿真研究。结果表明,所提控制策略使储能寿命和出力能力得到有效提升。

周期性脉动源对风力机功率的影响

针对WindPACT1.5 MW机组,通过大涡模拟探究风轮5°仰角时周期性脉动源(仰角、塔影效应、偏航、风剪切)对风力机总功率的影响,并结合逆叶素动量理论,进一步分析功率与升力系数之间的联系。结果表明,仰角、塔影效应加仰角与偏航加仰角均使得风力机总功率产生“3P”的波动规律,而风剪切加仰角使得总功率产生“锯齿状”的高频率波动规律,其中偏航是总功率损失的主要因素,塔影效应是功率波动的主要因素,且发现升力系数波动规律与功率单周期内的波动规律相似。

基于敏感频段识别的高风电渗透率电力系统频率特性研究

针对风电功率波动性显著的问题,展开了基于敏感频段识别的高风电渗透率电力系统频率特性的研究。分析了单机电力系统在有功功率扰动下的频率响应特性,构建了包含风电的多机电力系统PSASP暂态仿真模型,介绍了多机电力系统敏感频段的识别方法。通过仿真分析,探讨了敏感频段下风功率波动对多机电力系统频率特性的影响。研究结果表明,多机电力系统中确实存在敏感频段,并且随着风电渗透率的不断提升,系统的调频能力和抵御风功率波动的能力会逐渐减弱。该研究成果为更全面地评估风电系统的敏感频段特性提供了依据,同时也为提升风电功率预测精度提供了技术参考。

考虑通信延时的可再生能源与火力发电耦合系统无功控制优化

在可再生能源与火力发电耦合系统中,风电出力波动和远端故障扰动都会引起系统电压越限。文章在考虑通信延时的基础上,以耦合系统各节点电压偏差为量化指标,分析了耦合系统无功控制对电压稳定性的影响,提出了一种以静止无功发生器(Static Var Generator,SVG)和风电机组作为无功调节资源的耦合系统双层无功控制优化策略。该策略上层为SVG无功调节设备,以耦合系统各节点电压偏差综合最小为目标,构建了系统整体功率因数优化模型。下层针对电压偏差大的节点,利用节点附近的风电机组为无功调节设备,以系统电压偏差和网损综合最优为目标,构建了风电机组无功优化模型,采用Ybus与LinWPSO相结合的算法求解优化模型,并得出风电机组无功参考值。案例仿真结果表明,文章所提的双层无功控制策略可充分发挥风电机组无功调节潜力,兼顾到耦合系统的电压波动和网损,减少可再生能源功率波动对耦合系统的扰动,提高了耦合系统的电压稳定性。

风光互补发电系统混合储能系统容量优化方法研究

风光互补发电系统受风光资源影响发电功率波动较大,配置适当的储能系统可提高新能源发电的消纳能力和电能质量。针对风光互补发电系统储能容量优化配置问题,将运行投入成本作为优化目标,提出以抽水蓄能为基础,蓄电池和超级电容参与的混合储能系统模型。该储能模型以跟踪负荷曲线作为平抑目标函数,利用集合经验模态分解和滑动平均法,对抽水蓄能机组、蓄电池和超级电容设备进行功率分配。建立了风光发电系统模型,利用带免疫的粒子群算法对储能配置容量进行寻优求解。计算结果表明,所提基于抽水蓄能的混合储能容量优化模型,对发电系统输出功率波动情况改善明显,电能消纳能力和运行经济性有所提高。

计及多储能单元出力水平的风功率波动平抑控制方法

在风电场侧配置电池储能是缓解风电功率波动、提高风电可调控性的有效途径。为满足风功率波动平抑要求,提出了一种计及多储能单元出力水平的风功率波动平抑控制方法,充分考虑多储能单元实时出力能力,在兼顾功率平抑目标的同时实现减小储能电池能量调用、各储能单元充放电切换次数、放电深度及荷电状态波动区间。首先分析了滤波时间常数对风功率平抑效果以及储能功率分配方法对各单元荷电状态变化的影响;其次引入超短期风功率预测,根据风功率预测数据建立滤波时间常数优化模型,得到滤波时间常数最优解以及最小储能功率指令;然后分析了各储能单元出力水平与功率平抑需求的影响,进一步提出了一种分层复合式储能单元功率分配方法,实现了多储能单元的功率指令分配,避免了各储能单元频繁与过度充放电,有利于延长使用寿命;最后以湖南省某实际风电场为例,通过实际算例验证了所提方法的有效性。

新疆达坂城风区顺风向脉动风功率谱

为研究新疆乌鲁木齐所处达坂城风区的复杂脉动风环境,基于实测风场风速数据分析并拟合了该风区的顺风向脉动风功率谱。结果表明:以反比例函数拟合山区峡谷地形平均风速与湍流强度的关系误差较小;山区峡谷地形湍流积分尺度分布较离散,但整体随平均风速的增大而增大;考虑地形系数的Kaimal修正谱在含能区和惯性子区间能较好地表征实测谱,在耗能区选用三参数拟合描述实测谱效果良好;选用过渡函数来描述惯性子区间与耗能区接触区域的功率谱,拟合效果较为理想。可见达坂城风区具有特殊顺风向脉动风特性,以修正谱和拟合谱分段构成的函数模型可用于表征该风区顺风向脉动风功率谱。

改进的自适应小波包风电波动平滑控制策略

针对传统自适应小波包风电功率波动平滑技术存在过度平滑以及储能系统负担加重等问题,提出一种改进的自适应小波包风电功率平滑控制策略。首先,根据不同时间段风电功率波动特性,合理规划滤波时间尺度,并确定满足系统控制要求的最小滤波尺度。其次,利用自适应小波包分解滤波尺度内的风电功率,获得期望并网功率与波动功率。之后,采用由双储能电池与超级电容器组成的混合储能系统对波动功率进行平抑。最后,分析改进的平滑策略在降低储能系统负担方面的优势,并对储能系统的运行寿命进行评估。结果表明,在保证风电功率波动有效平滑的前提下,该策略既能降低储能系统的负担,又能延长其运行寿命。

基于随机预测理论的双馈风电机组参与电网调频控制策略

随着电力系统中的风电渗透率不断提高,系统中风电功率的随机波动给电网频率稳定性带来巨大挑战。针对上述问题,该文提出基于机会约束随机模型预测控制的附加功率调频控制策略。首先,综合考虑系统中风速及负荷的实时随机波动问题,建立风电并网系统频率响应模型;其次,以系统频率变化及风电输出功率波动最小为控制目标建立期望目标函数,并将机会约束纳入随机最优化模型中;最后,根据随机扰动的分布信息或坎泰利不等式,结合状态反馈控制律求解随机最优化模型,得到当前时刻的最优控制律。利用MATLAB/Simulink搭建风电并网系统进行仿真验证,结果表明,所提策略能够有效抑制风电功率波动及系统频率变化,提高了电网的频率稳定性。

考虑风电运行轨迹与场景划分的场级主动调压优化控制策略

传统风电场跟随主站电压指令调节的方式容易导致站内无功源频繁波动、站内无功裕度不足,影响风电场的调压能力。为此提出了一种考虑风电运行轨迹与场景划分的场级主动调压优化控制策略。首先,基于风电场功率预测数据和有功–电压灵敏度曲线,绘制并网点电压波动轨迹,结合AVC子站接收到的电压指令,协调风机和SVG的无功输出,有效降低了无功设备的调节频次。其次,根据电压跌落幅度划分详细运行场景,通过调整SVG的控制模式,有效抑制了电网电压的大幅波动。最后,构建了包含AVC功率控制器的仿真测试平台,验证对比了所提方法相对于传统风电场AVC控制策略在降低无功调节频次、提升无功裕度、主动电压支撑方面的效果,为实现风电场主动调压提供了新的解决思路。

风电与多端柔性直流输电系统自适应分频协调控制策略研究

针对风电接入多端柔性直流输电系统,为充分发挥风电参与系统调频能力,解决交直流并网故障引起的直流系统电压和交流电网频率波动问题,本文在现有下垂控制基础上提出了附加自适应分频控制策略。将直流电压偏差信号作为控制器输入信号,通过一阶低通滤波器将输入信号分为高频波动信号和低频波动信号,根据风电和直流输电系统各自调频能力的不同,将高频波动信号附加在风电机组转子侧换流器有功功率控制环,低频波动信号附加在直流有功功率控制外环,同时将电压源换流器(voltage source converter,VSC)实时功率裕度与直流电压变化量引入分频控制,实时调整低通滤波器的时间常数,动态调整功率输出,提高系统稳定性。在PSCAD/EMTDC中搭建仿真模型,仿真验证所提控制策略的有效性。