A novel coordinated control strategy considering power smoothing for a hybrid photovoltaic/battery energy storage system

This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.

A Unified Control of Super-capacitor System Based on Bi-directional DC-DC Converter for Power Smoothing in DC Microgrid

To improve the equivalent inertia of DC microgrids(DCMGs),a unified control is proposed for the first time for a bi-directional DC-DC converter based super-capacitor(SC)system,whereby power smoothing and SC terminal voltage regulation can be achieved in a DCMG simultaneously.The proposed control displays good plug-and-play features using only local measurements.For quantitative analysis and effective design of the critical parameter of unified control,two indices,equivalent power supporting time and inertia contributed by the unified controlled SC system,are introduced firstly.Then,with a simple but effective reduced-order model of a DCMG,analytical solutions are obtained for the two indices.In addition,a systematic design method is presented for the proposed unified control.Finally,to verify the proposed unified control,a switching model is developed for a typical DCMG in PSCAD/EMTDC,and theoretical analyses are conducted for different operating conditions.

Wind turbines output power smoothing using embedded energy storage systems

The ability of an energy storage system to improve the performance of a wind turbine(WT)with a fully rated converter was evaluated,where the energy storage device is embedded in the direct current(dc)link with a bidirectional dc/dc converter.Coordinated dc voltage control design of the line-side converter and the energy storage dc/dc converters was proposed using a common dc voltage measurement for smoothing the output power.A transfer function and Bode diagram were introduced to analyze the system performance with different control parameters.MATLAB/Simulink simulations are presented to demonstrate the effectiveness of the proposed methods.It was found that the proposed methods smooth the power output from the WT to the grid and thus improve the quality of the generated power.

Master-slave wave farm systems based on energy filter with smoothed power output

Wave energy is an important renewable energy source. Previous studies of wave energy conversion(WEC) have focused on the maximum power take-off(PTO) techniques of a single machine. However, there is a lack of research on the energy and power quality of wave farm systems. Owing to the pulsating nature of ocean waves and popular PTO devices, the generated electrical power suffers from severe fluctuations. Existing solutions require extra energy storage and overrated power converters for wave power integration. In this study, we developed a master-slave wave farm system with rotor inertia energy storage; this system delivers self-smoothed power output to the grid and reduces the number of converters. Two control methods based on the moving average filter(MAF) and energy filter(EF) are proposed to smooth the output power of wave farms. RTDS simulations show that the proposed systems and control methods facilitate simple and smooth grid integration of wave energy.

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.

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.

动力换挡变速器液压换挡过程仿真与试验研究

为满足重型车辆换挡动力不中断、换挡平顺的需求,本文设计了重型车辆动力换挡变速器换挡控制系统,利用AMESim软件,从换挡液压系统出发,对变速器换挡模块进行搭建分析,考察了换挡过程中液压系统油压特性、整车车速、冲击度以及离合器C1/制动器C2滑摩功动态特性。仿真结果表明系统能够满足动力换挡的要求;此外,针对所设计的液压换挡系统进行了台架试验,对仿真和试验的结果进行对比,仿真结果表明:目标车速响应时间提前了2.67 s, C2油压响应时间提前0.09 s且切换时间减少了13%,C1油压响应滞后0.07 s且出现压力超调量;试验结果显示:油压稳定性较差且转矩曲线响应时间提前0.06 s,并且冲击度变化曲线振幅较大。试验结果与仿真结果基本一致,验证了仿真结果的准确性。

考虑生产安全的工业园区联络线功率平滑策略

高比例新能源接入工业园区已成为高耗能工业负荷低碳转型的主要途径,而联络线功率剧烈频繁波动是园区低碳转型的关键问题.因此,提出一种考虑生产安全的工业园区联络线功率平滑策略.首先,分析电解铝和矿热炉的可控设备控制模型,构建基于联络线功率波动反馈的工业负荷功率闭环反馈控制模型.考虑工业生产核心影响因素,构建温度状态指标模型,形成考虑工业生产核心因素的典型工业负荷需求侧响应惩罚成本模型,并以工业生产的惩罚成本最小为优化目标,将控制目标分配至各工业负荷.最后,构建基于云南电网文山区域网架的MATLAB在线计算和RTDS仿真实时交互算例,结果表明,该算法自适应更新生产设备温度,有效降低功率调节对生产的影响,且联络线购电成本可降低36.4%.

基于层次聚类分场景的光伏汇聚趋势量化方法

持续功率曲线能反映长时间波动特性规律,通过研究已建设光伏集群持续功率曲线,建立预测模型揭示不同规模集群的汇聚演化规律,最终得到待建光伏集群的持续功率曲线。首先,利用层次聚类算法确定光伏集群汇聚规模的分层顺序,得到装机容量逐层递增的光伏集群,并提出汇聚效应指标验证顺序的有效性;其次,为了更好地判断和预测光伏持续功率曲线的变化趋势,对持续功率曲线进行出力场景划分;最后,为避免单一模型预测偏差,在各出力场景下,通过改进的信息熵组合预测模型掌握汇聚过程中规模演变规律,完成规划待建设集群持续功率曲线的预测。利用河北某地区实测数据仿真结果表明:验证聚类方法得到的集群分层顺序更能体现汇聚效应,并有效提高预测精度;出力场景划分准确刻画集群持续功率曲线汇聚趋势;通过模型对比表明分场景下改进信息熵组合预测模型更能精确完成待建光伏集群持续功率特性的量化分析。

基于机网变流器协同的波浪发电系统控制策略

为实现波浪发电系统的高效平稳入网,以直驱式波浪发电装置为例,建立其数学模型和并网结构。将装置输出功率分解为平均分量和波动分量,从发电系统主动式控制的角度,进一步提出了阻尼控制和阻尼弹力控制下的最优策略,以使其高效运行。通过直流侧储能配置及机侧和网侧变流器的协同控制,实现电能的平稳入网。仿真结果表明,阻尼弹力控制较于阻尼控制,发电效率更高同时波动更大,直流侧储能及机网侧协同控制可有效平抑功率波动,为波浪发电系统的入网控制设计提供参考。

基于活动性检测动态估计噪声的心音降噪算法

针对基于小波分解和最优改进对数幅度谱估计的心音降噪算法存在噪声残留和心音失真的问题,提出一种基于心音活动性检测(HSAD)动态估计噪声的心音降噪算法。通过设计的HSAD判断当前心音帧是否为基础心音帧(FHS),根据判断结果分别采用改进最小值控制递归平均(IMCRA)算法和递归平滑算法对噪声功率进行动态估计与更新,采用非因果先验信噪比,实现心音信号的降噪。实验结果表明,提出算法能更好在提升降噪性能的同时,降低FHS的失真。

基于瞬时功率镜像补偿的斜坡式重力储能系统功率平滑控制策略

针对重力储能系统因离散质量块切换引起的输出功率波动问题,提出了一种基于瞬时功率镜像补偿的功率平滑控制策略。首先介绍了斜坡式重力储能系统的工作原理,分析引起系统功率波动的原因;然后设计了抑制功率波动的系统结构以及功率平滑控制策略,并以11 kW的斜坡式重力储能系统为例,对系统结构参数进行理论计算;最后构建斜坡式重力储能系统仿真模型,分析了系统在质量块交替过程中的暂态波动特性。结果表明,应用所提方法,质量块在交替过程中可提供连续稳定的机械功率,较好地平滑重力储能系统的输出功率,验证了该方法的有效性。

适用于海洋动态观测设备嵌入式系统的低功耗管理预测模型

能耗是制约海洋设备在水下工作时长的关键因素。为进一步降低海洋动态观测设备嵌入式系统的动态功耗,本文针对前人提出的用于预测空闲时间的指数平滑算法所存在的权重系数基于凑数法确定、算法难以适应大波动等问题,设计了一种新的权重系数,并构建了一种自适应的低功耗管理预测模型。当模型检测到预测的空闲时间超过工作和休眠状态切换的时间阈值后,中央处理器关停系统的部分外设,使系统进入低功耗休眠状态。仿真和单片机实验均表明,本文提出的低功耗管理预测模型能够有效地提高对处理器工作的空闲时间预测的准确性,且面对突发状况具有良好的自适应性,可显著降低嵌入式系统的功耗,有效延长设备的工作时间。

基于EWT的分布式光储PCC功率波动自适应平抑方法

分布式光伏在交流侧公共连接点(point of common coupling,PCC)汇流的功率有较大的随机性与波动性,影响电网的稳定运行。为此,提出了基于经验小波变换(empirical wavelet transform,EWT)的分布式光储PCC功率自适应平抑方法。首先,针对混合储能(hybrid energy storage system,HESS)与分布式光伏接入PCC的典型场景,在分析EWT自适应处理波形的特点后,结合功率波动率与储能元件的响应特性,对PCC的光伏原始汇流功率进行EWT分解与优化修正,实现HESS的功率初级分配。之后为避免HESS的荷电状态(state of charge,SOC)频繁越限,提出了一种主动功率补偿的SOC控制策略,通过主动改变储能的参考信号使其SOC在安全范围内工作。结合实际数据的仿真验证表明,该平抑方法能够自适应地实现光伏出力的合理分解与功率分配,在延长储能使用寿命的同时有效满足并网功率波动的要求,为平抑光伏输出功率波动提供了新思路。

基于等价输入干扰的分布式光伏电源出力控制策略

分布式电源能够改善配电网潮流分布,使得电力系统具有更高的能源利用率以及灵活性,然而分布式电源的不合理出力则难以充分发挥自身优势,并且死区效应、电网电压畸变及系统参数不确定性等不确定性扰动也会对电力系统的可靠性构成严重威胁。针对此问题,提出了基于改进的等价输入干扰方法(improvedequivalentinputdisturbance,IEID)的分布式电源出力控制方法。其中上层优化结构以配电网网损最小为目标,建立配电网优化降损模型并求解得到分布式电源出力值;下层控制结构基于所提IEID设计分布式电源控制策略,把模型耦合项、死区效应、网压畸变及系统参数不确定性等干扰对系统输出的影响等价到输入通道上,并对其进行估计和补偿,能够有效地抑制未知扰动并高精度跟踪上层输出的出力值,极大地改善并网电能质量。以某21节点真实居民配电网为算例,仿真结果表明所提方法具有较好的扰动抑制能力,能够自主平稳出力,降低配电网网损。

混合超级电容器应用于光伏储能的研究

光伏发电具有波动性和间歇性的特点,无法直接向负载提供稳定的电能,而混合超级电容器组成的储能系统能提供适中的能量密度和较高的功率密度,且使用寿命长,能更好消纳光伏发电,提高储能效率和电能质量。搭建混合超级电容器(HSC)光伏储能系统和锂离子电池(LIB)光伏储能系统,比较不同天气条件下的电压波动以及电量变化。在晴天条件下,HSC模组的充电电量比LIB模组提高了7.8%,而两模组的电压波动均不大。在多云条件下,HSC模组的充电电量比LIB模组提高了10.4%,且HSC模组的电压波动程度比LIB模组小。在阴天条件下,HSC模组的充电电量比LIB模组提高了15.4%,两模组的电压波动都较小,但LIB的充电电压出现下降趋势。

基于云计算的电力营销统计报表核算系统

为改善电力营销统计报表核算存在的自动化程度较低、错误率较高问题。提出基于云计算的电力营销统计报表核算系统。从客户端角度和服务端角度探究云计算技术,分析其计算力集中、信息交互、兼容性强等特性,利用移动平滑方法过滤采集到的营销统计数据噪声;分别从故障抢修、电力线损计算与电费回收情况三方面综合统计营销效益;将改变现有业务模式、依托现有体系架构、统一规划作为系统设计原则,结合处理能力、安全能力等技术指标建立核算系统。仿真实验表明,该系统核算精准度较高、运行稳定,一定程度上可帮助提高营销业务工作效率。

提高双向调节能力的混合储能平滑风电控制策略

为有效平滑风电出力,避免电池频繁充放电,提出了基于模型预测控制-模糊控制的并网功率平滑控制策略。首先采用模型预测控制获取风电目标出力与混合储能总输出参考功率;然后,设计了基于超级电容荷电状态的模糊自适应时间常数的一阶低通滤波法,对超级电容与锂电池实现自适应功率分配;接着基于双储能系统的充放电不平衡指标设计了模糊荷电状态优化控制,同时设计了改进双储能工作模式及相应切换规则以避免荷电状态越限;最后在Matlab/Simulink平台上建模仿真,验证了该控制策略的有效性。结果表明,所提控制策略不仅可以有效平滑风电并网功率,减小储能容量与功率配置,还可以减小锂电池的充放电切换次数,提高系统的双向调节能力。