计及可控串联补偿器的系统电压失稳概率研究

可控串联补偿器(TCSC)可以灵活地调节线路潮流,提高系统运行的稳定性,传统分析方法在评估TCSC提高系统静态电压稳定性作用时存在缺陷,无法考虑不确定性因素的影响。因此,建立计及TCSC接入的系统负荷裕度概率模型,考虑运行参数的随机波动,通过半不变量法和Gram-Charlier级数计算负荷裕度概率特征,进而得到电压失稳概率值。分别在常态与故障下对比TCSC安装前后的IEEE39节点系统失稳概率,结果表明,TCSC能有效地提高系统的静态电压稳定性,验证了本文方法的可行性与准确性。     

基于随机潮流的高比例新能源接入配电网的极限线损分析

高比例新能源的接入使得配电网潮流具有波动性和不确定性,系统不确定性潮流将影响配电网极限线损准确计算。针对含高比例新能源的配电网,分析新能源出力及负荷的概率模型。结合对称采样无迹变换算法,建立计及新能源出力和负荷随机性的配电网极限线损模型。对基于随机变量相关性采样获得的样本点线损计算,经加权处理后得到配电网线损的概率特征。最后,以IEEE 69节点系统和某县配电网为例,选用蒙特卡洛模拟方法做对比,验证了该模型的可行性。     

考虑风光不确定性的电力系统概率潮流计算

针对概率潮流计算中采用蒙特卡罗算法而导致精度低、操作性复杂的问题,提出了一种基于改进拉丁超立方的蒙特卡罗法的概率潮流计算方法,按照样本在变量概率密度分布中所反映出的重要程度进行采样,得到的样本均值不变且方差较小。在含风电与光伏的IEEE-30节点系统概率潮流计算中的结果表明：该方法能更好地反映概率潮流计算中随机变量的数字特征,提高蒙特卡罗法的计算精度,降低随机函数尾部特性造成的误差,从而具有较好的工程实用价值。     

考虑分布式电源接入的电网源荷时序随机波动特性概率潮流计算

鉴于分布式电源的时序随机波动特性和负荷需求侧的电能质量是分布式电源接入系统的重要影响因素,从风光典型分布式电源和负荷需求的时序波动性出发,建立了综合考虑源荷时序特性的概率潮流计算模型。利用基于模糊特征聚类的概率潮流算法对IEEE 14节点系统进行计算,对比分析负荷需求侧对系统电压波动的影响情况。结果表明,所采用方法能够全面合理地模拟分布式电源接入时电网随机波动过程。     

风力发电选址和渗透率对连锁故障影响的研究

风力发电选址和渗透率提高加剧了电网系统潮流分布的复杂性,小范围的潮流异常分布能够引发连锁故障。文章基于节点电气介数方法分析了连锁故障,研究了在不同节点条件下的风力发电机选址、渗透率的变化对连锁故障影响的程度。研究发现,风电负荷加载在电气介数较小的节点上会引发系统潮流分布均匀性下降,导致潮流转移至其他线路,进而加剧连锁故障。通过IEEE30节点系统的仿真表明:风电渗透率的提升加剧了连锁故障;在相同的渗透率下,选址节点的电气介数越小其连锁故障越严重。     

含高渗透间歇性能源电网的薄弱节点识别

针对高渗透间歇性能源电网的薄弱节点识别问题,提出基于PV曲线有功负荷裕度和电压变化指标的综合分析方法。首先从有功负荷裕度角度机理分析间歇性能源电网静态电压稳定性的影响因素,在此基础上结合有功负荷裕度和电压变化指标识别电网的薄弱节点。以新疆某地区实际电网为例,验证了上述薄弱节点识别方法的有效性,同时通过PV曲线分析给出高渗透间歇性能源电网运行断面极限,对该电网运行提供一定借鉴。     

基于改进LHS的含风电电力系统概率潮流计算

基于拉丁超立方抽样的蒙特卡模拟法应用于概率潮流计算时存在精度相对较低和计算量复杂等问题,本文对拉丁超立方抽样算法中采样排序进行改进,提出一种将随机行走原理和拉丁超立方采样相结合的方法。将该方法应用在含风电的IEEE-14节点和IEEE-118节点并且和基于Gram-Schmidt拉丁超立方采样法进行比较分析。理论及数值计算结果表明:该方法能更好地解决拉丁超立方采样法中精度相对较低的缺陷,同时能更为精确地反应概率潮流计算中随机变量的数字特征,具有较好的工程实用价值。     

考虑负荷随机性的风电消纳能力概率评估

针对目前风电消纳能力的评估研究方法不能全面考虑电力系统随机性因素对风电消纳能力影响的不足,从电力系统中的不确定因素出发,考虑系统负荷的随机性,提出一种风电消纳能力的概率评估方法。首先采用加权高斯混合分布对负荷进行概率建模,然后采用切片采样算法对负荷的概率模型进行采样并获得其样本空间,最后将样本值依次代入潮流方程进行潮流计算,确定每组样本值在满足系统安全运行前提下所对应的最大风电接入功率,并统计其概率指标。对含有风电接入的IEEE 39节点系统进行仿真计算,当采样规模为3000次时,基于切片采样算法的马尔科夫链蒙特卡洛模拟法(S-MCMC)的标准差仅为0.08%,由此验证了该研究方法相比于传统研究方法的准确性和有效性。     

含风电的电力系统概率潮流计算

概率潮流求解中蒙特卡罗法只有在大规模采样的条件下进行多次模拟,才能提高精准度,其导致计算量大,耗费时间,难以处理风电中变量相关性的概率潮流。采用基于拉丁超立方采样的蒙特卡罗法对含有风电场的电力系统概率潮流问题进行分析。基于拉丁超立方采样的蒙特卡罗法,主要分为采样和排序。采样是为了确保样本空间能够被完整的采样,排序是为了降低随机变量之间的相关性。该方法将Gram-Schmidt和Cholesky2个排序方法结合,很好地降低随机变量之间的相关性。通过IEEE-39节点仿真,结论显示该方法能够较好地处理风电中的风速相关性,降低采样规模,提高精准度,是一种非常有效的处理含有风电场的概率潮流问题的方法。     

基于空间变换的含风电场和电动汽车配电网概率潮流计算CSCD

电动汽车和分布式发电的广泛接入增加了现代配电网的复杂性,同时输入随机变量的相关性对配电网的影响也越来越大。基于此,本文采用Nataf变换或者三阶多项式正态变换实现变量从相关非正态空间到相关标准正态空间的转换,采用初等变换或者正交变换实现变量从相关标准正态空间到独立标准正态空间的转换,从而得到标准的点估计运算所需的相互独立输入随机变量,进而建立了能用2m+1点估计方法求解的概率潮流模型,从而解决了相关输入随机变量的概率潮流问题,以实现含电动汽车的有源配电网系统的仿真运行分析。最后,在一个含风电和电动汽车的IEEE-33节点配电网中进行算例仿真,比较四个方案处理输入随机变量相关性的有效性。算例分析表明,Nataf变换结合初等变换具有最好的精度。     

基于概率潮流的含风电配电网无功优化

考虑风电输出功率和负荷功率的随机波动性,建立了风电和负荷的随机模型。采用卷积计算和Cornish-Fisher级数展开来处理随机性因素,从而完成概率潮流计算;并建立以降低成本-效益比值和电压稳定指标L为目标的综合无功优化模型,基于概率潮流和多Agent系统的混沌粒子群算法(MACPSO)对该配电网进行无功优化。IEEE 33节点算例分析表明,所提无功优化求解策略有效可行,同时所提算法在无功优化中具有一定优势。     

Probabilistic load flow with detailed wind generator models considering correlated wind generation and correlated loads

The enhancement in the penetration of intermittent generation necessitates the need to include uncertain behaviour in the conventional power flow programs. In this paper, four different wind generation models have been incorporated in probabilistic load flow for calculating the probability distribution of the reactive power consumed by the wind generators for three different scenarios; i) uncorrelated wind and uncorrelated loads ii) uncorrelated wind and correlated loads and iii) correlated wind and correlated loads The above mentioned scenarios have been implemented in probabilistic load flow using point estimate method in the IEEE-118 bus test system and accuracy of the results have been validated by comparing these results with those obtained by Monte Carlo simulation studies.     

基于改进LHS的半不变量法概率潮流计算

为提高概率潮流算法的精度和效率,提出一种将半不变量法和改进的拉丁超立方采样技术相结合的方法.首先,提出改进的非参数核密度估计算法,并用其建立光伏输出功率概率模型.其次,为改善各阶半不变量的计算精度和效率,根据输入随机变量的分布情况的不同,分别采用不同方法计算随机变量的各阶半不变量,并结合Gram-Charlier级数展...     

基于随机潮流的分布式电源多目标优化配置

风光等间歇性分布式电源(DG)出力具有随机性和波动性,在规划过程中采用确定性变量和约束处理间歇性DG出力与实际发电情况不符,难以得到真实的规划结果,同时也会造成不必要的资源浪费。对此,采用机会约束规划方法,建立综合投资效益、网损和电压偏差的DG多目标优化配置模型,采用基于半不变量法的随机潮流结果对相关机会约束进行概率校验,并将累积排序操作、精英保留操作和拥挤距离操作引入随机黑洞粒子群算法,提出一种改进多目标粒子群算法对模型求解。PGE-33节点配电系统仿真结果表明,DG合理接入与优化配置能有效提高电网运行经济性和供电可靠性,且从概率角度分析源荷侧不确定因素对电压水平的影响,评估规划方案与实际电网运行契合度,辅助规划人员进行科学决策。     

Probabilistic multiple distribution static compensator placement and sizing based on the two-point estimate method

This paper deals with the stochastic placement and sizing of the distribution static compensator in the distribution systems considering uncertainty. The proposed stochastic framework utilises the point estimate method to consider the forecasting uncertainty of the active and reactive loads in the load flow equations. The objective functions to be investigated are total active power losses and the voltage profile simultaneously. In order to reach a proper compromise to satisfy all the objective functions, an interactive fuzzy satisfying approach is employed. Also, since the problem investigated is a type of discrete, nonlinear, multi-objective optimisation problem, a new modified optimisation technique is proposed to escape from the local optima as well as the premature convergence. Finally, the satisfying performance of the proposed method is examined on the 86-bus IEEE distribution system.     

Using Copulas for analysis of large datasets in renewable distributed generation: PV and wind power integration in Iran

Renewable distributed generation introduced as an environmental friendly alternative energy supply while it provided the power system with ever-growing technical benefits such as loss reduction and feeder voltage improvement. The evaluation of the effects of small residential photovoltaic and wind DG systems on various system operating indices and the system net load is complicated by both the probabilistic nature of their output and the variety of their spatial allocations. The increasing penetration of renewable distributed generation in power systems necessitates the modeling of this stochastic structure in operation and planning studies. An advanced stochastic modeling of the system requires multivariate uncertainty analysis involving non-normal correlated random variables. Such an analysis is to epitomize the aggregate uncertainty corresponding to spatially spread stochastic variables. In this paper, an integration study of photovoltaics and wind turbines, distributed in a distribution network, is investigated based on the stochastic modeling using Archimedean copulas as a new efficient tool. The basic theory concerning the use of copulas for dependence modeling is presented and focus is given on an Archimedean algorithm. A comprehensive case study for Davarzan area in Iran is presented after reviewing Iran's renewable energy status. This study shows an application of the presented technique when large datasets, assuming 10-min interval between data points of PV, wind and load profiles, are involved where a deterministic study is not trivial.     

A novel method to investigate voltage stability of IEEE-14 bus wind integrated system using PSAT

The maximum demand of power utilization is increasing exponentially from base load to peak load in day to day life. This power demand may be either industrial usage or household applications. To meet this high maximum power demand by the consumer, one of the options is the integration of renewable energy resources with conventional power generation methods. In the present scenario, wind energy system is one of the methods to generate power in connection with the conventional power systems. When the load on the conventional grid system increases, various bus voltages of the system tend to decrease, causing serious voltage drop or voltage instability within the system. In view of this, identification of weak buses within the system has become necessary. This paper presents the line indices method to identify these weak buses, so that some corrective action may be taken to compensate for this drop in voltage. An attempt has been made to compensate these drops in voltages by integration of renewable energy systems. The wind energy system at one of the bus in the test system is integrated and the performance of the system is verified by calculating the power flow (PF) using the power system analysis tool box (PSAT) and line indices of the integrated test system. The PF and load flow results are used to calculate line indices for the IEEE-14 bus test system which is simulated on PSAT.     

模糊划分线性回归模型在电力负荷预测中的应用

针对电力负荷中长期预测中存在大量的不确定性因素及待预测的负荷变量与关联因素无法很好地满足整个样本序列上预测变量与解释变量间的线性相关性问题,引入了模糊划分理论,构建了基于模糊有序划分的线性回归预测模型。算例应用结果表明,该模型能在较少样本数据基础上实现对电力负荷较为准确的预测,且预测精度较高。