Coordination control method of photovoltaic and energy storage for distribution network based on virtual substation

针对农村地区配电网供电可靠性低以及光伏扶贫政策下大规模分布式光伏接入引起的电压越限和潮流倒送问题,提出一种基于虚拟变电站模式的光储协调控制方法,结合河北省营里乡配电网实际工程案例,对不同运行方案下系统的稳态性能,如电压水平、网络损耗等进行了对比分析,并基于蒙特卡洛模拟验证了所提方法对农村配电网供电可靠性提升的有效性。     

基于非凸矩阵分解的电网欺骗性数据注入攻击检测方法

电力系统状态估计中的量测数据容易受到欺骗性数据注入攻击的恶意篡改，使状态估计的稳定性受到影响。根据量测数据在连续时间段内的低维特性以及欺骗性数据攻击的稀疏特性，提出了一种基于非凸矩阵分解的电网欺骗性数据注入攻击检测方法。首先，将欺骗性数据注入攻击的检测问题视为稀疏低秩矩阵分解问题，并将分解问题转化为非凸优化问题，通过改进的交替方向乘子法求解此非凸问题，将受攻击的数据矩阵分解为正常量测矩阵和攻击矩阵；其次，利用分解出的攻击矩阵检测出欺骗性数据注入攻击的数值和位置，并以分解出的正常量测矩阵作为参考量测量，进行状态估计获得正确的状态变量；最后，通过IEEE-14节点系统分析了不同攻击幅值下的检测结果，验证了所提方法的准确性。     

含高比例光伏配电网电压安全性数字孪生预警方法

光伏的随机不确定性易引起配电网电压越限,而同时光伏又具有电压主动支撑能力,对电压影响产生一定的自消作用。因而,含高比例光伏的新型配电系统电压安全问题日益复杂。因此提出一种新型配电网数字孪生电压安全分析和预警方法。首先论述了孪生配电网电压安全预警的实现机理和功能方案,并基于运行数据建立配电网源荷随机行为的马尔科夫模型,提出不确定场景下电压越限风险评判指标。然后采用吉布斯算法对源荷马尔科夫模型进行蒙特卡洛随机抽样,根据配电网当前的运行状态,利用孪生配电网超实时计算能力快速仿真配电网未来随机场景,并计算电压风险指标,评判电压安全性。最后应用算例分析验证了所提分析方法的有效性及合理性。     

基于区间鲁棒控制的配电信息物理双层设备协调配置方法

为提高配电网消纳高比例分布式电源的经济性,充分利用一次侧储能和二次侧主动调控的灵活性,该文提出一种基于区间鲁棒控制的配电信息物理双层设备协调配置方法。首先,建立分布式电源控制选点与储能配置的协调优化综合经济性模型,而后,考虑源荷不确定性,以电压越限风险水平为约束,建立配电网区间鲁棒优化运行模型,形成双层优化模型;最后,给出基于差分进化算法的求解流程,并以IEEE-33节点配电系统为例验证模型的有效性,同时仿真分析不同可接受风险水平和设备价格对配置的影响,为高渗透配电网的经济消纳方案提供有益的参考。     

基于大数据的专变客户用能健康状态综合评价

提出了一种基于大数据的专变客户用能健康状态综合评价模型。首先从用能安全、经济效益和可靠性3个方面建立专变客户用能健康状态评价指标体系;进而利用改进层次分析法和熵权法对评价指标进行组合赋权;然后利用灰色关联度和马氏距离对理想解法进行改进,借助改进理想解法实现评价对象的综合排序,再结合秩和比法将评价对象分档,实现目标客户的筛选。基于某省电网专变客户的实际数据,验证了所提评价模型的可行性与有效性,并为目标客户制定了针对性用能改进策略。     

特高压交流输电线路下方民房晾衣架感应电特性及改善措施研究

特高压线路电压等级高,空间电场容易造成附近居民生活空间的暂态电击现象,影响居民日常生活和电网环保性。其中,民房金属晾衣架处暂态电击现象频发,是居民投诉的重点。为此,建立了1 000 kV特高压同塔双回交流输电线路和金属晾衣架模型,分析了金属晾衣架上感应电势和感应电场的大小,并定量讨论了多种屏蔽线架设方式对晾衣架上感应电的降低水平和改善效果。研究表明：屏蔽线对改善线下金属物的感应电现象效果显著,最大降低72%;屏蔽线架设根数、与晾衣架的水平距离对改善效果影响较大。考虑施工和经济性影响,也提出了相应场景下屏蔽线架设建议。     

一种适用于中压直流系统的电平多级倍增MMC拓扑及其调制策略

受到电平数的限制,应用于中压直流系统的模块化多电平换流器(modular multilevel converter,MMC)难以兼顾较低的运行损耗和较高的电压质量.为此,设计了一种电平多级倍增模块化多电平换流器(level multiplication modular multilevel converter,LM-M...     

电压互感器递进式二次核相流程的研究

无线二次核相仪器的使用显著缩减了人力和时间,但在智能分析方面存在不足.针对电压回路接线错误时无法为作业人员提供指导的问题.通过汇总某相线和中性线接错、两相线接错、三相全部接错的3类典型错误,提出了对采样数据按照幅值、对称性、相序和相位4个环节开展递进式的智能分析方法,各环节反馈的信息可为作业人员消缺提供指导.     

Online voltage stability assessment of load centers by using neural networks

This paper presents a neural network based method for evaluating online voltage stability conditions for a selected load center of an electric power system. Starting with a dynamic model of the system, a suitable index is defined to evaluate the proximity of the power network to voltage collapse. Then, a three-layer feedforward neural network is trained to give, as output to a prespecified set of inputs, the expected value of the voltage stability index. For this purpose, two different neural network architectures are proposed. The error back-propagation algorithm is used in this paper to train the chosen neural network structure. Moreover, it is shown that a good estimate of the real power margin of the selected load center can also be obtained using the value of the output of the designed neural network. To demonstrate the effectiveness of the proposed neural network based approach for voltage stability monitoring, a sample power system is considered. Test results show that neural networks can yield, in real time, an accurate assessment of voltage stability conditions.     

Regional forecasts and smoothing effect of photovoltaic power generation in Japan: An approach with principal component analysis

Regional forecasts of power generated by photovoltaic systems have an important role helping power utilities to manage grids with a high level of penetration of such systems. The objective of this study is to propose a method to obtain one-day ahead hourly regional forecasts of photovoltaic power when regional information is available. The method is based on the use of principal component analysis, support vector regression and weather forecast data. One-day ahead regional forecasts of photovoltaic power were done for 4 of the main regions of Japan for 1 year, 2009, using hourly power generation data of 453 photovoltaic systems. The performance of the method was characterized comparing the results it yielded with the ones provides by a persistence approach and by an approach that do not employ the principal component analysis. Moreover, the expected smoothing effect on the error achieved when the regional forecasts are based on forecasts for each photovoltaic system is presented, constituting an additional reference to evaluate the proposed method. The results show that the method performed well; its regional forecasts had a normalized annual root mean square error of 0.07 kWh/kW_rated in the worst case, and the persistence approach was outperformed by at least 51% regarding the same error. The use of principal component proved to be a simple and particularly effective approach, decreasing the bias of the forecasts in all regions, and causing a reduction of the normalized root mean square error from 20.2% to 57.8% depending on the region. The proposed method also yielded results within the same level of forecasts which benefitted from the smoothing effect; the former presented a maximum variation of 10.2% of the normalized root mean square error of the latter in the worst case.