一种改进的相量测量装置最优配置方法

以电力系统状态完全可观测和相量测量装置(PMU)配置数目最小为目标,提出了一种改进的PMU最优配置方法.将启发式方法和模拟退火方法有效结合以确保得到最优解,提高了基于启发式方法的初始PMU配置方案的质量,通过改进配置模型缩小了模拟退火方法的寻优范围,从而提高了求解速度.还提出了一种基于节点邻接矩阵的快速可观测性分析方法.最后采用IEEE 14、IEEE 30、IEEE 118节点系统和新英格兰39节点系统对该方法进行了验证.     

基于系统不完全可观的PMU优化配置新算法

限于同步相量测量装置(PMU)在电力系统中应用的局限性以及经济性,分析考虑了基于PMU的系统完全可观条件下电力系统状态估计过分冗余导致数据处理速度慢,收敛性不好等缺点,提出了基于系统不完全可观条件下,采用量子遗传算法对PMU进行合理配置,以期在最少PMU配置的基础上,使系统拥有足够的量测冗余度,得到的状态估计结果具有尽可能高的精度。通过算例仿真研究表明,该算法克服了深度优先算法(DFS)收敛性不好以及模拟退火法(SA)收敛速度慢的缺点,具有很好的收敛性和收敛速度,同时具有很好的精度要求。     

A novel hybrid state estimator for including synchronized phasor measurements

State estimator is crucial for on-line power system monitoring, analysis and control. With the increasing use of synchronized phasor measurement units (PMU) in power grids, how to utilize phasor measurements to improve the precision of state estimator becomes imperative. Since there are lots of traditional measurements in SCADA system and it is hard for phasor measurements to replace them in the near future, the best way is to develop hybrid state estimator which includes both phasor and traditional measurements to get better behavior. In this paper, a novel state estimator for including voltage phasors, branch current phasors and traditional measurements is proposed. The detailed model and how to calculate covariance matrix of PMU measurements are described in detail. New England 39-bus system and IEEE 118-bus system are used as test systems and the simulation results demonstrate that the proposed state estimation algorithm improves the precision greatly and gets better behavior as compared with other state estimators with or without phasor measurements.     

基于机端PMU量测的系统受扰轨迹预测

提出了基于机端相量测量单元量测数据的多机系统受扰轨迹预测方法，结合状态估计或潮流数据，在系统受扰后将其降阶简化为仅含有配置了相量测量单元的发电机节点系统，利用相量测量单元的量测数据修正降阶系统节点电压和电流之间的关系，然后将其代入相应的发电机模型，从而实现了系统受扰轨迹预测。该方法采用时间间隔较大的状态估计或潮流数据计算节点电压和电流传递关系矩阵的初值，并利用该矩阵主对角元的变化反映受扰后系统各元件的详细模型、网络拓扑和参数的改变，然后使用相量测量单元毫秒级的量测数据对其进行修正，从而为在实际应用中将相量测量单元与SCADA系统相结合做出了有益探索。最后以一个6机25节点系统为例验证了该方法的有效性。     

电力系统PMU最优配置数字规划算法

随着相量量测装置(PMU)硬件技术的逐渐成熟和高速通信网络的发展,PMU在电力系统中的状态估计、动态监测和稳定控制等方面得到了广泛应用.为达到系统完全可观,在所有的节点上均装设PMU既不可能也没有必要.文中提出一种基于系统拓扑可观性理论的数字规划算法,利用PMU和系统提供的状态信息,最大限度地对网络拓扑约束方程式进行了简化,以配置PMU数目最小为目标,形成了PMU最优配置问题,并采用禁忌搜索算法求解该问题.其突出优点是利用了系统混合测量集数据,即不仅考虑了PMU实测数据,同时计及了可用的潮流数据.在IEEE14节点和IEEE 118节点系统的仿真结果表明,与常规的PMU最优配置算法相比,所提出的数字规划算法可以实现安装较少数量的PMU而整个系统可观的目标.     

船舶电力系统相量测量单元多目标优化配置问题

为实现船舶电力系统潮流方程直接可解,同时保证相量测量单元(PMU)配置数目最少和N-1电压相量可解冗余度最高,提出了船舶电力系统PMU多目标优化配置方法。首先根据船舶电力系统不同工况下潮流方程的特点,分析得到PMU配置方案是否满足不同工况下潮流方程直接可解的判断方法;在此基础上,着重考虑最大运行工况下PMU配置数目最少和N-1电压相量可解冗余度最高的要求,建立了PMU多目标优化配置模型,并采用量子遗传优化算法对模型进行求解。以24节点典型船舶电力系统为例对所提方法进行了说明和验证,结果表明,该方法可实现全局多目标寻优,从而找到准确而完整的Pareto最优前沿。得到的PMU优化配置方案可为船舶电力系统配置PMU提供参考。     

基于记忆的改进克隆算法及其PMU配置多目标优化应用

以PMU安装数、量测系统可观测性和基于混合量测的状态估计精度三者为优化目标的PMU优化配置(OPP)是二层规划问题。该文证明了用单次状态估计精度评价量测系统性能的可行性，提出精度加权估算公式。将二层规划目标简化为分段函数，提出基于记忆的改进克隆算法。除模仿生物免疫系统的克隆选择和受体编辑机制外，该算法引入记忆加速算子以强化邻域搜索，并分段调整循环补充规模、高频变异与重组操作概率，从而显著加快和稳定进化进程，避免搜索陷入局部最优解。基于IEEE 14/57节点系统的算例表明，该算法能快速稳定地求出全局最优解及近似解，比原克隆算法等更适用。     

基于博弈演化算法的PMU最优配置方法

为实现电力系统可观测性,提出一种新的相量测量单元(PMU)配置方法,即基于博弈论的演化算法。该算法将寻找PMU最优配置方案的问题映射为理性主体寻求自身利益最大化的博弈过程,PMU最优配置方案即对应于博弈中的纳什均衡解。其突出优点是演化方向确定、全局收敛性好、收敛速度快、解具有多样性。应用该算法在IEEE 30节点、新英格兰39节点、某128节点系统进行仿真计算,与深度优化算法、模拟退火算法和最小生成树算法的结果进行比较,说明了该算法的可行性及优势。     

Multi‐objective PMU placement optimization considering the placement cost including the current channel allocation and state estimation accuracy

The optimal phasor measurement unit (PMU) placement problem in power systems has been considered and investigated by many researchers for accurate and fast state estimation by PMUs. However, the current channel cost of the PMU affects the total placement cost. This paper proposes a novel formulation in the multi‐objective optimal PMU placement, which minimizes the PMU placement cost with the current channel selection and the state estimation error. The current channel selection is represented as a decision variable in the optimization. For trade‐off objective functions, the Pareto approach by nondominated sorting genetic algorithm II (NSGA‐II) is applied in the optimization. The result of the numerical experiment in this paper demonstrates the advantage of considering the appropriate PMU current channel allocation, compared with the conventional method that ignores it, in the modified IEEE New England 39‐bus test system. As a result, the proposed method obtained a better Pareto solution compared with the conventional one because of the consideration for the current channel selection. An advantage of the proposed PMU placement is that it is able to reduce the total PMU placement cost while maintaining the state estimation accuracy.     

量测量的时延差对状态估计的影响及其对策

监控和数据采集(SCADA)系统的量测量没有统一的时标,更新周期长,而且时延较大。同步采样的相量测量单元(PMU)正成为电力系统中另一种重要的数据采集装置,它可以反映动态响应且时延较小;由于带有精确时标,即使通道传输存在时延也能保证时间断面的一致性。为在状态估计中协调这两种量测量,处理各量测量不同的时延,建立了SCADA量测时延的均匀分布模型,分析了各量测数据所反映的时间断面不一致性对状态估计精度的影响,提出了对时延不同的量测量的处理方法。通过对IEEE14节点电网和一个366节点的实际电网的仿真,验证了该方法的有效性。     

基于图论的电力系统PMU布点优化算法

基于最小支配集理论和电力系统线性量测模型,提出了可观测节点集合、WAMS可观测矩阵两个概念以及一种新的节点可观测性计算规则。以保证系统的完全可观测性和以系统图的最小支配集为搜索范围构成约束条件, 以电力系统状态完全可观测和相量测量装置（PMU）配置数目最小为目标,形成了PMU配置优化问题。并应用禁忌搜索(TS)方法求解该问题,保证了全局寻优。最后采用 IEEE 14、30、57 、118节点系统和新英格兰 39 节点系统对该方法进行了验证,仿真结果表明该方法的有效性和可行性。     

Novel Clustering-based Hidden Markov Model (CHMM) optimization approach for optimal PMU placement

A Phasor Measurement Unit (PMU) is an important device for monitoring the wide-area power distribution network. Placement of the PMUs across the network enables reliable monitoring of the network to identify the faults in the bus system. Due to the increase in the installation cost of the PMUs, optimal placement of the PMU is a significant task. But the existing techniques do not provide the optimal solution for the PMU placement. To overcome this issue, this paper proposes a novel Clustering-based Hidden Markov Model (CHMM) optimization approach to achieve optimal placement of PMUs in the power distribution network. Optimal PMU placement is achieved by applying cluster formation in the bus system to extract the data with neighboring buses. Best optimal position for placing the PMU is estimated by using Fuzzy logic-based rale formation to update the binary table of the bus system. The HMM approach is used for updating weight in the cluster formation. Our system is implemented in various bus systems like IEEE 28-bus system, 69-bus system and also in Karnataka 155-bus system. The proposed approach is implemented in the IEEE bus system and Karnataka Power Transmission Corporation Limited (KPTCL) bus system and compared with the existing approaches, based on the total number of PMU placement. The proposed approach achieves better performance in the optimal placement of PMU than the existing optimization algorithms.     

三相不平衡下交直流配电网状态估计

基于电压源型换流器(VSC)的柔性直流技术被越来越多地运用到配电网中,需要对含VSC的三相不平衡交直流配电网进行准确的状态估计,而配置相量测量单元(PMU)的测量数据是实现配电网准确状态估计的有效手段。首先,提出了考虑配电网三相不平衡特性的交直流配电网状态估计模型,采用加权最小绝对值法进行状态估计;其次,进行PMU测量数据的线性描述,给出了PMU及数据采集与监控(SCADA)系统的混合测量方程,并将多种交直流设备在测量方程中统一描述;最后,在三相不平衡的IEEE 33节点交直流配电网算例上,验证了所提方法的有效性和实用性。     

Optimal allocation of phasor measurement unit for full observability of the connected power network

This paper presents binary particle swarm optimization (BPSO) technique for the optimal allocation of phasor measurement units (PMUs) for the entire observability of connected power network. Phasor measurement units are considered as one of the most important measuring devices in the prospect of connected power network. PMUs function may be incorporated to the wide-area connected power networks for monitoring and controlling purposes. The optimal PMU placement (OPP) problem provides reference to the assurance of the minimal number of PMUs and their analogous locations for observability of the entire connected power networks. Binary particle swarm optimization (BPSO) algorithm is developed for the solution of OPP problem. The efficacy and robustness of the proposed method has been tested on the IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, IEEE 118-bus and Northern Regional Power Grid (NRPG) 246-bus test system. The results obtained by proposed approach are compared with other standard methods and it is observed that this BPSO based placement of phasor measurement units is found to be the best among all other techniques discussed.     

计及PMU的电力系统状态估计混合模型的研究

在等效电流量测变换状态估计模型的基础上引入旋转变换,实现方程的实、虚部严格解耦,并建立一种非线性估计和线性估计相结合的混合状态估计模型:首先把PMU节点的状态量测值以及PMU相关节点的状态推算值作为估计值进行非线性估计,然后再利用非线性估计结果和PMU量测进行线性估计。该模型可以充分利用PMU的量测,提高状态估计收敛速度,同时可以进一步利用PMU量测来提高估计精度,所需的存储量较小,具有较好的工程应用前景。最后采用IEEE14和IEEE30节点系统对该模型进行了验证。     

Placement of Synchronized Measurements for Power System Observability

This paper presents a method for the use of synchronized measurements for complete observability of a power system. The placement of phasor measurement units (PMUs), utilizing time-synchronized measurements of voltage and current phasors, is studied in this paper. An integer quadratic programming approach is used to minimize the total number of PMUs required, and to maximize the measurement redundancy at the power system buses. Existing conventional measurements can also be accommodated in the proposed PMU placement method. Complete observability of the system is ensured under normal operating conditions as well as under the outage of a single transmission line or a single PMU. Simulation results on the IEEE 14-bus, 30-bus, 57-bus, and 118-bus test systems as well as on a 298-bus test system are presented in this paper.      

基于混合量测的电力系统状态估计混合算法

研究了相量量测装置(PMU)相量量测和监控与数据采集(SCADA)量测混合使用时的数据匹配问题,提出了利用状态量转换预测得到预报系统状态和预报节点注入电流向量的方法。在此基础上,提出了应用PMU实时相量量测和预报节点注入电流向量的线性静态状态估计算法,以及应用PMU实时相量量测和预报系统状态的线性动态状态估计算法。文中将这2种算法与传统状态估计算法相结合,组成了状态估计混合算法,保证了状态估计的计算精度。该混合算法有效减少了状态估计的计算时间,对PMU的量测配置也没有严格的要求,具有很好的通用性。最后采用IEEE30节点系统对该方法进行了验证。     

基于相量量测的电力系统线性状态估计

分析了相量量测装置的量测误差情况,指出了相量量测参与状态估计计算的必要性。在完全使用相量量测的情况下,给出了基于直角坐标系的实数形式的电力系统线性量测方程和相应的线性静态状态估计算法。对负荷预报加潮流计算的系统状态预报方法进行改进,通过对误差协方差阵计算公式的推导与简化,提出了新的预报误差协方差阵计算公式,并将其与线性量测方程相结合,提出了基于相量量测的线性动态状态估计算法。最后讨论了线性状态估计算法的使用条件,并采用IEEE30节点系统对提出的算法进行了验证。     

Curvature quantified Douglas-Peucker-based phasor measurement unit data compression method for power system situational awareness

Facing constraints imposed by storage and bandwidth limitations, the vast volume of phasor measurement unit (PMU) data collected by the wide-area measurement system (WAMS) for power systems cannot be fully utilized. This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications. In this work, an effective curvature quantified Douglas-Peucker (CQDP)-based PMU data compression method is proposed for situational awareness of power systems. First, a curvature integrated distance (CID) for measuring the local flection and fluctuation of PMU signals is developed. The Douglas-Peucker (DP) algorithm integrated with a quantile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals. This allows adaptive adjustment of the algorithm parameters, so as to maintain the desired compression ratio and reconstruction accuracy as much as possible, irrespective of the power system dynamics. Finally, case studies on the Western Electricity Coordinating Council (WECC) 179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method. The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system, and alleviates the compression performance degradation problem faced by existing compression methods.     

基于SCADA/PMU混合量测的广域动态实时状态估计方法

根据来自监视控制与数据采集(supervisory control and data acquisition，SCADA)系统和相量测量单元(phasor measurement unit，PMU)的数据特点，提出了一种基于SCADA/PMU混合量测的广域动态实时状态估计方法，该方法充分利用了各节点间电压变化的相互联系，通过SCADA系统提供的初始值和安装PMU的节点的电压量测可简单地获得其他未安装PMU节点的电压相量。该方法有效地解决了在PMU配置不足的情况下如何观测电网状态以及如何在动态过程下实时观测电网。最后，通过对新英格兰10机39节点系统的多种故障进行仿真，验证了该方法的有效性和准确性。