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.     

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.     

ILP-based multistage placement of PMUs with dynamic monitoring constraints

This paper addresses two aspects of the optimal Phasor Measurement Unit (PMU) placement problem. Firstly, an ILP (Integer Linear Programing) model for the optimal multistage placement of PMUs is proposed. The approach finds the number of PMUs and its placement in separate stages, while maximizing the system observability at each period of time. The model takes into account: the available budget per stage, the power system expansion along with the multistage PMU placement, redundancy in the PMU placement against the failure of a PMU or its communication links, user defined time constraints for PMU allocation, and the zero-injection effect. Secondly, it is proposed a methodology to identify buses to be observed for dynamic stability monitoring. Two criteria, which are inter-area observability and intra-area observability, have been considered. The methodology identifies coherent groups in large power systems by using a new technique based on graph theory. The technique requires neither full stability studies nor a predefined number of groups. Also, a centrality criterion is used to select a bus for monitoring each coherent area and supervise inter-area oscillations. Then, PMUs are located to ensure complete observability inside each area (intra-area monitoring). Methodology is applied on the 14-bus test system, the 57-bus test system with expansion plans, and the 16-machine 68 bus test system. Results indicate that the optimization model finds the optimal number of PMUs when the PMU placement by stages is required, while the observability at each stage is maximized. Additionally, it is shown that expansion plans and particular requirements of observability can be considered in the model without increasing the number of required PMUs, and the zero-injection effect, which reduces the number of PMUs, can be considered in the model.     

Optimal placement of PMUs with limited number of channels for complete topological observability of power systems under various contingencies

In optimal PMU placement problem, a common assumption is that each PMU installed at a bus can measure the voltage phasor of the installed bus and the current phasors of all lines incident to the bus. However, available PMUs have limited number of channels and cannot measure the current phasors of all their incident lines. The aim of this paper is to recognize the effect of channel capacity of PMUs on their optimal placement for complete power system observability. Initially, the conventional full observability of power networks is formulated. Next, a modified algorithm based on integer linear programming model for the optimal placement of these types of PMUs is presented. The proposed formulation is also extended for assuring complete observability under different contingencies such as single PMU loss and single line outage. Moreover, the problem of combination of PMUs with different number of channels and varying costs in optimal PMU placement is investigated. Since the proposed optimization formulation is regarded to be a multiple-solution one, total measurement redundancy index is evaluated and the solution with the highest redundancy index is selected as the optimal solution. The proposed formulation is applied to several IEEE standard test systems and compared with the existing techniques.     

基于改进的整数规划法结合零注入节点的PMU优化配置方法

为了提高同步相量测量装置的优化速度并利用最少数量的相量量测单元(PMU),结合零注入节点的特性,提出了基于整数规划算法的PMU优化配置算法。根据电力系统全网的可观测性建立其数学模型,并考虑了零注入节点的相关特点,求解系统模型获得PMU的优化位置。对IEEE-14节点、IEEE-18节点、IEEE-30节点以及IEEE-118节点系统分别进行了实验仿真,并利用Matlab以及Lingo工具对所提改进的整数规划法进行了验证,对约束方程进行优化,获得了PMU的数量和位置。将该算法与整数规划算法、模拟退火法以及改进过的遗传算法相比较,该算法可以用更少数量的PMU设备使全网可观,验证了该方法的有效性和优越性。     

基于多目标进化算法的PMU的优化配置

研究了配置相量测量单元(PMU)后电力系统可观测性的判断方法,以保证电力系统完全可观测为约束条件,以配置PMU数目最小和保证测量量具有最大量测冗余度为目标,建立了PMU最优配置问题的数学模型。这是一个多目标优化问题,需要寻求一组Pareto最优解,应用多目标进化算法求解该问题可以得到多种满足条件的PMU配置可行方案。最后,以IEEE39节点系统为例验证了该方法的合理性。     

基于01整数规划的多目标最优PMU配置算法

针对目前缺乏多目标PMU配置方法,提出了一种基于线性01规划的多目标优化配置算法。并在此基础上导出了三种特殊模型,分别处理系统在正常运行方式下完全可观测的PMU布点问题,在线路N-1故障时系统仍可观测的PMU布点问题及在PMU N-1故障时系统仍可观测的PMU布点问题。该方法的突出特点在于能够同时将以上三种布点需求使用统一的形式同时处理,并且最终的布点方案在保证PMU数目最少或保证配置PMU所需费用最少的基础上获得了最高的测量冗余度。通过IEEE30、IEEE 57、IEEE118节点系统布点验证了该方法的有效性和灵活性。     

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.      

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.     

A Multi-objective PMU Placement Method in Power System via Binary Gravitational Search Algorithm

This paper presents a Binary Gravitational Search Algorithm (BGSA) methodology for the optimal placement of Phasor Measurement Units (PMUs) to achieve full and maximum observability of the power system. The gravitational search technique has been extended in this investigation to incorporate binary variables for this purpose. The objective of proposed methodology is to minimize the total number of PMUs installed at various buses, which in turn minimize installation cost of the PMUs and improves observability redundancy by including an additional objective. Thus, the PMU placement problem has been expressed as a multi-objective problem. Besides, single PMU outage or single line outage cases in the presence of zero injection buses have been investigated. In this algorithm, the searcher agents are the collection of masses, which interact with each other using Newton's laws of gravity and motion. The proposed BGSA has been applied to the IEEE 14-bus, -30-bus, -118-bus, Northern Regional Power Grid 246-bus Indian system, and Polish 2383-bus system. Case studies reveal that the lower number of PMUs or equal number of PMUs has been produced by the proposed method compared to methods reported in the literature. In cases of equal number of PMUs, the observability produced by proposed method is higher or at least equal.     

基于免疫BPSO算法与拓扑可观性的PMU最优配置

以电力系统状态完全可观测和相量测量单元PMU配置数目最小为优化目标,基于PMU的功能特点和电力网络的拓扑结构信息,形成快速且通用的电网拓扑可观测性判别方法,并设计了一种结合免疫系统信息处理机制的二进制粒子群优化算法对目标函数进行求解,该算法综合了粒子群优化算法简单快速和免疫系统种群多样性的优点,明显改善了进化后期算法的收敛性能和全局寻优能力.最后通过对IEEE14和新英格兰39母线系统进行PMU优化配置仿真及量测冗余性分析,验证了本文方法的有效性和优越性.     

Optimal PMU placement for power system state estimation with random component outages

Phasor measurement units (PMUs) provide globally synchronized measurements of voltage and current phasors in real-time and at a high sampling rate. Hence, they permit improving the state estimation performance in power systems. In this paper we propose a novel method for optimal PMU placement in a power system suffering from random component outages (RCOs). In the proposed method, for a given RCO model, the optimal PMU locations are chosen to minimize the state estimation error covariance. We consider both static and dynamic state estimation. To reduce the complexity, the search for the optimal PMU locations is constrained to the set of locations guaranteeing topological observability. We present numerical results showing the application and scalability of our method using the IEEE 9-bus, 14-bus, 39-bus and 118-bus systems.     

电力系统相量测量装置最优配置混合算法的研究

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最优配置问题。将遗传算法和禁忌算法有效结合形成禁忌遗传算法,该算法在改进交叉和变异算子的基础上,继承和发展了遗传算法基于多点搜索、鲁棒性强等诸多优点,每当群体有出现早熟而陷入局部最优解的趋势时,利用禁忌搜索增强算法的爬山能力,避免算法早熟而陷入局部最优解,增强算法的全局收敛能力和收敛速度。与遗传算法和禁忌搜索方法相比,禁忌遗传算法具有更好的全局收敛能力和收敛速度。最后采用IEEE14,IEEE30和IEEE57节点系统对算法的有效性进行了验证。     

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.     

Optimal placement of PMUs to maintain network observability using a modified BPSO algorithm

This paper presents a novel approach to optimal placement of Phasor Measurement Units (PMUs) for state estimation. At first, an optimal measurement set is determined to achieve full network observability during normal conditions, i.e. no PMU failure or transmission line outage. Then, in order to consider contingency conditions, the derived scheme in normal conditions is modified to maintain network observability after any PMU loss or a single transmission line outage. Observability analysis is carried out using topological observability rules. A new rule is added that can decrease the number of required PMUs for complete system observability. A modified Binary Particle Swarm Optimization (BPSO) algorithm is used as an optimization tool to obtain the minimal number of PMUs and their corresponding locations while satisfying associated constraint. Numerical results on different IEEE test systems are presented to demonstrate the effectiveness of the proposed approach.     

考虑系统完全可观测性的PMU最优配置方法

基于电力系统线性量测模型，研究了引入相量测量单元（PMU）相关量测集后的增广关联矩阵的电力系统可观测性拓扑分析方法，以保证系统结构完全可观测性和最大量测数据冗余度为约束，以配置PMU数目最小为目标，形成了PMU最优配置问题，并应用禁忌搜索（TS）方法求解该问题，保证了全局寻优。算例表明，该方法准确可靠、有效可行。     

Fault Location Observability Using Phasor Measurement Units in a Power Network Through Deterministic and Stochastic Algorithms

This article studies deterministic and stochastic algorithms for placing minimum number of phasor measurement units (PMUs) in a power system in order to locate any fault in the power system. The optimization problem is initially formulated in a mixed integer linear programing framework with binary-valued variables as well as in a binary integer linear programing model. Then, the optimization problem is formulated as an equivalent non-linear programing model, minimizing a quadratic objective function subject to equality non-linear constraints defined over a bounded and closed set. The problem is solved by using a Sequential Quadratic Programming algorithm. The non-linear program is illustrated with a 7-bus test system. Also, stochastic algorithms such as binary-coded genetic algorithm and particle swarm optimization have been implemented in solving the optimal PMU placement under fault condition. The accuracy of suggested algorithms is independent from the fault type and its resistance. The optimization models are applied to the IEEE systems. The numerical results indicate that the proposed algorithms locate minimizers at the optimal objective function value in complete agreement with those obtained by branch-and-bound algorithms.     

Weak bus-constrained PMU placement for complete observability of a connected power network considering voltage stability indices

Phasor measurement units (PMUs) are preferred for installation at weak buses in a power network. Therefore, the weak buses need to be located and the strategic locations of PMUs identified to ensure network observability. Thus, the primary aim of this work is to identify the placements of the maximum number of PMUs installed at the weak buses in the electrical network. The voltage collapse proximity indicator, line stability index, fast voltage stability index, and a new voltage stability indicator utilizing load flow measurement are used to determine the weak buses. A novel deterministic methodology based on a binary-integer linear programming model is then proposed to determine the optimal locations of PMUs. The effect of a single PMU outage considering the weak buses is also demonstrated. The effectiveness of the developed approach is tested and validated on the standard IEEE 14-, 118-, 300-, and New England 39-bus systems. The obtained results are also compared to those using different weak bus methodologies.     

基于系统同调性的PMU最优布点

从电力系统的同调性出发，优化相量测量单元(PMU)的布点，以最少数量的PMU反映系统在各种扰动下的主要动态行为。该方法利用扩展等面积准则(EEAC)稳定性理论中的主导模式概念，识别所有可能出现的暂态功角失稳模式，并据此将所有的发电机节点划分为不同的同调群。在每个群中选择一台发电机安装PMU，以捕捉关键的功角动态信息。同时，利用暂态电压稳定和暂态电压跌落可接受性的概念，识别所有可能出现暂态电压问题的相邻母线的子集。在每个子集中选择一条母线安装PMU，以捕捉关键的电压动态信息。根据该最小PMU集提供的动态信息，不但可以正确地定性判断系统的同步稳定性和电压稳定性，并可通过数据挖掘方法评估其稳定裕度。结合华东电网验证了该方法的有效性。     

Robust Measurement Design by Placing Synchronized Phasor Measurements on Network Branches

This paper is concerned about optimal placement of synchronized phasor measurements that can monitor voltage and current phasors along network branches. Earlier investigations on placement of phasor measurement units (PMUs) have assumed that a PMU could be placed at a bus and would provide bus voltage phasor as well as current phasors along all branches incident to the bus. This study considers those PMUs which are designed to monitor a single branch by measuring the voltage and current phasors at one end of the monitored branch. It then determines the optimal location of such PMUs in order to make the entire network observable. The paper also addresses the reliability of the resulting measurement design by considering loss or failure of PMUs as well as contingencies involving line or transformer outages. Developed placement strategies are illustrated using IEEE test systems.