Key operational and protection functions of power systems (e.g., optimal power flow scheduling and control, state estimation (SE), protection, and fault location) rely on the availability of models to represent the system’s behavior under different operating conditions. Power system models require knowledge of the components’ electrical parameters and the system topology. However, these data may be inaccurate for several reasons (e.g., inaccurate information of components datasheets and/or outdated topological information). The deployment of time synchronization in phasor measurement units (PMUs) and remote terminal units (RTUs) enables the collection of large datasets of synchronized measurements to infer power system models and learn associated power flow constraints. Within this context, this article presents a comprehensive review of measurement-based estimation methods for power flow models using time-synchronized measurements. It begins by exploring advancements in time dissemination technologies and the characterization of uncertainties in PMUs and instrument transformers (ITs), along with their implications for parameter estimation. This article then examines the power system parameter estimation problem, highlighting key techniques and methodologies. In the following, this article focuses on measurement models for state-independent power flow model estimation, including line parameters, admittance matrices, topology, and joint state-parameter estimation. Finally, this article discusses recent approaches for estimating state-dependent power flow models, with particular reference to linearized power flow approximations because of their large use in control applications.

In this article, a new security vulnerability in electricity market operations is identified. It involves certain parameters in the network model database whose errors, by nature, are difficult to detect and identify. These errors can either occur due to unintentional reasons or be maliciously introduced by cyber-adversaries. It is shown that by impacting the injection shift factors and transmission line congestion patterns, these errors may exert biases on locational marginal prices (LMPs), and thus impact the revenues received by the holders of financial transmission rights (FTRs). A method is then developed for identifying the network parameters whose errors are difficult to detect and may have severe impacts on the LMPs and FTR revenues. Simulation results in the IEEE 57-bus system are presented to illustrate and verify the analysis and the proposed method. The proposed framework can be used to conduct cyber-vulnerability assessment for power system model databases.

This paper describes implementation of a multi-area state estimation approach where a converged solution can be obtained for a large part of the network even if the conventional state estimator does not converge. This is accomplished by locating and isolating the area which contains the gross error that is responsible for divergence. The paper investigates and addresses two main issues, namely area partitioning and network observability. Simulation results are provided to illustrate the effectiveness of the proposed approach.

The main objective of this paper is to describe a multilevel framework that facilitates seamless integration of existing state estimators (SEs) that are designed to function at different levels of modeling hierarchy in order to accomplish very large-scale monitoring of interconnected power systems. This has been a major challenge for decades as power systems grew pretty much independently in different areas, which had to operate in an interconnected and synchronized fashion. The paper initially provides a brief historical perspective which also explains the existing state estimation paradigm. This is followed by a review of the recent technological and regulatory drivers that are responsible for the new developments in the energy management functions. The paper then shows that a common theoretical framework can be used to implement a hierarchical scheme by which even very large-scale power systems can be efficiently and accurately monitored. This is illustrated for substation level, transmission system level as well as for a level between different transmission system operators in a given power system. Finally, the paper describes the use and benefits of phasor measurements when incorporated at these different levels of the proposed infrastructure. Numerical examples are included to illustrate performance of the proposed multilevel schemes.

This paper investigates the optimal placement of synchronized phasor measurement units (PMU) in order to fully observe a given power system. Optimal placement methods to account for contingencies, loss of measurements as well as existing conventional measurements and zero injections have already been presented in previous publications. What differentiates this study from those already reported in the literature is the fact that it accounts for the number of available channels for the chosen type of PMU. This is shown to be a critical factor in strategic placement of these devices. Furthermore, it is also demonstrated that depending upon the topology of the network, there will be an upper limit on the number of channels for the PMUs beyond which installation costs will not be reduced any further. Results of applying the developed optimization method to systems with different sizes and topologies are presented. The results of this study will be more useful as the number of PMU installations increase to levels that will make the system fully observable based solely on PMUs with different number of channel capacities.

Many power system applications, particularly those related to monitoring,control, and protection, depend on the use of field data recorded by intelligent electronic devices (IEDs) in substations. With the introduction of IEDs in the last 20 years, the amount and type of data collected in substations have dramatically increased. This paper explores the benefits of data integration and information extraction achieved by merging temporal and spatial considerations. In the new approach, time and space issues are treated consistently across all IEDs, and as a result new applications with improved performance characteristics can be defined. As an illustration, two new monitoring functions are discussed in detail: 1) automated fault analysis and 2) hierarchical state and topology estimation. Discussion ends with a description of an implementation framework that will allow development of other functions that will benefit from the merger of time and space considerations.

This paper extends the results of our previous work presented in [see IEEE Trans. on Power Systems], to the problem of multiple measurement placement. The essential contribution of this work is based on the multiple rank updating of triangular factors, which are subsequently utilized in the state estimation solution following the measurement placement. Examples are used to illustrate the effectiveness of proposed method in placing measurements in typical power systems.

This paper is about the problem of estimating switch statuses in radial distribution systems. The true status information for each switch in a distribution system must be known in order to maintain an up to date system model for that system. The paper presents a linear programming based formulation by which the switch statuses can be estimated based on the limited number of line current measurements and available historical load curves.

This paper investigates the use of loop equations in power system analysis. Nodal equations are commonly preferred over the loop equations in almost all power system applications. The paper presents two specific applications namely the load flow for weakly meshed subtransmission systems and the observability analysis for state estimation, where the use of the loop equations will actually facilitate the problem solution. Examples are included to demonstrate the benefits of making this choice for these applications.