Floyd Galvan

Advances in the SuperCalibrator Concept - Practical Implementations

The supercalibrator concept was introduced to take advantage of the characteristics of GPS-synchronized equipment (PMUs). Specifically, GPS-synchronized equipment has the capacity to provide precise phase measurements (to 0.01 degrees accuracy) and relatively good quality magnitude measurements (up to 0.1% accuracy). However in a practical environment this precision is not achieved for a variety of reasons, such as errors from instrumentation, system unbalanced conditions, etc. The supercalibrator concept is based on a statistical estimation process that fits GPS-synchronized measurements and all other available standard data into a three-phase, breaker-oriented, instrumentation inclusive model. In this paper, this concept has been extended to provide a decentralized state estimator for power systems. The decentralized state estimator operates on substation data. The resulting substation state estimate is globally valid as long as there is a valid GPS-synchronized measurement at the substation. The paper describes the supercalibrator methodology. Presently the concept is implemented on five substations. Numerical experiments with these systems illustrate the superiority of this approach. The paper also describes preliminary implementation and performance issues. The implications of the overall approach are substantial. The supercalibrator applied to substations provides a decentralized, highly reliable and robust state estimator for large power systems

Decision tree assisted controlled islanding for preventing cascading events

At stressed operating conditions, critical contingencies can initiate loss of synchronism and trigger cascading events. Controlled islanding is the last line of defense to stabilize the whole system. This paper presents a decision tree assisted scheme to determine the timing of controlled islanding in real time by using phasor measurements. In addition, a slow coherency based approach is used to determine where to island. This scheme is tested on the operational model of the Entergy system and a severe N-2 outage case is used to demonstrate the phenomenon of cascading events due to protective relay actions. The results show that training one decision tree only for a specified critical contingency that can potentially cause cascading events can yields high prediction accuracy. Being aware of loss of synchronism in real time, operators can implement controlled islanding at carefully designed transmission interfaces and rapidly stabilize each island. Thus a significant amount of load is still served compared to uncontrolled system islanding.

Delivering accurate and timely data to all

This paper discusses a model-based substation automation application for advanced data availability. The SuperCalibrator concept provides a basic technology to filter all substation data that are readily available by the substation automation scheme. The SuperCalibrator is conceptually very simple. It is a state estimator using a detailed three-phase breaker-oriented instrumentation-inclusive substation model. As such, the errors introduced by the instrumentation are compensated and the estimated values are closer to the actual values of the electric power system. The overall methodology identifies bad data and wrong topologies and quantifies the quality of the filtered data expressed in terms of the expected error in this data. Substation automation enables the seamless implementation of the SuperCalibrator. In turn, the SuperCalibrator substantially contributes toward the promise of substation automation to reliably provide accurate data to all clients. The applications discussed in this article should ignite the dialog and the realization that substation automation can make it possible to dramatically improve our approaches and tools in monitoring, controlling, and protecting the electric power grid infrastructure.

Distributed State Estimator Advances and Demonstration

Present state estimator performance is not 100% reliable. Specifically, there is significant probability that the state estimators may not converge to an acceptable solution. On an industry wide basis, the probability of non convergence is about 5%. The reasons for this performance have been investigated and have been reported in earlier papers. In this paper we report on a new approach that alleviates the sources of state estimator unreliability and at the same time distributes the computational procedure to each substation of the system, assuming there is at least one GPS-synchronized device (relay, PMU, recorder, meter, etc.) at each substation. This results in a true distributed estimator. The results of the distributed state estimator are communicated to the control center where the overall system state is constructed. The approach has been implemented to two subsystems of two substations each. This paper describes the overall approach and provides results from the two pilot implementations.

Recent experience with a hybrid SCADA/PMU on-line state estimator

PMU devices are expected to grow in number from a few to several hundreds in the next five years. Some relays are already global positioning system-capable and could provide the same type of data as any PMU. This introduces a new paradigm of very fast accurate synchrophasor measurements from across the grid in real-time that augment and parallel existing slower SCADA measurements. Control center applications will benefit from this PMU data; for example, use of PMU data in state estimation is expected to improve accuracy and robustness, which in turn will result in more timely and accurate N-1 security analysis, resulting in an overall improvement of grid system reliability and security. This paper describes results from a recent implementation of this technology, the benefits and future work.

GPS-Synchronized Data Acquisition: Technology Assessment and Research Issues

GPS-synchronized equipment (PMUs) is in general higher precision equipment as compared to typical SCADA systems. Conceptually, PMU data are time tagged with accuracy of better than 1 microsecond and magnitude accuracy that is better than 0.1%. This potential performance is not achieved in an actual field installation due to errors from instrumentation channels and system imbalances. Presently, PMU data precision from substation installed devices is practically unknown. On the other hand, specific applications of PMU data require specific accuracy of data. Applications vary from simple system monitoring to wide area protection and control to voltage instability prediction. Each application may have different accuracy requirements. For example for simple system monitoring in steady state highly accurate data may not be critical while for transient instability prediction high precision may be critical. For addressing data precision requirements for a variety of applications, it is necessary to quantify the accuracy of the collected PMU data. We discuss data precision requirements for a variety of applications and we propose a methodology for characterizing data errors. In particular, we propose a new approach for improving data accuracy via estimation methods. The proposed methodology quantifies the expected error of the filtered data. Examples are provided that define the instrumentation requirements for specific applications.

Metrics for Success: Performance Metrics for Power System State Estimators and Measurement Designs

Power system state estimators (ses) have come a long way since the introduction of the concept nearly four decades ago by Fred Schweppe. Over the years, the concepts initial formulation, implementation techniques, computational requirements, data manipulation and storage capabilities, and measurement types have changed significantly. Today, SEs are instrumental in facilitating the security and reliability of power system operation and play an important role in the management of power markets where transactions have to be carefully evaluated for feasibility and determination of real-time prices. One of the most recent developments in SEs has been the availability of synchronized phasor measurements and their introduction into the state estimation process. Synchrophasor-assisted state estimation (SPASE) is changing the way we view and operate the grid. As such, the ability to monitor and maintain SE performance within known performance standards (metrics) is a new practice. Unlike deterministic applications such as power fl ow, the state estimation solution is not deterministic and depends on the statistical characteristics of the measurements as well as the level of certainty of the assumed network model.

Phasor Measurement Units (PMU) instrumental in detecting and managing the electrical island created in the aftermath of Hurricane Gustav

During the landfall of Hurricane Gustav on September 1, 2008, an electrical island was formed in an area including the New Orleans, LA and Baton Rouge, LA metropolitan areas. This paper discusses the use of Phasor Measurement Units (PMU) in detecting and identifying the island, as well as, the use of PMUs in the management of the island during the 33 hours the island was in place. This paper is a testament of actual events and actions taken during a hurricane whose destructive capacity in terms of customer outages is only second to Hurricane Katrina. Our conclusions from this experience include: (1) PMUs are vital in the identification and warning of islanding conditions, and (2) PMUs provide significant insight in managing an island.

Dynamic modeling and resilience for power distribution

Resilience of power distribution is pertinent to the energy grid under severe weather. This work develops an analytical formulation for large-scale failure and recovery of power distribution induced by severe weather. A focus is on incorporating pertinent characteristics of topological network structures into spatial temporal modeling. Such characteristics are new notations as dynamic failure- and recovery-neighborhoods. The neighborhoods quantify correlated failures and recoveries due to topology and types of components in power distribution. The resulting model is a multi-scale non-stationary spatial temporal random process. Dynamic resilience is then defined based on the model. Using the model and large-scale real data from Hurricane Ike, unique characteristics are identified: The failures follow the 80/20 rule where 74.3% of the total failures result from 20.7% of failure neighborhoods with up to 72 components “failed” together. Thus the hurricane caused a large number of correlated failures. Unlike the failures, the recoveries follow 60/90 rule: 59.3% of recoveries resulted from 92.7% of all neighborhoods where either one component alone or two together recovered. Thus about 60% recoveries were uncorrelated and required individual restorations. The failure and recovery processes are further studied through the resilience metric to identify the least resilient regions and time durations.

Synchro-Phasor Assisted State Estimation (SPASE)

This paper describes development of a Synchro-Phasor Assisted State Estimator (SPASE). In addition to having the capability to incorporate voltage and current phasor measurements, this state estimator provides some novel metrics related to measurement configuration and quality in order to improve reliability, accuracy, solution performance and measurement design. It also creates the necessary output files that will enable importance-based visualization of these metrics as well as the solution of the state estimator.