Matthew K. Donnelly

Damping of inter-area oscillations using energy storage

Low frequency inter-area oscillations have been identified as a significant problem in utility systems due to the potential for system damage and the resulting restrictions on power transmission over select lines. Previous research has identified real power injection by energy storage based damping control nodes as a promising approach to mitigate inter-area oscillations. In this paper, a candidate energy storage system based on UltraCapacitor technology is evaluated for damping control applications in the Western Electric Coordinating Council (WECC), and an analytical method for ensuring proper stability margins is also presented for inclusion in a future supervisory control algorithm. Dynamic simulations of the WECC were performed to validate the expected system performance. Finally, the Nyquist stability criteria was employed to derive safe operating regions in the gain, time delay space for a simple two-area system to provide guaranteed margins of stability.

Methodology to determine the technical performance and value proposition for grid-scale energy storage systems :

As the amount of renewable generation increases, the inherent variability of wind and photovoltaic systems must be addressed in order to ensure the continued safe and reliable operation of the nations electricity grid. Grid-scale energy storage systems are uniquely suited to address the variability of renewable generation and to provide other valuable grid services. The goal of this report is to quantify the technical performance required to provide di erent grid bene ts and to specify the proper techniques for estimating the value of grid-scale energy storage systems.

Autonomous demand response for frequency regulation on a large-scale model of an interconnected grid

This research examines the use of autonomous demand response to provide primary frequency control in an interconnected grid. The work builds on previous studies in several key areas: it uses a large realistic model; it establishes a set of metrics which can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology. More than 6,000 simulations of the power system model were conducted during the course of the study. The studies demonstrated that very few conditions associated with autonomous demand response have the potential to degrade reliability, and that the marginal benefit attributable to autonomous demand response is quantifiable and can be used to determine the value of the technology, as compared to traditional means, for providing primary frequency control.

Overview of System Identification for Power Systems from Measured Responses

Abstract Large interconnected power systems are arguably some of the most complicated man-made systems to understand and to characterize. The scale of the problem is immense, involving large numbers of generators, controllers, and transmission lines covering millions of square kilometers. Measurement technology has reached a point where Phasor Measurement Units (PMUs) are being widely installed in power systems all over the world. These devices provide time synchronized (via GPS) phasor measurements from throughout the power grid to Phasor Data Concentrators (PDCs) at power system control centers. These time series can be used to better characterize the system and hopefully, in the long term, to better control the system. This paper presents a tutorial on estimating power system characteristics from measured responses. About a given operating point, power system low-frequency dynamics are well modeled as a high-order, multi-input, multi-output linear system. Of primary interest is the estimation of the inter-area electromechanical modes of the system. These inter-area modes involve generators from one area of the system oscillating against generators in another area of the system. The modes are characterized by their frequency, damping, and shape. In August 1996, the western United States experienced a massive wide spread black out caused by an unstable inter-area mode, involving generators in the north swinging against generators in the south. This paper overviews the problem and examines several methods of estimating the electromechanical modes under different signal conditions. Several real-world examples are given for estimating the electromechanical modes from ambient, transient, or probing situations. When the system is probed, more general state-space and transfer-function models are estimated. Probing a power system with known inputs is challenging and is discussed in this paper. Estimation performance issues are also discussed.

Optimal locations for energy storage damping systems in the Western North American interconnect

Electromechanical oscillations often limit transmission capacity in the western North American Power System (termed the wNAPS). Recent research and development has focused on employing large-scale damping controls via wide-area feedback. Such an approach is made possible by the recent installation of a wide-area real-time measurement system based upon Phasor Measurement Unit (PMU) technology. One potential large-scale damping approach is based on energy storage devices. Such an approach has considerable promise for damping oscillations. This paper considers the placement of such devices within the wNAPS system. We explore combining energy storage devices with HVDC modulation of the Pacific DC Intertie (PDCI). We include eigenanalysis of a reduced-order wNAPS system, detailed analysis of a basic two-area dynamic system, and full-order transient simulations. We conclude that the optimal energy storage location is in the area with the lower inertia.

An adaptive modeling framework for simulating power system dynamics

Power system operation has changed significantly in the last several decades. Factors such as renewable energy integration and deregulation are major contributors to this change. In response, robust simulation techniques must be developed to ensure stable and reliable operation. A simulation environment that encompasses system dynamics of multiple time frames, called an Adaptive Modeling Framework, is introduced. The simulation framework is capable of modeling multiple dynamic characteristics including slow dynamics, such as transient stability, as well as long term dynamics such as frequency regulation or voltage stability.

Initial investigation of data mining applications in event classification and location identification using simulated data from MinniWECC

Phasor measurement units can provide high resolution, synchronized measurements of a power system. These measurements result in massive amounts of data which is tall over time (30 samples per second) and wide over many channels. Data mining techniques are promising tools for quick and efficient examination of power system events with respect to multidimensional correlated data. In this paper, we discuss the implementation and performance of various data mining techniques for classifying common event types and the associated event location. Results are presented using test data from the MinniWECC model of the Western Electricity Coordinating Council (WECC) which is designed to maintain inter-area modal properties. Results show promising performance of these techniques for identifying both events (classification rates exceeding 99%) and event locations (classification rates exceeding 80%). This paper also discusses strategies and challenges for implementing such data mining techniques to real world PMU data.