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Synchrophasor Technology at BPA

From Wide-Area Monitoring to Wide-Area Control

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Power System Grid Operation Using Synchrophasor Technology

Part of the book series: Power Electronics and Power Systems ((PEPS))

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Abstract

Bonneville Power Administration (BPA) was among the first adopters of the synchrophasor technology in the early 1990s. Initial PMUs were installed as stand-alone disturbance recorders at four substations collecting data locally at a rate of 30 times each second. The value of the synchrophasor technology was evident when the synchronized dynamic data enabled detailed analysis of some of the events/outages that happened in 1996. Following the outages, BPA greatly expanded its PMU coverage to monitor large power plants, interties, and load centers. BPA also researched, developed, and prototyped several applications that use wide-area synchronized measurements for power system analysis. This chapter presents BPA’s efforts and contributions in using synchrophasor technology in managing the grid.

Contributors:

BPA Transmission Planning

BPA Transmission Operations

BPA Transmission Engineering

BPA Transmission Innovation

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Abbreviations

BPA:

Bonneville Power Administration

CERTS:

Consortium for Electric Reliability Technology Solutions

CAISO:

California Independent System Operator

COI:

California–Oregon Intertie

DOE:

US Department of Energy

EIM:

Energy Imbalance Market

EPRI:

Electric Power Research Institute

ERCOT:

Electric Reliability Council of Texas

FCRPS:

Federal Columbia River Power System

LBNL:

Lawrence Berkeley National Laboratory

NASPI:

North American Synchrophasor Initiative

NERC:

North American Reliability Corporation

NREL:

National Renewable Energy Laboratory

PNNL:

Pacific Northwest National Laboratory

RAS:

Remedial Action Scheme

TIP:

(BPA) Technology Innovation Project

UVIG:

Utility Variable generation Integration Group

WECC:

Western Electricity Coordinating Council

References

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Acknowledgements

We gratefully acknowledge BPA engineers who paved the road to the deployment of the synchrophasor technology at BPA. Bill Mittelstadt, John Hauer, Carson Taylor, Jules Esztergalyos, and Ken Martin were among the first visionaries to recognize the value of the technology, develop the first synchrophasor network, research and prototype leading-edge applications. Support from John Haner, Susan Wiess and Don Watkins helped BPA to move through early stages of technology deployment.

BPA executives and management provided strong support and inspiration for the research, development, and deployment of the synchrophasor technology at BPA, including Vickie VanZandt, Brian Silverstein, and Larry Bekkedahl.

BPA synchrophasor investment project was unprecedented for the Agency with a very aggressive timeline. Jim Dow developed the initial project plan, schedule, and cost estimates. Scott Lissit served as a Project Manager during the critical first phase of the project. The successful execution of the synchrophasor investment project is attributed to BPA Project Management Organization.

A project of this complexity and magnitude requires collaboration with industry organizations, other utilities, national laboratories, and researchers. We want to acknowledge Alison Silverstein, NASPI Project Manager, for her leadership in the technology outreach and vision for the technology potential. Phil Overholt at DOE, Jeff Dagle at PNNL, and Joe Eto at LBNL have been supporting research and development of the synchrophasor technology over the past two decades, taking concepts and ideas and converting them into production-quality applications. Ryan Quint and Bob Cummings at NERC have been the visionaries on how the technology can be applied for improving system reliability. Damir Novosel has been the technology champion for the past two decades, leading work on standards, technology solutions, and value proposition. Armando Salazar, Bharat Bhargava, Jim McIntosh, and Jim Hiebert were among the first pioneers to bring the technology in a control room environment. We greatly value collaboration with many operating entities in the West and their technical staff.

We are certainly grateful for the opportunity to work with the leading researchers in the industry and collaborate with them on application development and deployment—Dan Trudnowski, Matt Donnelly, John Pierre, Dave Schoenwald, Bernie Lesieutre, Chris DeMarco, Joe Chow, Pouyan Pourbeik, Henry Huang, Jim Follum, Pavel Etingov, Frank Tuffner, and Ning Zhou, and many others.

We are especially thankful to Alison Silversten, NASPI Manager, for her extensive contributions to this publication.

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Appendices

Appendix A: July 2, 1996 Western Interconnection Outage

On July 2, 1996, a large-scale power outage occurred in the Western Interconnection. It started with a loss of two 345-kV transmission lines from Wyoming to Idaho. Thermal overloads cascaded into lower-voltage lines, which resulted in voltage collapse in the Boise, Idaho area. But the disturbance did not stop there. Voltage collapse propagated into Southern Oregon and caused fast voltage decline on the California–Oregon AC Intertie (COI) as shown in Fig. 4.3. Line protection opened three COI lines, resulting in uncontrolled system breakup and loss of load and generation. Total of 2 million customers were affected, and 11,850 MW of power interrupted.

Fig. 4.3
figure 3

Voltages on California–Oregon Intertie during July 2, 1996 Western Interconnection power outage

Appendix B: August 10, 1996 Western Interconnection Outage

On August 10, 1996, another large-scale power outage occurred in the Western Interconnection. The interconnection broke into four islands, interrupting service to 7.5 million customers mainly in California and the Southwest. The sequence of events was initiated by the loss of a Keeler–Allston 500-kV line near Portland, Oregon. The line loss resulted in overloads on lower-voltage transmission lines in the area and depressed grid voltages. Several minutes later, two lower-voltage lines in Portland area tipped due to thermal overloads, and further depressing voltages. McNary generators were already boosting full reactive power to support grid voltages, and started sequentially tripping by over-excitation protection. McNary tripping started growing voltage and power oscillations on California–Oregon Intertie as shown in Fig. 4.4. COI lines were opened by line protection about 90 s from the time oscillations began.

Fig. 4.4
figure 4

Voltages on California–Oregon Intertie during August 10, 1996 Western Interconnection power outage

Appendix C: June 14, 2004 Generation Outage in the West

A delayed cleared fault in Arizona caused generation loss in excess of 4,000 MW, which in turns drove system frequency down to 59.5 Hz, and created large power swing and voltage drop at California-Oregon Intertie [21]. Once the system settled, BPA operators were presented with a dilemma: system frequency was abnormally low at 59.75 Hz, while COI power flows were significantly above its system operating limit (Fig. 4.5).

Fig. 4.5
figure 5

Frequency, power, and voltages during June 14, 2004 event

Appendix D: Frequency Response Analysis at BPA

4.4.1 Event Detection

BPA runs the frequency event detection application in real time. Both BPA and partner data are used by the algorithm. The application takes a derivative of voltage phasor angles to calculate bus frequency. Although PMUs report bus frequency, there is a difference between frequency filtering algorithms used by various PMUs . An onset of frequency deviation is detected by magnitude of frequency deviation and its rate of change. The application uses rate of frequency change to locate the source of frequency disturbance, as the bus frequency will decline the fastest closer to the event location.

4.4.2 Notification

The application sends out a notification of the event occurrence as well as information about the magnitude of frequency deviation and PMU which had the fastest rate of change of frequency.

4.4.3 Visualization

BPA technical staff has access to visualization displays similar to ones used by BPA dispatchers in the control room.

An overview display shows Western Interconnection map (with zoom in on Pacific Northwest). The size of the dot corresponds to rate of frequency change at that PMU location. In this case, it is evident that a frequency disturbance originated in Arizona.

BPA technical staff can also pull out 90-s plots of system frequency during the event, as well as power flows on California–Oregon Intertie, Northern Intertie, and Montana Intertie.

4.4.4 Data Extract

BPA has several applications to extract data from its OSI Soft PI servers. One of the advantages of OSI Soft PI architecture at BPA is that an application can simultaneously access both SCADA and PMU PI historians. BPA uses high-resolution measurement of bus frequencies, voltages, phasor angles, intertie flows, and generation from PMU historian, and 2-s AGC quantities from its SCADA historian. SCADA data are time-synchronized at control center, so that there is a time lag between PMU and SCADA measurements , in our experience at least SCADA scan rate of 2 s. The data extract applications can time-shift SCADA quantities for better alignment with synchrophasor measurements .

4.4.5 Analysis

BPA uses the frequency response analysis tool (FRAT), co-developed with PNNL, for its frequency response analysis . FRAT is an interactive application to perform frequency response analysis at an interconnection and Balancing Authority levels according to NERC BAL-003-1 methodology.

4.4.6 Baselining

The FRAT database has an extensive system event log, going back to 2008. This log creates the opportunity to evaluate frequency response trends over many years. BPA has been using the FRAT baseline to support its arguments in filings with Federal Energy Regulatory Commission (FERC) during the development of NERC BAL-003-1 Frequency Response Reliability Standard.

First, we can trend the Western Interconnection frequency response and compare against the requirement set forth by NERC BAL-003-1 Reliability Standard. Trending WECC frequency response is important for tracking the impact of the changing generation resource mix has on the frequency response.

Similar plots can be made for BPA’s Balancing Authority. Ultimately, a Balancing Authority is an entity responsible for compliance with NERC BAL-003-1 Standard. Such analysis is very helpful for BPA to understand its inventory of frequency responsive reserves, and factors affecting its performance. BPA can perform correlation analysis between observed frequency response and generation resource mix—hydro, wind, etc. For BPA, there is a strong correlation between available hydro-generation capacity and its frequency response performance.

4.4.7 Generating Fleet Performance Analysis

BPA developed a MATLAB application for analysis of generator performance during a frequency disturbance event. An application plots observed versus expected range of generator responses. The application is very useful in identifying generator response abnormalities.

Example below shows examples of good and questionable responses to the event. The red lines represent the expected range of the governor response, and the blue lines represent the observed generator response. These data can be shared with the USACE and USBR to develop a solution for undesired plant behavior.

4.4.8 Power Pickup Analysis

Frequency response is not only about arresting system frequency decline and recovery following a resource loss. Governor response to frequency deviation can increase power flows on transmission system and thereby create voltage stability risks. This is particularly relevant to California–Oregon Intertie which can be post-transient voltage stability limited by generation outages in California and Desert Southwest. BPA has been baselining governor pickup on California–Oregon Intertie since late 1990s to make sure that actual pickup is accurately represented in power system studies.

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Kosterev, D. (2019). Synchrophasor Technology at BPA. In: Nuthalapati, S. (eds) Power System Grid Operation Using Synchrophasor Technology . Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-89378-5_4

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