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This report examines the impact of announced retirements on the mix of available generating capacity, prices, resource availability, and air emissions in the Eastern Interconnection. The report uses a security constrained economic dispatch (SCED) model - Ventyx's PROMOD IV 11.1 - of the bulk electric system (BES) to model the interconnection.
In the United States, recent environmental regulations will likely result in the removal of nearly 30 GW of oil and coal-fired generation from the power grid, mostly in the Eastern Interconnection (EI). The effects of this transition on voltage stability and transmission line flows have previously not been studied from a system-wide perspective. This report discusses the results of power flow studies designed to simulate the evolution of the EI over the next few years as traditional generation sources are replaced with environmentally friendlier ones such as natural gas and wind.
As increasing amounts of renewable energy (RE) resources are incorporated into the bulk-power grid, power system oscillations are expected to change. This work investigates how RE generation impacts the frequency and damping ratio (DR) of two dominant inter-area modes in the U.S. Eastern Interconnection (EI) using regularly updated estimates collected over a 12-month period. Quantile regression is used to derive the correlation between operating conditions and mode properties, and a bootstrap method is used to quantify the uncertainty associated with the correlation estimates. Results show that with an increase in system load, the frequency of a mode decreases and DR increases. Evidence that increasing RE generation results in an increase in frequency and decline in DR was found for one of the two modes studied. This work shows that increasing RE levels will impact the properties of inter-area oscillations in the EI, but it does not indicate the presence of immediate threats to grid stability. The outlined approach can be used to periodically assess changing mode properties as RE levels continue to grow and flag stability concerns before they become serious reliability threats.
Although extensive studies have been conducted on inter‐area oscillation detection and analysis by using phasor measurement data, few have focused on inter‐area oscillation statistics due to the lack of considerably long‐term and high‐resolution recorded data. A preliminary statistical analysis on the inter‐area oscillations that occurred in the U.S. Eastern interconnection from 2010 to 2015 is presented. These oscillation events were captured and recorded by the wide‐area frequency monitoring network FNET/GridEye. Oscillation occurrence, dominant frequency, damping ratio and oscillation excitation types are investigated to explore the statistical characteristics of the detected inter‐area oscillations. The results from this paper will provide valuable information for system operators and planners regarding network operation and future grid development.
A power system's inter-area electromechanical modes of oscillation determine if the system is small-signal stable. Mode meters are tools that estimate the modes based on ambient synchrophasor measurements, allowing continuous monitoring of the system's stability margin. This paper reports on the application of mode meter algorithms to 21 months of synchrophasor measurements from the United States Eastern Interconnection (EI). Estimates for three modes were updated every minute, providing a much more comprehensive set of results than previous studies based on disturbance recordings. The detailed signal designs and mode meter configurations provided in this paper can be used to accelerate mode meter deployments in the EI. Analysis of the mode estimates reveal for the first time how seasonal load changes and system reconfiguration impact the EI system's dynamics.
Reliable power system operation requires that small-signal stability be maintained at all times. Mode meters are measurement-based tools that provide operators with situational awareness of the system's stability margin. They operate by continually tracking the inter-area modes of oscillation that govern small-signal stability. This paper reports on the deployment of mode meters for online monitoring of two dominant modes of oscillation in the United States' Eastern Interconnection (EI). The use of measurements from system operators across the interconnection to provide continuous tracking is novel in the EI. Results from over four months of analysis reveal diurnal patterns in the modes and demonstrate that they can be tracked through a variety of system conditions. The results from this study continue to build an understanding of the EI's modes that will inform future modeling and monitoring efforts.
A power system electromechanical wave propagates from the disturbance location to the rest of system, influencing various types of protections. In addition, since more power-electronics-interfaced generation and energy storage devices are being integrated into power systems, electromechanical wave propagation speeds in the future power systems are likely to change accordingly. In this paper, GPS-synchronized measurement data from a wide-area synchrophasor measurement system FNET/GridEye are used to analyze the characteristics of electromechanical wave propagation in the U.S. Eastern Interconnection (EI) system. Afterwards, high levels of photovoltaic (PV) penetration are modeled in the EI to investigate the influences of a typical power-electronics--interfaced resource on the electromechanical wave propagation speed.
Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. To derive reduced models of large power systems, this paper proposes a measurement-based dynamic equivalent, which uses a set of measurements at the boundary nodes between the study area and external area for model parameter identification. Case studies on the U.S. Eastern Interconnection (EI) demonstrate that the measurement-based equivalent technique can capture the external system behaviors accurately and improve computation efficiency.
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Presented by NETL at Carbon Capture, Utilization, and Storage (CCUS) Conference, 06/16
As photovoltaic (PV) generation penetration increases, the inertial and primary frequency response of North American electric grids after a generation loss disturbance will decrease. This change could negatively influence North American power grids frequency stability. This project produced a series of high PV penetration models from detailed, validated base models of all three U.S. interconnections (Eastern Interconnection, Western Electricity Coordinating Council, and Electric Reliability Council of Texas) so that the effects of increased PV generation on their frequency responses can be fully quantified. Mitigation strategies were also developed and validated using both software and hardware test beds.
This technical report is a summary of work performed under the DOE GMLC program under the task titled “Discovery through Situational Awareness”. The focus of this work was to apply big data, statistical techniques to PMU data to do the following: 1) baseline PMU data and find anomalies with a focus on phase angle pairs, 2) identify the frequencies of dominant modal oscillations between different parts of a power system, and 3) identify and classify frequency events in PMU data. This work was performed on PMU data from the Western Interconnect. Many of these algorithms will be applied to wide area phase angle pair data on the Eastern Interconnect in a tool called ESAMS (Eastern Interconnect Situational Awareness Monitoring System). ESAMS was built by EPG (Electric Power Group) and PNNL and is currently being installed on the Eastern Interconnect. The results discussed in this report were made from 14 PMUs from data ranging from Oct 2016 to May 2018. The PMU data were measured 60 times each second. Fourteen phase angle pairs were included, with reactive and active power being calculated at 14 sites. All results have been de-identified for this report. The methodologies applied in the ESAMS tool are described in Section 2. A baseline of PMU data is created using the last 120 days of data. This baseline describes typical behavior as understood from the data. The baseline is then applied to the next day’s data and anomalies from that baseline are identified. Plots are created to help describe what is anomalous during that specific moment in time. These algorithms are currently being installed on the Eastern Interconnect. FY19 work will include discussing the results and findings from the ESAMS tool. A new method of identifying the frequencies of dominant modal oscillations between different parts of a power system is described in Section 3. A list of 199 frequency events provided by Bonneville Power Administration were used to create algorithms to detect frequency events and to create classification rules that can be used to identify future frequency events. Section 4 discusses the results the performance of 7 different event detection, clustering-based methods. Accuracy percentages ranged from 93.59% to 99.16%, with most methods being very fast. GBM (Gradient Boosting Machine) performed well and quickly. These 7 different methods were also tested to determine how well each built classification rules on training data and then applied those rules to identify future frequency events. Accuracy percentages ranged from 89.09% to 99.9%, with all methods performing quickly. GLM (General Linear Model) was viewed as the top performer when considering accuracy and processing time. Because the list of events consisted of 80% of them as active power events and only 20% as faults, all methods struggled to identify events as faults. Small faults were especially difficult to identify. A separate algorithm was created to help with this. Additional work will be done in FY19 on event detection using more data and more events and refinements to the methods.
Nonsynchronous generations such as photovoltaics (PVs) are expected to undermine bulk power systems (BPSs)' frequency response at high penetration levels. Though the underlying mechanism has been relatively well understood, the accurate assessment and effective enhancement of the U.S. interconnections, frequency response under extra-high PV penetration conditions remains an issue. In this paper, the industry-provided full-detail interconnection models were further validated by synchrophasor frequency measurements and realistically-projected PV geographic distribution information were used to develop extra-high PV penetration scenarios and dynamic models for the three main U.S. interconnections, including Eastern Interconnection (EI), Western Electricity Coordinating Council (WECC), and Electric Reliability Council of Texas (ERCOT). Up to 65% instantaneous PV and 15% wind penetration were simulated and the frequency response change trend of each U.S. interconnection due to the increasing PV penetration level were examined. Most importantly, the practical solutions to address the declining frequency response were discussed. This paper will provide valuable guidance for policy makers, utility operators and academic researchers not only in the U.S. but also other countries in the world.
In 2023 additional electricity transmission would have provided the most value for links that crossed between grid interconnection regions in the United States (the Western Interconnection, the Eastern Interconnection, the Texas Interconnection) or crossed between system operator regions within the same interconnection. Many multi-interconnection or multi-region links had values of greater than $\$20$/MWh, or up to $\$175$ million/yr per 1 GW expanded transmission (subject to limits to the depth of the market at each side of the link). In contrast, many links within regions, or between regions in the northeast, had relatively low values in 2023, following the overall decline in wholesale electricity prices in 2023 compared with 2021-2022. The most valuable link in 2023, at $\$61$ /MWh, was between Texas and the Southwest. Multiple events in 2023 (high natural gas prices in the western U.S., and high summer temperatures in Texas and the Southwest) were observed to have driven this high value. Of particular note, high prices in Texas occurred at a largely distinct set of hours from high prices in the Southwest, helping to drive up the value of transmission in total and demonstrating significant value to both regions. This example demonstrates the unique value of transmission (compared to other solutions, such as building local generation resources) in delivering benefits to multiple regions given its ability to connect areas of the country that inevitably face differing circumstances.