Publications

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Inverters using phase-locked loops for control depend on voltages generated by synchronous machines to operate. This might be problematic if much of the conventional generation fleet is displaced by inverters. To solve this problem, grid-forming control for inverters has been proposed as being capable of autonomously regulating grid voltages and frequency. Presently, the performance of bulk power systems with massive penetration of grid-forming inverters has not been thoroughly studied as to elucidate benefits. Hence, this paper presents inverter models with two grid-forming strategies: virtual oscillator control and droop control. The two models are specifically developed to be used in positive-sequence simulation packages and have been implemented in PSLF. The implementations are used to study the performance of bulk power grids incorporating inverters with gridforming capability. Specifically, simulations are conducted on a modified IEEE 39-bus test system and the microWECC test system with varying levels of synchronous and inverter-based generation. The dynamic performance of the tested systems with gridforming inverters during contingency events is better than cases with only synchronous generation.

Momentary cessation refers to an inverter control mode. When the inverter terminal voltage falls below (or exceeds) a certain level, the inverter ceases to output any current, but attempts to maintain (or quickly regain) phase-locked loop synchronization to allow for quick reinjection of current when the voltage recovers to a certain point. This paper presents a photovoltaic (PV) momentary cessation model developed in PSS/E. Simulations are presented for a high voltage transmission line fault contingency in the Hawaiian island of Oahu power system on a validated PSS/E model, modified to include a custom distributed PV inverter model, and different near-future distributed PV penetration levels. Simulations for the island power system include different penetration levels of PV, and different recovery times (ramp rates and delays) after momentary cessation. The results indicate that during low voltage events, such as faults, momentary cessation can produce severe under frequency events, causing significant load shed and shortly thereafter, in some cases, over frequency events that cause generation to trip offline. The problem is exacerbated with higher penetration levels of PV. If momentary cessation is used (as is typically the case for distribution-connected resources), the recovery process after momentary cessation should be carefully considered to minimize impacts to bulk power system stability.

This report presents a complete listing, as of May 2019, of the damping controller (DCON) project accomplishments including a project overview, project innovations, awards, patent application, journal papers, conference papers, project reports, and project presentations. The purpose of the DCON is to mitigate inter-area oscillations in the WI by active improvement of oscillatory mode damping using phasor measurement unit (PMU) feedback to modulate power flow in the PDCI. The DCON project is the result of a collaboration between Sandia National Laboratories (SNL), Montana Technological University (MTU), Bonneville Power Administration (BPA), and the Department of Energy Office of Electricity (DOE-OE).

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Utilizing historical utility outage data, an approach is presented to optimize investments which maximize reliability, i.e., minimize System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) metrics. This method is designed for distribution system operators (DSOs) to improve reliability through small investments. This approach is not appropriate for large system planning and investments (e.g. new transmission lines or generation) since further economic and stability concerns are required for this type of analysis. The first step in the reliability investment optimization is to create synthetic outage data sets for a future year based on probability density functions of historical utility outage data. Once several (likely hundreds of) future year outage scenarios are created, an optimization model is used to minimize the synthetic outage SAIDI and SAIFI norm (other metrics could also be used). The results from this method can be used for reliability system planning purposes and can inform DSOs which investments to pursue to improve their reliability metrics.

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This study describes the implementation of a tool to estimate latencies and data dropouts in communication networks transferring synchrophasor data defined by the C37.118 standard. The tool assigns a time tag to synchrophasor packets at the time it receives them according to a global positioning system clock and with this information is able to determine the time those packets took to reach the tool. The tool is able to connect simultaneously to multiple phasor measurement units (PMUs) sending packets at different reporting rates with different transport protocols such as user datagram protocol or transmission control protocol. The tool is capable of redistributing every packet it receives to a different device while recording the exact time this information is re-sent into the network. The results of measuring delays from a PMU using this tool are presented and compared with those of a conventional network analyzer. The results show that the tool presented in this paper measures delays more accurately and precisely than the conventional network analyzer.

The Grid of the Future was a one-day workshop to discuss a resilient grid for the 21st and 22nd century. The workshop gathered experts from various fields to explore concepts for the electric power grid of the future with an emphasis on improving resilience. The event was co-sponsored by Sandia National Laboratories, the Albuquerque IEEE Section, the University of New Mexico, New Mexico State University, and the Santa Fe Institute. The presenters identified radical changes to the grid that are expected to occur over the next 25-50 years and the role of resilience. The workshop was held at the University of New Mexico on Wednesday, August 22nd, 2018. This report summarizes presentations and discussions from the workshop.

This report serves as the executive summary to the comprehensive document that describes the software, control logic, and operational functions of the Pacific DC Intertie (PDCI) Oscillation Damping Controller. The purpose of the damping controller (DCON) is to mitigate inter-area oscillations in the Western Interconnection (WI) by active improvement of oscillatory mode damping using phasor measurement unit (PMU) feedback to modulate power flow in the PDCI. This report provides the high level descriptions, diagrams, and charts to receive a basic understanding of the organization and structure of the DCON software. This report complements the much longer comprehensive software document, and it does not include any proprietary information as the more comprehensive report does. The level of detail provided by the comprehensive report on the software documentation is intended to assist with the process needed to obtain compliance for North American Electric Reliability Corporation Critical Infrastructure Protection (NERC-CIP) as a Bulk energy system Cyber Asset (BCA) device. That report organizes, summarizes, and presents the charts, figures, and flow diagrams that detail the organization and function of the damping controller software. The PDCI Wide-Area Damping Controller is the result of a collaboration between Sandia National Laboratories (SNL), Bonneville Power Administration (BPA), Montana Tech University (MTU), and the Department of Energy (DOE).

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Power system utilities continue to strive for increased system resiliency. However, quantifying a baseline system resilience, and deciding the optimal investments to improve their resilience is challenging. This paper discusses a method to create scenarios, based on historical data, that represent the threats of severe weather events, their probability of occurrence, and the system wide consequences they generate. This paper also presents a mixed-integer stochastic nonlinear optimization model which uses the scenarios as an input to determine the optimal investments to reduce the system impacts from those scenarios. The optimization model utilizes a DC power flow to determine the loss of load during an event. Loss of load is the consequence that is minimized in this optimization model as the objective function. The results shown in this paper are from the IEEE RTS-96 three area reliability model. The scenario generation and optimization model have also been utilized on full utility models, but those results cannot be published.

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