Sandia’s advanced hardware and analytical solutions address emerging issues in our transmission and distribution systems to minimize the consequences one or more threats can have on the grid.

Why Reliability Is Not Enough

In the wake of 2012’s Superstorm Sandy, New York City residents of a nearby blackout zone wait to fill fuel cans at a station that still had electricity to power the gas pumps.

Grid reliability, which the North American Electric Reliability Corporation (NERC) defines as a combination of grid adequacy (having sufficient generation to meet load) and grid security (having the ability to withstand disturbances), is a conceptually sound but outdated framework for the nation’s 21st century smart grid. Instead, our nation requires a grid that adapts to both large-scale environmental and unnatural events and remains operational in the face of adversity—minimizing the catastrophic consequences that affect quality of life, economic activity, national security, and critical-infrastructure operations. The concept of reliability must be replaced with a resiliency approach—one that looks at the grid not strictly as a flow of electrons but as a grid that services, interfaces with, and impacts people and societies. Put another way, it is the consequences, not the outages per se, that matter.

Sandia’s Solution

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The Resilience Analysis Process (RAP) is a comprehensive methodology for quantifying resilience and evaluating competing alternatives to improve resilience.

Because the complex network of electrical infrastructure that stretches across the United States is critical to our economic well-being and quality of life, grid owners and operators work hard to ensure the system is reliable and able to withstand the effects of common threats. However, strengthening grid resilience, or its ability to minimize the consequences of extreme weather or malicious physical or cyber-attacks, requires understanding the consequences of specific threats to the systems. For example, a grid operator wanting to increase system resilience may not have the tools needed to quantitatively assess the system baseline, nor to optimally select infrastructure improvements to maximize resilience given a budget.

To help grid operators make effective, defensible decisions about protecting local and regional communities from catastrophes related to grid damage, Sandia has developed the Resilience Analysis Process (RAP), a comprehensive methodology for quantifying resilience and evaluating competing alternatives to improve resilience.

This multi-step method, which is based on Sandia’s extensive experience with critical energy infrastructure security, calls for working closely with stakeholders to identify the most crucial potential threats and high-level consequences in their region. Sandia analysts then create a detailed system model and evaluate the model against the specified threats to determine system response and consequences. Finally, the analysts apply stochastic optimization algorithms to identify improvements to the system that minimize consequences and achieve the greatest system resiliency. Specific capabilities include the following:

Sandia has developed a grid damping control strategy that employs real power injections at strategically located points in the grid based upon feedback from real-time Phasor Measurement Units (PMU). The primary objective of this work is to design and demonstrate a prototype control system for damping inter-area oscillations in large-scale interconnected power systems. A key element of the control strategy is a high-level supervisory controller that monitors the behavior of the power system, the PMU network, and the real-time control loop to ensure safe, secure, and reliable damping performance.
Sandia has invested substantially in the development of analytic methods that can quantify resilience using risk based, probabilistic methods as it relates to geomagnetic disturbances (GMD). In the case of this work, the high consequence events take the form of voltage stability margin or specific critical load lost. The threat or threat vector would be one or more specific GMD scenarios. This framework, using an extended version of an AC optimal power flow, enables decision makers to optimally invest in resilience improvements, preventing voltage collapse and widespread blackout.
PRESCIENT, a stochastic production cost modeling tool, automatically produces probabilistic forecasts from deterministic historical forecasts for load, solar, and/ or wind power production and their respective time-correlated actuals. Optimization problems for the grid are exceptionally difficult to solve stochastically, but PRESCIENT’s solution method can take hundreds of scenarios and solve the system’s commitment and dispatch problems in tens of minutes, showing the real value of variable generation. This tool uses commercially available solvers such as CPLEX and GUROBI or freely available ones such as GLPK and CBC.
Phasor Measurement Units are used in Sandia’s Control & Optimization of Networked Energy Technologies Lab to advance the grid’s resiliency and reliability.

Phasor Measurement Units are used in Sandia’s Control & Optimization of Networked Energy Technologies Lab to advance the grid’s resiliency and reliability.