Over 10 years on, the U.S. Department of Energy has worked with industry leaders to inquire, explore, and develop policy that strengthens our energy infrastructure against such widespread failure. Two pieces of legislation supported this work:
- Title XIII of the Energy Independence and Security Act of 2007;
- The American Recovery and Reinvestment Smart Grid projects in October 2009.
Upon the passage of the ARRA act, President Obama justified the act's investments:
"It will make our grid more secure and more reliable, saving us some of the $150 billion we lose each year during power outages."
The Department of Energy published this report two months ago, in October, outlining the progress and accomplishments that these programs have made. This report's format and content reflects the unfortunate reality of metrics-driven organizations, where the majority of content is taken up by reporting on tables and graphs that show us that work has been done (not very surprising!), versus information that might indicate that participants are meeting fundamental objectives.
For example, here's some work that's being done for the entire SGIG program. All you information display purists, please hold back! The design choices of these visuals are not the point of the blog.
Finally, on page 28 of 44, we are given this table:
We want to know whether we're meeting the objective of greater resilience. But this table summarizes the performance of sampled substations in a distribution network. We'd like to get to the more fundamental issue: has the error tolerance in the electrical grid improved? Can we have information about the most vulnerable spots are in the grid under any contingency scenarios, and what's being done to reinforce them?
Stepping back: error tolerance in a network (here, the electrical grid), driven by the centrality and capacity of the network's nodes (e.g. power transmission facilities) is a technical way of describing the conditions under which a network will succumb to a cascading failure. Although it's only a framework for describing huge complexities, it helps to describe and visualize how electrical grids fail.
Additionally, the DOE attributes the performance to the investment. Essentially,
We invested --> performance improved --> the investment caused the improvement.The DOE should strive to do better than reporting using a classic outcome bias statement. Here, the DOE is telling us that the investments worked because the performance improved.
Why can't we get more insight? Well, to be fair, it's hard. It's easier to report on what you do than to report on what you are fixing. Reporting on what you do can be done by putting together surveys, like the DOE did here. This survey formed the basis for the ongoing reporting we're seeing. And it's similar to what the U.S. Treasury did to assess the results of TARP and other bank support activities during the financial crisis of 2008.
But to get to what you are fixing is much, much harder. That requires a depiction of the system and its vulnerabilities. Platts has detailed maps of the energy grid that show interconnections and transmission areas. By seeing the relative magnitude and importance of these network nodes, we have a context for the network, and some initial insights into its error tolerance. If the DOE overlaid its effort in this grid context, it would be a step forward in explaining how these investments are targeted or prioritized.
Furthermore, the DOE is currently classifying these projects by what is being installed, rather than what is being fixed or otherwise reinforced. It would be a lot more informative if the DOE could classify those investments and projects in the context of the grid system's interdependencies and vulnerabilities.
We put forward a project suggestion to the DOE that we hope they'll take up. It's worth exploring. Help us make that more compelling to them by voting for it, here.