Creating a better risk model
When dealing with the complex infrastructure of an electric, gas or water utility system, things often go wrong. Things go wrong because there are so many factors that can contribute to a problem. Utility operators face an enormous task. They must gather accurate and timely data, understand the relative importance of each factor, and determine relative risk of damage to the system. Once utility risk is understood, a rational mitigation and investment strategy can be developed. Most utilities are able to prioritize maintenance and replacement projects based on factors such as equipment age, and the history of maintenance, operation, and failure.
Despite such measures, unexpected things happen. In the event of an outage or leak, you will often hear experienced field workers say, “I knew this water main would burst,” or “I suspected this transformer would fail,” and “That gas main has always been troublesome.”
The problem is this: Some of the factors that often contribute to system failure or add risk of failure are not systematically built into the utility risk model. What these experienced workers are doing is a form of spatial analysis in their heads.
Experienced workers know that a pole at the bend of the road is more apt to be hit by a car than a pole along a straight-a-away. A transmission line that crosses a river or canal has a higher risk of being damaged due to river-way traffic. A direct buried cable is more likely to fail if it has experienced a deep freeze followed by a fast thaw if it is buried in rocky soil. While crucial infrastructure information is often known by employees, it is hard to quantify in a risk model. The key to better risk management is a risk model with spatial analysis that reaches both within and outside the utility.
Utilities can now access all kinds of information online and easily incorporate it into a risk model using GIS. We must look to web-based data sources, and take advantage of geo-enabled handheld devices to help build a better risk profile. In addition to internal data, utilities have access to a wide variety of information related to weather, soil, flood patterns, hazards, newsfeeds, and more. Sources include predictive and measured data as well as social media data.
Further, a utility can update its risk model to include information from those experienced workers who have a qualitative understanding of the company’s infrastructure vulnerabilities. Most of this information is spatial in nature, and can be collectively organized on a GIS platform for risk analysis. GIS has the most convenient way of presenting the results of the analysis--in the form of an interactive map that can be viewed over the web, in the field, and from the desktop.
How can GIS technologies and spatial analysis be more readily employed by utilities to enhance their risk models?
