In September 2018, a field engineer’s mistake while replacing cast iron main in Lawrence, Massachusetts (USA), led to a death and over a billion dollars of property damage. Residents and businesses in the area were without natural gas service for months, at a time of the year when temperatures had already started dropping. One year later, every natural gas utility in the United States is bearing a share of the brunt of the backlash, as the National Transportation Safety Board starts to lay the groundwork for increased regulations nationwide. One aspect of the heightened attention on natural gas utilities is the vulnerability of the regulator stations themselves, even though the cause of the disaster cited above was traced back to a misplaced sensing line. Regulator stations are such a critical element of a distribution network that any comprehensive risk analysis program must include them.

One tool that could help is a regulator station risk model that evaluates the potential fail open and fail closed scenarios for numerous regulator station design types. The likelihood of these events is then paired with the potential consequences, including health and safety, property damage, and network outage impacts.

The output of these risk models form a critical set of inputs for use in an overarching probabilistic risk model, as being promoted by the Pipeline and Hazardous Materials Safety Administration (PHMSA), to support risk-informed decision-making.

The early part of this paper describes the regulator station risk model itself. The latter part documents the methodology used to provide critical information required by the risk model for determining consequence of failure. Finally, a parametric study approach is added to analyze the hydraulic consequences of regulator stations completely failing open.

This paper discusses how the application generates results, including number of customers affected, how much pressure is seen downstream, station scoring, and total length of pipe overpressured. This analysis is performed wholly on Microsoft Azure public cloud, using a version of a commonly-used hydraulic engine from a desktop product. This architecture enables an entire system to be analyzed in minutes compared to hours or days for an engineer to complete manually. Time is always a barrier to performing lengthy analyses, and this application helps to erode that barrier by enabling utilities to generate the results they need to perform risk analyses more frequently. This is important because these natural gas systems are constantly in states of disrepair or repair. Having an up-to-date risk model helps to keep the public safe and helps the utility to make the best decisions for managing and operating their system.

DNV works directly with clients to implement necessary measures to define threats and comply with federal and local regulations. The paper’s authors intend on partnering with select utilities to develop comprehensive station risk management plans, which will help refine the methodologies described in the paper. This may not take place until after this paper is published, so any advancements derived from these partnerships may have to wait for publication at the 2021 conference.

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