Implicit in Public Service Electric & Gas’s Energy Strong infrastructure plan is the notion that spending money now will save money later by preventing future outages.
But while PSE&G has calculated the costs of its program — $3.9 billion — the monetary benefits are much more difficult to predict.
Ralph LaRossa, PSE&G’s president, said everyone agrees a stronger infrastructure would help. Cost is where the debate lies.
“From a need standpoint, we seem to be on the same side of the table,” he said. “From a recovery standpoint, we’re not asking for more than the national average.”
In justifying the unprecedented cost of Energy Strong, LaRossa pointed to a Rutgers University study that put the total economic cost of Hurricane Sandy at $25 billion. The storm knocked out power to 90 percent of PSE&G’s 2.2 million customers. The Rutgers study totaled utility damage at $1.7 billion, and the cost to businesses at $6.2 billion, though the latter came from a variety of factors, not just outages.
In response to PSE&G’s filing, the Board of Public Utilities sent a series of written questions, including one asking the utility to rank its infrastructure projects by importance using a cost-benefit analysis.
Frank Felder, director of the Center for Energy, Economic and Environmental Policy at Rutgers, said that’s a critical consideration.
“At some point, you’re going to spend more money to prevent an outage than it’s worth,” he said.
Felder’s center has been retained by the BPU to help it calculate the costs and benefits of post-Sandy infrastructure programs like Energy Strong.
One component of PSE&G’s ranking was a metric known as “value of lost load,” which attempts to quantify the lost revenue incurred by businesses and residential customers during power outages, and using those figures to determine the economic benefits of preventing or shortening outages.
Felder said that metric has been around for decades, but it — like other such calculations — is fraught with potential for error, because it necessarily requires a long list of assumptions, such as what types of businesses are affected, how often outages will occur and how long those outages will last.
For instance, he said, a data center might have massive financial losses from even a short outage. A butcher, however, might only suffer severe loss if the outage lasts long enough to destroy his refrigerated inventory.