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How to Plan for a More-Distributed Grid, Part 1

Four Exciting Projects from around the Country, Part One of Three

This is the first blog in a three-part series. The second blog in this series is available here, and the third here.

One of the main themes at the 2018 RMI Electricity Innovation Lab (eLab) Accelerator event, held in Sundance, Utah, in May, was distributed grid infrastructure—the use of least-cost portfolios of distributed energy resources (DERs) to complement traditional electric grid infrastructure or to defer or avoid investments in it. These combinations, also known as clean energy portfolios (CEPs), consist of resources like utility-scale and distributed wind and solar generation, battery energy storage, energy efficiency, and demand response technologies used in place of new power plants or transmission and distribution infrastructure.

In a recent report, The Economics of Clean Energy Portfolios, RMI showed that new-built CEPs are already an economically attractive alternative to new gas-fired power plants in most cases and are likely to beat just the operating costs of efficient gas-fired power plants within the next two decades. With a system as heavily regulated, complex, and interconnected as the electric grid, however, stakeholders can’t just spot a favorable alternative to traditional practice and wing it.

Four teams came to Accelerator to work on distributed grid infrastructure projects from around the United States because they recognize that the falling costs of DERs present new opportunities to serve customers better and meet their growing demands for choice—and that seizing such opportunities requires new grid-planning approaches. These are their stories. In this first part of the blog series, we consider the first team’s work.

Modeling Clean Energy Portfolios

One of the fundamental questions about how to plan for distributed grid infrastructure is how utilities should model it. The default has been to calculate how much generation capacity the grid will need to meet demand in the coming years, and then simply plan for a thermal power plant—coal, nuclear, or natural gas—to provide that capacity, knowing that such a plant will also provide (more than) adequate grid services. It’s now clear that less-expensive combinations of renewables and DERs can often provide the same grid benefits as a thermal power plant, but there’s no good way to include these attributes in the planning process—even industry-standard modeling software doesn’t have a good way to include DERs.

The Accelerator team that tackled this problem included representatives from utilities in Tennessee and California, DER technology providers, and nonprofit organizations. Their common goal was to explore how the resources that make up CEPs can supplant new power plants (in practice, this almost always means new gas-fired plants) and how utilities can change the planning process to include all options to enable an informed choice.

The difficulty in comparing DERs to power plants means utilities risk making an uneconomic choice and potentially stranding assets like power plants that are still within their operating lives but whose operating costs make them uncompetitive. And it makes it hard for outside advocates for clean energy to propose alternatives to new fossil-fueled power plants, on top of the general lack of access to data that often frustrates such environmental advocacy in the electric industry. These issues are not theoretical; there are several cases today where gas-plant projects amounting to billions of dollars of investment are on hold while regulators try to determine whether renewable energy and storage technologies might be better options.

The question, “what is the basis for comparing these things?” leads to questions that are tricky in their own right, such as if CEPs need to do exactly what a gas-fired plant would do. Ideally, a utility would define how much peak generation capacity, ramping capacity, frequency regulation capacity, and so forth that new resources need to have. But, explained the team’s facilitator, RMI manager Mike Henchen, “New gas plants don’t match exactly what a utility needs.” They typically oversupply ramping and frequency regulation, among other grid services. “So matching a gas plant with a clean energy portfolio exactly would overinvest.”

Another tricky question is how to handle the values that CEPs provide that gas plants do not, but that are difficult to assign a dollar value to. For instance, placing renewable energy generation and battery energy storage resources across the distribution grid reduces the need for added transmission and distribution infrastructure that a new, centralized power plant would require. But it’s difficult to model exactly how many substations and how many miles of lines would be avoided with DERs because so many factors, like the changing scale and location of demand, must be estimated over so many years.

The team conceived of near-term and long-term solutions to these planning problems. In the near term, they found ways to take existing planning processes and plug different portfolios of resources into them, however inelegantly. This approach has immediate value while not changing the entire utility planning process, and importantly, it can be piloted right away.

For the long term, the team discussed an attribute-based approach in which a utility establishes what increments of different attributes it will need, year by year, over the next 10 or 20 years, and then judges whether a CEP or a power plant would be the least-cost source of those attributes. This would take into account the dynamic, incremental nature of DER investment, instead of treating DERs like one-off power plant investments. Some utilities are piloting this attribute-based planning approach in limited, small-scale experiments. One of the most advanced is the Preferred Resources Pilot, a project of one of the team members, Southern California Edison. More than 100 MW of DERs are expected to be operational by the end of the year in Orange County, California.

But while the team broadly aligned on a shift to attribute-based modeling, accounting for the extra value of CEPs remains a tough nut to crack. For the foreseeable future, CEPs will retain the handicap of not having their full value included in cost-benefit comparisons with new power plants. Still, with the goodwill and effort of stakeholders like the Accelerator team, that problem should be solved soon.