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Modeling Utility Financial Impacts with Optimus

Optimus is an RMI-developed tool that quantifies the economic impacts of utility planning and policy scenarios on various stakeholder groups, such as ratepayer classes and shareholders. Optimus can quantify distributional impacts for a range of policy, regulatory, and market sensitivities, including:

  • Existing or potential state and federal policies, such as expanded production tax credits;
  • Refinancing mechanisms, such as securitization;
  • Performance-based regulatory mechanisms, such as multi-year rate plans, revenue decoupling, and performance incentive mechanisms; and
  • Unforeseeable market dynamics, such as demand shocks or fuel cost spikes.

Enhancing Capacity Expansion Modeling and Integrated Resource Plans

Optimus is a complementary analytical tool to capacity expansion modeling. Optimus uses results from capacity expansion models and then applies a variety of policy, financial, and market levers to calculate their impacts on rates, corporate credit and equity metrics, and pollutant emissions. All inputs and levers can be adjusted separately, and all outputs are presented as annual values and reportable at different levels of granularity.

Optimus is nimbler than the models typically run by utilities for integrated resource plans (IRPs) and rate cases analyses. Due to time and resource constraints, utility IRPs usually only assess total ratepayer costs under a limited number of sensitivity scenarios, while rate cases analyses do not account for the full, long-term impacts of investment portfolios. Optimus not only bridges the gap between these existing analytical efforts by streamlining the input-output interactions, but it also accommodates a more comprehensive set of sensitivities that can affect the economics for either the entire system or particular stakeholder groups.

Real World Applications

RMI utilized Optimus in collaboration with parties involved in the North Carolina Carbon Plan. RMI’s analysis showed that an alternative scenario utilizing more clean resources would be less expensive for ratepayers, and less vulnerable to demand shocks and fuel price increases, compared with one of Duke’s proposed scenarios.

The visual below demonstrates how Optimus can attribute the savings and additional costs to specific resources, such as the avoidance of new gas and nuclear buildout.

The below visual demonstrates how Optimus can be used to compare resource portfolios on their vulnerability to fuel price increases. The cleaner resource portfolios depicted - labeled Clean and Regional - are more insulated to increased costs resulting from fuel price increases in years where fueled resources are relied upon most heavily.

Fuel Price Spike Sensitivity Applied to Years Where Fossil Fuel Generation is Relied Upon Most, DEC and DEP Combined (note that the x-axis minimum is $10 Billion).

A real-world example of how Optimus has been used in a regulatory proceeding can be found in RMI’s report: Analyzing the Ratepayer Impacts of Duke Energy’s Carbon Plan Proposal and Synapse’s Alternative Scenarios.

Using Optimus

Lawmakers, regulators, utilities, and stakeholders can use Optimus to assess the distributional effects of transition scenarios, answering questions such as:

  • How will a utility and its ratepayers benefit from different resource planning pathways? How do different pathways alter risks for a utility as well as for its ratepayers?
  • What is the potential financial impact on a utility and its ratepayers from a demand shock (or other market contingencies) for a given resource planning pathway? How would the risk for ratepayers and utility shareholders be apportioned differently under varying policy and regulatory scenarios?
  • Which mechanisms and policies can better balance financial impacts on a utility and its ratepayers, and to what extent?
  • How can performance-based regulation be designed to incentivize the utility to identify resource planning options that can maximize benefits and minimize risks for ratepayers?

Currently, Optimus focuses on evaluating bulk power systems and ratepayer impacts aggregated to the customer class level. We are currently working to extend the model to assess customer impacts by income (low- and medium-income customers) and technology (behind the meter solar+storage, EVs). Existing tools — LBNL’s FINDER tool and Synapse Energy Economics’ study — can provide deeper insights into the customer impacts of demand-side resources.

If you are interested in leveraging Optimus to explore the economic implications of utility resource planning and various decarbonization pathways, contact us at