Clean repowering is a project development strategy that sites new clean generation at the same point of interconnection as existing or retiring fossil generators. This allows these projects to take advantage of specific IRA incentives and to potentially pursue a streamlined interconnection process.

Not necessarily. There are two types of clean repowering: surplus interconnection and generator replacement. Surplus interconnection refers to adding new generation at the site of an existing plant that would continue to operate. The majority of the clean repowering opportunities identified in this analysis are surplus interconnection, which doesn't require retirements. Generator replacement refers to adding new generation at the site of a retiring plant, which requires that the existing generator retire when the new generator comes online. Specifically, a generator replacement request must be made one year prior to retirement, and the new generator must come online within three years.

This analysis includes generation assets reported to EIA in the contiguous United States (Hawaii and Alaska were excluded due to data constraints). The map displays data at the individual load-serving entity (LSE) level.

The timeframe of this analysis is 2025-2054. Resource additions are allowed between 2025 and 2031 to reflect near-term opportunities to capture IRA incentives, while the annual operation and cost impact assessment runs through 2054.

The business-as-usual (BAU) scenarios refer to each utility's planned portfolio as reflected in EIA data, including proposed generators and scheduled retirements.

The clean repowering scenarios refer to the cost-optimized scenarios that leverage clean repowering opportunities. Under these scenarios, the model runs every year between 2025 and 2031 to determine whether a discrete number of additional clean repowering opportunities reduce total generation cost relative to no additional clean repowering, and if so, selects the option with the lowest cost. Then the model runs through 2054 to assess the annual operation and cost impact.

Not necessarily. Some LSEs show increased costs because the analysis constructs a set of potential clean repowering portfolios for each balancing authority and then selects the portfolio from that set that provides the most savings for the balancing authority as a whole. Optimizing at a broad level does not provide the maximum benefits to all LSEs in the balancing authority, as the scenarios are not tailored to individual LSEs and may be misaligned to an individual LSE's needs. These LSEs may benefit from a clean repowering strategy specifically designed for them. For example, Mississippi Power generates a large amount of revenue from off-system sales. If Mississippi Power and other LSEs all take advantage of clean repowering, Mississippi Power will generate less off-system sale revenues, creating an appearance of increased costs. The reason for cost increases varies case by case, therefore it requires further investigation to determine the economic feasibility for an individual LSE.

This analysis begins with each utility's planned portfolio as reflected in EIA data (including proposed generators and scheduled retirements) and then adds clean resources on top of that planned portfolio. This ensures the clean repowering portfolios proposed in the analysis will deliver reliability at least as good as the utility's planned portfolio and likely better as the portfolio will be more diverse.

This analysis is focused on how renewables deployed through a clean repowering process can displace the generation of fossil generators to meet current demand and save customers money. This is done by looking at historical hourly fossil generation and assembling portfolios of renewables and storage within 45 km of a fossil site that can best displace the grid region's historical generation while reducing the cost of energy. Then an hourly simulation is run for each grid region using 15 years of historical weather and load data to assess the operational impact of different portfolios and ensure that load in every hour can be met under each scenario.

The analysis starts by calculating the net present value (NPV) of the cost of generation (both capital costs and operational generation costs) for each generation owner. The calculation spans across the period of 2025-2054 for both the BAU scenario and clean repowering scenario using a discount rate equaling the weighted average cost of capital for the generation owner adjusted for deductibility of interest, which would be equivalent to the allowed rate of return for a regulated utility.

Then the analysis calculates customer costs for each LSE, which accounts for both the cost of owned generation and the effect of the purchase and sale of power. To do this it compares the annual owned generation from the model with historical annual retail sales of each LSE as reported by EIA. If a utility's modeled generation exceeds its retail sales, that excess is sold to and pooled at the balancing authority level. The model assumes the price that such a utility gets for its excess generation is its average cost. If a utility's modeled generation is less than its retail sales, it purchases the difference from the balancing authority level pool and all such utilities pay the weighted average cost of utilities that sold into the pool. The same process is repeated at the national level when balancing authority level generation differs from balancing authority level retail sales.

Finally, the analysis calculates the difference in customer costs between the BAU and clean repowering scenarios to get the total customer cost savings for each LSE.

The analysis starts by multiplying the NPV of total customer savings by the fraction of residential sales out of total sales for that utility and state. It then divides that by the number of customers and the number of months in the analysis period (for this analysis, the number of months is 360 — the total clean repowering asset lifetime is 30 years; 12 months*30 years equals 360).

In instances when an LSE has revenue and customers in multiple states, lifetime savings are calculated by multiplying the total cost savings for that LSE by the share of residential revenue across all states, then the value is divided by the total number of residential customers across all states.

Utilization rate is essentially the capacity factor of a point of interconnection. It is calculated as the total deliverable annual generation of all the resources that share the incumbent generator's point of interconnection divided by the maximum deliverable generation possible in that year (the capacity of the incumbent generator multiplied by the number of hours in the period.).

The analysis assumes that clean resources can be connected alongside any fossil generator, essentially turning it into a hybrid resource. But we assume the interconnection capacity is the same as the fossil generators' capacity as a hard constraint. In other words, the amount that can be connected is limited to the capacity of the fossil generator, and during operations we do not allow the output of the combined system (i.e., the fossil generator and clean generators together) to exceed that interconnection capacity.

ITC and PTC (base credits and bonus adders): For new clean assets that are eligible for both the Investment Tax Credit and the Production Tax Credit, the analysis compared the economics of both options and selected the one with the lowest present value of customer costs, which is driven by the capacity factors of the renewable resource and the total up-front capital expenditure. Additionally, a 10% bonus for the energy community adder was selected for projects on a brownfield site, located in a metropolitan statistical area (MSA) or non-MSA meeting fossil employment and unemployment criteria, or located in or adjoining a coal closure community. An increasing amount of domestic content over time was assumed, such that only 20% of the domestic content bonus in 2025 can be claimed (i.e., 2% additional tax credit) increasing linearly to 80% (or 8% additional tax credit) by 2031 and staying constant until the end of the expiration of tax credits.

Tax Transferability: To monetize tax credits, investor-owned utilities (IOUs) were assumed to transfer the corresponding ITC or PTC at 95% of their total dollar value. Nonprofit utilities like municipal utilities, rural cooperatives, and public power companies were assumed to take advantage of direct pay only when they started to meet the domestic content requirements for this benefit as per the domestic content assumptions outlined above; otherwise, nonprofit utilities used the same tax transferability assumptions as IOUs.

Energy Infrastructure Reinvestment (EIR): The analysis uses a conservative estimate of 30% replacement of debt and 20% replacement of equity using EIR funding. The total amount of EIR funding committed under these assumptions would not come close to maxing out the $250 billion EIR loan authority, which is indicative of potential for more aggressive EIR deployment.

Yes, you can download the data file here .