Financial Forecast Tool
The Financial Forecast Tool (FFT) is an in-house financial planning tool, created by the city. It is used to evaluate the cash flows and budget associated with the operation of a local electric utility over time. The tool provides flexibility to change assumptions and run a variety of scenarios that enable decisions to be made about the utility’s financial health.
Originally released in 2016, the Excel-based model is updated as new information becomes available. This page provides information on the December 2018 update. For additional information about the tool and financial analysis, review the December 2018 staff information packet memo to City Council . For previous versions of the tool, please email [email protected]
After updating the high-impact variables, the tool demonstrates that operating a local electric utility shows promising financial feasibility. This is, in large part, due to significantly less expensive power supply options that also provide greater amounts of renewable energy.
The Tool In Depth
The Financial Forecast Tool is an in-house financial planning tool completed in November 2016. It is used to evaluate cash flows and budgets associated with the operation of a local electric utility over time. The tool provides flexibility to change assumptions and run a variety of scenarios that enable decision-making about the utility’s financial health.
- Generates budget forecasts and financial metrics and a proforma cash flow to provide to rating agencies for use in evaluating the electric utility's credit worthiness prior to bond issuance;
- Formulaically represents relevant city financial policies;
- Demonstrates sensitivity and impact on cash flows from varying scenarios at a case-by-case level—at minimum, changes to resource costs, capital costs, operations costs, sales and economic trends;
- Tracks historic costs and generates forecasts;
- Generates budgets to be placed into the city’s accounting/financial system; and
- Evaluates key metrics related to debt service coverage, performance and liquidity.
This tool does not:
- Design rates
- Generate load forecasts
- Plan long-range power supply
- Create forecasts related to City Charter metrics on reliability, renewable energy and carbon intensity
- Compare rates with peer utilities, including other municipal utilities
Complete details of the inputs can be found in the Financial Forecast Tool User Manual.
For the purposes of this analysis, the following range of assumptions were used as the following variables:
- Acquisition Cost: The cost to acquire the electric system assets from Xcel Energy
- Interest Rates
- Debt Service Coverage Ratio: The measure of cash flow available to meet debt obligations
- Annual Operations and Maintenance Costs
- Load Growth Rates: How fast electric load grows in Boulder on an annual basis
|Acquisition Cost||Interest Rates (Taxable/Tax Exempt)||Debt Service Coverage Ratio||Annual Operations and Maintenance||Load Growth Rates|
|Source||City Charter/ Xcel Energy||Financial Advisor||Financial Advisor||American Public Power Association (APPA)/ City Research||Xcel Energy/ City analysis|
- Power Supply Scenarios: There are three power supply scenarios programmed into the FFT:
- 100% Xcel Energy
- 3-years Xcel Energy, then high renewables (Gradual Departure)
- Day 1 High Renewables
- 100% Renewable Electricity
From these ranges of variables, staff used the medium case (highlighted above) as a fair and conservative proxy for what is most likely to occur.
The city used the medium case (highlighted) with variations on acquisition cost and power purchase costs to produce the four runs presented as results. Staff believes Scenario 1 is conservative representation financial feasibility using today's best data.
|Scenario||Load Growth||Acquisition Cost||Power Supply Scenario|
As stated previously, staff considers the medium case described in Table 1 as a conservative scenario. The medium-level assumptions serve as the base assumptions for most other scenarios analyzed.
Each scenario is based on a 10-year forecast. Financial feasibility is measured through the net present value (NPV) of savings or losses over five and 10 years. This is measured in two ways:
- The NPV of the difference in the revenues requirements, or earnings test, is determined by using Xcel Energy’s rates and the revenue requirement of the municipal utility. The revenue requirement of the municipal utility includes all expenses and the amount the charter says the city needs to set aside to cover debt payments. Therefore, years that are negative are ones where additional revenue or operational savings may be needed to meet the target amounts to be collected.
- The NPV of the actual cash flows over the forecast period. This analysis shows the amount of cash the utility has available to use each year after all expenses and debt payments are made. The cash flow includes the revenues collected for debt service coverage, because the utility can use money collected to meet debt service coverage for reinvestment in the system, building cash reserves or other utility purposes.
Below is a high-level summary of the net present value over five and years for each of the four scenarios listed in the tab above shown by both revenue requirement and cash flow.
|Results - Revenue Requirement/ Earnings Test||Scenario|
|Net Present Value (NPV) of Savings/(Losses) $ in (000s)||1||2||3||4|
|NPV of Savings/(Losses) over 5 years||$37,905||$10,156||$11,513||$(47,319)|
|NPV of Savings/(Losses) over 10 years||$134,228||$59,892||$80,919||$37,721|
|Results - Cash Flow, no minimum DSCR set $ in (000s)||1||2||3||4|
|NPV of Savings/(Losses) over 5 years||$104,984||$76,982||$92,155||$20,936|
|NPV of Savings/(Losses) over 10 years||$257,491||$182,701||$228,687||$163,808|
The results of this analysis show there are multiple scenarios that are financially viable. Scenarios one, two, and three demonstrate a municipal electric utility with enough annual and cumulative savings to provide flexibility to manage risks and meet the local goals set out for forming a municipal utility. For example, savings could support building even more robust reserves, accelerating undergrounding, increasing incentives for renewable energy and storage, or paying down debt.
Scenario 4 presents the most expensive case in this analysis. This scenario would require additional revenue or operational savings to produce a positive net present value during the first five years of operation. This is because Boulder would be purchasing 100 percent of its electricity requirements from Xcel Energy as a wholesale customer for three years, which is substantially more expensive than other options. Staff anticipates the city’s power supply obligations will become clearer through additional negotiations and regulatory and legal proceedings. It is important to note that the forecasts presented do not account for decisions and adjustments that would be made on an annual or even more frequent basis to manage cash flow and other changes to conditions. These decisions would be made through public input, review by the electric utility governing board and the city council.
In December 2018, city staff held a demonstration of the tool. Watch the demonstration below:
|Address||Phone||Executive Director||Want to stay in touch?|
1101 Arapahoe Ave.
Boulder, CO 80302
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