Power forward curves and forecasting services are the universally accepted authority on predicting wholesale electricity price performance. But are they accurate?
Recent CFR research suggests forecasting services have consistently overestimated annual growth rates of wholesale power pricing across every U.S. grid region. Organizations using these metrics in decision making may be inaccurately predicting economic performance and leaving savings on the table.
While it is impossible to predict the future, organizations pursuing renewable energy can ensure they receive best-in-class predictions by partnering with a trusted advisor that is able to understand market forecasts in the context of broader trends.
Why Brown Power Prices Matter to Renewable Energy Deals
While it is commonly understood that the unprecedented boom in U.S. hydraulic fracturing, or “fracking,” has led to record-low natural gas prices, less acknowledged is the impact of this phenomenon on the economics of large-scale renewable energy (RE). Recent CFR research sheds new light on this connection, demonstrating that conventional power price forecasting methods have consistently overestimated medium-term trends.
Increasing ambition among universities, corporates, and other large institutions to meet lofty greenhouse gas (GHG) reduction standards has led many to pursue the financial and strategic value associated with large-scale RE procurement. Power purchase agreements (PPAs) are the most prominent instrument used by such organizations to directly enable the development of new RE projects. In their simplest form, PPAs provide renewable electricity at a fixed price over a long period of time, while allowing the off-taker to capture revenue from the resale of the project’s power into the wholesale market.
A well-executed PPA is designed to generate savings and create a natural hedge against ongoing brown power purchases from the off-taker’s local grid – and in regions where PPA prices are below the prevailing wholesale price of electricity, PPAs are especially attractive. However, the relationship between PPA rate and wholesale strike price is difficult to project into the future, thereby introducing risk into the transaction. While PPA prices are typically fixed over the contract term, wholesale prices can be quite unpredictable. CFR’s role as an advisor to clients is to help them understand and mitigate this wholesale commodity risk before making the decision to enter into a long-term contract.
Developers and brokers typically project wholesale prices based on a combination of power forward curves (derived from highly liquid traded instruments from OTC Global Holdings) and power price forecasting services (e.g. S&P Global, Wood Mackenzie, etc.). These rigorously vetted sources are the best available in the market, and it can be tempting to take these projections at face value. Unfortunately, reality is a bit more complicated.
Our Finding: Power Prices Grew Slower Than Forecasted
CFR recently analyzed annual forward curves from OTC Global Holdings and annual power price forecasts from S&P Global Market Intelligence at primary trading hubs in each of the seven U.S. RTOs/ISOs originating between 2012-2015 (with expected pricing extending 7-20 years depending on the source). We pulled curves and forecasts from each quarter where data was available during this period, along with actual wholesale electricity prices from 2012-2018. We then compared implied growth rates over durations of three to six years against actual historical rates for each of the sources under examination.
As shown in Fig. 1, the data reveal that across all hubs, forwards and forecasts consistently overshot actual performance. Indeed, this gap between expectations and reality can have substantial implications for the economics of PPA contracts.
Wholesale PPAs are attractive but inherently risky contracts that must be rigorously tested, modeled, and vetted prior to implementation. It is critical for organizations looking to implement large-scale RE contracts to partner with a trusted advisor who is familiar with these markets and has developed robust risk assessment tools. For example, CFR employs a suite of tools including analysis of broader market fundamentals, Monte Carlo simulation, and sensitizing key forecasting assumptions. PPAs remain a tremendous source of potential value to help organizations achieve their financial and strategic goals, but they must be evaluated rigorously in order to capture that value and protect against risk.
Key findings
- In every region, at least 70% off forecast or forward curves had expected compound annual growth rates (CAGRs) greater than actual growth over the same time period.
- Predictions of growth were as high as 20-30% percentage points in excess of actual growth over the same period.
- Predictions of growth averaged 2-14% percentage points in excess of actual growth over the same period.
Data
| Description | Source | CAISO | ERCOT | SPP | PJM | ISO-NE | NYISO | MISO |
| Frequency of expected > actual CAGRs | OTCGH forwards | 90% | 90% | 100% | 100% | 80% | 100% | 95% |
| S&P forecast | 70% | 70% | 100% | 100% | 90% | 100% | 80% | |
| Max %pt. spread between expected and actual CAGRs | OTCGH forwards | 20% | 31% | 14% | 26% | 26% | 33% | 19% |
| S&P forecast | 6% | 26% | 5% | 22% | 23% | 23% | 10% | |
| Average %pt. spread between expected and actual CAGRs | OTCGH forwards | 7% | 10% | 9% | 8% | 8% | 11% | 5% |
| S&P forecast | 2% | 5% | 5% | 11% | 8% | 14% | 5% |
