In the first two articles of our retail electricity pricing blog series, we focused on the basic principles of rate setting for Retail Energy Providers (REPs), EDI partners, and billing providers. In our third edition, it’s important to highlight wholesale cost forecasting and recovery as a central component of every retail pricing model.
In the first two articles of our retail electricity pricing blog series, we focused on the basic principles of rate setting for Retail Energy Providers (REPs), EDI partners, and billing providers. In our third edition, it’s important to highlight wholesale cost forecasting and recovery as a central component of every retail pricing model. Some explicit components of the wholesale cost, such as capacity, can be forecasted accurately; however, there are more subtle implicit risks that require a degree of statistical extrapolation to account for. While there are many hidden costs to fixed rate pricing, such as residual broker fees, mid-term contract breakage, and renewal probabilities, this article focuses on a few of the most significant, yet abstract concepts: Shape Risk, Swing Risk, and Liquidity / Slippage premiums.
As discussed in the first blog on load profiling, wholesale energy settlements occur at the hourly level, while futures contracts typically trade as ‘blocks’ of specific hour types. These blocks include peak hour (5x16) contracts, off-peak contracts, weekend peak hour (2x16) contracts, and overnight hour blocks (7x8). Shape risk describes the differences in costs incurred to serve an hourly load-shape at actual hourly prices versus the costs associated with the bucketed average hourly load for each hour-type. This is one method for reconciling differences between block-averages with the settlement costs incurred during a given contract. Internal analyses of historical data indicate that shape risk costs are seasonal in nature and depend on the customer-type (e.g., residential, small-commercial, industrial). These costs are proportional to the load-shape of a given hour type within a month. Since the relationships that dictate the intraday LMP curve are dynamic, it is paramount the shape-risk analysis is refreshed at regular intervals within a pricing model to accommodate evolving market dynamics.
(Top) Hourly metered load is contrasted against a block futures contract. (Middle) Real time LMP. (Bottom) Load exposure to real time LMP as measured by the difference between the hedge volume and the metered volume.
Swing risk is best described as the financial impact of temperatures which deviate from expected averages in long-range cost forecasting. Although forward energy marks can be expected to price in available forecasted weather conditions, load-shapes are traditionally weather-normalized and reflect rate class average usage behavior. Actual temperatures during a contracted term are expected to deviate from their average values, causing load estimations for a particular customer to come in either too high or low. In the case of the former, REPs that hedge the full load expectation of a contract in the forward markets will over-procure a (presumably) more expensive energy contract, settling against a lower day ahead hourly energy price. Should temperatures deviate to the more extreme, hedged volumes will fall short of a given account’s actual load obligation to expose the REP to higher than expected energy costs. Under certain market conditions, exposure to the spot-market can result in increased revenue; however, an effective risk management strategy seeks to limit any exposure to volatile commodity prices when possible. While shape risk and swing risk describe similar price effects for fixed-rate contracts, shape risk is a temperature normalized effect while swing risk explicitly handles the impact of temperature deviations from normal.
In addition to these load-centric effects, there are other execution risks that exist for all REPs offering fixed-rate contracts. As discussed above and in previous blog posts, it is important to include all variable or amortized fixed costs that are impacted by adding new customers into its pricing. A retail pricing model should include non-ISO costs by including a premium for liquidity and slippage risks. Liquidity risk describes the typical premium incurred by REPs when hedging small volumes above the mid-market value. An additional buffer should be included to account for market moves between customer enrollment and the procurement of the hedge. Of course liquidity and slippage risks vary based upon location, time of year, velocity of sales, and product type (peak, 2x16 or 7x8). If a broker is used to secure a particular contract, the commission or broker fee should also be included as a piece of the finalized contract rate. Additionally, it is also common for REPs to include a portion of their ISO collateral obligation and the cost of customer procurement into the finalized fixed rate contract.
The execution risks discussed above are present irrespective of a REP’s ability to forecast wholesale ISO costs. To capture the intended margin on any fixed-rate contract, these risks must be analyzed, quantified, and incorporated into the rate structure. Shaping, swing, liquidity, and slippage risks will vary depending on location, volume, and account type. Contact GP Energy Management to ensure that your pricing strategies covers both the implicit and explicit costs of retail supply.