In this blog series, we’ve already discussed a variety of the costs and risks to account for in a retail pricing model. Here, we focus on how important it is for Retail Energy Providers (REPs) to account for these costs while setting volumetric rates for fixed-rate customers.
In this blog series, we’ve already discussed a variety of the costs and risks to account for in a retail pricing model. Here, we focus on how important it is for Retail Energy Providers (REPs) to account for these costs while setting volumetric rates for fixed-rate customers. The effects of an account’s load shape on the overall cost of goods sold (COGS) are difficult to navigate. Not only does the seasonal and daily shape of an account’s usage affect the cost of energy, but it can also lead to large differences in how fixed monthly costs are unitized as part of a fixed-rate contract. Most of the fixed-costs can be attributed to demand charges associated with various reliability markets, typically calculated against a REP’s Peak Load Contribution (PLC). While the definition varies slightly across different markets, the PLC of every account is typically calculated by measuring the instantaneous demand during specific hours of the summer when the system wide load peaks. The relationship between an account’s PLC and their ‘average’ hourly usage is called the “load factor” and it can be expressed as a percentage using the following simple equation:
The exact structure and mechanism of reliability markets have similar purposes but vary considerably across different Regional Transmission Operators (RTOs). Some differences include forecast pool requirements and capacity performance charges of PJM and ISO-NE, seasonal and monthly capacity auctions of NYISO, and zonal scaling factors of ISO-NE. PJM also ensures reliability through the Network Integration and Transmission Service charges. The capacity and network transmission charges are dictated primarily by an account’s PLC from the previous planning year.
Stated simply, these charges represent a fixed monthly cost throughout the year. To calculate a $/MWh rate, the fixed charges are first unitized by dividing by the monthly usage of the account. The unitized fixed costs are inversely related to the account’s load-shape (i.e., lowest during high-usage periods and highest during low-usage periods). On balance, this results in lower volumetric COGS for high load factor accounts in contrast to low usage accounts with identical capacity obligations (see below).
Comparison of COGS for three accounts with identical usage but varying load factors
Load factors typically range from 0 to 100 percent (although winter peaking accounts may have a load factor more than 100 percent). Accounts with load factors closer to 100 percent are cheaper to serve and represent a more flat load shape. Accounts with load factors less than 50 percent are more expensive to serve and frequently represent a more volatile subset of potential customers. It is imperative that this relationship is defined prior to enrollment of an account and, in some contexts, a bad load factor may indicate the enrollment of a specific account should be avoided. It is worth noting that customers with different usages and capacity obligations can nevertheless have similar COGS result for accounts with similar load factors.
As metering infrastructure and Retail Pricing Models continue to improve, it is increasingly necessary to incorporate load factor in the setting of fixed-rate contract structures. Since load factor is such an important piece of determining the wholesale cost of any given account, many REPs are starting to incorporate tiered rate structures to add load factor into their mass marketing efforts. This is an effective way to minimize risk when custom pricing is unavailable. However, if an REP chooses to make their pricing sensitive to load factor, this concept is too often ignored and load factor should be policed in order to ensure enrollments are of the highest quality. For a better understanding of retail pricing, contact the GP Energy Team.