Rethinking Wholesale Metering for Community Choice Aggregators

In my April 2018 CPX blog, Method Used To Calculate Wholesale Electricity Cost May Result In Losses And Liabilities, I pointed out the potential cost and risk implications of the current method with which most Community Choice Aggregators (CCAs), particularly those in PG&E services territory, meter and settle their wholesale energy transactions. This wholesale metering method is commonly known as Settlement Quality Meter Data (SQMD). 

In response to its challenges, a new and improved CCA wholesale metering technique has been developed. Over the past two years, this new CCA wholesale metering technique has been approved by both California Independent System Operators (CAISO) and the California Public Utilities Commission (CPUC), and independently verified and audited by a consulting firm. 

We have accumulated substantial real-world operating experience with the new and improved method, and in the process, gained more insights about wholesale metering for CCAs. In this blog, I want to share these insights. And more importantly, I wish to highlight the opportunities that a more accurate, interval-based wholesale metering method can bring to CCAs.

Almost a decade since the first CCAs were launched, technical solutions and best practices for setting up and operationalizing CCAs have increasingly matured and been commoditized. The industry has addressed a set of technical, regulatory and operational challenges of launching and operating CCAs. The new challenges of the CCA business model are now how to operate a CCA in the way that meets its financial and policy objectives. To effectively maximize the dual goals, it is important to maintain the financial viability and optimize revenues so that CCAs can deliver on policy objectives. It turns out that accurate wholesale metering holds one of the most important keys to achieve and optimize the financial strength of CCAs. 

Two CCA Wholesale Metering Methods

Before we dive into the details, let’s first review the two methods used by CCAs to meter their wholesale energy transactions. 

  • The current method, commonly used by most CCAs (particularly by those in PG&E service territory), employs PG&E load profiles as an approximation to the CCAs own load profile. The PG&E load profiles are then used to retrofit the monthly aggregated billing data shared by PG&E into hourly meter data for wholesale metering and settlement purposes. 
  • The new and improved method takes advantage of the interval meter data shared by PG&E directly. After calibration against the billing data, the interval data is aggregated directly into the CCA system load profiles. By aggregating the interval data shared by PG&E into the CCA system load profiles, the new method has the advantage of more precisely calculating the CCA’s actual load profiles, whereas the current method is only an approximation.   

Depending on the CCA, and the season, the interval-based wholesale metering method can improve the accuracy by as much as 25% on an hourly basis.

It is worth pointing out that the challenge of having to rely on the retail meter data for the wholesale metering is unique to CCAs and other retail business models. For Investor Owned Utilities (IOUs), wholesale metering traditionally leverages a set of wholesale meters, which meter the total amount of energy delivery in the points of energy injections. The wholesale metering system involves a different set of meters than the retail meters, from which CCAs are getting their meter data for billing purposes. 

CCAs, as Load Serving Entities (energy suppliers) with no ownership or control of the distribution grid, do not have access to the IOU’s wholesale meter data, and hence have to leverage the IOU’s retail metering system for wholesale metering and settlement purposes. 

The Need to Precisely Meter Wholesale Transactions 

Interval-based CCA wholesale metering is advantageous because of its ability to precisely calculate a CCA’s load profile. The current method uses PG&E’s load profiles as proxies to a CCA’s load profile, which is only an approximation. In reality, each CCA has a different load profile which is distinct from PG&E’s. 

More precise measurement of wholesale energy transactions is driven by the need to more precisely settle energy transactions, as well as to procure the right amount of Resource Adequacy (RA) to meet CPUC requirements. The former is obvious, while the latter requires some additional explanation. 

The CPUC requires that all Load Serving Entities (LSEs), including CCAs, procure a sufficient amount of RA to meet their respective peak demands on an annual and monthly basis. One year in advance, CCAs must demonstrate that they have secured adequate supply capacity and, on a month-ahead basis, that it has procured sufficient energy to meet 115% of monthly peak demand. The higher a CCA’s peak demand, the more RA it needs to procure. In other words, the shape of a CCA’s load profile matters. Even if two CCAs purchase the same amount of electricity in aggregate, the CCA with a peakier load profile would need to procure more RA than the one with a flatter load profile (see Figure 1). RA is expensive and hence there is a need to precisely meter the wholesale demand. In some cases, the difference between the two can be as much as 10% of the wholesale procurement cost.


Comparison of two hypothetical CCAs—one with a flatter load profile (in Yellow) than PG&E’s (in Blue color), and the other with a peakier load profile (in Green). Even if both CCAs procure the same amount of total energy, the CCA with the peakier load profile must procure more RA than the CCA with flatter load profile to meet CPUC requirements.

 

The Current CCA Wholesale Metering Method May Lead to Potential Under or Over Procurement of Resource Adequacy 

The use of PG&E load profiles as approximations of CCA load profiles in CCA wholesale metering can potentially lead to under or over-procurement of RA. For CCAs with flatter load profiles than PG&E’s (for example, CCAs in the coastal climate zone), the current CCA wholesale metering method can potentially lead to over estimation of the peak demand and over-procurement of RA. For CCAs with peakier load profiles than PG&E’s (for example, the CCAs in the inland climate zones), the current wholesale metering method can potentially lead to under estimation of the peak demand and hence result in under-procurement of RA. The amount of RA each CCA has over- or under- procured since its inception, depends on the discrepancies between the CCA’s actual load profiles and PG&E’s. 

The Current CCA Wholesale Metering Method Can Impact CCA Finance  

Given the cost of RA today, the financial impact of over- or under procurement of RA can be significant. It can determine whether a CCA is financially viable or not.  

Potential Regulatory Issues with Current Wholesale Metering Method

The current CCA wholesale metering method, by using PG&E load profiles as approximations for individual CCAs, has additional implications beyond over or under procurement of RA and its impact on CCA finance. 

Since PG&E load profiles represent the socialized (average) load profiles of all communities within PG&E’s service territory, the CCAs with flatter load profiles overpay for RA, while the CCAs with peakier load profiles underpay. In other words, the current method of CCA wholesale metering creates RA-related cost shifts from one CCA to another – shifting of RA procurement cost from CCAs with the peakier load profiles to those with the flatter load profiles.

Opportunities with a More Accurate CCA Wholesale Measurement Method

A more accurate wholesale metering technique not only avoids the cost, risk and regulatory issues of approximating CCA wholesale transactions, but also creates a number of opportunities for CCAs to optimize their financial viability. Through more accurate metering of load profiles, CCAs can develop better rates and Demand Side Management programs to re-shape their load profiles and lower wholesale energy procurement costs. Use of PG&E load profiles as an approximation obscures such opportunity.  

More importantly, given that the load profiles vary for different classes of customers, more accurate determination of the load profiles for different classes of customers will allow CCAs to develop better rates for each customer class to optimize its viability and profitability. The increased viability and profitability will ultimately allow CCAs to invest in more programs that respond to community needs and achieve policy goals.

 

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