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Allocating Unaccounted for Energy (UFE) in MISO. Shawn Fountain Vice President. Presentation overview. Overview of MISO market What is UFE Common UFE allocation methods Financial Impact. All numbers in this presentation are for illustration purposes only. Process Inbound Reads.
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Allocating Unaccounted for Energy (UFE) in MISO Shawn Fountain Vice President
Presentation overview • Overview of MISO market • What is UFE • Common UFE allocation methods • Financial Impact All numbers in this presentation are for illustration purposes only
Process Inbound Reads Determine Samples Create Profiles Dynamically Report Missing Required Data Create Profiles Estimate Usage Dynamically Validate Reads Validate for Profiling Process Estimate Usage Dynamically Estimate Usage Estimate Usage Estimate Reads Apply Profiles Apply Profiles Perform Analyses Edit Reads Calculate Determinants Aggregate Apply Profiles Create Profiles Apply Profiles Report Missing Reads Send Data to Market Prepare Bills Receive Data from Market Reconcile Data Main processes by functional area Load Research MDM Settlement Billing Estimate Reads Create Profiles
MISO “MDM” Market Participants • Meter Data Management Agent (MDMA) ─ An entity designated by a Market Participant to manage and conduct the metering services on the Market Participant’s behalf • Billing Agent ─ An entity designated by a Market Participant to manage and conduct the settlement and billing services on the Market Participant’s behalf
MISO Commercial Model • A representation of relationships between Market Participants and their Resources, Commercial Pricing Nodes, and transactions • Derived from the Transmission Network Model
Entities in the Commercial Model • ENode (Electrical Node) ─ Physical point of injection or withdrawal in the network model • EPNode (Elemental Pricing Node) ─ An ENode for which a price is calculated • Lowest level of granularity of the LMP calculation and the lowest level represented in the Commercial Model • EPNodes and their LMPs are not published • CPNode (Commercial Pricing Node) ─ An aggregate price for a collection of EPNodes • All settlements occur at the CPNode level
MISO settlement runs • Settlement 7 (S7) ─ 7 days after Op Day • Settlement 14 (S14) ─ 14 days after Op Day • Settlement 55 (S55) ─ 55 days after Op Day • Settlement 105 (S105) ─ 105 days after Op Day
What is UFE? • The difference between aggregated metered load adjusted for distribution losses AND the net energy delivered (generation, imports and exports) adjusted for transmission losses • Sources of UFE include metering errors, invalid profiles, loss errors, unreported load or generation, etc. • UFE is also referred to as residual load
MISO calculation for Balancing Area UFE (BA_BLL_MTR + NAIBA + BA_LOSS ) * (-1) Where • BA_BLL_MTR = Sum of all asset Commercial Node meter data within the given Balancing Authority Area. Injections are represented by negative values and load by positive values • NAIBA = The Net Actual Interchange. A positive value represents energy flowing out of the area while a negative value represents energy flowing into the area • BA_LOSS = The transmission losses for the given Balancing Authority Area. Losses are positive values
MISO rules for UFE allocation • MISO recommends “that Balancing Authorities be responsible for allocating UFE to all load serving entities on a Balancing Authority Area load ratio share or other fair and equitable allocation methodology” • UFE may be allocated to each Retail CP Node using a load ratio share methodology • There is no single approach to allocating UFE
Assigning UFE to load owners • MISO performs this calculation and allocates all of the UFE to a Residual Load Owner • For Market Participants submitting load to MISO, it may be beneficial to calculate and allocate UFE prior to data submittal • If actual reads are adjusted to account for UFE prior to submittal to MISO, the MISO UFE calculation should yield little to no UFE
Scalar and interval meters • Scalar meters are cumulative meters generally read once per month • If interval meters are working properly, interval meters will have negligible impact on UFE • Scalar usage is profiled to determine the necessary interval values using a process called profile application • Most of deviation resulting in UFE is thought to be due to profile application of scalar usage
Definitions (slide 1) • Profile Creation ─The creation of shape and volume profiles generally via sample interval meters • Profile Application ─Applying the shape from a profile to scalar usage to convert the scalar usage to interval data • Usage Estimation ─ The estimating of scalar usage for scalar meters, or interval usage for interval meters, when no actuals exist for a given time period and that period is prior to the system date and time
Definitions (slide 2) • Usage Forecasting ─The forecasting of usage for a time period that is after the system date and time • Dynamic Profile Creation ─ Using historic data in a modeling process like regression to directly produce an interval estimate for a scalar meter for the settlement period • Dynamic Profile Creation generally takes a profile from the Profile Creation process as an input
Profiling techniques are dependent on the available data • Actual readings available for settlement day • No readings for settlement day, but historical readings are available • No readings for any period (e.g. new construction)
Nine main data states for profiling Profile Data State There are many more possible data states, e.g., a read or profile exists for part of the settlement period Read Data State
Feb Mar Meter Reads System Date Existing Profile X Settlement Period Illustration of primary calculation approach for Scenario 1 For each interval in the settlement period, (profile value for interval / total profile for the start and stop of the meter read) * the meter read consumption value
Estimating meter consumption • Regression ─ Regression against one or more independent variables • Proxy Day ─ Historical usage from the most like day in history based on the shape, volume, day type and/or other attributes; typically used when regression not viable • Like Day ─ The avg of historical usage for like days (e.g. day type and season); more commonly used for forecasting
Reasons for profile application error • Profile shape is not accurate for a given day and/or for hours across that day • Usage may have to be estimated and the estimate will almost always never be 100% • Arguably not profile application error but usage estimation error compounds profile accuracy error
Allocating UFE to all meters by LRS • MDMAs can generally estimate the UFE % within a tight tolerance • The simplest approach is spreading UFE across all scalar and interval meters
Allocating UFE only to scalar meters • It is generally accepted that most UFE is the result of inaccuracies from profile application • Therefore an approach is to assign all UFE to scalar meters
Financial impact of allocating UFE via these two different approaches • Assuming 68,000 meters with avg 50 kW peak demand and avg 60% load factor • Assuming average LMP = $60/MWh • Multiplying by 8760 hours
Wrap-up • MISO allows Market Participants to allocate UFE in different ways • Market Participants can adjust their meter reads by the estimated UFE and provide those adjusted values to MISO • A common approach for allocating UFE is to allocate all UFE to scalar meters based on load ratio share
For any additional information, please do not hesitate to contact the organizers Contact the organizers Devi Paulsen Spintelligent Phone: 888 559 8017 (US)devip@spintelligent.com www.american-utility-week.com