Analysis of the Xoserve Read Validation Proposal

Author: Alex Cullin27/08/2014

Objectives

Determine read rejection rate (if no over-ride flag was set) if the NEXUS rules (which employs a flat line RAQ apportionment) were applied.

Repeat the exercise using a seasonally adjusted (WAALP) RAQ apportionment and compare the results.

Highlight any significant weaknesses in the proposal and suggest alternatives.

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Method

Obtain list of live meters on live meter points

For each month:Determine the GT accepted readings in that month.For each reading, locate the previous GT accepted readingCalculate the kWh consumption between the two readingsRetrieve the RAQ for the previous GT accepted readingUsing the straight-line apportionment method determine the portion of the RAQ applicable to the

meter reading advance periodApply the GT tolerance rules to determine which readings pass or fail the proposed GT validation.

Repeat the exercise with WAALP adjusted RAQ values.

NB: The reads used in this analysis are already accepted by GT so exceptions volumes estimated in this

analysis would be in addition to any read exceptions currently produced.

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Exclusions / Limitations / Sample Size

Reads were excluded if: We failed to calculate an RAQ for the last GT accepted reading

Recent Gains Meter exchanges in RAQ period

We failed to determine which readings were accepted by GT IGT sites

All E.ON obtained, GT accepted readings were considered however where multiple readings were

accepted by the GT within a 30 day period only the latest reading in the period has been used for the

analysis. This limitation has minimal impact on the figures because the vast majority of E.ON MPRS have

an AQ below 73,200 and therefore read submission is limited to one reading every 63 days (25

days post NEXUS).

The total number of readings used in the analysis (after exclusions) was 5.4M

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Results

Over the year, 6.25% of readings sent to the GT would be rejected (if no over-ride flag was set).

However there’s a large degree of seasonality with the rejection rate dipping to 2% in June and peaking at 26% in September.

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Results

The exception volumes lag behind the change in seasonal usage. This is because it’s not the

reading that’s being validated but the period of usage between the reading and the one prior.

This period is on average 116 days so the exceptions are delayed by roughly half this amount.

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Exception Breakdown

Of the 6.25%, 81% failed when they breeched the lower threshold (20% of RAQ) with the majority of failures occurring in the months associated with summer consumption periods.

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Exception Breakdown

The majority of the exceptions are caused by the consumption breaching the lower 20% tolerance check. A simple comparison of the straight-line 20% lower tolerance vs the expected seasonal usage shows the weakness in the method.

The next graph shows the consumption for a standard residential house 13,500 kWh/pa.

It’s clear that a standard residential consumer will intersect the lower 20% tolerance with normal expected usage during the summer months.

This will in turn translate into higher exceptions volumes for consumers using even marginally lower than expected consumption.

 

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Proposed lower tolerance vs Expected residential usage

Blue - AQ apportioned per day (straight-line method)

Green - 20% lower tolerance based on the straight line apportioned AQ.

Red - WAALP adjusted expected usage.

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WAALP Adjusted

Clearly if a WAALP adjusted lower tolerance were used a customer with typical

consumption would never intersect the tolerance and only reads relating to consumption

periods which show significantly lower than expected usage will be rejected (or require

the over-ride flag to be set).

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Exception Comparison WAALP vs Straight-line RAQ

Below is a comparison of exception volumes using the tolerances on a straight-line apportioned

RAQ vs a WAALP adjusted RAQ. NB: Only band 1 customers (AQ between 0-73,200) were used

in this comparison and an EM LDZ profile was used regardless of MPR LDZ

Band 1 MPRs make up the majority of E.ONs rejections.

 

The majority of the seasonal peak has been removed and reduced the % failure from 6% to 2.7%

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Dealing with Low consumption / Low Expectation of Consumption

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Change in usage

Splitting the lowest AQ band in two does not directly address customers that are showing a sustained change in consumption patterns but for a period which is less that the minimum RAQ period.

This is because although the RAQ mechanism is triggered by the most recent reading, the consumption that influences the RAQ is between 6 and 36 months old (soon to be 9-36 months).

Where the consumption on the meter point is changing the RAQ is slow to catch up and only alters after a sustained period at the new usage.

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Change in usage

The reading in red is taken after a period of sustained low usage but the RAQ will still not be fully reflective of the new consumption pattern. The

low consumption readings (green and red) will therefore test the lower 20% tolerance for a number of months before the RAQ reacts sufficiently.

The RAQ is affected to lesser degrees (and the change further delayed) if the reduced consumption takes place in summer vs winter months due to

the WAALP profiling used to calculate the RAQ.

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Low expected usage

Scenario 1

A meter point which has not consumed for some time (AQ = 1) would breach the

upper tolerance check (300%) if a reading showing an annual consumption of 4 kWh

were submitted, the reading would breach the market breakers tolerance of 700% if

7kWh consumption were submitted.

Of the meter points with an RAQ of 1 prior to the read being submitted. The vast

majority failed the market breaker tolerance check.

Where the market breaker tolerance is exceeded the reading can not be over-ridden.

Scenario 2

For a meter point with an RAQ of 3000, if the consumption returns to a normal

residential level of 12,000 kWh the upper tolerance (300%) would be breached.

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Market Breakers

Of the 5.4M readings sent 0.4% would breach the Market Breakers tolerance rules and would be rejected.

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Market Breakers

When comparing the results for Band 1 only (0-73,200 kWh) the market breaker failures is actually

slightly higher overall with the WAALP adjusted RAQ compared to the straight-tine RAQ. 0.46% vs

0.43%. The distribution of exception throughout the year is different.

This shows that WAALP adjusting the RAQ is not a solution to high volumes of market breakers.

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Seasonality Conclusion

WAALP adjust the RAQ before applying the Xoserve proposed Tolerances.

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Low consumption ConclusionsThere are more numerous valid scenarios where a residential customer is legitimately using very

little consumption (either for short or prolonged periods of time) compared to those that need

investigation.

Splitting the lower AQ band and applying a new tolerance does not fully address these issues. If the

BG proposal were taken forward (in additional to WAALP adjusting the RAQ) then I believe

removing the lower tolerance (or setting it to 0%) for the sub 20,999 kWh band would be a prudent

proposal.

Low Expectation Conclusions

An upper tolerance of 300% and market breaker tolerance of 700% should only be applied to the sub

20,999 band if the actual (annualised) consumption between the 2 readings exceeds 20,999 kWh.

So where the RAQ is 1 to 20,999 (NDM):

Readings that have an actual consumption (annualised using the WAALP) of less than 20,999 would not

be subject to upper tolerance / Market Breaker checks.

Readings that have an actual consumption (annualised using the WAALP) of more than 20,999 would be

subject to the 300% upper tolerance and 700% market breakers checks.

Where this consumption is legitimate the MPR would need to undergo the AQ correction process.

These proposals would still protect the industry from spurious readings entering into settlements would

better fit with the reality of customer consumption patterns.

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