Analysis of the Xoserve Read Validation
Proposal
Author: Alex Cullin
27/08/2014
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 reading

Calculate the kWh consumption between the two readings

Retrieve the RAQ for the previous GT accepted reading

Using the straight-line apportionment method determine the portion of the RAQ
applicable to the meter reading advance period

Apply 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 override 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
BG propose splitting the lowest tolerance band (currently 0-73,200) into 2
bands and applying a different tolerance to each.
 0 to 20,999
 21,000 – 73,200
The BG analysis did not suggest what these new tolerances should be:
The majority of the E.ONs MPRs in the lower AQ band (0-73,200) sit within
the lower sub band of 0-20,999
This is because the lower band includes typical residential usage of around
12,000-13,500 kWh.
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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.
Low consumption Conclusions
There 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.
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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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