Efficient management of gas day operations involves matching supply to demand, keeping pressure in the pipelines relatively constant and avoiding big swings. The biggest challenge is volatile demand during the day, particularly during its final days, or end-of-day run-up, which combines the greatest volatility with little time to adjust before the end of the day. Operators already use forecasting models to plan the overall daily delivery, but to best cope with these challenges they need the ability to plan for gas output throughout the day to match hourly swings. By utilizing tailored industry solutions and established best practices, pipeline operators can use accurate forecasting solutions to break down daily demand forecasts into hourly predictions. Using hourly forecasts instead of a flat daily projection better matches actual demand and while small deviations from the forecast will occur, an hour-by-hour system allows pipelines operators to track the accuracy of projections and more easily adjust for unanticipated changes. These forecasts are not based only on current factors, but rely on historical analysis as well to develop a more accurate prediction of demand. Particularly during the extra-volatile end-of-day run-up, compiling and analyzing historical data on a continual basis provides a rational prediction of demand for any given conditions. Taking these existing tools and data sources, the challenge of managing the end-of-day run-up can be significantly reduced.

1. Gas Day Planning: Managing
volatile end of day run-up
September 2012 / White paper
Make the most of your energySM

2. Summary
Executive summary ................................................................................... p 1
Introduction ............................................................................................... p 2
Send out and contract management —
the basics of planning the gas day.............................................................. p 4
End-of-day volatility disrupts daily forecasts................................................ p 5
Managing run-up towards the end of the gas day....................................... p 6
Conclusion ................................................................................................ p 8

3. Executive summary
Gas Day Planning: Managing Volatile End-of-Day Runup
Efficient management of gas day operations involves matching supply to
demand, keeping pressure in the pipelines relatively constant and avoiding big
swings. The biggest challenge is volatile demand during the day, particularly
during its final days, or end-of-day run-up, which combines the greatest
volatility with little time to adjust before the end of the day.
Operators already use forecasting models to plan the overall daily delivery,
but to best cope with these challenges they need the ability to plan for gas
output throughout the day to match hourly swings. By utilizing tailored industry
solutions and established best practices, pipeline operators can use accurate
forecasting solutions to break down daily demand forecasts into hourly
predictions. Using hourly forecasts instead of a flat daily projection better
matches actual demand and while small deviations from the forecast will occur,
an hour-by-hour system allows pipelines operators to track the accuracy of
projections and more easily adjust for unanticipated changes.
These forecasts are not based only on current factors, but rely on historical
analysis as well to develop a more accurate prediction of demand. Particularly
during the extra-volatile end-of-day run-up, compiling and analyzing historical
data on a continual basis provides a rational prediction of demand for any
given conditions. Taking these existing tools and data sources, the challenge of
managing the end-of-day run-up can be significantly reduced.
White paper on gas day planning | 01

4. Introduction
White paper on gas day planning | 02
Gas Day Planning: Managing Volatile End-of-Day Runup
In the gas distribution and transmission business, accurate demand
forecasting is essential for a smoothly running gas day. With the help of
tailored industry solutions and established best practices, pipeline operators
can not only effectively manage overall gas day operations but better mitigate
the challenges of the volatile run-up at the end of the gas day.
The most sophisticated modeling software solutions set a new standard for
best practices by breaking daily forecasts down into hourly segments. They
also are not based on current factors alone, but rely on historical analysis to
develop a more accurate prediction of demand. With a fully developed diurnal
model in place, operators can create a more accurate forecasting model to
better plan for the gas day and the often volatile run-up during its final hours.

5. Hourly forecasting
makes efficient gas day
management easier

6. White paper on gas day planning | 04
Gas Day Planning: Managing Volatile End-of-Day Runup
Send out and contract management —
the basics of planning the gas day
The challenge of gas day operations lies in balancing supply and demand,
while keeping pressure in the pipelines relatively constant. Sophisticated
demand forecasting can help achieve that balance ahead of time,
mitigating the effects of a volatile gas day. A complete forecast aggregates
predicted send-out, based on environmental factors, the day of the week
and other factors, with agreed upon contract obligations based on daily
nominations. This forecast can be constructed in a hierarchical manner,
where, for example, a plan is established for each geographical area and
type of consumer. Throughout the day, this mapping is fed with real-time
information that allows for effective load monitoring through a SCADA
operator console (Figure 1). In this console, temperature, humidity and
wind speed are displayed, as well as delivery forecasts, actuals and
the difference at each hour of the gas day. While small deviations from
forecasts cannot be completely avoided, industry best practices call for a
goal of no more than two percent variation.
Figure A
Forecasting Send-Out
The biggest influence on residential heating
demand is, of course, the weather. As
shown, there is a direct correlation between
temperatures and demand — therefore load
forecasting is a priori possible with the help of a
simple equation that takes not only temperature,
but also other weather factors such as humidity
and wind speed into account. Furthermore, in
countries where gas is used primarily for heating,
one can anticipate the impact of seasonal
fluctuations. In Figure A, for example, demand
drops down to zero during the summer. For a
complete send-out model, other factors, such
as the day of the week, need to be taken into
account.

7. Gas Day Planning: Managing Volatile End-of-Day Runup
White paper on gas day planning | 05
End-of-day volatility disrupts daily
forecasts
Of the two variables of the forecasting model, contract management can
generally be considered a fixed variable due to incentives and penalty
clauses. The amount of required send-out, however, is much more volatile.
Demand for send-out usually increases in the morning hours, which in many
countries, including the United States, coincides with the end of the gas day.
This is the time of the day that sees increased residential activity after a down
period during the night. Demand for gas surges in the morning because
heating appliances switch into daytime cycle, and because gas is needed
for heating water and for cooking. With the increased use of programmable
thermostats, the swing from low overnight demand to high daytime demand
is even more dramatic. Where gas is used to generate electricity, forecasting
demand becomes even more challenging.
This is particularly challenging because as companies close in on the end
of the gas day, they begin to run out of time to correct for deviations from
the forecast. In order to ensure that the system predicts loads as accurately
as possible, special attention should be given to designing solutions that
mitigate the volatility of the end of the gas day. Best practices in gas control
rely on new ways of thinking:
• Design systems hour-by-hour, rather than day-by-day: Break forecasts
down into hourly increments instead of daily values, both for contract
nominations and send-out patterns.
• Take load history into account: Build a historic pattern based on a diurnal
model that informs current forecasts.
Figure 1
Contract Management
Contracts are usually established
with industrial and commercial
clients. Within the parameters of
the contract, these clients nominate
their requirements according to
an industry-wide schedule, such
as the North American Energy
Standards Board daily nomination
cycle. Ideally, these nominations
are provided in an hourly format.
If provided by the contract, they
may also issue maximum hourly
quantities and alert limits.

8. Gas Day Planning: Managing Volatile End-of-Day Runup
White paper on gas day planning | 06
Managing run-up towards the end of
the gas day
Hourly versus flat projections
Once the daily output has been forecast, it is also necessary to plan for how
that output will be delivered over the course of the gas day. Relying on flat
daily projections alone gives a simple picture but is limited in its description of
daily swings in demand. When compared to actual demand figures, the two
track well during the first several hours of the gas day but during nighttime
and morning hours, actual demand deviates from the flat projections.
Specifically, if only relying on flat estimates, there would be an overestimation
of demand during the nighttime, increasing pressure in pipelines. Shortly
afterwards, the end-of-day surge spurred by residential morning activities
would lead to underestimating demand and decreasing pressure in
the pipelines. In Figure 2, which depicts daily accumulations versus flat
projections, one can see that the end-of-day run-up causes the largest
deviation from flat projections, with up to 10 percent difference. This is far
more than the accepted industry best practice of two percent derivation.
Ultimately, this could lead to failure of delivering service.
Figure B
Ongoing monitoring and reporting
With a complete forecasting model in place, pipeline
operators can track the accuracy of projections
hour-by-hour and react to unanticipated changes
accordingly. This figure shows a sample reporting
graph with relatively small variations between forecasts
and actuals.
Figure 2

9. Gas Day Planning: Managing Volatile End-of-Day Runup
White paper on gas day planning | 07
Analyzing system load with the help of diurnal modeling
Risk can be spread out by using hourly forecasts instead. Forward thinking
industry leaders are using diurnal modeling as a critical component of
accurate forecasting technology. As shown in Figure 3, diurnal modeling can
be displayed as a two-dimensional histogram of an aggregated hour-by-hour
break-out of deliveries. With the help of the coded colors, a historic pattern
is established that can inform current models. The brighter colored clusters
from hour zero to hour 15 demonstrate a predictable pattern that can inform
forecast models.
However, this example also demonstrates the challenge of volatility at the
end of the gas day. Towards the final hours of the gas day, the amount of
delivered gas is much more spread out and shows much less predictability.
This is why aggregating data is important to build as accurate a forecast
as possible. Whereas the above histogram relies on one year of data
aggregation, ideally historic modeling would build on five years or more of
weather data and recorded send-out actuals. In order to stay relevant, data-
sets that extend beyond five years will generally be adjusted for demographic
and appliance technological changes.
Additionally, in the example of Figure 3, end-of-day volatility is exacerbated by
seasonal variations, as indicated by the two separate clusters at the end of
the day. In such a case, customers should consider creating seasonal profiles
in order to obtain greater accuracy.
Figure 3
The left axis describes a percentage of daily total
delivery and the horizontal axis depicts the hours of the
gas day. The colored squares represent the amount of
days that a specific percentage was delivered at that
hour. While the first half of the gas day follows a very
predictable pattern, the second half is much more
volatile.

10. Conclusion
Gas Day Planning: Managing Volatile End-of-Day Runup
White paper on gas day planning | 08
Recapping gas day planning solutions:
• Using an hour-by-hour demand forecast gives pipeline operators valuable
insights into send-out and gas control. This allows the operator to more
easily adjust for demand volatility throughout the day, particularly during the
end-of-day run-up.
• The collection and analysis of historical demand data is essential, as it
provides a statistical model for diurnal forecasting. Data should be tracked
over several years but refreshed once it ages more than five years in order
to keep up with technology advances and other societal changes.
• Investments in advanced modeling software solutions allow for state-of-
the art forecasting analysis which lets pipeline operators to save time and
minimise business losses due to unanticipated demand.

11. ©2012SchneiderElectric.Allrightsreserved.
August 2012
Schneider Electric USA, Inc.
10333 Southport Rd SW, Ste 200
Calgary, AB T2W3X6
Phone: 1-866-338-7586
Fax: 1-403-259-2926
www.schneider-electric.com/us