Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

[Oil & Gas White Paper] Gas Day Planning: Managing volatile end of day run-up

508 views

Published on

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.

  • Be the first to comment

  • Be the first to like this

[Oil & Gas White Paper] Gas Day Planning: Managing volatile end of day run-up

  1. 1. Gas Day Planning: Managing volatile end of day run-up September 2012 / White paper Make the most of your energySM
  2. 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. 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. 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. 5. Hourly forecasting makes efficient gas day management easier
  6. 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. 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. 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. 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. 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. 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

×