Using Power Grid Schedules in Dynamic Optimization of Gas Pipelines
- Anatoly Zlotnik (Los Alamos National Laboratory) | Michael Chertkov (Los Alamos National Laboratory) | Richard Carter (DNV-GL) | Alex Hollis (DNV-GL) | Andrew Daniels (DNV-GL) | Scott Backhaus (Los Alamos National Laboratory)
- Document ID
- Pipeline Simulation Interest Group
- PSIG Annual Meeting, 10-13 May, Vancouver, British Columbia
- Publication Date
- Document Type
- Conference Paper
- 2016. Pipeline Simulation Interest Group
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- 86 since 2007
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The recent increase in the use of natural gas as a fuel for electricity production has greatly strengthened the interdependence between the electric power and natural gas industries. The resulting intra-day fluctuations in pipeline loads caused by intermittent or unexpected gas-fired electric power plant operations have become particularly problematic. To mitigate this issue, regulatory changes have been initiated to lower the barriers on communication between operators of power grids and gas pipelines. In this paper, we examine some types of intra-day operational information that pipeline managers can obtain from power grid operators in order to forecast time-varying pipeline loads and characterize uncertainty of these loads in space and time. We also present methods that could be developed by the pipeline simulation industry to more effectively use such information to mitigate intra-day gas-electricity interdependence issues. Specifically, we describe new techniques for using transient optimization to find feasible compressor operation schedules, which are resilient under uncertainty, given such power system data. Bringing these methods into practice can enable gas pipelines to reduce the risk of service interruptions caused by intermittent power plant activity. Additionally, pipelines will be able to more reliably service power plants that use their gas nominations during only part of the day, or that may start up or shut down with little warning.
Extensive gas-fired power plant construction, as well as subsequent utilization of these plants to serve peak electric loads and provide generating reserves, has caused electric power grids to increasingly depend on greater and more reliable gas supplies. Such gas-fired generation can be intermittent, which causes large and sudden variations in takes from high pressure gas pipelines. These conditions lead to gas price fluctuations, line pressure drops, operational flow orders, and increased operating expenses for both industry sectors. Because natural gas is now the largest fuel source used for electric power production in many regions of North America, interest in coordinating the operations of these systems has grown. However, natural gas pipelines and power grids operate on very different spatial and temporal scales, and this makes the coordination of market clearing procedures and physical infrastructure operations difficult.
While gas is purchased using nominations for steady takes over 12 to 24 hour intervals, power system operators often require gas-fired generators to commit to production schedules in which their nomination is burned over only part of the contract period. Furthermore, this schedule may change unexpectedly because of real-time re-dispatch and reserve generator activation. Thus, pipelines must use line pack and storage to balance supply rates with variable and uncertain delivery volumes. In light of this, pipeline system managers would benefit greatly from information about upcoming or possible changes in gas takes. Adapting pipeline operations to maximize efficiency and security under these new conditions requires simulation and optimization methods that accurately account for transient flows. It is well-understood that transient optimization methods for managing time-varying flows throughout intercontinental pipeline systems require a predictive element to be effective, because changes in one pipeline zone may take many hours to be felt in a different, distant zone. Specifically, information about the volume, timing, and uncertainty of variable and intermittent gas takes is necessary. These variations are currently caused primarily by the commitment and re-dispatch of gas-fired generators.
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