1 / 18

WECC Transmission Expansion Planning Policy Committee (TEPPC)

WECC Transmission Expansion Planning Policy Committee (TEPPC). Modeling Work Group (MWG) Workshop Hydro Generation & Transmission Planning John Fazio, NWPCC Jamie Austin, PacifiCorp PDX Conference Center January 22-23, 2007. Hydro Generation & Transmission Planning John Fazio, NWPCC.

snow
Télécharger la présentation

WECC Transmission Expansion Planning Policy Committee (TEPPC)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. WECC Transmission Expansion Planning Policy Committee(TEPPC) Modeling Work Group (MWG) Workshop Hydro Generation & Transmission Planning John Fazio, NWPCC Jamie Austin, PacifiCorp PDX Conference Center January 22-23, 2007

  2. Hydro Generation & Transmission Planning John Fazio, NWPCC

  3. Outline: • The problem with hydroelectric generation • What’s been done in the past • Peak shaving algorithms • Historical data (e.g. SSG-WI) • How can we make it better? • Improve historical data approach • Add better hydro algorithms to the models

  4. The Problem with Hydro • NW hydro cannot sustain its peak generation • Due to physical and operational storage limits • Due to ramp up and ramp down rates • Due to other non-power operations including bypass spill for fish • In the NW hydro generation makes up half of firm resources and on average produces 75% of the region’s electricity • Not modeling hydro correctly can lead to wrong conclusions for NW planners

  5. NW Hydro Capability and Loads January

  6. NW Hydro Capability and LoadsJuly

  7. What’s been done in the past? • Peak Shaving algorithms • Included in most production costing/transmission models (GridView and ProMod) • Overestimates the flexibility of the NW hydroelectric system to meet daily and hourly loads • Using historical hydro generation • Not available at all sites • Non-power constraints change over time • May be subject to special one-time operations • Must be aligned properly with future loads

  8. How can we make it better? • Improve the method of using historical data • Refine process to obtain and standardize data • Adjust generation for special operations or for changes to non-power constraints • Automate method for aligning hourly hydro generation with hourly loads (i.e. making sure historical generation for a Monday say, lines up with a future load for a Monday) • Can work (e.g. SSG-WI study) but cumbersome

  9. How can we make it better? • Incorporate better hydro algorithms into the models • Enhance peak-shaving techniques • Incorporate detailed monthly and hourly hydro algorithms • Incorporate existing approximation methods, such as the trapezoidal approximation, or others • Develop streamlined monthly and hourly algorithms • Use existing stand-alone monthly and hourly models to provide input for production costing/transmission models

  10. Recommendations • Depends on time frame • In the short term using historical data may be the only option • In the long-term, production costing models should include better hydro algorithms • More than peak shaving • Less than the full blown detailed stand alone versions

  11. Hydro Modeling SSG-WI database Jamie Austin, PacifiCorp

  12. SSG-WI database • The following sources of hydro data are in the database: • NW federal, Mid-C Nonfederal, and PacifiCorp: recent historical hourly hydro generation that is reasonably reflective of latest Biological Opinion. Actual hourly hydro data from three historical years is chosen: Medium (2002), Low (2003) and High (2000). • Other NW nonfederal: actual hourly data is lacking. Fallback is monthly actual data, to which peak shaving algorithm is applied (source EIA) • Central Valley Project: Due to difficulty of disaggregating hourly forecasted data to individual plants, CAISO historical hourly data is used • Other California: CAISO has provided hourly historical hydro data aggregated by river system. • Colorado: Bureau of Reclamation--Upper and Lower Colorado Regions provided monthly forecasted data, which reflects recent severe drought in terms of updated hydrology and operational algorithms, to which GV peak shaving algorithm is applied. Still need to obtain non-Federal Hydro data. • Canada: BC Hydro provided monthly hydro for adverse, average and above average hydro conditions grouped by their coastal, Peace River and Columbia River facilities. Data is shaped using year 2002 actual loads and hourly flows in and out of BC Hydro territory, combined with treating the thermal generation as a block resource. • Arizona/Desert SW: Non-Federal hydro data from Salt River Project and other projects was used.

  13. Med. Hydro Low Hydro Creating a Low NW Hydro Sensitivity – DOE Study • NW hydro generation • Reflects NWPPC’s 2003 (low water year) generation data • 2003 represents a year with runoff in the lowest quartile • No change to Canada and Colorado hydro due to extensive storage capabilities • No change to Northern California hydro as 2003 was a medium hydro year in CA • No change to remaining hydro in the west – low hydro conditions may not be present due to geographical diversity • NW Loads – two sensitivities • Loads consistent with 2003 low hydro year • 2008 monthly energy and peak loads were adjusted by NWPCC to reflect 2003 temperatures (provides consistency in NW load and generation profiles) • These monthly energy and peaks were then converted to hourly using 2003 actual load as shapes • Loads consistent with 2002 medium hydro year • This sensitivity was done to isolate the effect of lower hydro conditions without the corresponding decrease in loads

  14. NW load profiles low vs medium NW hydro year conditions 3% reduction in annual energy demand 3% reduction in winter peak hour 18% reduction in summer peak hour

  15. Results • Low NW Hydro Sensitivity: • No large impact on area production costs • No large impact on congestion – physical or congestion rent • Reasons: • Temperature adjusted loads are lower and partially offset reduced hydro generation • Resource capacity is surplus (high planning margin) – ample relatively low-cost generation available to offset reduced hydro generation • Going forward: • Low hydro case that includes low hydro conditions in CA and BC is warranted • This case should employ a more realistic planning margin for resource additions, i.e., 15 percent for non-hydro

  16. Process: using fixed data • Cumbersome • Too involving • Room for errors • Would need to be redone for each study • Limiting • Inflexible; optimization of hydro outside the model • One hydro generation shape (monthly, daily and hourly) for all future years

  17. SSG-WI Hydro Modeling Objectives • Past SSG-WI discussions on improved hydro modeling included simulating spatial and temporally correlated uncertainty in hydro inflows, runoff, and bus bar loads in a stochastic manner • Hydro resources, e.g. pump storage, as well as long- and short-term storages optimized by modeling detailed cascading hydro networks. Energy and ancillary services co-optimization is comprehensive and fully integrated

  18. WECC Hydro Modeling Objectives • Develop a set of minimum requirements for a dynamic hydro model • Top needs should include: • Capability for hourly hydro simulation • At an individual project level • Incorporating project operating constraints • Minimum and maximum operating elevations • Minimum and maximum outflows • Release and fill ramp rates • Lag time between projects • Bypass spill requirements • Capability to select various water conditions • Enhanced feature may include ability to use random water conditions for stochastic studies

More Related