HyMet Company. Streamflow and Energy Generation Forecasting Model Columbia River Basin

Transcription

1 HyMet Company Streamflow and Energy Generation Forecasting Model Columbia River Basin HyMet Inc. Courthouse Square Vashon Hwy SW Suite 201 Vashon Island, WA Phone:

2 Columbia River Basin Streamflow and Energy Generation Forecasting HyMet Company has developed an advanced model to forecast seasonal and daily streamflow within the Columbia River basin. The main features of the computer model are: 1. The snowpack water content, soil moisture and groundwater storage are determined for each 50 meter (165 feet) altitude interval within each sub-basin for which forecasts are made. 2. Runoff forecasts for any future time period from 1 day to 9 months are based on the amount and the altitude distribution of water stored in the basin on the day of the forecast. 3. In addition to a volume forecast of seasonal runoff, a daily hydrograph is predicted for the period beginning on the forecast day and ending on July All forecasts are updated daily by the application of a short, pre-forecast test season. 5. Based on the runoff forecast, an energy generation forecast is made for the same season for a varying number of days in the future. 6. Runoff scenarios are included that show the effect of precipitation and temperature deviations on the forecast. 7. Input to the model is only readily available daily observations of precipitation and temperature, plus the reconstructed inflow at the forecast site, thus forecasts can be made daily if desired, and with minimum labor and cost. Precipitation station selection is done by a split-sample process so that only those stations that enhance forecast accuracy are used. 8. Forecast error has been demonstrated to be lower than other Columbia River models. The minimum mean forecast error is approximately 6.5 percent and the maximum R 2 is about 0.90.

3 HyMet Forecasting Services Available HyMet s forecasting service provides timely and accurate projections of the timing and quantity of river runoff. The focus of these forecasts is the impact of the timing and quantity of runoff on hydroelectric generation in the Columbia River basin. These forecasts allow utilities and traders to update the Northwest hydroelectric component of their WECC supply and demand models based on the best available information. Utilities and traders can then use this information to gain a competitive advantage in various WECC forward electricity and transmission markets. The following forecasting services are presently available for the Columbia River basin: Actual and forecast runoff from October 1 through August 31 at each of the following locations: Grand Coulee Dam, The Dalles, Lower Granite (former location, Ice Harbor, on the Snake River). Actual and projected generation from November 1 through August 31 at each of the following locations: Grand Coulee, The Dalles, Lower Granite. Graphical depiction of projected flows and generation vs. 30 year average. Depiction in both Megawatt-hours and percent of normal. Basin Snowpack Water Content (expressed in inches and MAF of equivalent water content) above Grand Coulee, The Dalles, and Lower Granite actual and mean. Special forecasts based on storm events or abnormal weather forecasts (i.e. weather that will change timing or quantity of runoff such as warmer or drier than average weather forecast). Commentary. What will be the timing of runoff this season given the altitude distribution of this season s snow pack? What will happen to runoff if we have a warm, cool, dry or wet spring in selected portions of the Columbia River basin? These and other scenarios can be quantitatively addressed based on real time data updates. Consultation is available to provide more detailed interpretation of forecast data. HyMet s forecasting model is currently in use in several other river basins in the WECC where it is being used to forecast runoff for purposes of optimizing basin hydroelectric resources. The model can be adapted to any river basin with significant winter snowpack and can provide an important tool in planning reservoir releases and/or optimizing hydroelectric resources.

4 Introduction The area-altitude profile of the Columbia River basin is calculated using a digital elevation model (DEM) with one kilometer resolution which divides the surface area of the basin, as well as major sub-basins, into increments of 50 meters (165 feet). Figure 1 is a topographic map of the Columbia River basin above The Dalles that was generated by assigning a color to each of the approximately 700,000 pixels that correspond to the altitude of each square kilometer of area. Figures 2 and 3 are similar topographical maps for the sub-basins above Grand Coulee Dam and Ice Harbor Dam. Figure 4 is the area-altitude histogram for the basin above Grand Coulee.

5 Figure 1. Map of the Columbia River basin above The Dalles, Oregon, generated from a digital elevation model (DEM) from 1 square kilometer resolution grid points.

6 Figure 2. Map of the Columbia River basin above Grand Coulee Dam. Figure 3. Map of the Columbia River basin above Ice Harbor Dam.

7 Figure 4. Area-altitude distribution of the basin above Grand Coulee in 50 meter (165 feet) intervals.

8 Model Design Figure 5 is a simplified flow diagram of the model that demonstrates how precipitation and temperature observations at relatively low-altitude weather stations are converted to such hydrologic variables as snowfall, rain, snowmelt, soil moisture and evapo-transpiration at each altitude interval. Fifteen coefficients are used in algorithms to make these conversions each day throughout the period of record (approximately 30 years). Runoff forecasts are derived from the sum of the snowpack water content and groundwater storage. Figure 6 shows the mean, 1992 and 1997 daily storage of water within the basin above Grand Coulee Dam as calculated by the HyMet model. Figure 5. Flow chart of the HyMet Forecasting model demonstrating how precipitation and temperature observations from cooperative weather stations are converted to snow accumulation and melt, soil moisture, groundwater, evapo-transpiration and other hydrologic variables at each area-altitude interval.

9 Figure 6. The daily water storage (snowpack plus groundwater) of the basin above Grand Coulee Dam for a high runoff year (1997), low runoff year (1992) and the average for the period. All forecasts, whether for one day or for several months, are directly dependent on the amount of water stored in the basin above the reservoir inflow site on the day of the forecast. Runoff for a specified season is then related to basin water storage on the forecast day for as many years as weather and runoff data are available. An example of observed runoff versus calculated storage on March 1 for the Columbia River at Grand Coulee is shown for each year of the period in Figure 7.

10 Figure 7. Observed runoff for the March 1 to July 31 season (in inches of water averaged over the basin area and in MAF) versus basin water storage on March 1 for each year of the period. Real-time forecasts of runoff on March 1 are based calculated storage and on the runoff/storage relationship shown in this plot.

11 The selection of precipitation stations to use in the model is critical to forecast accuracy. Most stations have been found to be unrepresentative of basin precipitation and would be detrimental to accuracy if used. Therefore, a split-sample technique was designed to determine which stations likely will produce reliable real-time forecasts. For example, the first 15 years of a 30-year record is used to calculate optimum forecast coefficients (designated the calibration period); the same coefficients are then used to make forecasts during the final 15 years (the verification period). Observations from stations that demonstrate the lowest forecast error are then averaged with observations from similar stations to form a single weighted-average station. The model is calibrated by simultaneously finding optimum values for these coefficients using a simplex optimization process. Forecasts based on basin water storage are made each day starting on January 1 and ending July 1 throughout the period of record. Thus for one iteration of the coefficient optimization simplex, nearly 800,000 daily/altitude determinations are made to generate 150 individual streamflow forecasts. The root mean error for each forecast is found and an average for all errors is obtained. The coefficient values are automatically adjusted by optimization until a minimum the mean forecast error is attained. The final values determined for the 15 coefficients by this technique are then available to use for operational forecasting. Forecasts are automatically updated daily by a pre-forecast "test-season". A short-term forecast (1-10 days) is made prior to the main forecast and its error calculated on the forecast day. It has been found that the test-season error is a predictor of the main season error, therefore the seasonal forecast error can be reduced, often considerably. Figure 8 demonstrates the large improvement in accuracy that results from the application of the test-season.

12 Figure 8. Runoff accuracy as a function of forecast date demonstrates the reduction in forecast error from the application of a pre-forecast test-season. The pink line shows the R 2 resulting from forecasts made for the period based on the calculated basin water storage. The blue line shows the R 2 when the testseason is applied prior to the main seasonal forecast.

13 In addition to volume forecasts of inflow to reservoirs, a hydrograph prediction is also made on the day the forecast is made. The daily distribution of the volume forecast is based on the altitude distribution of water storage (mainly the snowpack), which is influential in controlling the timing of subsequent runoff (high altitude snow will usually melt later in the season and at a lower rate than snow at low altitudes). An example of a forecast hydrograph for the high runoff year of 1997 is shown in Figure 9, along with the altitude distribution of the snowpack at the beginning of each month for the same year in Figure 10. Figure 9. Forecasts of the daily hydrograph are made for the season following the volume forecast, and are based on the altitude distribution of the snowpack. The 1997 hydrograph of forecast, observed and average daily discharge of the Columbia River at Grand Coulee is shown for the March 1 to July 31 season. Figure 11 depicts the forecast, observed and average runoff that occurred each day from November 1 through the end of the season (July 31). Note that the forecast runoff shows a significant divergence from the observed and is much closer to the average on November 1, but rapidly moves toward the observed and after about mid-january tracks it quite closely and with a minimum error. Deviations of both precipitation and temperature from normal during the forecast season will affect the runoff forecast, however long-term forecasts of these meteorological variables are still unreliable. Historical analysis of the relationship between runoff and these weather parameters has been used to develop scenarios that quantitatively demonstrate the effect that abnormal precipitation or temperature will have on streamflow. An example that shows the range of probable runoff amounts that will occur for given precipitation and temperature departures is shown at the end of this document.

14 Figure 10. The altitude distribution of the snowpack water content is shown for each month during the 1997 forecast season. The volume forecast is derived from the total snowpack water content and the hydrograph is forecast primarily from the altitude distribution plus the snowpack volume.

15 Figure 11. Forecast observed and average runoff for each day starting on November 1 and ending on July 1 during the 1997 season demonstrates the model s tendency to reduce the forecast error as the season progresses. Forecasts of electrical generation based on the forecast runoff are also made for various periods of time following the forecast day. The accuracy, given as the R 2 for the period, of the generation forecasts as a function of days following the forecast are shown in Figure 12.

16 Figure 12. The accuracy of forecasting energy generation on the forecast day improves as the number of days in the period increases. For example, a 7-day energy forecast has an R 2 less than 0.50, while a 150-day forecast R 2 is Reservoir storage above Grand Coulee allows generating units on the Columbia to react to short-term demand and market conditions, thereby limiting accuracy of short-term generation forecasts. However, the model accurately predicts the total megawatt-hours that will be generated during the 150 days following the forecast date and is particularly accurate in forecasting generation from the forecast date through July 31. A scatter plot of observed 150-day energy generation versus forecast runoff on March 1 is shown in Figure 13.

17 Figure 13. Energy generation in millions of MWH for the March-July season versus the forecast runoff on March 1, for each year of the period. A sample forecast that includes all the features described above can be found on this web page by clicking on Example Forecast and Plots.

18 HYMET FORECASTING MODEL - SEATTLE, WASHINGTON COLUMBIA RIVER AT GRAND COULEE INFLOW FORECAST SEASON 1 MAR 2000 TO 31 JUL 2000 LENGTH: 153 DAYS TODAYS DATE MAR TIME:12:48 FORECAST MAF MEAN CFS 95.3 PERCENT OF MEAN BASED ON STORAGE THAT IS INCHES OR 90.0 PERCENT OF MEAN EXPECTED FORECAST ERROR: 7.40 PERCENT 4.20 MAF R-SQUARED= HISTORICAL 30 YEAR MEAN MAF CFS SNOWPACK WATER CONTENT IN INCHES = MEAN = PERCENT 90.4 CONFIDENCE LOWER UPPER (MAF & %) INTERVALS LIMIT LIMIT 95% CONFIDENCE 45.9 ( 81.%) 62.4 ( 110.%) 90% CONFIDENCE 47.2 ( 83.%) 61.0 ( 108.%) 80% CONFIDENCE 48.7 ( 86.%) 59.5 ( 105.%) 70% CONFIDENCE 49.3 ( 87.%) 59.0 ( 104.%) GENERATION FORECAST PERIOD MIL-MWH MEAN % OF MEAN (%)ERROR R-SQR 7 DAYS

19 30 DAYS DAYS DAYS DAYS TO JUL ALTERNATIVE FORECASTS BASED ON PERCENT OF NORMAL SEASONAL PRECIPITATION AND TEMPERATURE DEPARTURES IN MILLIONS OF ACRE-FEET(MAF) AND PERCENT COLUMBIA RIVER AT GRAND COULEE SEASON 1 MAR 2000 TO 31 JUL 2000 LENGTH: 153 DAYS PERCENT PRECIPITATION DEG % OF MEAN DEG % OF MEAN DEG % OF MEAN

20 -0.5 DEG % OF MEAN DEG % OF MEAN DEG % OF MEAN DEG % OF MEAN DEG % OF MEAN DEG % OF MEAN

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23 Summary of Columbia River forecasts made with HyMet model during the 2000 season, compared with those supplied by the Bonneville Power Administration (BPA), from the Northwest River Forecasting Center (NWRFC). Forecasts of inflow to the Columbia River sites at Grand Coulee and The Dalles were made daily with the Hymet model during the January 1 to July 1 season. The model can be updated daily because it requires only precipitation and temperature observations at low-altitude weather stations located in or near the Columbia River watershed. Out of the approximately fifty tested, twenty precipitation stations and two temperature stations were selected for each of the forecasting sites. Precipitation is a weighted-average for each station based on split-sample testing, using the period for calibration and the period for verification. Although they were made retrospectively (after July 31), the HyMet forecasts made for the 2000 season can be considered real-time because model calibration and verification are for the period. Therefore, it is expected that forecasting accuracy in future years will be similar to that shown here. It is likely that HyMet model accuracy will tend to improve with time as more years are added to the calibration period. Comparison of HyMet s forecasts with official forecasts supplied by BPA are shown in Figures 1 and 2 for the standard January 1-July 31 season. Comparison forecasts for the Snake River (at Lower Granite or Ice Harbor) have not been completed because of an unresolved question regarding the accuracy of the inflow reconstruction.

24 Figure 1. January-July season forecasts of the Columbia River at Grand Coulee Dam are made daily with the HyMet model (triangles and solid line) and semi-monthly by NWRFC, with other federal agencies (diamonds). NWRFC forecasts are supplied by BPA. Figure 2. January-July forecasts at The Dalles demonstrate a similar pattern to those at Grand Coulee. Except for those on January 1 and 10, HyMet model errors are less than the official forecasts.