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Thanks, Julia!
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<div class="">There is a lot of very useful information here.</div>
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<div class="">Abido has put together a summary about the natural gas prices which we will share shortly. He found that the coal prices hadn’t changed enough to be worth worrying about. By my assessment, the effect of the coal and nuclear fuel costs will be
in the noise, but that the natural gas prices could have substantial effect, so that’s where he focused his effort. In the long run, there is fairly good consistency between the projected natural gas prices, the bigger variation is in the near term, reflecting
how natural gas prices seldom do what you predict…. 😊</div>
<div class="">I think we should be able to get that summary to you on Monday.</div>
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<div class="">Sarah<br class="">
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<div class="">On Oct 16, 2020, at 4:39 PM, Julia Szinai <<a href="mailto:jszinai@berkeley.edu" class="">jszinai@berkeley.edu</a>> wrote:</div>
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<div class="">Hi Sarah et al,</div>
<div class="">Here are a couple of things I've promised.</div>
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1. This google <a href="https://docs.google.com/document/d/1YInHwhHxFy4rMweN4OCT1NqBUhiiD2F2GirKd9Z6aWk/edit?usp=sharing" class="">
doc</a> is a table of the key parameters that comprise a SWITCH scenario, from the load forecast to the costs and generator list. I need to do some preliminary SWITCH runs for a separate project that has an upcoming conference deadline, so I've listed what
I plan to use for the baseline run for that SWITCH analysis. Some of these parameters will definitely change and be refined for the CEC project's baseline analysis (like the time sampling strategy). The highest priority items left on my to-do list to start
doing some runs are highlighted in yellow: updated overnight costs and fuel costs. I'm working on finishing updates on the items in green.
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<div class="">2. Regarding the wind class to use for overnight costs in the ATB, I'm fine with using what the current ATB calls 'class 5' if that is the most common class of speeds in the WECC region. I can't tell from the SWITCH documentation what the average
wind speeds or classes were assumed in each load zone but I've copied the relevant info from previous supplemental materials on how the hourly capacity factors were calculated for candidate wind generators. See below:<br class="">
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<div class="">"Hourly wind turbine output is obtained from the 3TIER wind power output dataset produced for the Western Wind and Solar Integration Study (WWSIS) (3TIER 2010). 3TIER models the historical 10-minute power output from Vestas V-90 3 MW turbines
in a 2-km by 2-km grid cells across the western United States over the years 2004-2006 using the Weather Research and Forecasting (WRF) mesoscale weather model. Each of these grid cells contains ten turbines, so each grid cell represents 30 MW of potential
wind capacity. The Vestas V-90 3 MW turbine has a 100 m hub height.<br class="">
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<span style="" class="">Grid cells were selected by </span>3TIER<span style="" class=""> using the following criteria</span>:</p>
<div style="margin: 0in 0in 0in 0.5in; text-align: justify; font-family: Calibri, sans-serif;" class="">
1.<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;font-family:"Times New Roman"" class="">
</span>Wind projects that already exist or are under development</div>
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<span style="" class="">2.<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;font-family:"Times New Roman"" class="">
</span></span><span style="" class="">Sites with the high wind energy density at 100 m within 80 km of existing or planned transmission networks</span></div>
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<span style="" class="">3.<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;font-family:"Times New Roman"" class="">
</span></span><span style="" class="">Sites with high degree of temporal correlation to load profiles near the grid point</span></div>
<div style="margin: 0in 0in 0in 0.5in; text-align: justify; font-family: Calibri, sans-serif;" class="">
4.<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;font-family:"Times New Roman"" class="">
</span><span style="" class="">Sites with the highest wind energy density at 100 m (irrespective of location)</span></div>
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<div class=""><span style="font-family:Calibri,sans-serif;text-align:justify" class="">All of the grid cells in the
</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">3TIER</span><span style="font-family: Calibri, sans-serif; text-align: justify;" class=""> dataset (> 30,000)</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">
within WECC are aggregated into 3,311 onshore and 48 offshore wind farms. Many of the grid cells are very near each other; adjacent wind points are aggregated if their area is within the corner-to-corner distance of each other, 2.8 km. Wind points with standard
deviations in their average SCORE-lite power output greater than 3 MW are aggregated into different wind farms. Offshore and onshore wind points are aggregated separately. The 10-minute SCORE-lite power output for each wind point is averaged over the hour
before each timestamp, and then these hourly averages are again averaged over each group of aggregated grid cells to create the hourly output of 3,311 onshore (875 GW) and 48 offshore (6 GW) wind farms. The onshore wind farms are then put through the site
selection process </span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">(Section
</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">2.10.12</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">:
</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">Site Selection of Variable Renewable Projects</span><span style="font-family:Calibri,sans-serif;text-align:justify" class="">), resulting in 1,527 sites with 466 GW of potential
capacity."</span></div>
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<div class="">3. These reports from LBNL on Wind and Solar cost forecasts may be helpful in how to adjust the overnight costs to account for the PTC and ITC incentives. </div>
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<div class="">Wind: </div>
<div class=""><a href="https://emp.lbl.gov/publications/2018-wind-technologies-market-report" class="">https://emp.lbl.gov/publications/2018-wind-technologies-market-report</a></div>
<div class="">see p85 in PDF:</div>
<div class=""><a href="https://eta-publications.lbl.gov/sites/default/files/wtmr_final_for_posting_8-9-19.pdf" class="">https://eta-publications.lbl.gov/sites/default/files/wtmr_final_for_posting_8-9-19.pdf</a><br class="">
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<div class="">Solar:</div>
<div class=""><a href="https://emp.lbl.gov/utility-scale-solar" class="">https://emp.lbl.gov/utility-scale-solar</a><br class="">
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<div class="">see p11 in PDF: </div>
<div class=""><a href="https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf" class="">https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf</a><br class="">
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<div class="">Hope this helps. Have a good weekend all!</div>
<div class="">Best,</div>
<div class="">Julia</div>
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<div style="font-family:arial;font-size:small" class=""><font style="font-size:13px" face="garamond, serif" class=""><b class="">Julia Szinai</b></font></div>
<div style="font-family:arial;font-size:small" class=""><font style="font-size:13px" face="garamond, serif" class="">PhD Candidate | Energy & Resources Group | </font><span style="font-family: garamond, serif; font-size: 13px;" class="">University of California,
Berkeley</span></div>
<div style="font-family:arial;font-size:small" class=""><font style="font-size:13px" face="garamond, serif" class="">Graduate Student Researcher | Lawrence Berkeley National Lab</font></div>
<div style="font-family:arial;font-size:small" class=""><font style="font-size:13px" face="garamond, serif" class="">NSF InFEWS Fellow</font></div>
<div style="font-family:arial;font-size:small" class=""><span style="font-size: 13px; font-family: garamond, serif;" class="">Energy & Resources Group, MS '17</span><br class="">
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<div style="font-family:arial;font-size:small" class=""><font face="garamond, serif" class=""><span style="font-size:13px" class="">Goldman School of Public Policy, MPP '17</span></font></div>
<div style="font-family:arial;font-size:small" class=""><font face="garamond, serif" class=""><font style="font-size:13px" class="">University of California, Berkeley</font><br class="">
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<div style="font-family:arial;font-size:small" class=""><font style="font-size:13px" face="garamond, serif" class=""><a href="mailto:jszinai@berkeley.edu" style="color:rgb(17,85,204)" target="_blank" class="">jszinai@berkeley.edu</a></font></div>
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