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Cloud Shadow Speed Sensor The Future of Solar Forecast Technology Ed Chen, National Tsing Hua University, Taiwan Ricardo Vidrio: UC LEADS/UCSD STARS Mentor: Dr. Juan Luis Bosch PI: Dr. Jan Kleissl 1 R E

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Cloud Shadow Speed Sensor The Future of Solar Forecast Technology

Ed Chen, National Tsing Hua University, TaiwanRicardo Vidrio: UC LEADS/UCSD STARS

Mentor: Dr. Juan Luis BoschPI: Dr. Jan Kleissl


OutlineIntroductionSolar Forecast TechnologyUC San Diego Sky ImagerCloud Shadow Speed Sensor

AT Tiny (Ed)Phototransistor Selection (Ed)

Quality control statistical analysis (Ricardo)Comparing results with CSS and USI (Ricardo)

USI video cloud type analyze(Both)Arduino(Both)Artificial Cloud Speed Simulator(Both)CSSv3 deployment(Both)CSSv4 wiring(Both)

Future WorksReferenceAcknowledgements2

Opening Question Think about this


The US has the capa city to power it self

Mathematically, Yes. But not in practicle.3

IntroductionOur way of life is not greenSolar Energy Engineerings Challenge


Fossil fuel will run out one day, and we all wish to power our life in a green way. However, there are some challenge.


We all want renewable energy, but there are some pros and cons.ProsEnvironmental friendlyAvoid using fossil fuelConsGenerally more expensive than unrenewable energy.Unstable dynamic output. 5E

We all want renewable energy, butIts usually more expensive.Levelized Costs Of Energy



1.Green energy are usually more expensiveWhy not wind? We have more sun than wind here in US6

We all want renewable energy, butOutput of renewable energy is usually unstable.Output vs. time graph


And also, renewable energy is a little expensive, economically inefficient. 7

ConsGenerally more expensive than unrenewable energy.Fossil fuel will be more expensive in the long runSolar forecasting technology

Unstable dynamic output.Solar forecasting technology


***By forecasting, operator wont over compensate the electric grid with unrenewable energy cause we know the solar output in the next few mins.Over-compensate~!8

Why cant we power the whole US with only Solar Energy?Output VariationDay & NightSunny & CloudyLoss in Long Distance TransmissionCable ResistanceTransformer EfficiencyEnergy StorageStore energy at day time for night time usage.Battery efficiency.9R


Solar Energy Engineerings ChallengeChanging cloud cover is a major source of solar radiation variability, and pose challenges for the integration of solar energy.



Possible Solutions for Dynamic Output of Solar PowerBuild more solar power plant, so that we can still have high output in cloudy day.expensive, occupy spaces. Not practical at all.Construct energy storage system, so that we can store energy when its sunny, and release the energy when its cloudy.a little expensive, energy loss. Not very practical.Predict the solar output in the next few hours, so that we can use other energy source to compensate the drop off.need solar energy forecasting technology, can intergrade with current electric grid. Practical.



How toPredict the solar output in the next few hours?Ask someone to monitor the cloud all day.Not precise, tiring. Not practical at all.

Use Doppler radar to measure the velocity of clouds. Too expensive($200,000), cloud speed and direction doesnt totally represent cloud shadow. Not practical at all.

Build a cheap system to gather the data of sky image and cloud shadow speed.Acceptable.


Need time and money to develop. However, the system is suitable for many solar power plant to use. 12

Solar Forecast TechnologyGoal:Predict the solar output in the next few minutes or hours in order to compensate the incoming drop off with other adjustable energy sources and keep the electric grid stable.





CSSCloud Shadow Speed Sensor15

Cheap feasible way to predict short term cloud speeds and directionEstimated cost ~ $400R


The layout of the CSS16


The Cross Correlation Method

We need this to find our highest correlated time lag between all nine sensorsR

USIUC San Diego Sky Imager



A brief introductionRelated to our project, but not our work.18

Flood of DataThree persons team assigned to complete spreadsheets such as this one

DateMultiple Cloud LayersCloud Changed?Cloud CoverCloud Direction12/1/2013no/no/nono75/45/25SW/SSW/SW12/2/2013no/no/nono85/90/95WSW/SW/WSW12/3/2013yes/no/nono95/95/90SSW/SSW/SSW12/4/2013no/yes/nono35/65/55WSW/WSW/SW12/5/2013no/no/nono60/65/0SW/SSE/NA12/6/2013no/no/nono30/65/10S/S/SSE12/7/2013no/no/yesno95/100/85W/WSW/W12/8/2013yes/yes/yesyes95/40/85WSW/S/W12/9/2013no/no/nono40/75/65W/WSW/WSW12/10/2013no/no/noyes45/35/53SSE/S/S12/11/2013yes/yes/noyes30/55/85NNE/SSE/SE12/12/2013no/no/nono15/0/0N/NA/NA12/13/2013no/no/nono25/25/20SW/SW/WSW12/14/2013no/no/nono0/0/0NA/NA/NA


Was watching the videos worth it?How far we were from one anotherMonth (Morn)Person 1Person 2SimilarityDEC217.1219.698.50%JAN22321998.20%FEB22321998.20%MARCH224.1216.396.60%APRIL221202.591.70%MAY168.8172.597.80%JUNE176.9189.693.30%JULY221.5183.282.70%

Month (Evening)Person 1Person 2SimilarityDEC0.130.13100%JAN0.250.2183.30%FEB0.260.3575%MARCH0.30.3781.80%APRILN/AN/AN/AMAY0.0650.1640%JUNE0.0690.2133.30%JULY0.40.5375%

Cloud DirectionMultiple Layer of CloudsR

The CSS Data21

Comparing the CSS and USISome of our results are illogical. This makes sense, and will take time to analyze

R1/2/2014MornCD (CSS) CD (USI) #1CD (USI) #2Cloud Cover #1Cloud Cover #2No CloudNo Cloud337.5/NNW0%5%

1/2/2014AfternoonCD (CSS) CD (USI) #1CD (USI) #2Cloud Cover #1Cloud Cover #2No CloudNo Cloud292.5/WNW0%10%

1/2/2014 EveningCD (CSS) CD (USI) #1CD (USI) #2Cloud Cover #1Cloud Cover #2No Cloud292.5/WNW292.5/WNW20%10%

References(1/2)Fung, Victor, Juan Luis Bosch, and Jan Kleissl. "Cloud Shadow Speed Sensor." Atmospheric Measurement Techniques, 2014: 1693 - 1700.Bosch, Juan Luis, and Jan Kleissl. "Cloud Motion Vectors from a network of ground sensors in a solar power plant." Center for Renewable Resources and Integration, 2013.Kent. Kent Solar Panels. 2011. http://uk-solarpanels.blogspot.com/ (accessed August 11, 2014).Wile, Rob. Business Insider. May 29, 2012. http://www.businessinsider.com/chart-heres-why-renewable-energy-has-miles-to-go-before-it-leaps-into-mainstream-2012-5 (accessed August 9, 2014).Levelized Cost of New Electricity Generating Technologies. n.d. http://instituteforenergyresearch.org/wp-content/uploads/2011/02/Levelized-Cost-of-New-Electricity-Generating-Technologie11.pdf (accessed August 8, 2014).Zyga, Lisa. PHYS ORG. April 9, 2011. http://phys.org/news/2011-04-energy_1.html (accessed August 8, 2014).


References(2/2)US energy use chart shows we waste more than half of our energyhttp://phys.org/news/2011-04-energy_1.htmlhttp://www.caiso.com/outlook/systemstatus.htmlWhy Expanded Alternative Energy Increases the Need for Natural Gashttp://theenergycollective.com/jemillerep/178096/expanded-wind-and-solar-power-increase-need-natural-gasWhy is The Peak Output of Solar Panels So Low? Why do my solar panels generate less than their rating?http://uk-solarpanels.blogspot.com/2012/05/solar-panels-low-peak-output.htmlCHART: Here's Why Renewable Energy Has Miles To Go Before It Leaps Into Mainstreamhttp://www.businessinsider.com/chart-heres-why-renewable-energy-has-miles-to-go-before-it-leaps-into-mainstream-2012-5Levelized Cost of New Electricity Generating Technologieshttp://instituteforenergyresearch.org/wp-content/uploads/2011/02/Levelized-Cost-of-New-Electricity-Generating-Technologie11.pdf


AcknowledgementsUC LEADSUCSD STARSUniversity System of TaiwanNational Tsing Hua UniversitySummer Research International UndergraduatesVictor Fung (Creator of CSS)Prof. Jan KleisslDr. Juan Luis BoschDominic FongJoel Zahnd


26REQuestionsThank You