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Sustainability Studies at the Intersection of Energy , Water , and Food Systems Elliott Campbell, Assistant Professor, UC Merced. Overview. Background SEED Application Service Learning Capstone. Background. Research. - PowerPoint PPT Presentation
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Sustainability Studies at the Intersection of Energy, Water, and Food SystemsElliott Campbell, Assistant Professor, UC Merced
Overview
• Background• SEED Application• Service Learning• Capstone
Background
Research
• Themes (Sustainable Energy, Systems Engineering, Integrated Assessment)
• Discovery (Campbell et al., Science, 2008; Campbell et al., Science, 2009; Tsao et al., Nature Climate Change, 2012; Mendu et al., PNAS, 2012)
• Support (*with UCSC co-I's) – NSF/CAREER– CITRIS*– DOE/BER– USDA/AFRI*
Student Organizations
SEED Application
Pyranometer Pyrheliometer
Solar Tracker LabNSF CCLI #0942439 A Web-Enabled, Interactive Remote Laboratory for Renewable Energy, Joel Kubby, Ali Shakouri, Brook Haag
Course Overview• Text: Renewable and Efficient Electric Power Systems
• Soon to become SoE requirement• Teaching Technologies: Clickers, Adobe Connect• Assessment: Consultant, Surveys, Pre/Post Meeting Quizzes• Developing new SEED labs (Electro-Coagulation, International Climate
Negotiations, Land-Use/GIS, Economics/HOMER)
Student Performance
• Total insolation is similar between measurements and predictions• However the model does a poor job of predicting the partitioning to direct and
diffuse insolation
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6 7 8 9 10 11 12 13 14 15 16 17 18
Appendix
Simulated Direct
Simulated Total
Class - Total
Class - Direct
Assessment
• High student engagement suggested by survey and outside assessment
• Student understanding of theory and measurements improved
• Limited understanding of optimization and model calibration achieved
Service Learning
Rural Electrification• Partner: ESW• Results: Survey development for social sustainability
metrics; Data collection in Madhya Pradesh, India• Support: SunEdison
(McKuin & Campbell, In Prep)
Environmental Microfinance• Partner: Kiva.org• Results: Marketing data; pilot website; Kiva buy-in• Support: PGE
Food and Climate• Partners: P&D Willey Farms, UC Merced Dining Services• Results: Climate impact assessment for local farmer and for
campus.• Support: PGE
Capstone
Water Recycling• Partner: City of Merced• Results: Hydraulics; Carbon credits.• Support: Dean
Harvesting Energy from Irrigation Canals• Results: Prototype testing; Energy efficiency, Patent
application.• Support: Dean
Conclusions
Summary
• Engineering technical elective that integrates SEED curriculum
• Service-learning with local and international partners
• Capstone for students from social science and engineering
Next Steps
• Social science contributions on technology use• GE Course on Energy, Water, Food Nexus• SEED Lab Curriculum• EILS Collaborations!
Elliott CampbellAssistant ProfessorUC MercedEmail: [email protected]: 209.631.9312Skype: elliott.campbell
Extra Slides
Seasonal Storage
Bioenergy Without Land?
Efficiency of CO2 input and harvesting critical to sustainability (Wiley, Campbell, McKuin, WER, 2011)
(Trent, 2010)
Bioenergy Without Land II?
(Mendu et al., PNAS, In Press)
Science Communication
(McDade and Campbell, 2009)
4. Use Google maps and a sun-path diagram to estimate the timing of obstructions in the afternoon.
Azimuth of obstruction (φ): Altitude angle of obstruction (β):
φ = -tan-1(Y/X) = -58°
φX
YZ
Height (H) roughly 9 metersβ = tan-1(H/Z) = 72°
4. Use Google maps and a sun-path diagram to estimate the timing of obstructions in the afternoon.
5. Does your sun-path diagram analysis agree with the measured data?
2. Comment on the reason for the difference and on what parameter adjustments might be required to obtain a better match.
1. Larger optical depth (k) to get less direct.2. Larger sky diffuse factor (C) to get more diffuse
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Measured Model (k = 0.171, C = 0.092) Model (k = 0.45, C = 0.75)
Inso
latio
n (W
/m^2
)
Total
Direct
Diffuse
Solar Resource Lab
Learning Goals• Students will be able to understand sources of variation in insolation,
construct insolation forecasting models, validate these models with solar radiation measurements, and gain an appreciation for solar forecasting as an intriguing challenge for the design of renewable energy systems.
Learning Outcome• Forecast seasonal and daily variation in insolation on a collector surface using
clear-sky insolation theory.• Estimate model error using pyrheliometer and pyranometer measurements.• Propose plausible sources of error in model and derive optimal parameter
estimates.• Predict the quantity and timing of insolation losses due to obstructions using
site maps and sun-path diagrams.
Lab Overview• Background: Two lectures on insolation theory.• Objective: Students will be able to develop solar
forecasting models and evaluate with measurements.• Format: – Clicker Pre/Post Quiz– Introduction– Parallel Investigations – Group Reporting– Survey