power output analysis of distributed photovoltaic systems in
TRANSCRIPT
Power Output Analysis of Distributed
Photovoltaic Systems in San Diego County
Mohammad Jamaly, Juan L Bosch, and Jan Kleissl
Department of Mechanical and Aerospace Engineering,
University of California, San Diego
Outline
• Objective: Analyzing aggregate ramp rates of distributed PV
systems in San Diego, CA and surrounding area (SDG&E
territory which covers an area of 10,600 Km2) in 2009
– Processing power output of the PV systems
– Comparing PV power output against ground measured and
satellite-derived irradiation (irradiation is converted to
power)
– Analyzing Ramp Rates of Aggregate measured and
modeled power output of the PV systems
Outline
• Objective: Analyzing aggregate ramp rates of distributed PV
systems in San Diego, CA and surrounding area (SDG&E
territory which covers an area of 10,600 Km2) in 2009
– Processing power output of the PV systems
– Comparing PV power output against ground measured and
satellite-derived irradiation (irradiation is converted to
power)
– Analyzing Ramp Rates of Aggregate measured and
modeled power output of the PV systems
Data
• CSI Measured Power Output:
• Provided by California Solar Initiative (CSI) RD&D program at
California Public Utilities Commission
• 15-min power output of PV systems
• SolarAnywhere (SAW): Satellite-Derived Irradiation
• Provided by Clean Power Research
• Derived from GOES visible imagery
• Global horizontal irradiation (GHI) and direct normal irradiation (DNI)
at 1 km spatial and 30-min temporal resolution
• CIMIS: Measured Irradiation
• Operated by California Irrigation Management Information System
• Measured Hourly GHI (60 minute-by-minute samples are averaged and
reported for 1 hour intervals) at 5 ground weather station
Data
• CSI Measured Power Output:
• Provided by California Solar Initiative (CSI) RD&D program at
California Public Utilities Commission
• 15-min power output of PV systems
• SolarAnywhere (SAW): Satellite-Derived Irradiation
• Provided by Clean Power Research
• Derived from GOES visible imagery
• Global horizontal irradiation (GHI) and direct normal irradiation (DNI)
at 1 km spatial and 30-min temporal resolution
• CIMIS: Measured Irradiation
• Operated by California Irrigation Management Information System
• Measured Hourly GHI (60 minute-by-minute samples are averaged and
reported for 1 hour intervals) at 5 ground weather station
Map of PV Systems and CIMIS Stations
• 86 PV systems with total 6.41 MW PTC rated capacity (kWAC), a
mean size of 74.54 kWAC and median size of 6.08 kWAC were applied
• Modeled GHI of the SAW pixels which contain the PV systems are
applied
• Measured CIMIS GHI at 5 CIMIS stations are applied
Aggregate Ramp Rates
• Differences in the aggregate PV power output (normalized by
the aggregate PV capacity) for different ramp duration
intervals; 15-min through 5-hour in 15-min increments
Largest step size of normalized
aggregate PV output versus ramp
time interval
Cumulative distribution of absolute
value of 1-hour ramp rates of
normalized aggregate PV output
Aggregate Ramp Rates
• Differences in the aggregate PV power output (normalized by
the aggregate PV capacity) for different ramp duration
intervals; 15-min through 5-hour in 15-min increments
Largest step size of normalized
aggregate PV output versus ramp
time interval
Cumulative distribution of absolute
value of 1-hour ramp rates of
normalized aggregate PV output
The Day with the Largest 1-hour Ramp Rate
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for the day with the
largest 1-hour ramp rate in 2009
• The largest aggregated 1 hour ramp for
this period was 50.6% of PV capacity
and occurred from 900 to 1000 PST
GOES Satellite Images on the day with the
largest 1-hour ramp rate in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min averaged
output to annual maximum output at that
time of day (ToD)
The Day with the Largest 1-hour Ramp Rate
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for the day with the
largest 1-hour ramp rate in 2009
• The largest aggregated 1 hour ramp for
this period was 50.6% of PV capacity
and occurred from 900 to 1000 PST
GOES Satellite Images on the day with the
largest 1-hour ramp rate in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min averaged
output to annual maximum output at that
time of day (ToD)
The Day with the Largest 1-hour Ramp Rate
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for the day with the
largest 1-hour ramp rate in 2009
• The largest aggregated 1 hour ramp for
this period was 50.6% of PV capacity
and occurred from 900 to 1000 PST
GOES Satellite Images on the day with the
largest 1-hour ramp rate in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min averaged
output to annual maximum output at that
time of day (ToD)
Largest 1-hour Ramp Rates
Aggregate modeled & measured power of all 86 PV sites and Aggregate GHI of 5 CIMIS
stations for the days with the (a) second, (b) third, and (c) fourth largest 1-hour ramp rates
Histogram of the largest 1-hour ramp rates (30% and larger) of aggregate PV output
Largest 1-hour Ramp Rates
Aggregate modeled & measured power of all 86 PV sites and Aggregate GHI of 5 CIMIS
stations for the days with the (a) second, (b) third, and (c) fourth largest 1-hour ramp rates
Histogram of the largest 1-hour ramp rates (30% and larger) of aggregate PV output
A Day with Marine Layer Breakup • Occurred when cloud evaporation coincides with an increase in solar altitude
GOES Satellite Images on a day with
marine layer breakup in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min
averaged output to annual maximum
output at that time of day (ToD)
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for a day with marine
layer breakup
• The largest aggregated 1 hour ramp for
this period was 38.1% of PV capacity
and occurred from 800 to 900 PST
(Transition from marine layer overcast
status to clear condition)
A Day with Marine Layer Breakup • Occurred when cloud evaporation coincides with an increase in solar altitude
GOES Satellite Images on a day with
marine layer breakup in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min
averaged output to annual maximum
output at that time of day (ToD)
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for a day with marine
layer breakup
• The largest aggregated 1 hour ramp for
this period was 38.1% of PV capacity
and occurred from 800 to 900 PST
(Transition from marine layer overcast
status to clear condition)
A Day with Marine Layer Breakup • Occurred when cloud evaporation coincides with an increase in solar altitude
GOES Satellite Images on a day with
marine layer breakup in 2009
• The circles represent 86 PV systems
• The area of the circles is proportional to
the power rating of the PV system (the
largest system is 939 kW)
• Color bar shows ratio of 15-min
averaged output to annual maximum
output at that time of day (ToD)
Aggregate modeled & measured power of
all 86 PV sites and Aggregate GHI of 5
CIMIS stations for a day with marine
layer breakup
• The largest aggregated 1 hour ramp for
this period was 38.1% of PV capacity
and occurred from 800 to 900 PST
(Transition from marine layer overcast
status to clear condition)
Conclusions • In 2009, the largest hourly ramp was 50.6% of PTC capacity
followed by several ramps of up to 44% of PTC capacity, which
indeed cause more challenges and additional costs for the system
operator in a very high PV penetration scenario
• The SAW was able to follow the CSI power output (measured over
86 systems) typically within 6% during the four largest ramps and
also matched the timing of the ramps accurately
• CIMIS observations were not as accurate as SAW due to smaller
number and non-representative geographical distribution with
respect to the PV sites
• The largest number of ramps occurred in the spring and summer
(many of them are caused by summer marine layer breakup)
• In April-October all large ramps were morning up-ramps which is
desirable because the load also increases during those times
Conclusions • In 2009, the largest hourly ramp was 50.6% of PTC capacity
followed by several ramps of up to 44% of PTC capacity, which
indeed cause more challenges and additional costs for the system
operator in a very high PV penetration scenario
• The SAW was able to follow the CSI power output (measured over
86 systems) typically within 6% during the four largest ramps and
also matched the timing of the ramps accurately
• CIMIS observations were not as accurate as SAW due to smaller
number and non-representative geographical distribution with
respect to the PV sites
• The largest number of ramps occurred in the spring and summer
(many of them are caused by summer marine layer breakup)
• In April-October all large ramps were morning up-ramps which is
desirable because the load also increases during those times
Conclusions • In 2009, the largest hourly ramp was 50.6% of PTC capacity
followed by several ramps of up to 44% of PTC capacity, which
indeed cause more challenges and additional costs for the system
operator in a very high PV penetration scenario
• The SAW was able to follow the CSI power output (measured over
86 systems) typically within 6% during the four largest ramps and
also matched the timing of the ramps accurately
• CIMIS observations were not as accurate as SAW due to smaller
number and non-representative geographical distribution with
respect to the PV sites
• The largest number of ramps occurred in the spring and summer
(many of them are caused by summer marine layer breakup)
• In April-October all large ramps were morning up-ramps which is
desirable because the load also increases during those times
Acknowledgements
• Funding and data from the California Solar Initiative RD&D program at
California Public Utilities Commission
• Jennifer Luoma for reading in the data
• Timothy Treadwell from the California Center for Sustainable Energy for
providing the 2009 SDG&E CSI data
• Stephan Barsun (Itron) for helpful discussions on data quality control
Thank You