Upload
informa-australia
View
51
Download
1
Embed Size (px)
Citation preview
Colin Bonner, Fulcrum3D
Sodar | Cloud Monitoring | Solar Forecasting | Environmental Monitoring
4 April 2017 Informa - Large Scale Solar 2017 Page 1
Benefits of on-site real-time solar forecasting with CloudCAM
Monitoring for renewable energy
Compact-beam Sodar
low cost, flexible, reliable monitoring solution
performance verified by industry experts
optimised for the wind energy industry
High speed data loggers
unique design allows sampling rate up to 200Hz
noise and weather monitoring
high speed solar monitoring
wind monitoring
CloudCAMsolar forecasting
innovative camera-based cloud monitoring system
cloud detection and cloud statistics
short term cloud prediction (up to 30 min)
Flightdeck data centre
data delivery, analysis & asset management
online fault reports and error detection
24hr secure access web server
Fulcrum3D and 3rd
party products
Page 2
The problem: solar variability
solar power output is can be variable due to clouds
output can drop or rise by ~80% in a matter of a seconds
major problem as PV penetration increases on microgrids or weak-grids. current solution are:
– storage to provide support during a cloud events, or
– excessive spinning reserve in case of cloud event
– limit penetration
Page 3
The solution: CloudCAM
real-time cloud detection & solar forecasting
integrate with SCADA via Modbus
– completely standalone system
optional emote access via Flightdeck
Focusing on grid stability / ramp-rate limiting and spinning reserve control.
– Opportunity for LCOE, bidding etc…
Page 4
CloudCAM images and detection
Clearsky:no cloud detected
Note camera flare, dirt etcremoved
Cloud:robust cloud detected and identified
Site specific horizon mask removes impacts of local vegetation etc
Page 5
All Sky image Cloud detection
Page 6
Spinning reserve management
Reduce spinning reserve to save fuel if we know there are no clouds in area. Smaller diesel for less time:
– Operational maintenance saving
– Direct fuel savings
For example, switching from a 640kW set to a 320kW set would save around 12L/h, or reduce spill of PV by reducing the minimum diesel loading constraint, e.g. switching down from a 640kW at 40% minimum loading to a 320kW set at 80% loading would save -- as an extremely rough estimate -- 20L/h for 6h/d for 250d/y at 1$/L = 30000$/y *
ROI of ~1 year for 500~1000kW micro grids without getting too fancy.
Page 7* Rough estimate based on NT Power Water Corp tenders
Curtail PV to increase yield ?
Batteries and inverters are cool … but they still obey the first law of thermodynamics.
Page 8
-80
-60
-40
-20
0
20
40
60
80
100
120
PV IN System out Battery Power
Curtail PV to increase yield ?
Batteries and inverters are cool … but they still obey the first law of thermodynamics.
Page 9
-80
-60
-40
-20
0
20
40
60
80
100
120
PV IN System out Battery Power
Curtail PV to increase yield ?
Batteries and inverters are cool … but they still obey the first law of thermodynamics.
Page 10
-80
-60
-40
-20
0
20
40
60
80
100
120
PV IN System out Battery Power
Pre-emptive ramp down
Curtail PV to increase yield ?
Reduction in output from pre-emptive curtailment is less than the power used to charge batteries as charger, battery chemistry and inverter inefficiencies are removed.
Page 11
-80
-60
-40
-20
0
20
40
60
80
100
120
PV IN System out Battery Power System out (CloudCAM)
Benefits of solar forecasting
Forecasting make sense for low-energy high-power storage systems
AEMO ASEFS “Estimated Power” for NEM connected as of Q2 2017
Efficiency driver:
– Use of solar forecasting can increases system yield by reducing use of lossy elements (batteries, chargers, inverters, quiescent fly-wheel load)
Financial drivers:
– CAPEX:
• Reduces size of battery required ( current thought is ~25% )
– OPEX:
• Reduces cycling through battery to extend their life
• Spinning reserve management – direct maintenance and fuel savings
Cost of CloudCAM is in the noise for utility scale solar projects…Page 12
Case study: TKLN
TKLN sites are three high penetration sites on NT Power Water Corp microgrids. Sites are owned and operated by Epuron.
Operational since 2013 with up to 90% instantaneous PV penetration, designed for 30% energy.
AC coupled batteries for ramp-rate limiting during cloud events.
– Battery designed life of 10 years (GEL Lead Acid)
– Greater than expected degradation after ~4 years
Retrofitted CloudCAM without modifying PLC or previously commissioned systems.
– CloudCAM in direct control of PV array
– Ran CloudCAM in passive mode for before switching live
Page 14
Case study: TKLN
TKLN sites are three high penetration sites on NT Power Water Corp microgrids. Sites are owned and operated by Epuron.
Page 15
Case study: TKLN
Page 16
SMACluster
ControllerPLC
Tripower
Tripower
Tripower
Tripower
Batteries
PWC Set point
Battery Inverters
Metering point
Modbus
Case study: TKLN
Page 17
SMACluster
ControllerPLC
Tripower
Tripower
Tripower
Tripower
Batteries
PWC Set point
Battery Inverters
Metering point
ModbusCloudCAM
Modbus
CloudCAM installation at Ti Tree, NT
Page 18
Case study: TKLN
Page 19
Cloud detected; predictive ramp-down commences; cloud clears; ramp up and resume normal operation
Note different ramp-up and ramp-down rates are allowed for in this design.
Cloud detected; predictive ramp-down occurs until solar output reaches “safe” level
Cloud clears; ramp up and resume normal operation
Setpoint (Max kW)
PV Output (kW)
System Output (kW)
Battery output (kW)
Possible solar Output (kW)
“safe” level pre-set
Case study: TKLN
Page 20
Setpoint (Max kW)
PV Output (kW)
System Output (kW)
Battery output (kW)
Possible solar Output (kW)
Significant fluctuations avoided; minor loss of production; elimination of penalties
Elimination of battery cycling and battery capacity required.
Case study: TKLN
Page 21
Significant fluctuations avoided; minor loss of production; elimination of penalties
Setpoint (Max kW)
PV Output (kW)
System Output (kW)
Battery output (kW)
Possible solar Output (kW)
Dramatic reduction in battery cycling; dramatic reduction in battery capacity required (max 50kW battery to cover a 250kW potential step change)
Case study: TKLN
Significant reduction in penalties
Reduced battery use by 90% *
Yield (normalised to irradiance) increased 4~5% *
Page 22* Daniel Gilbert, Epuron
Case study: Karratha Airport
ARENA funded system with storage and solar forecasting on Horizon network
Power topology similar to TKLN, however, CloudCAM supplied as “black box” to integrator and PLC controls PV.
Commissioning Q3 2016 – Q2 2017
Page 23
ARENA knowledge sharing
1 Hz pyranometer data (K&Z SMP11) from test sites:
https://flightdeck.fulcrum3d.com/ARENA/
Requires free registration for access to static archived data. Terms and conditions on website. We’ll be adding more data with a typical delay of a month or so.
Page 24
Unit 4, 76 Reserve Rd
Artarmon NSW 2064
AUSTRALIA
www.fulcrum3d.com
+61 (2) 8456 7400
4 April 2017 Page 25