modeling dispatchability potential of csp in south africa

Report
CSP energy systems modelling in
STERG
Paul Gauché
SA Energy Modelling Colloquium
31 July 2012
Fakulteit Ingenieurswese

Faculty of Engineering
2
Agenda
• Introduction to STERG
• Why we do CSP systems modelling
• How we do plant and systems modelling
• What we can do and don’t/won’t do
• How we can collaborate
3
STERG INTRODUCTION
4
STERG fits in here
Stellenbosch
University
Engineering
Mechanical
Engineering
STERG
• NEW: Eskom chair
• Sasol researcher
• DST/NRF spoke
DST/NRF CRSES
(Renewable Centre)
5
STERG research structure
STERG Holistic/Multidisciplinary Research
Social & Political
Engineering
Economic Sciences
Sciences
SWH,
Process Heat,
Desalination
etc.
SUNSTEL
Stellenbosch University Solar Thermal Electricity Project
(Primary projects: SUNSPOT, LFR)
System R&D (Modelling, Techno-economic,
Resources, etc)
Solar
Resource
Measure &
R&D
Component
R&D: Eg. Dry
Cooling
Component
R&D: Eg.
Thermal
Storage
Component
R&D: Eg.
Heliostats,
Receivers
6
Technology focus areas for R&D (and modelling)
11+ Projects from distribution to system to
components focused on SUNSPOT
7
Experimental foundation
18 m tower
Solar resource
station
8
WHY WE DO CSP SYSTEMS
MODELLING
9
SA background
• SA learned good lessons in last 15 years
• Struggle to bring IPP’s and renewables onto grid
• Introduced the Integrated resource plan, a robust planning
process as law
Tender year
IRP horizon
| Basic IRP timeline structure
IRP 2010
CSP Allocation
Tender: 200 MW Total: 1,000 MW
2012
2013
Tender: 100 MW? Total: 1,000 MW
IRP 2
Tender: 100 MW? Total: >1,000 MW?
2014
201x
|  20 years
IRP 3
On-going…
10
IRP summary
Capacity
Electricity produced
11
Background
CSP Status
•
•
•
CSP Need
Just entering growth phase of tech lifecycle
Largely unknown in SA (no plant
experience)
~1% of installed capacity by 2030 (IRP)
•
•
•
LTMS, IEA, (Eskom) see CSP as foundation post fossil
Climate change & fossil resources suggest crisis
Large wind and PV allocation in IRP require 100%
capacity backup  not accounted for
GAP
Sources:
Grobbelaar, S., A road map for CSP industry development in South Africa: current policy gaps and
recommended next steps for developing a competitive CSP industry, Essay, University of Cambridge, 2011.
IRP2010. 2011. Integrated Resource Plan for Electricity 2010-2030. Government Gazette, Republic of
South Africa, 6 May, 2011.
Winkler (ed) 2007. Long Term Mitigation Scenarios: Technical Report. Prepared by the Energy Research
Centre for Department of Environment Affairs and Tourism, Pretoria, October 2007.
12
Wind and solar in symphony (Denholm & Mehos - NREL)
?
?
13
SA background
• CSP potential has been investigated by Fluri (short term)
and Meyer & van Niekerk (longer term)
• Short term multi-constraint potential (500GWe+) vastly
exceeds current or future electricity needs
• IRP 2010/11 allocates generously to renewables but not CSP
– we see this as risk for baseload or peaking.
• This work extends previous work to explore full potential
14
Rutledge coal model
• Based on Hubbert peak model – finite resources follow a
normal distribution production curve.
• It works very well. Would have forecast British coal
depletion to within months 100 years earlier.
15
South African coal
16
South African coal
Source
Patzek & Croft (2010)
Peak year (and peak
production)
2012 (258 Mt/y)
Similar to others but prefers
not to comment due to peak
year volatility
2007
Hartnady (2010)
2020 (284 Mt)
(478.6 EJ calculated as 17.15
Gt)
23 Gt
& (2012)
2012/2013 (254.3 Mt/yr)
18.675 Gt
Mohr & Evans (2009)
Rutledge (2011)
90% year (and/or total
cumulative extraction)
18.6 Gt
2048 (18 Gt)
What are these models saying?
Peak coal: Now – 2020
Then it’s downhill to about mid century
17
Other resources (worldwide)
Conventional uranium: ~2065
Other conventional and unconventional
fuels also limited
18
Wind, water and solar
• Note: 2030 IRP annual power need =~ 500 TWh
• The wind resource is about 80 TWh
• Hydro is not a major source in SA
• Wave and ocean current is for the future
• Solar resource is immense and vastly exceeds future needs
• Both are intermittent and a problem
• This concludes the major energy sources
19
CSP w
Storage
900
CSP no storage 900
Wind
80
PV
900
2030 energy needs
~500 TWh
Intermittent
CSP
Future
>> 900
Hydro
15
Coal
300 TWh
CCGT
10
Low
Localization potential
High
Making sense of it all
OCGT
10
Nuclear
77 TWh
Baseload
Dispatch
20
HOW WE DO CSP SYSTEMS
MODELLING
21
Introduction
• Dispatchability = storage + low inertia = CSP value prop
• 20 MWe Gemasolar plant demonstrated 24h full load
22
Method: Plant
• Based on the Gemasolar plant
• Approximated optical
performance + ChambadalNovikov engine (modified
Carnot) + inertia capacitance
+ storage capacitance
• Model validated using
• eSolar measured data
(Gauché et al. SolarPACES
2011)
• NREL predicted annual
electricity generation for this
plant (110 vs. 115 GWh/yr)
Item
Country, Region
Land area
Solar resource
Value
Spain, Seville Andalucía
37°33′ 44.95″ North, 5°19′ 49.39″
West
195 Ha
2,172 kWh/m2/yr
Electricity Generation
110 GWh/yr (planned)
Cost
O&M jobs
230,000,000 Euro
45
Heliostat aperture area
304,750 m2
Number of heliostats
2,650
Heliostat size
Tower height
Heat transfer fluid
Receiver outlet / inlet
temperature
120 m2
140 m
Molten salt
Location
565 °C / 290 °C
Turbine capacity (gross)
19.9MWe
Cooling
Storage
Wet
2 tank, 15 hours
23
Method: Plant
• Heliostat field
Optical efficiency
1
0.8
0.6
y = 0.4254x6 - 1.148x5 + 0.3507x4 + 0.755x3 - 0.5918x2 + 0.0816x + 0.832
R² = 0.9998
0.4
0.2
0
0
• Receiver balance
0.2
0.4
0.6
0.8
1
Zenith Angle [radians]

   4 − 4 + ℎ  −  + 
(1 − ) = 
=1
• Inertia & storage model
• Heat engine
ℎ = 1 −
1.2


&  = ℎ 
1.4
1.6
24
Method: Spatial solar and weather data
• Plant model only requires 3 parameters for each hour for
dry cooled plant (DNI, Tamb, wind)
• Grid of points for all South Africa:
• 0.375 ° increments latitude and longitude
• 823 points in the boundaries of SA
25
823 Grid points (uniform / unbiased)
Pretoria
Johannesburg
Bloemfontein
Durban
Cape Town
26
Method: Spatial solar and weather data
• Plant model only requires 3 parameters for each hour for
dry cooled plant (DNI, Tamb, wind)
• Grid of points for all South Africa:
• 0.375 ° increments latitude and longitude
• 823 points in the boundaries of SA
• Helioclim-3 data derived from Meteosat
• Real 2005 data (not TMY)
• Point validation of wind and ambient temperature using SA
weather data.
• Sensitivity analysis to DNI, Tamb, wind showed strong
sensitivity to DNI and very weak sensitivity to wind and
Tamb.
• Helioclim DNI data has issues. The method is still
demonstrable.
27
Method: The spatial analysis
• 823 grid points * 3 parameters * 8760 hours = 21.6 million
inputs
• 1 output parameter (power) = 7.2 million outputs
• Proxy for testing dispatchability
• Run plant as-is (generates power when it can)
• Half size power block (emulates half the 823 plants attempting
to run at any 1 time)
• Quarter size power block (emulates quarter of 823 plants
attempting to run at any 1 time)
• Some other combinations were tried
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Results and analysis: Time plots
8 January days
8 June days
29
Results and analysis: Time plots
Data anomaly
1 out of 4 plants running at a time practically
demonstrates baseload
30
Results and analysis: Spatial
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What we can do and don’t/won’t do
• STERG centric (CRSES to some degree, but not SI)
• Can do in future
• Through partnerships: Real and TMY solar, wind* and weather
data – multi year
• CSP, PV & wind spatial and time modelling
• GIS modelling for multi-criteria spatial type analysis
• Develop and improve underlying technology models
• Don’t / won’t do (as far as I can tell)
• ERC-like TIMES modelling (stochastic, complex multi-criteria
systems considerations)
• Climate and climate change models
• Anything in the policy or social space
32
Areas for collaboration
• Collective database of
•
•
•
•
•
•
Discount rate sets for RE technologies (scenarios)
Capacity and capacity factor scenario sets for all options
Technology models
Conventional resource estimation scenarios (fossil and fissile)
Common solar, wind and weather data sets (real and TMY)
Demand profiles at least to hourly demand (historical and
forecast)
• Other…
• For IRP
• Set of assumptions on demand per year and finer resolution
• Recognition of non electric energy needs that transition to
electricity – particularly transport
• Other…
33
Thank you!

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