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 28 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 31 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!