Craig L. Hart Consultant Energy Exemplar Africa (Pty) Ltd South Africa

Transcription

1 Craig L. Hart Consultant Energy Exemplar Africa (Pty) Ltd South Africa

2 Proven Natural Gas Reserves in Africa (2015) Source of data: U.S. Energy Information Administration - International Energy Statistics

3 Wind and solar resources in Africa Source: 3TIER Source: SolarGIS Source: GeoModel Solar

4 PLEXOS Overview and scope PLEXOS Integrated Energy Model is a proven auditable energy market modelling and simulation software tool using mathematical programming (LP, IP, MILP, QP) and stochastic optimisation techniques combined with modern GUI and data handling capabilities to provide an easy-to-use, comprehensive and robust analytical framework.

5 The gas-electric hybrid model Conventional generation mix of gas (OCGT), hydro and coal Split of: 20% Coal 30% Hydro 50% Gas Peak load = 2500 MW 40% reserve margin without RE i.e. of dispatchable generation

6 Demand profile Daily load profile Seasonality (winter peak)

7 Techno-financial parameters Property Coal Gas Hydro Unit size (MW) Number of units Total installed capacity (MW) 700 1,750 1,050 Ramp rate (%/min) Min Up Time (hours) Min Down Time (hours) Heat Rate (GJ/MWh) Fuel Price ($/GJ) VO&M Charge ($/MWh) Annual Capacity Factor (%)

8 Renewable model Three penetration scenarios: Low (10%) Medium (20%) High (30%) Very High (40%) p = P ren P coal + P gas + P hydro + P ren where p = penetration level P ren = installed RE capacity P coal = installed coal-fired capacity P gas = installed gas-fired capacity P hydro = installed hydropower capacity

9 Renewable model Uses hourly data from Wind Atlas for South Africa (WASA) and South African University Radiometric Network (SAURAN) Two sites used for each technology Three compositions of RE assessed: Equal mix of solar PV and wind Solar PV only Wind only

10 Simulation options PASA (Projected Assessment of System Adequacy): Optimal placement of maintenance during periods of low demand Medium-Term (MT) Schedule: Decomposition of medium and long-term constraints into short-term using reduced chronology (load duration curve) Short-Term (ST) Schedule: Optimisation over full chronology Property Horizon Step sizes Solver Value 1 year 1 week Xpress-MP

11 Merit-order of generation mix Short-Run Marginal Cost (SRMC) determined by: VO&M charges Fuel cost Production cost function (simple heat rate in this model) Ranking Plant SRMC ($/MWh) 1 Wind/Solar 0 2 Hydro 6 3 Coal 34 4 Gas 114

12 PASA Projected Assessment of System Adequacy Optimal placement of planned outages during periods of low demand

13 Results - Full generation mix Annual energy per generation type for each renewable scenario Hydro Coal Gas RE

14 Results - Full generation mix Non-displaced gas generation is the amount of gas generation that is NOT displaced by RE penetration This is against the merit order Based on technical capability Calculated using the amount of energy from gas generation in the No RE case as a base

15 Results Full generation mix Despite its position in the merit order, there is out-oforder dispatch of gas generation Becomes significant in the very high penetration scenario

16 Results Limited generation mix Annual energy per generation type for each renewable scenario with no hydro Hydro Coal Gas RE

17 Results Limited generation mix More defined trend with use of gas System requires gas as a flexible reserve

18 Normalised daily output No renewables 20% penetration 10% penetration 40% penetration Hydro Coal Gas RE

19 Conclusions GTP and renewable sectors may be significant in Africa going forward RE generation requires flexible reserves to balance supply & demand Hydro/GTP provide this flexibility Out of merit order dispatch of gas can be significant especially in systems without any or reliable hydro resources Gas requirements may be necessary for systems pursuing ambitious RE programmes

20 Questions