Energy Modelling for South Africa, Latest Approaches & Results in a Rapidly Changing Energy Environment Keynote Address at STERG Symposium 2017

Transcription

1 Energy Modelling for South Africa, Latest Approaches & Results in a Rapidly Changing Energy Environment Keynote Address at STERG Symposium 217 Dr Tobias Bischof-Niemz, Head of the CSIR Energy Centre Stellenbosch, 13 July 217 Cell: TBischofNiemz@csir.co.za Dr Tobias Bischof-Niemz Chief Engineer

2 Research Groups overview: Value-chain logic, driven by end-user demand and system view Technology-focussed Research Groups System-focussed Research Group End user-focussed Research Groups ED Energy Demand ESu Energy Supply ESt Energy Storage ESy Energy Systems EI Energy Industry (DTI) E. Market Design (DoE/NERSA) EM Energy Efficiency Technologies Energy Meteorology Battery Technologies Energy System Design Demand Shaping Technologies Renewable Energy Technologies Hydrogen Technologies Heat Storage Technologies Energy System Operation Industry demand / pull Technology performance and cost (today and future) System view on technologies user requirements Products (hardware), solutions (software) 4 EAC Real-world implementation of research programme Energy-Autonomous Campus

3 Interns/Students Employees Employees CSIR s Energy Centre currently has ~4 highly qualified staff members ASF ECL Administrative Support Functions EC Leadership RSF 1) Head 2) Technical Lead 3) Commercial Lead 4) Operational Lead 5) HCD Lead Research Support Functions 1) Technical (labs, GIS) 2) Project Management 3) Specialist 5 2 ~2 ED ESu ESt ESy EM EI EAC Energy Demand Energy Supply Energy Storage Energy Systems Energy Markets and Policy Energy Industry Energy- Autonomous Campus Demand Assessment in End-use Sectors Resource Assessment (solar & wind) 11 Batteries (design and integration) Energy Planning 9 Energy Economics 4 Local Content 1 EAC Energy Demand 6 31 Demand-side Technologies 1 (energy efficiency & demand shaping) Renewable Energy Technologies 7 (solar, wind, biogas, small hydro, HPs) Hydrogen (production and storage) 2 Grid Planning (incl. smart grids) 2 Energy Markets (local, regional, global) Energy Industry Development 1 EAC Energy Supply 13 5 Demand 21 Forecasting (short-term, longterm, spatially) Position filled In recruitment process Long-term plan Supply Forecasting (short-term, spatially) Heat Storage Interns Storage System Integration 4 (P2eMobility, P2pumping) 11 Island Grids Bursars Energy-System Operations 1 Energy Regulation Energy Trading Energy Statistics??? EAC Energy Storage EAC Grid Design EAC Operations (control and visualisation)

4 HCD Highlights: Quick ramp up, very strong and diverse team Very fast, yet very high-profile ramp-up achieved so far (from in July 214 to 4 in July 217) Entire leadership team (Research Group Leaders and Programme Managers) is South African and black 4 black female engineers (South African) 6 Examples of internationally recognised experts Former head of systems operations at Eskom, was in charge to operate entire national grid Energy Commissioner in the National Planning Commission led by Minister in the Presidency Former CEO/MD of Swaziland Electricity Company, well connected in the region Chief Engineer transmission grid planning for Eskom and the region

5 7 Context

6 World: In 216, 124 GW of new wind and solar PV capacity installed globally Global annual new capacity in GW/yr Solar PV Wind Total South African power system (approx. 45 GW) Sources: GWEC; EPIA; BNEF; CSIR analysis This is all very new: Roughly 8% of the globally existing solar PV capacity was installed during the last five years

7 World: Significant cost reductions materialised in the last 5-8 years Global annual new capacity in GW/yr Solar PV Wind Solar PV technology cost Wind technology cost 455% % % 7 54 Total South African power system (approx. 45 GW) Subsidies Cost competitive 9 Sources: IEA; GWEC; EPIA; BNEF; CSIR analysis

8 Renewables until today mainly driven by US, Europe, China and Japan Globally installed capacities for three major renewables wind, solar PV and CSP end of 215 Operational capacities in GW end of USA Canada 19 2 Americas w/o USA/Canada Europe Middle East and Africa India 77.3 China 5 3 Japan 4 6 Australia 4 7 Rest of Asia Pacific Wind Solar CSP PV Total World Sources: GWEC; EPIA; CSPToday; CSIR analysis Total RSA power system (45 GW) South Africa has 1.5/1.5/.2 GW installed capacity of wind, solar PV and CSP end of 216

9 REIPPPP results: new wind/solar PV 6-8% cheaper than first projects Results of Department of Energy s RE IPP Procurement Programme (REIPPPP) and Coal IPP Proc. Programme Significant reductions in actual tariffs Actual average tariffs in R/kWh (Apr-216-R) Nov Mar % -83% Aug Aug 214 Solar PV Wind Nov Notes: Exchange rate of 14 USD/ZAR assumed Sources: Deployment-NERSA.pdf; StatsSA on CPI; CSIR analysis

10 Actual tariffs: new wind/solar PV 4% cheaper than new coal in RSA Results of Department of Energy s RE IPP Procurement Programme (REIPPPP) and Coal IPP Proc. Programme Significant reductions in actual tariffs have made new solar PV & wind power 4% cheaper than new coal in South Africa today 17 Actual average tariffs in R/kWh (Apr-216-R) Nov Mar % -83% Aug Aug 214 Solar PV Wind Nov 215 Actual average tariffs in R/kWh (Apr-216-R) Notes: Exchange rate of 14 USD/ZAR assumed Sources: Deployment-NERSA.pdf; StatsSA on CPI; CSIR analysis.62 Solar PV IPP -4%.62 Wind IPP 1.3 Baseload Coal IPP

11 18 Approach to Power-System Planning

12 Last promulgated IRP is IRP 21, update currently ongoing (IRP 216) The enforceable IRP in South Africa is still the IRP 21 as promulgated in 211, it planned until 23 A number of changes since IRP 21 (demand forecast and confirmation of wind/solar PV cost decrease) The IRP 216 plans until 25 and is currently being developed IRP 21: promulgated in 211, plans from IRP Update 213: Not promulgated IRP 216: first draft publ. in Nov 216, plans from

13 IRP process as described in the Department of Energy s Draft IRP 216 document: least-cost Base Case is derived from technical planning facts Scenario 1 Scenario 2 Planning Facts Constraint: RE limits Least Cost Base Case Constraint: e.g. forcing in of nuclear, CSP, biogas, hydro, others Constraint: Advanced CO 2 cap decline Case Base Case Scenario 1 Scenario 2 Scenario 3 Cost Base Base + Rxx bn/yr Base + Ryy bn/yr Base + Rzz bn/yr 1. Public consultation on costed scenarios 2. Policy adjustment of Base Case 3. Final IRP for approval and gazetting Scenario 3 21 Sources: based on Department of Energy s Draft IRP 216, page 7;

14 The CSIR conducted in-depth power-system analyses to determine the least-cost expansion path for the South African electricity system The Integrated Resource Plan (IRP) is currently being updated by the Department of Energy / Eskom Draft IRP 216 Base Case entails a limitation: Amount of wind and solar PV capacity that the model is allowed to build per year is limited, which is neither technically nor economically justified/explained (no techno-economical reason provided) The CSIR is therefore conducting a study to determine the Least Cost electricity mix in RSA until 25 Majority of assumptions kept exactly as per the Draft IRP 216 Base Case First and most important deviation from IRP 216: no new-build limits on renewables (wind/solar PV) Second (smaller) deviation: costing for solar PV and wind until 23 aligned with latest IPP tariff results Scope of the CSIR study: purely techno-economical optimisation of the costs directly incurred in the power system Two scenarios from the Draft IRP 216 are compared with the Least Cost case Draft IRP 216 Base Case new coal, new nuclear Draft IRP 216 Carbon Budget significant new nuclear Least Cost least-cost without constraints An hourly capacity expansion and dispatch model (incl. unit commitment) using PLEXOS is run for all scenarios to test for technical adequacy same software platform as by Eskom/DoE for the IRP 22 Sources: CSIR analysis

15 The IRP currently only optimises for the generation cost component of total system cost (this is the dominant component) Optimised in PLEXOS model Not optimised in PLEXOS modelling framework (CSIR assumption for all scenarios =.3 R/kWh) [br/yr] 23 Costs included in Gx optimisation model: CAPEX (plant level) FOM 1 VOM 2 Fuel Costs excluded in Gx optimisation model: Externalities e.g. CO 2 emissions costs Decommissioning costs Waste management and/or rehabilitation Major mid-life overhaul Shallow grid connection costs Generation (Gx) High-level costing applied to PLEXOS outcomes Transmission network (Tx) Not considered Distribution network (Dx) Qualitatively discussed (quantified for system inertia) System services 3 Not considered Other (metering, billing, customer services, overheads) Total system cost 1 FOM = Fixed Operations and Maintenence costs; 2 VOM = Variable Operations and Maintenence costs; 3 Typically referred to as Ancillary Services includes services to ensure frequency stability, transient stability, provide reactive power/voltage control, ensure black start capability and system operator costs.

16 CSIR team has significant expertise from power system planning, system operation and grid perspective Dr Tobias Bischof-Niemz Head of the CSIR Energy Centre Member of the Ministerial Advisory Council on Energy (MACE) under previous Minister Member of IRP21/213 team at Eskom, energy planning in Europe for large utilities Joanne Calitz Senior Engineer: Energy Planning (CSIR Energy Centre) Previously with Eskom Energy Planning Former engineer in Eskom that produced the Medium-Term Outlook and IRP for RSA Robbie van Heerden Senior Specialist: Energy Systems (CSIR Energy Centre) Former General Manager and long-time head of System Operations at Eskom Mamahloko Senatla Researcher: Energy Planning (CSIR Energy Centre) Previously with the Energy Research Centre at University of Cape Town 24 Crescent Mushwana Research Group Leader: Energy Systems (CSIR Energy Centre) Former Chief Engineer at Eskom strategic transmission grid planning Jarrad Wright Principal Engineer: Energy Planning (CSIR Energy Centre) Commissioner: National Planning Commission (NPC) Former Africa Manager of PLEXOS

17 25 Key Input Assumptions

18 Input as per IRP 216: Demand is forecasted to double by 25 Forecasted demand for the South African electricity system from 216 to 25 Electricity Demand in TWh/yr IRP 216 IRP 21 Note: by 25 the electricity demand per capita would still be less than that of Australia today Sources: DoE (IRP 216); Eskom MTSAO ; StatsSA; World Bank; CSIR analysis

19 Input as per IRP 216: Decommissioning schedule for existing plants Energy supplied to the South African electricity system from existing plants between 216 and 25 Electricity in TWh/yr Decommissioning of Eskom s coal fleet Demand Existing supply Solar PV CSP Wind Other Peaking Gas (CCGT) 82 Hydro+PS Nuclear Coal 25 All power plants considered for existing fleet that are either: 1) Existing in 216 2) Under construction 3) Procured (preferred bidder) 27 Sources: DoE (IRP 216); Eskom MTSAO ; StatsSA; World Bank; CSIR analysis

20 Demand grows, existing fleet phases out gap needs to be filled Forecasted supply and demand balance for the South African electricity system from 216 to 25 Electricity in TWh/yr Decommissioning of Eskom s coal fleet Demand Supply gap Solar PV CSP Wind Other Peaking Gas (CCGT) Hydro+PS Nuclear Coal The IRP model fills the supply gap in the least-cost manner, subject to any constraints imposed on the model 28 Note: All power plants considered for existing fleet that are either Existing in 216, Under construction, or Procured (preferred bidder) Sources: DoE (IRP 216); Eskom MTSAO ; StatsSA; World Bank; CSIR analysis

21 PLEXOS actual inputs are individual cost items that together with the utilisation of the plant (a model output) allow to calculate LCOE Overnight R/kW Cost (plant level) Construction %/a Cash Schedule Discount Rate Economic Lifetime % a R/kW/a Fixed O&M (FOM) f CAPEX R/kW (plant level) f R/kW/a Annualised CAPEX + FIXED COST R/kW/a./. + PLEXOS inputs PLEXOS output LCOE R/kWh h/a Utilisation (capacity factor) 29 Variable R/kWh O&M (VOM) Fuel Price R/GJ Heat Rate kj/kwh (1/efficiency) x R/kWh Fuel Cost + R/kWh VARIABLE COST

22 Inputs as per IRP 216: Key resulting LCOE from cost assumptions for new supply technologies Today s new-build lifetime cost per energy unit 1 (LCOE) in R/kWh (April-216-Rand) 211 As per South African IRP Fixed (Capital, O&M) Variable (Fuel) Solar PV CO 2 in kg/mwh Wind Baseload Coal (PF) Nuclear Gas (CCGT) Mid-merit Coal Gas (OCGT) Diesel (OCGT) Assumed capacity factor 2 82% 9% 5% 5% 1% 1% 3 1 Lifetime cost per energy unit is only presented for brevity. The model inherently includes the specific cost structures of each technology i.e. capex, Fixed O&M, variable O&M, fuel costs etc. 2 Changing full-load hours for new-build options drastically changes the fixed cost components per kwh (lower full-load hours higher capital costs and fixed O&M costs per kwh); Assumptions: Average efficiency for CCGT = 55%, OCGT = 35%; nuclear = 33%; IRP costs from Jan-212 escalated to May-216 with CPI; assumed EPC CAPEX inflated by 1% to convert EPC/LCOE into tariff; Sources: IRP 213 Update; Doe IPP Office; StatsSA for CPI; Eskom financial reports for coal/diesel fuel cost; EE Publishers for Medupi/Kusile; Rosatom for nuclear capex; CSIR analysis

23 Supply technologies (technical characteristics) 31 Similar to the IRP wind and solar PV profiles for 27 supply areas (with exclusion masks) were used NOTE: These profiles were then aggregated into one profile that defines expected new wind and solar PV profiles Sources: CSIR Wind and solar Aggregation Study

24 Wind: supply profile assumptions Normalised power output 1. Utilisation Annual capacity factor = 36% Hour of the year 32

25 Solar PV: supply profile assumptions Normalised power output 1. Utilisation Annual capacity factor = 2.4% Hour of the year 33

26 Areas already applied for Environmental Impact Assessments can cater for 9 / 33 wind / solar PV capacity Polokwane Johannesburg All EIAs (status early 216) Wind: 9 GW Solar PV: 33 GW Latitude Upington Bloemfontein Durban Cape Town Port Elizabeth EIA: Onshore Wind EIA: Solar PV REDZ Longitude Sources:

27 35 Results

28 Draft IRP 216 Base Case is a mix of roughly 1/3 coal, nuclear, RE each Draft IRP 216 Base Case Total electricity produced in TWh/yr As per Draft IRP (5%) 93 (18%) 47 (9%) 33 (6%) 148 (28%) (33%) More stringent carbon limits 36 Sources: DoE Draft IRP 216; CSIR analysis Solar PV CSP Wind Gas (CCGT) Nuclear Peaking Hydro+PS Coal

29 Draft IRP 216 Carbon Budget case: 4% nuclear energy share by 25 As per Draft IRP 216 Draft IRP 216 Base Case Total electricity produced in TWh/yr Draft IRP 216 Carbon Budget Total electricity produced in TWh/yr (28%) (5%) 93 (18%) 47 (9%) 33 (6%) 173 (33%) More stringent carbon limits (14%) (6%) (8%) 11 (21%) 185 (35%) 78 (15%) No RE limits, reduced wind/solar PV costing, warm water demand flexibility 37 Sources: DoE Draft IRP 216; CSIR analysis Solar PV CSP Wind Peaking Gas (CCGT) Hydro+PS Nuclear Coal

30 Least Cost case is largely based on wind and solar PV As per Draft IRP 216 Draft IRP 216 Base Case Total electricity produced in TWh/yr Draft IRP 216 Carbon Budget Total electricity produced in TWh/yr Total electricity produced in TWh/yr Least Cost (5%) 93 (18%) 47 (9%) 33 (6%) (33%) (28%) More stringent carbon limits (8%) 11 (21%) 74 (14%) 32 (6%) 185 (35%) 78 (15%) No RE limits, reduced wind/solar PV costing, warm water demand flexibility (21%) 257 (49%) 12 (2%) 55 (1%) 33 (6%) 6 (11%) 38 Sources: DoE Draft IRP 216; CSIR analysis Solar PV CSP Wind Peaking Gas (CCGT) Hydro+PS Nuclear Coal

31 Least Cost means no new coal and no new nuclear until 25, instead 85 GW of wind and 74 GW of solar PV plus flexible capacities As per Draft IRP 216 Draft IRP 216 Base Case Draft IRP 216 Carbon Budget Least Cost Total installed net capacity in GW Total installed net capacity in GW Total installed net capacity in GW More stringent carbon limits No RE limits, reduced wind/solar PV costing, warm water demand flexibility Note: REDZ = Renewable Energy Development Zones Current REDZ cover 7% of South Africa s land mass Sources: DoE Draft IRP 216; CSIR analysis Solar PV CSP Wind Peaking Gas (CCGT) Hydro+PS Nuclear Coal Plus 3 GW demand response from residential warm water provision

32 Conservative renewables and battery costing: Least Cost is R6-75 billion/yr cheaper than Draft IRP 216 by 25 As per Draft IRP IRP 216 Base Case IRP 216 Carbon Budget Least Cost Energy Mix in 25 Demand: 522 TWh 5% 14% 18% % % 1% 9% 6% 28% 19% 8% 21% % % % 16% 6% 13% 35% 21% 49% 11% 6% 1% 1% 2% Cost in 25 Total system cost 1 (R-billion/yr) 7 Average tariff (R/kWh) % cheaper Environment in 25 CO 2 emissions (Mt/yr) Water usage (billion-litres/yr) Cleaner Jobs 2 in 25 Direct & supplier ( ) % more jobs 4 Because of lack of data, zero jobs for Coal Nuclear Hydro + PS Peaking Other storage CSP biomass/-gas assumed Coal (new) Nuclear (new) Gas Biomass/-gas Wind Solar PV (affects Decarbonised) 1 Only power generation (Gx) is optimised while cost of transmission (Tx), distribution (Dx) and customer services is assumed as.3 R/kWh (today s average cost for these items) 2 Lower value based on McKinsey study (appendix of IEP), higher value based on CSIR assumption with more jobs in the coal industry; Sources: Eskom on Tx, Dx cost; CSIR analysis; flaticon.com

33 41 Operational Aspects

34 Weekly electricity demand profile in 25 Demand and Supply in GW 12 Exemplary Week in Monday Tuesday Wednesday Thursday Friday Saturday Sunday Customer demand 42 Sources: CSIR analysis, based on DoE s Draft IRP 216

35 Draft IRP 216 Base Case: Nuclear and coal dominate the supply mix in 25 Demand and Supply in GW 12 Exemplary Week under Draft IRP 216 Base Case (25) Monday Tuesday Wednesday Thursday Friday Saturday Sunday Solar PV Wind CSP Peaking DR Hydro + PS Gas Biomass/-gas Coal Nuclear Customer demand 43 Sources: CSIR analysis, based on DoE s Draft IRP 216

36 Draft IRP 216 Base Case: Nuclear and coal dominate the supply mix in 25 Demand and Supply in GW 12 Exemplary Week under Draft IRP 216 Base Case (25) Monday Tuesday Wednesday Thursday Friday Saturday Sunday Solar PV Wind CSP Peaking DR Hydro + PS Gas Biomass/-gas Coal Nuclear Customer demand 44 Sources: CSIR analysis, based on DoE s Draft IRP 216

37 Draft IRP 216 Base Case: Nuclear and coal dominate the supply mix in 25 Demand and Supply in GW 12 Exemplary Week under Draft IRP 216 Base Case (25) Monday Tuesday Wednesday Thursday Friday Saturday Sunday Solar PV Wind CSP Peaking DR Hydro + PS Gas Biomass/-gas Coal Nuclear Customer demand 45 Sources: CSIR analysis, based on DoE s Draft IRP 216

38 Scenario: Least Cost - Solar PV and wind dominate supply mix in 25, with curtailment and variability managed by flexible gas Demand and Supply in GW 12 Exemplary Week under Least Cost (25) Monday Tuesday Wednesday Thursday Friday Saturday Sunday Curtailed solar PV and wind Solar PV Wind CSP Peaking DR Hydro + PS Gas Biomass/-gas Coal Nuclear Customer demand Demand (incl pumping, DR, storage) 46 Sources: CSIR analysis

39 IRP PLEXOS model only optimises for cost of power generation (Gx) two additional key aspects considered: system stability and grid cost System Stability (inertia): worst case below 1% of Gx cost Connecting nuclear/coal via HVDC and/or solar PV/wind to the grid reduces the system inertia This reduces the inherent stabilising effect of synchronous inertia during contingency events Technical solutions to operate low-inertia system exist In this study the worst case was costed State-of-the-art technology (very high costs assumed, no further tech/cost advancements) Assumption: No further increase in engineering of how to deal with low-inertia systems by 25 In all scenarios, the worst-case-cost are well below 1% of the total cost of power generation (Gx) by 25, cost differences between scenarios are much lower than 1% 47 Transmission grid cost: Gx Least Cost also cheapest for Tx High-level cost estimate for shallow and deep grid connection cost for all scenarios was developed Least Cost (Gx) case is additionally R2-3 billion/yr cheaper compared to Draft IRP 216 Base Case and Carbon Budget case on transmission grid side

40 48 Next Steps and Summary

41 What has not been considered yet that makes Least Cost even cheaper? Further cost reductions in solar PV, wind and battery technologies Solar PV cost were assumed to only decrease 2% by 25 Wind and battery cost were assumed to stay constant until 25 CSP cost were assumed to decrease to only 1.2 R/kWh until 23 (for mid-merit operations) With realistic cost reductions assumed, Least Cost is 25-3% cheaper than the IRP Base Case Increasing penetration of Electric Vehicles (EV) No EV uptake assumed at all With 5 million EVs by 25, a large source of flexible demand is introduced into the system Demand side flexibilisation only marginally considered Only source of flexibility considered: domestic electric warm water provision With all heat/cool & pumping load made flexible, large source of flexible demand can be introduced 49 Transmission grid expansion for distributed power generators less costly Transmission grid costs assumed to be equal for all scenarios Preliminary costing: transmission for Least Cost additionally R2-3 billion per year cheaper

42 Summary: A mix of solar PV, wind and flexible power generators is least cost It is cost-optimal to aim for >7% renewable energy share by 25 Solar PV, wind and flexible power generators (e.g. gas, CSP, hydro, biogas, demand response) are the cheapest new-build mix for the South African power system There is no technical limitation to solar PV and wind penetration over the planning horizon until 25 Clean and least-cost is not a trade-off anymore: South Africa can de-carbonise its electricity sector at negative carbon-avoidance cost The Least Cost mix is >R7 billion per year cheaper by 25 than the current Draft IRP 216 Base Case Additionally, Least Cost mix reduces CO 2 emissions by 55% (-1 Mt/yr) over Draft IRP 216 Base Case 5 Note: Wind and solar PV would have to be 5% more expensive than assumed before the IRP Base Case and the Least Cost case break even Sources: CSIR analysis

43 51 Outlook for Energy Planning beyond Electricity

44 Electricity demand is fluctuating intraday, intra-week, and seasonally Actual RSA demand for week from Aug 11 in 15-minute resolution, scale to ~ 225 demand level GW Monday Tuesday Wednesday Thursday Friday Saturday Sunday 52 Sources: CSIR analysis Electricity Demand

45 Future energy system will be built around variability of solar PV & wind Actual scaled RSA demand & simulated 15-minute solar PV/wind power supply for week from Aug GW Sources: CSIR analysis 1 3 Monday Tuesday Wednesday Thursday Friday Saturday Sunday Excess Solar PV/Wind Residual Load (flexible power) Useful Wind Demand shaping Power-to-Power 1 Useful Solar PV Day of the week Electricity Demand X-to-Power (natural gas, biogas, hydro, CSP) Power-to-X (sector coupling into heat/transport/chemicals) 2 4

46 Nuclear can add carbon-free electricity: cost, not a technical question Actual scaled RSA demand & simulated 15-minute solar PV/wind power supply for week from Aug GW 1 Demand shaping 2 X-to-Power (natural gas, biogas, hydro, CSP) Power-to-Power 4 Power-to-X (sector coupling into heat/transport/chemicals) Monday Tuesday Wednesday Thursday Friday Saturday Sunday Excess Solar PV/Wind Nuclear Residual Load (flexible power) Useful Wind Useful Solar PV Electricity Demand Sources: CSIR analysis

47 Scenario: Electricity the new primary energy, complemented by bio Hypothetical energy-flow diagram (Sankey diagram) for South Africa in the year 2?? Sun T Transport H2 Non-energy E.g. fertiliser Wind Electricity H2 Hydro Electricity E Electricity H2 PtL fuels H2 Natural Gas Heat Electricity CO2 Heat H Liquid biofuels Heat 55 Biomass

48 Ha Khensa Re a leboha Siyathokoza Enkosi Thank you Re a leboga Ro livhuha Siyabonga Dankie 56 Note: Thank you in all official languages of the Republic of South Africa