Introduction to the power sector baseline scenarios and the IRENA SPLAT-W/MESSAGE tool

Transcription

1 Introduction to the power sector baseline scenarios and the IRENA SPLAT-W/MESSAGE tool International Renewable Energy Agency (IRENA) Innovation and Technology Centre Development of the ECOWAS RE and EF National Action Plans and SE4ALL Abidjan, March 2014

2 RE target setting Common inconsistencies: Bottom-up targets do not meet the overall energy needs Sum of sector targets does not meet the overall energy needs Top-down targets imply unrealistic speed of technology transition It is crucial to have an accounting framework for: Overall future energy needs Overall future energy supply mix 2

3 Energy system models Bottom up models Accounting suited to demand side analysis (e.g., LEAP, MAED) Optimization suited to supply side analysis (e.g., MARKAL, TIMES, MESSAGE etc) IRENA SPLAT-W model: optimization model built based on the MESSAGE modelling framework 3

4 NREAP and SPLAT-W Interested countries can use SPLAT-W to benchmark their power sector trajectory Define the future energy mix (installed capacity and power generation by technology to meet a given set of demand) Assess implications on policy goals (financial, environmental, energy security etc) Compare with alternative future energy mix under different scenarios 4

5 NREAP scenario At the request of ECREEE, a NREAP scenario is being developed for each ECOWAS countries using SPLAT-W. Note on process IRENA s desk-top study, not meant to give recommendations on countries trajectories It provides a useful benchmark Interested countries are invited to verify data with IRENA (data verification sheet) Interested countries are invited to use the tool to develop/adjust the scenario Many ECREEE countries have trained national experts 5

6 How did we define the NREAP scenario? (1) Step 1 Power demand till 2030 is defined for industry, urban, rural demand Demand patterns (seasonal, weekly, daily) are defined for each demand category Distribution losses are defined for each demand category Step 2 Database of existing power plans and international transmission lines are set up, with performance parameters 6

7 How did we define the NREAP scenario? (2) Step 3 Database of projects (PP or interconnector) under implementation/considerations are set up Database of possible power generation options is set up with economic and performance parameters PP with fossil fuel inputs (diesel 1kW system, Diesel 100kW system, utility diesel, utility HFO, coal, OCGT, CCGT) Hydro (utility / decentralized only to serve rural demand) Biomass Wind (20% CF, 30% CF) Solar PV (utility scale) Solar PV 1 kw decentralized (no storage / 1 hour storage / 2 hour storage) CSP (no storage, with storage, with gas co-firing) Database of RE resource availability is set up 7

8 How did we define the NREAP scenario? (3) Step 4 The model calculates the least-cost combinations of power supply options to meet the specified demand at a specified time, under certain conditions Step 5 Certain conditions includes: NREAP regional targets are met Reserve margin to be at least 10% (installed firm capacity need to be 10% higher than peak-demand) Capacity credits of non-dispatchable RE technologies vary depends on CF and level of spatial distribution of resources locations Coal and biomass plants cannot be ramped-up very fast Among those interconnecting projects being considered, economically viable ones would be implemented to allow electricity trade Other conditions are similar to those assumed under WAPP master plan Trade with Central Africa / CO 2 price could be added as an option 8

9 Share of renewable [capacity] 120% 100% 80% 60% 40% 20% Share of RE capacity: Regional results 0% in relation to peak (non-hydro) in relation to total installed capacity (non-hydro) 9

10 Share of renewable [capacity] 500% 450% 400% 350% 300% 250% 200% 150% 100% 50% In relation to peak 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% In relation to total installations 0% % Benin Burkina Cape Verde Cote d'ivoire Gambia Ghana Guinea Guinea-Bissau Liberia Mali Niger Nigeria Senegal Sierra Leone Togo 10

11 TWh Cote D Ivoire Final energy demand Industry Urban Rural Existing PP (as of 2010) Gas Turbine: 790 MW Hydro: 585 MW ( TWh) In the pipeline Gas Turbine: 860 MW Resources Additional identified hydro: 3-5 TWh Wind 20% CF: 430 TWh CSP 220 TWh Solar PV 10,300 TWh Fuel availability Coal: import Gas: domestic Oil: import Import from neighbors Existing: Ghana, Burkina Faso Committed: Ghana, Liberia, Mali 11

12 LCOE ($/MWh) Cote D Ivoire LCOE at generation HFO OCGT CCGT CCGT (in the pipeline) Supercritical coal Hydro (280 MW project) Hydro (50MW project) Small Hydro Biomass Bulk Wind (20% CF) Solar PV (utility) Solar PV (roof top) Rooftop PV with 1h Battery Rooftop PV with 2h Battery Solar thermal no storage Solar thermal with Storage Solar thermal with gas co-firing 12

13 LCOE ($/MWh) Cote D Ivoire LCOE with TnD needs industry urban Rural Diesel Centralized Diesel 100 kw system HFO OCGT CCGT CCGT (in the pipeline) Supercritical coal Hydro (280 MW project) Hydro (50MW project) Small Hydro Biomass Bulk Wind (20% CF) Solar PV (utility) Solar PV (roof top) Rooftop PV with 1h Battery Rooftop PV with 2h Battery Solar thermal no storage Solar thermal with Storage Solar thermal with gas co-firing

14 Cote D Ivoire Electricity production [TWh] Rural demand [GWh] (5) (10) Share of RE [capacity] 0 RE share capacity (peak) (total installed capacity) Dist.Solar PV Mini Hydro Dist. Oil Net Imports Wind Solar Thermal Solar PV Biomass Hydro Nuclear Gas Oil Coal dom. System dmd RE capacity [GW] Grid Diesel Mini-hydro Hydro Biomass Mini Hydro Dist.Solar PV 14

15 Billion $ Cote D Ivoire Annualized costs [billion $] Investment needs [billion $] 2.5 O&M Inv. Fuel Ann.Dom.Tr ans Inv Ann.Trans Inv Import costs Export Revenues Average generation costs [$/MWh] Cote D'Ivoir ECOWAS average International Transmission Domestic transmission Decentralized

16 Contributions to NREAP Development of power sector baseline trajectory for ECOWAS countries IRENA s desk-top study, developed using SPLAT-W Normative scenario, illustrating the implications of EREP on each country Provide useful benchmark Data review sheet can be made available to interested countries The SPLAT-W is available with tutorials 16

17 Planning for the Global Energy Transition IRENA s resources: Sound statistics and data Statistical methodology: statistics@irena.org GIS mapping and assessment of theoretical generation potential RE technology costing analysis: costs@irena.org RE technology brief Transparent methodology: SPLAT-W model (benchmarking, transfer the tool, list of resource people) Ownership of the planning skill: long term CB is being discussed, engaging local experts 17

18 Thank you for your attention Asami Miketa