Energy Storage and Sector Coupling at SA Energy Storage 2017 by Dr Peter Klein, CSIR Energy Centre 1
Agenda 1. Energy storage research at Energy Centre 2. Introduction to sector coupling and energy storage 3. Flexibility resources from two recent Energy Centre studies 4. Conclusions and outlook 2
3 Context for Energy Storage Research at the Energy Centre
CSIR s new Energy Centre streamlines and expands CSIR s energy research offerings in six areas 4
Context for Energy Storage: Uptake of Solar PV and Wind 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% 120 124 4 4 0 154% 7 7 0 7 8 17 13 3 39 39 41 0 9 9 2 12 1 27 15 20 7 8 1 8 1 2011 22 33 46 7 56 17 71 30 76 31 45 73 38 35 91 40 51 57 63 100% 70 54 Total South African power system (approx. 45 GW) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2012 2013 2014 2015 2016 Subsidies Cost competitive 5 Sources: IEA; GWEC; EPIA; BNEF; CSIR analysis
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 15-21 Aug 11 6 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 GW Sources: CSIR analysis Monday Tuesday Wednesday Thursday Friday Saturday Sunday Excess Solar PV/Wind Residual Load (flexible power) Useful Wind Useful Solar PV Day of the week Electricity Demand
Energy Storage Amount of storage adopted will depend on the costs and benefits relative to other flexibility options Demand Side Management Flexible Generation Energy Storage & Sector Coupling Grid Expansion Interconnection 7
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 15-21 Aug 11 8 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 GW Sources: CSIR analysis 1 2 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 2 3 4 Day of the week Electricity Demand X-to-Power (natural gas, biogas, hydro, CSP) Power-to-X (sector coupling into heat/transport/chemicals) 3 4
9 Energy Storage and Sector Coupling
Today, very little sector coupling electricity relatively easy to decarbonise, but transport and heat sectors are more challenging 2010 Direct Emissions by Sector 1 Decarbonisation Potential Other 18% E Electricity High RE Potential RE fully cost competitive Unlimited RE tech. potential Transport 8% 52% H Heat Biomass limited potential Needs coupling to electricity Liquid Fuel Refineries 10% Industry 12% Electricity T Transport Biofuels limited potential Needs coupling to electricity 10 1 Department of Environmental Affairs. 2013 GHG Inventory for South Africa 2000-2010
Liquid fuels Hydrogen Scenario: Electricity the new primary energy, complemented by other renewable sources including bio, solar thermal E Electricity Power-to-Heat Heat-to-Power H Heat Power Storage PHS, CAES, flywheel batteries capacitors, SMES, fuel cells G Gas Gas Storage/Network Thermal Storage Sensible heat Latent heat Thermochemical Hydrogen SNG Methanol Chemicals: e.g. Ammonia 11 Modified from AGORA Electric Vehicles T Transport
Identified Power-to-Power Use Cases Power in from grid -> storage -> power back onto grid Bulk Energy Services Ancillary Services Grid Infrastructure Services Customer Energy Management Services Time-shifting of electric energy (arbitrage) Frequency support(reserves) Transmission upgrade deferral Power quality Schedulable capacity Voltage support (reactive power) Distribution upgrade deferral Power reliability Re-dispatch (>10 min reserves) Bottleneck management (congestion relief) Energy charge management Black-start capability Demand charge management Island and offgrid 12
Identified Use Cases for Sector Coupling Utilisation of excess power outside electricity sector Power-to-Gas/Liquids Power in -> hydrogen -> fuels/feedstocks Fuels Chemical Feedstocks Grid Infrastructure Services Power-to-Heat Power in -> heat (res., comm., ind.) Customer Energy Comfort Heat Management Services Industrial Heat Inf Power-to-Gas (Methane) Hydrogen as feedstock Space Heating/Cooling Process heating (water, steam) Power to Liquids (Methanol) Carbon dioxide as feedstock Water Heating Process heating (non-water, smelters) Hydrogen as fuel Process Cooling System Integration 13 Power-to-eMobility Power-to-Pumping System integration of electric vehicles System integration of large scale pumping
14 Case Studies: Power-to-Heat and Power-to-eMobility
Modelling presented from 2 recent Energy Centre Publications 15 Author s J. Wright, T. Bischoff Niemz, J Calitz, C. Mushwana, R. van Heerden, M. Senatla
Demand shaping as a demand side resource - domestic electric heaters (EWHs) Many opportunities for demand shaping in a number of end-use sectors (domestic, commercial, industrial) In the scenarios assessed by CSIR - the intention of including one particular demand shaping opportunity (domestic electric water heating) is to demonstrate the significant impact this can have on the power system. Modelled as a resource with intra-day controllability (can be dispatched as needed on any given day) based on power system needs 16 Key input parameters to estimate potential demand shaping via EWH: South African population (to 2050) Number of households (current) Number of persons per household (future) EWHs (current) EWHs per household (future) Adoption rate of demand shaping via EWHs (future) Calibration for power (MW) and energy (TWh) used electric water heating (existing) Movement to EWH technologies i.e. heat pumps vs electric geysers (future)
Flexible Daily EWH Demand [GWh/d] Power-to-Heat Demand shaping can provide ~70 GWh/d of dispatchable energy by 2050 at low cost storage Description Unit 2016 2030 2050 Population million 55.7 61.7 68.2 Number of households million 16.9 22.4 27.3 Households with EWH million 4.7 11.2 27.3 Households with EWH % 28 50 100 Demand shaping adoption % 0 25 100 EWH individual unit power kw 3 1 80 70 60 50 40 30 77 72 Electric Geyser Storage Costs: CAPEX 150l = R3000 Q = (150)(4179)(70-15)/(3.6x10 6 ) = 9.57 kwh th CAPEX = R313/kWh th = $21.3/kWh th 20 15 10 0 0 1 2016 2020 2030 2040 Transition to more efficient EWH 2050 17 Sources: CSIR estimates; StatsSA; AMPS survey; Stastista; Eskom; Draft IRP 2016 2016 Resistance heating 2050: Heat pump (COP=3)
Electric vehicle usage for demand side flexibility Inclusion of a demand side flexibility resource in the form of mobile storage (electric motor vehicles) demonstrates impact on the power system as adoption increases Modelled similar to EWH demand shaping as a resource with intra-day controllability (can be dispatched as needed on any given day) based on power system needs Key input parameters to estimate potential demand shaping via electric motor vehicles: Current population Expected population growth to 2050 Current number of motor vehicles Expected motor vehicles per capita Adoption rate of electric vehicles to 2050 Electric vehicle fleet capacity (MW) Electric vehicle energy requirement (GWh/d) Proportion of electric vehicle fleet connected simultaneously 18
BNEF Li-ion battery pack price ($/kwh) Flexible Daily EV Demand [GWh/d] Power-to-eMobility Electric vehicle demand shaping can provide ~100 GWh/d daily dispatchable energy 2050 Description Unit 2016 2030 2050 Population million 55.7 61.7 68.2 Number of motor vehicles million 7 8.0 8.9 EV adoption rate % 0 10.0 55.5 Number of EVs million 0 2.4 15 45 40 35 30 25 41 1 000 800 600 400-20% -20% -7% -10% -35% -22% 20 15 10 5 0 0 2016 1 2020 7 2030 17 2040 2050 200 0 2010 2011 2012 2013 2014 2015 2016 19 Sources: CSIR estimates; StatsSA; AMPS survey; Stastista; Eskom; Draft IRP 2016, BNEF battery price survey
20 Energy storage in the context of high renewable scenarios
Two Scenarios considered from recent Energy Centre publications Flexibility resources for different costs assumptions for wind, solar PV and battery storage Electricity [TWh/yr] 500 400 300 200 100 0 2016 307 58 Planned decommissioning of Eskom s coal fleet 352 197 Demand 277 295 286 382 2020 2025 2030 2035 2040 2045 2050 Low growth in Demand Scenario 382 TWh/yr by 2050 Scenario A Moderate cost reductions solar PV No cost reductions for wind No cost reductions for batteries Reserve requirement 3.8GW (2016) 5.6 GW (2050) Includes demand shaping for EWH Scenario B 70% cost reductions solar PV by 2050 (BNEF) 40% cost reductions for wind by 2050 (BNEF) 86% cost reductions in battery storage ($100/kWh by 2050) Reserve requirement 3.9GW (2016) 9.6 GW (2050) Includes demand shaping for EWH and EV 21 For details on modelling for Scenario A see Wright et al. 2017. Formal Comments on the Integrated Resource Plan (IRP) Update Assumptions, Base Case and Observations 2016 For details on modelling for Scenario B see Wright et al. 2017. Future wind deployment scenarios for South Africa. WindAc 2017
Tariff in R/kWh (Apr-2016-Rand) Two Scenarios considered from recent Energy Centre publications Flexibility requirements analysed for different costs assumptions for wind, solar PV and battery storage PLEXOS modelling Tariff in R/kWh (Apr-2016-Rand) Wind Cost Assumptions Solar PV Assumptions 4.0 4.0 3.5 3.5 3.65 3.0 3.0 2.5 2.0 2.5 2.0 2.18 1.5 1.52 1.5 1.19 1.0 0.87 0.69 0.5 0.62 0.0 0.62 0.46 0.62 0.35 0.62 0.35 1.0 0.5 0.0 0.62 1.17 0.91 0.56 0.37 0.52 0.20 0.49 0.20 2010 2020 2030 2040 2050 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year Year 22 For details on modelling for Scenario A see Wright et al. 2017. Formal Comments on the Integrated Resource Plan (IRP) Update Assumptions, Base Case and Observations 2016 For details on modelling for Scenario B see Wright et al. 2017. Future wind deployment scenarios for South Africa. WindAc 2017
Overnight Cost R/kWh (Apr-2016-Rand) Battery cost reductions and some technical assumptions Scenario A (1hr) Scenario B (1hr) Scenario A (3hr) Scenario B (3hr) 10 000 9 891 9 891 9 891 9 891 1h and 3h batteries considered in the model 9 000 8 000 7 000 6 000 8 100 8 100 8 100 8 100 Battery can be assigned to reserves or bulk energy supply Battery lifespan of 10 years 23 5 000 4 000 2 800 3 000 2 030 2 000 2 293 1 400 1 000 1 720 1 147 0 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year No cycle life limitation or battery degradation 89% Round trip efficiency
Flexible resources built by model for each scenario Low cost solar PV and battery offsets gas turbines (CCGT) Scenario A Scenario B 24 WARNING: Storage deployment in B is due to combined effect of low cost solar PV and batteries
Curtailed Energy [TWh] 55 TWh 55 TWh Curtailed Energy from least cost modelling Opportunities for sector coupling 60 50 40 55 9 Solar PV Wind 1.1 million tonnes Hydrogen 1 30 20 26 2 46 Or absorb as process heat? 10 0 0 0 0 0 0 0 1 1 0 24 1 assuming 50 kwh/kg H 2 2016 2020 2030 2040 2050 25
Conclusions Decarbonisation requires an integrated energy system with sector coupling Low hanging fruit such as electric geysers can add flexibility through low cost thermal storage Two scenarios contrast deployment of flexible resources based on different cost assumptions If no cost reductions for batteries are assumed flexible generation from CCGT is more cost effective Significant cost reductions for batteries and solar PV result in a 17GW/48GWh deployment of energy storage by 2050 Future work to be conducted to asses the opportunities and implications for energy storage, which will be a focus area for the Energy Centre 26