Battery Energy Storage in the Australian National Electricity Market

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Potential economic viability of battery storage in the Australian National Electricity Market

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Battery Energy Storage in the Australian National Electricity Market

  1. 1. Battery Energy Storage in the Australian National Electricity Market Potential commercial viability ENERGY TECHNOLOGY Thomas Brinsmead, and others 25 October 2015
  2. 2. Who else contributed? • The Integrated Energy & Economic Systems Modelling group Paul Graham Luke Reedman Jenny Hayward
  3. 3. Darwin Alice Springs Geraldton 2 sites Atherton Townsville 2 sites Rockhampton Toowoomba Gatton Myall Vale Narrabri Mopra Parkes Griffith Belmont Geelong Hobart Sandy Bay Wodonga Newcastle Armidale 2 sites Perth 3 sites Adelaide 2 sites Sydney 5 sites Canberra 7 sites Murchison Cairns Irymple Melbourne 5 sites Commonwealth Scientific and Industrial Research Organisation (CSIRO) Werribee 2 sites Brisbane 6 sites Bribie Island People Locations Flagships Budget 6500 58 12 $1B+ Precincts | CSIRO site
  4. 4. Battery Storage in the Australian electricity market: overview • Overview • Key Question(s) • Key Assumptions • Main results • Questions raised and limitations
  5. 5. Main Question • Under what circumstances will electricity customers find it economically viable to install battery energy storage? • Under various • Customer scales and load profiles • Tariff alternatives • Whether or not PV is installed • Tariff alternatives considered • Flat – energy based (with or without PV) • Time-of-Use (with or without PV) • Maximum Demand (capacity, with or without PV) • Presentation based on Future energy storage trends: An assessment of the economic viability, potential uptake and impacts of electrical energy storage on the NEM 2015–2035
  6. 6. Key Assumptions • Battery prices projected using technological learning models • Tariffs and rebates. • Tariffs based on existing in current market, scaled by a price index. • PV rebates based on existing legislation • Load profiles based on a finite number of “representative customers” at a handful of representative scales • Residential analysis only, since there is limited load profile data available for non-residential
  7. 7. Key Assumptions • Battery management based on heuristic according to tariff, rather than optimised • Financial comparison only of with and without storage, no consideration of customers changing load profile, tariff, or on-site generation (PV). • Batteries and PV system sizes selected for high benefit-cost ratio rather than high NPV, under low solar Feed-in-Tariff • Uptake rate based on logistic function with parameters dependent on payback period only, and calibrated to PV experience
  8. 8. Battery Management Heuristic • For Flat Tariff • No value in storage • For Time of Use Tariff • Charge during off-peak hours until full, discharge during peak hours until empty • For Capacity Tariff • Charge if demand greater than target til full, discharge if demand less than target until empty • For PV • Charge if net demand is negative until full, discharge if positive until empty • For PV with time of use • Charge if net demand negative or off-peak, discharge if demand positive during peak
  9. 9. Key Assumptions • Battery Costs
  10. 10. Key Assumptions • Solar PV Costs
  11. 11. Key Assumptions • Customer Load profile
  12. 12. Key Results • Payback periods • Indicative uptake • Indicative impact on load profile
  13. 13. Payback periods • Payback periods: Without PV, Time of Use • No payback for Capacity Tariff
  14. 14. Payback periods • Payback periods: With PV, Time of Use/ Flat
  15. 15. Payback periods • Payback periods: Bundle PV and Battery, Time of Use/ Flat…
  16. 16. Indicative Uptake? • With PV
  17. 17. Indicative Uptake? • Time of Use Tariff
  18. 18. Indicative Impact on load profile • Typical Day… Without/ with PV
  19. 19. Indicative Impact on load profile • Maximum Day… Without/ with PV
  20. 20. Aggregate Impact
  21. 21. Aggregate Impact • Low PV case
  22. 22. Aggregate Impact • High PV case
  23. 23. Aggregate Impact • High Time of Use Tariff Case
  24. 24. Questions raised and limitations • Customer Load Diversity • Future evolution of tariffs • Impact of peak demand reduction at various scales in the supply network hierarchy. • Tariff switching, behaviour change, leaving the grid, demand reduction technologies • How best can incentives under a highly regulated industry be aligned to economically efficient outcomes?
  25. 25. Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem ADD BUSINESS UNIT/ENERGY FLAGSHIP You are welcome
  26. 26. Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem Division/Unit Name Presenter Name Presenter Title t +61 2 9123 4567 e firstname.surname@csiro.au w www.csiro.au/lorem ADD BUSINESS UNIT/ENERGY FLAGSHIP

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