economics of storage local meeting july 8 2009
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ECONOMICS OF STORAGE LoCal Meeting - July 8, 2009. Presented by Mike He and Prabal Dutta. Lots of Storage Technologies. Pumped Water. LiSulphur. NiMH. SMES. Supercap. NiCad. Flywheel. EEStor. Li+. Thermal. Compressed Air. LiPoly. LiSulphur. Why Store Energy?. Peak-to-Average

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economics of storage local meeting july 8 2009

ECONOMICS OF STORAGELoCal Meeting - July 8, 2009

Presented by Mike He and Prabal Dutta

lots of storage technologies
Lots of Storage Technologies

Pumped Water

LiSulphur

NiMH

SMES

Supercap

NiCad

Flywheel

EEStor

Li+

Thermal

Compressed Air

LiPoly

LiSulphur

why store energy
Why Store Energy?
  • Peak-to-Average
    • Reduce electricity rate by shaving peak load
  • Match Supply and Demand
    • When supply/demand is inelastic or intermittent
  • Economic Arbitrage
    • When price of electricity varies substantially and
    • An efficient market exists to buy and sell real energy
peak to average
Peak-to-Average
  • When electricity cost is set by peak power draw
    • Peak-shaving yields big dividends
    • Benefits accrue at all times, not just at peak load times
  • Load shift if possible
  • Generate electricity locally if feasible economically
  • LoCal
    • Buy electricity when local demand is low
    • Convert and store electricity for later use
    • Convert and use electricity when highest local demand
match supply and demand
Match Supply and Demand

When supply/demand is inelastic or intermittent

Solar

S/D well-matched for typical industrial loads; storage overkill

S/D poor-match for early morning or evening residential loads

Wind

S/D matching is variable, TBD

Statistical multiplexing plays a role in smoothing out

LoCal

Store when supply is high but demand is low

Use when supply is low but demand is high

economic arbitrage
Economic Arbitrage

When a sufficient wholesale price difference exists

Buy electricity when price is low

Convert and store electricity for later sale

Convert and sell electricity when price is high

ieso a concrete analysis
IESO: A Concrete Analysis

http://www.iemo.com/imoweb/marketdata/marketToday.asp ($1 CAD = $.86 USD)

ontario ieso july 7 2009
Ontario IESO (July 7, 2009)
  • Wholesale electricity price ($CAD/MWh)
    • Min: $3.52
    • Avg: $20.99
    • Max: $42.32
    • Range: $38.80
  • Average hourly demand
    • Min: 15,000 MW
    • Avg: 17,162 MW
    • Max: 19,570 MW
    • Range: 5,070 MW
storage economics
Storage Economics
  • To be marginally viable, must satisfy:
    • CostPUE / PriceDeltaPUE < CycleLife
    • CostPUE / PriceDeltaPUE => cycles needed to profit
  • Where
    • CostPUE is Cost per unit of energy storage
      • Li+ (e.g. $300/kWh)
      • Pumped Hydro ($10-$45/kWh)
    • PriceDeltaPUE is max(price) - min(price) per unit energy
    • CycleLife is number of cycles of storage technology
storage economics1
Storage Economics
  • IESO Case Study on July 7, 2009
    • PriceDeltaPUE = $38.80
  • (CostPUE / PriceDeltaPUE / CycleLife) ?
  • Tech CostPUE PDPUE CycleLife LHS
  • Li+ $300/kWh $.0388/kWh 1200 6.44
  • Pump. Hydro $45/kWh $.0388/kWh Inf (need 1160) <1
marginal revenue potential drops quickly and varies
Marginal revenue potential drops quickly and varies

Mild Spring Weekend Day

Warm Summer Weekday

storage power density matters small window to buy cheap
Storage power density matters:Small window to buy cheap

Mild Spring Weekend Day

Warm Summer Weekday

1x

Power Density

2x

unexpected arbitrage can create opportunistic profits
Unexpected arbitrage cancreate opportunistic profits

http://www.iemo.com/imoweb/marketdata/marketToday.asp ($1 CAD = $.86 USD)

must disentangle residential commercial industrial and night life party loads
Must disentangle residential, commercial, industrial, and night life/party loads

Ontario

Night Life

limitations
Limitations
  • Assumes Time-of-Use pricing
  • Assumes zero price-elasticity
    • For marginal profit potential analysis
    • Likely reality: price sensitivity high at peak load times
  • Garbage-in/Garbage-out
    • Wholesale prices and load profiles are average values
    • No distinction between $USD and $CAD
  • Only a marginal viability analysis
    • Average-case viability much lower
takeaways
Takeaways
  • Storage still has a long way to go for economic viability in financial arbitrage
  • Peak to average case may be more economically viable
  • Cost, power density, efficiency, cycle life are important factors
  • Need a metric for: Capacity X CycleLife
  • 100W lightbulb for a day = Raising a car ~1km
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