ECONOMICS OF STORAGE LoCal Meeting - July 8, 2009 Presented by Mike He and Prabal Dutta

Lots of Storage Technologies NiMH NiCad Li+ LiPoly LiSulphur Supercap EEStor Compressed Air Pumped Water SMES Flywheel Thermal

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  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  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  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 ($1 CAD = $.86 USD)

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

Ontario IESO (July 7, 2009)

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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 Economics  IESO Case Study on July 7, 2009  PriceDeltaPUE = $38.80  (CostPUE / PriceDeltaPUE / CycleLife) ?<? 1  TechCostPUEPDPUECycleLifeLHS  Li+$300/kWh$.0388/kWh  Pump. Hydro$45/kWh$.0388/kWhInf (need 1160)<1

Energy Density

Cost

Lifetime vs Efficiency

Per-cycle Cost

Summary Table Storage Technology Energy Density Cost Self-dischargeRound Trip EfficiencyLifetime Thermal (various media) kWh/m3 $40-65/ kWh 1-2% per day90%Unlimited Flywheel0.2 Wh/kg $300/kWh Minimal80-90%~20 years Compressed Air2 kWh/m3 $1-5/kWh (storage only) None80%Unlimited Superconductin g Magnetic Energy Storage 1-10 Wh/m3 $54,000/kWh None with cooling90-95%Unlimited Pumped Hydro m $10-45/kWh None75%Unlimited NiMH Battery30–80 Wh/kg $364/kWh 30%/month66% cycles NiCad Battery40-60 Wh/kg $400/kWh 20%/month70-90%1500 cycles Lithium Ion Battery 160 Wh/kg $300/kWh 5%/month99.90%1200 cycles Lithum Polymer Battery Wh/kg $500/kWh 10%/month99.50%1000 cycles Lead Acid Battery Wh/kg $ /kWh 3%-4%/month70%-92% cycles

Sample Load Profiles

Marginal revenue potential drops quickly and varies Mild Spring Weekend Day Warm Summer Weekday

Storage power density matters: Small window to buy cheap Mild Spring Weekend Day Warm Summer Weekday 1x Power Density 2x

Buy-low/sell-high cycle rate is limited: must hold for a while

Unexpected arbitrage can create opportunistic profits ($1 CAD = $.86 USD)

Must disentangle residential, commercial, industrial, and night life/party loads Ontario Night Life

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  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