1. Negative Wholesale Power Prices: Why They Occur and What to Do about Them A Study of the German Power Market Maria Woodman, Student Economics Department, New York University

2. Research Motivation: The German Power Market and Negative Wholesale Power Prices Market Anomaly – Electricity doesn’t obey traditional commodity price behaviors – Negative wholesale prices can result Three Causes – Increases in wind infeed when demand is low – Government incentives to favor wind producers – Flat rate prices cause customers to consume electricity regardless of the value of each MW

3. Wind Behavior

4. [ALZ1] [ALZ1] FIX THESE!!!![ALZ1] Power Prices and Wind Generation

5. Power Generation Supply (without Wind) Hydro Nuclear Lignite Coal Bituminous Coal Gas Turbine Wholesale clearing price MW of Capacity Marginal Cost Demand Supply Merit Order Curve Combined Cycle Gas Turbine

6. Nuclear Lignite Coal Bituminous Coal Wholesale clearing price MW of Capacity Marginal Cost Demand Supply – with Wind Shifted Merit Order Curve Combined Cycle Gas Turbine WIND 0 Power Generation Supply (with Wind) Supply – No Wind

7. Increased Wind Infeed An influx of wind power shifts that merit order curve rightward, which drives prices down

8. Flat Rate Retail Prices Retail prices don’t represent a consumers true willingness to pay In the case of negative wholesale prices, they grossly overpay in the retail market. D Retail Market S L P Wholesale Market 0 P L S D D

9. Is Dynamic Pricing the Answer? What is dynamic (“time-of-day”) pricing? – Allows retail prices to match wholesale prices in real time Stimulates a demand side price response How can it impact negative prices ? – The solution isn’t simple An estimated retail demand curve isn’t defined when prices are negative

10. Existing Studies of Dynamic Pricing Studies evaluating the results of implemented programs have returned varied ranges of end-user price response Long Run Elasticity – 0.3-0.5 (Borenstein, 2005) Short Run Industrial End-User Elasticity – 0.01-0.27 (Boisvert, 2007; Neenan, 2004; Braithwait and Sheasy, 2002; Patrick and Wolak, 1997) Using these ranges, the studies focused on the use of dynamic pricing to reduce peak price and load

11. Method for Analyzing RTP Construct wholesale supply and demand curves for a set of hours representing different combinations of demand and wind infeed Construct demand curves representing different levels of price response using differing price elasticities Induce an increase in wind power by shifting the supply curve Solve for the new equilibrium points given the new supply and demand curves

12. Allocation of Hours It was found that a necessary condition for negative prices appeared to be either high wind in-feed ( >12 GW) coupled with moderate system demand (40-50 GW) or low system demand ( <40 GW) coupled with moderate wind in-feed (5-10 GW) (Genoese, 2010). Using these metrics, I was able to disaggregate the hours into their respective buckets for analysis High Wind InfeedLow Wind Infeed High Demand Jan 12 - 7 PM - WeekdayOct 7 - 8 PM - Weekday Wind MW: 12594.75Wind MW: 2361.5 Total Demand: 72826Total Demand: 65847 Low Demand Mar 8 – 9 AM - WeekendMay 17 – 5 AM - Weekend Wind MW: 9914.25Wind MW: 2276 Total Demand 43358Total Demand: 33394 Hours of focus

13. Constructing the Model

14. Preliminary Results For the hour type of low demand and high wind infeed, on average, a price elasticity of at least -0.14 was needed to have a market clearing price of €0.00 – For the case of increased wind generation Following the same logic, a price elasticity of approximately -0.44 was necessary to raise the price to equal the existing retail flat rate price. – The elasticity value is unrealistic given previous estimates of consumer price response

15. Occurrence of Negative Prices WeekdayWeekendGrand Total Early Morning14.08%36.62%50.70% Mid Day2.82%1.41%4.23% Night21.13%23.94%45.07% Grand Total38.03%61.97%100.00% Negative Prices: Hours of Occurrence Of the 1% of hours that were affected in 2009 The vast majority fell during early morning and weekend hours

16. Conclusions RTP may not have a significant effect and in some cases might even be a hindrance to the market. Other demand side management techniques may be more effective in mitigating the market inefficiency of negative prices Additional R&D in electric vehicles, smart grid technology and implementation, and smart appliances could aid in making demand side management viable

17. Thank You! Questions? Maria Woodman, New York University Email: mjw399@nyu.edu