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Redesigning Electricity Markets to Manage Variability in Wind Power

Many countries have set ambitious goals for renewable energy integration. In his 2011 State of the Union address, US President Obama set a target of serving 80% of the Country痴 electricity demand from clean resources by 2035. California has set a target of 33% renewable energy penetration by 2020. Wind power will play a key role in realizing such aggressive targets. However, unlike conventional generation (e.g., coal, nuclear, natural gas), wind power is inherently variable. It is non-dispatchable, highly intermittent, and difficult to forecast on horizons exceeding 15 minutes. To manage the attending variability in production, the system operator (SO) schedules conservative reserve margins whose cost is socialized among load serving entities and ultimately passed on to consumers. If we maintain the current approach to wind integration, we argue that the associated cost of variability will become unsupportable at levels of deep penetration.

In this talk, we値l discuss why conventional market designs and generation dispatch procedures lead to over-procurement of reserve capacity when managing quantity risk in wind power and suggest various alternatives to the modus operandi that attenuate reserve costs. I値l advocate the addition of intra-day markets (spanning day-ahead and real-time) as a means for the SO to more effectively balance quantity risk and reserve costs by leveraging on decreasing prediction horizons to incrementally procure reserve capacity in sequence of forward markets. The incremental reserve purchasing policy is derived in closed form as a solution to a stochastic optimal control problem and is shown to have a threshold structure. Additionally, I値l present several numerical examples that demonstrate the value of intra-day markets in reducing the aggregate cost of procured reserve capacity.

In part two of the talk, I値l suggest a more radical transformation of electricity markets to allow for price-differentiation of quality of supply. Namely, package random wind power into electricity with different levels of reliability and sell them at different prices. Such a variable-reliability market for wind requires no reserve capacity, as the risk of insufficient wind power is borne by the consumers who purchase lower cost, less reliable electricity. However, we have to think of electricity differently.

Type of Seminar:
IfA Seminar
Dr. Eilyan Bitar
Department of Computer Science, California Institute of Technology
Oct 25, 2011   17:15

LFV E 41, Schmelzbergstrasse 7
Contact Person:

John Lygeros
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Biographical Sketch:
Eilyan Bitar is currently a Visiting Assistant Professor in the School of Electrical and Computer Engineering at Cornell University. Concurrently, for the 2011-2012 academic year, he値l be engaged as a Postdoctoral Fellow at both the California Institute of Technology and the University of California, Berkeley in the schools of Electrical Engineering and Computer Science. He received both his Ph.D. (2011) and B.S. (2006) from the University of California, Berkeley in Mechanical Engineering. His current research centers on the development of tools for stochastic systems, control, and optimization theory with applications to power systems engineering and economics. In particular, his work aims to address the challenge of achieving deep integration of renewable energy into the electric grid by rethinking the way the grid is architected, operated, and protected. Areas of focus are: novel market design and risk management, demand-side resource aggregation and control, renewable resource aggregation, and wind modeling and forecasting.