Speaker: Yang Yu Stanford University
Time: 2016-03-17 14:00-2016-03-17 15:00
Venue: FIT 1-222

Abstract:

Smart grid requires system-perspective-based data analytics to understand new technologies’ system impacts and associated market design. By modeling the interaction of wind energy’s intermittence and system operation, we reveal the incompatibility between the new technologies, old system operations, and climate-change policies. Our results suggest the incompatibility will weaken wind energy’s ability to reduce Greenhouse Gases and threat the efficiency of a carbon tax. We suggest that market regulators must reexamine the current market design and policy settings based on system-perspective-based data analysis. For example, we develop a criteria system to help market operators use wind-energy and market data to select an appropriate dispatch protocol. The criteria system is deduced by modeling the system dynamics of adopting different dispatch protocols to integrate wind energy into a power grid. An empirical study, which is calibrated according to the data from the Electric Reliability Council of Texas (ERCOT) market, confirms the effectiveness of the criteria system for dispatch protocol selection. By using the criteria system to adjusting the dispatch protocol, wind energy’s capability to reduce CO2 is improved by 30% in the ERCOT market. We also demonstrate that the stochastic dispatch must replace the static dispatch, which is currently used in most electricity markets, once a carbon tax is implemented. Actually, if a $6/ton carbon tax is implemented in the Texas market operated according to the stochastic protocol, the CO2 emission is similar to the emission level from the same market with a $16/ton carbon tax operated according to the static protocol. Correspondingly, the $16/ton carbon tax associated with the static protocol costs 42.6% more than the $6/ton carbon tax associated with the stochastic protocol.

Short Bio:

Yang Yu is a Ph.D. Candidate in Stanford University. He focuses on environment and energy system by adopting, combining, and developing tools from data analytics, optimization, and economics. His Ph.D. study examines the incompatibility between renewable-energy technologies, the current market design, and climate change policies. He won the “Dennis J. O'Brien USAEE/IAEE Best Student Paper Award” from the United States Associate for Energy Economics/International Association for Energy Economics in 2015 for his research on wind power producer’s cost structure and market power. He also was awarded the “2015 IAEE Annual Meeting Best Student Paper” for his research on the conflict between renewable-energy policies and transmission congestion policies.