In this paper, we present a method to determine unit commitment schedules, while considering CO2 emissions and costs along with the frequency regulation capability of the units, in order tomitigate fluctuations in wind power. We developed an extended procedure that obtains a trade-off solution of cost versus CO2 emissions, including a significant wind power penetration, and developed Plug-in Electric Vehicles (PEVs) as additional reserves. The proposed method was tested on a 10-unit, 24-hour model system using the estimated wind power curve derived from an actual wind farm. The results, such as shadow prices of CO2 obtained using the trade-off analysis, may provide a basis of evaluating the equivalent cost of wind farms and PEVs, and their contributions to CO2 reduction.
|ジャーナル||Journal of Advanced Computational Intelligence and Intelligent Informatics|
|出版ステータス||Published - 2013 1|
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Human-Computer Interaction