Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 109-115 |
| Number of pages | 7 |
| Journal | Journal of Advanced Computational Intelligence and Intelligent Informatics |
| Volume | 17 |
| Issue number | 1 |
| Publication status | Published - 2013 Jan |
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Keywords
- Frequency regulation
- Plug-in electric vehicle
- Trade-off analysis
- Unit commitment
- Wind power
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
Cite this
Thermal unit scheduling for CO2 reduction including wind power and electric vehicles. / Yamashita, Daiki; Yokoyama, Ryuichi; Niimura, Takahide.
In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 17, No. 1, 01.2013, p. 109-115.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Thermal unit scheduling for CO2 reduction including wind power and electric vehicles
AU - Yamashita, Daiki
AU - Yokoyama, Ryuichi
AU - Niimura, Takahide
PY - 2013/1
Y1 - 2013/1
N2 - 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.
AB - 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.
KW - Frequency regulation
KW - Plug-in electric vehicle
KW - Trade-off analysis
KW - Unit commitment
KW - Wind power
UR - http://www.scopus.com/inward/record.url?scp=84879435552&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84879435552&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84879435552
VL - 17
SP - 109
EP - 115
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
SN - 1343-0130
IS - 1
ER -