Abstract
This paper proposes algorithm, defining the dynamic transformer rating (DTR) for maximization of energy transfer through oil-immersed transformer. Algorithm ensures that windings temperature and loss of insulation life do not exceed their permissible limits. To achieve this goal, we use receding horizon control. Receding horizon control considers load and ambient temperature at past and future intervals to update the DTR. Proposed algorithm is intended for application in real-time economic dispatch at balancing market where it could allow the decreasing of energy generation cost. We consider a two-machine power system as case study, where cheap generation is constrained by transformer rating. The expensive generation does not have any network constraints. The algorithm application increased the cheap generation by 12% in comparison with static thermal limit and by 3% in comparison with static thermal limit corrected to ambient temperature. The generation rescheduling, allowed by DTR, decreased the energy generation cost by 27.9% and 9.8% correspondingly.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE Milan PowerTech, PowerTech 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538647226 |
| DOIs | |
| Publication status | Published - 1 Jun 2019 |
| Event | 2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italy Duration: 23 Jun 2019 → 27 Jun 2019 |
Publication series
| Name | 2019 IEEE Milan PowerTech, PowerTech 2019 |
|---|
Conference
| Conference | 2019 IEEE Milan PowerTech, PowerTech 2019 |
|---|---|
| Country | Italy |
| City | Milan |
| Period | 23.6.19 → 27.6.19 |
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Keywords
- Balancing market
- Dynamic transformer rating
- Economic dispatch
- Receding Horizon Control
- Transformer thermal model
ASJC Scopus subject areas
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Safety, Risk, Reliability and Quality
Cite this
Receding horizon algorithm for dynamic transformer rating and its application for real-time economic dispatch. / Daminov, Ildar; Prokhorov, Anton; Caire, Raphael; Alvarez-Herault, Marie Cecile.
2019 IEEE Milan PowerTech, PowerTech 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8810511 (2019 IEEE Milan PowerTech, PowerTech 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Receding horizon algorithm for dynamic transformer rating and its application for real-time economic dispatch
AU - Daminov, Ildar
AU - Prokhorov, Anton
AU - Caire, Raphael
AU - Alvarez-Herault, Marie Cecile
PY - 2019/6/1
Y1 - 2019/6/1
N2 - This paper proposes algorithm, defining the dynamic transformer rating (DTR) for maximization of energy transfer through oil-immersed transformer. Algorithm ensures that windings temperature and loss of insulation life do not exceed their permissible limits. To achieve this goal, we use receding horizon control. Receding horizon control considers load and ambient temperature at past and future intervals to update the DTR. Proposed algorithm is intended for application in real-time economic dispatch at balancing market where it could allow the decreasing of energy generation cost. We consider a two-machine power system as case study, where cheap generation is constrained by transformer rating. The expensive generation does not have any network constraints. The algorithm application increased the cheap generation by 12% in comparison with static thermal limit and by 3% in comparison with static thermal limit corrected to ambient temperature. The generation rescheduling, allowed by DTR, decreased the energy generation cost by 27.9% and 9.8% correspondingly.
AB - This paper proposes algorithm, defining the dynamic transformer rating (DTR) for maximization of energy transfer through oil-immersed transformer. Algorithm ensures that windings temperature and loss of insulation life do not exceed their permissible limits. To achieve this goal, we use receding horizon control. Receding horizon control considers load and ambient temperature at past and future intervals to update the DTR. Proposed algorithm is intended for application in real-time economic dispatch at balancing market where it could allow the decreasing of energy generation cost. We consider a two-machine power system as case study, where cheap generation is constrained by transformer rating. The expensive generation does not have any network constraints. The algorithm application increased the cheap generation by 12% in comparison with static thermal limit and by 3% in comparison with static thermal limit corrected to ambient temperature. The generation rescheduling, allowed by DTR, decreased the energy generation cost by 27.9% and 9.8% correspondingly.
KW - Balancing market
KW - Dynamic transformer rating
KW - Economic dispatch
KW - Receding Horizon Control
KW - Transformer thermal model
UR - http://www.scopus.com/inward/record.url?scp=85072312147&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072312147&partnerID=8YFLogxK
U2 - 10.1109/PTC.2019.8810511
DO - 10.1109/PTC.2019.8810511
M3 - Conference contribution
AN - SCOPUS:85072312147
T3 - 2019 IEEE Milan PowerTech, PowerTech 2019
BT - 2019 IEEE Milan PowerTech, PowerTech 2019
PB - Institute of Electrical and Electronics Engineers Inc.
ER -