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Understanding the Benefits of Dynamic Line Rating under Multiple Sources of Uncertainty
- Source :
- IEEE Transactions on Power Systems, IEEE Transactions on Power Systems, Institute of Electrical and Electronics Engineers, 2018, 33 (3), pp.3306-3314. 〈10.1109/TPWRS.2017.2786470〉, IEEE Transactions on Power Systems, Institute of Electrical and Electronics Engineers, 2018, 33 (3), pp.3306-3314. ⟨10.1109/TPWRS.2017.2786470⟩
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- International audience; This paper analyses the benefits of dynamic line rating (DLR) in the system with high penetration of wind generation. A probabilistic forecasting model for the line ratings is incorporated into a two-stage stochastic optimization model. The scheduling model, for the first time, considers the uncertainty associated with wind generation, line ratings and line outages to co-optimize the energy production and reserve holding levels in the scheduling stage as well as the re-dispatch actions in the real-time operation stage. Therefore, the benefits of higher utilization of line capacity can be explicitly balanced against the costs of increased holding and utilization of reserve services due to the forecasting error. The computational burden driven by the modelling of multiple sources of uncertainty is tackled by applying an efficient filtering approach. The case studies demonstrate the benefits of DLR in supporting costeffective integration of high penetration of wind generation into the existing network. We also highlight the importance of simultaneously considering the multiple sources of uncertainty in understanding the benefits of DLR. Furthermore, this paper analyses the impact of different operational strategies, the coordination among multiple flexible technologies and installed capacity of wind generation on the benefits of DLR.
- Subjects :
- Technology
Operations research
Computer science
020209 energy
Scheduling (production processes)
Energy Engineering and Power Technology
UNIT COMMITMENT
02 engineering and technology
7. Clean energy
Dynamic line rating
stochastic programming
Engineering
Power system simulation
[SPI.ENERG]Engineering Sciences [physics]/domain_spi.energ
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
probabilistic forecasting
wind generation
[ SPI.ENERG ] Engineering Sciences [physics]/domain_spi.energ
Science & Technology
Energy
Wind power
business.industry
0906 Electrical And Electronic Engineering
Engineering, Electrical & Electronic
Stochastic programming
Nameplate capacity
13. Climate action
Index Terms—Dynamic line rating
Stochastic optimization
Probabilistic forecasting
business
Subjects
Details
- Language :
- English
- ISSN :
- 08858950
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Power Systems, IEEE Transactions on Power Systems, Institute of Electrical and Electronics Engineers, 2018, 33 (3), pp.3306-3314. 〈10.1109/TPWRS.2017.2786470〉, IEEE Transactions on Power Systems, Institute of Electrical and Electronics Engineers, 2018, 33 (3), pp.3306-3314. ⟨10.1109/TPWRS.2017.2786470⟩
- Accession number :
- edsair.doi.dedup.....9fdcebdf8645d25172a52f665586e7cb
- Full Text :
- https://doi.org/10.1109/TPWRS.2017.2786470〉