LAPSE:2019.0801
Published Article
LAPSE:2019.0801
Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration
Ilias G. Marneris, Pandelis N. Biskas, Anastasios G. Bakirtzis
July 26, 2019
The uncertain and variable nature of renewable energy sources in modern power systems raises significant challenges in achieving the dual objective of reliable and economically efficient system operation. To address these challenges, advanced scheduling strategies have evolved during the past years, including the co-optimization of energy and reserves under deterministic or stochastic Unit Commitment (UC) modeling frameworks. This paper presents different deterministic and stochastic day-ahead UC formulations, with focus on the determination, allocation and deployment of reserves. An explicit distinction is proposed between the uncertainty and the variability reserve, capturing the twofold nature of renewable generation. The concept of multi-timing scheduling is proposed and applied in all UC policies, which allows for the optimal procurement of such reserves based on intra-hourly (real-time) intervals, when concurrently optimizing energy and commitments over hourly intervals. The day-ahead scheduling results are tested against different real-time dispatch regimes, with none or limited look-ahead capability, or with the use of the variability reserve, utilizing a modified version of the Greek power system. The results demonstrate the enhanced reliability achieved by applying the multi-timing scheduling concept and explicitly considering the variability reserve, and certain features regarding the allocation and deployment of reserves are discussed.
Keywords
deterministic programming, multi-timing scheduling, real-time dispatch, stochastic programming, uncertainty reserve, variability reserve, wind integration
Suggested Citation
Marneris IG, Biskas PN, Bakirtzis AG. Stochastic and Deterministic Unit Commitment Considering Uncertainty and Variability Reserves for High Renewable Integration. (2019). LAPSE:2019.0801
Author Affiliations
Marneris IG: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Biskas PN: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Bakirtzis AG: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece [ORCID]
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Journal Name
Energies
Volume
10
Issue
1
Article Number
E140
Year
2017
Publication Date
2017-01-23
Published Version
ISSN
1996-1073
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Original Submission
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PII: en10010140, Publication Type: Journal Article
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LAPSE:2019.0801
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doi:10.3390/en10010140
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Jul 26, 2019
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CC BY 4.0
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Jul 26, 2019
 
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Calvin Tsay
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