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A Lagrangian relaxa...
A Lagrangian relaxation approach to an electricity system investment model with a high temporal resolution
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- Granfeldt, Caroline, 1991 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences
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- Strömberg, Ann-Brith, 1961 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences
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- Göransson, Lisa, 1982 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2023
- 2023
- Engelska.
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Ingår i: OR Spectrum. - 1436-6304 .- 0171-6468. ; 45:4, s. 1263-1294
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The global production of electricity contributes significantly to the release of carbon dioxide emissions. Therefore, a transformation of the electricity system is of vital importance in order to restrict global warming. This paper proposes a modelling methodology for electricity systems with a large share of variable renewable electricity generation, such as wind and solar power. The model developed addresses the capacity expansion problem, i.e. identifying optimal long-term investments in the electricity system. Optimal investments are defined by minimum investment and production costs under electricity production constraints—having different spatial resolutions and technical detail—while meeting the electricity demand. Our model is able to capture a range of strategies to manage variations and to facilitate the integration of variable renewable electricity; it is very large due to the high temporal resolution required to capture the variations in wind and solar power production and the chronological time representation needed to model energy storage. Moreover, the model can be further extended—making it even larger—to capture a large geographical scope, accounting for the trade of electricity between regions with different conditions for wind and solar power. Models of this nature thus typically need to be solved using some decomposition method to reduce solution times. In this paper, we develop a decomposition method using so-called variable splitting and Lagrangian relaxation; the dual problem is solved by a deflected subgradient algorithm. Our decomposition regards the temporal resolution by defining 2-week periods throughout the year and relaxing the overlapping constraints. The method is tested and evaluated on some real-world cases containing regions with different energy mixes and conditions for wind power. Numerical results show shorter computation times as compared with the non-decomposed model, and capacity investment options similar to the optimal solution provided by the latter model.
Ämnesord
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Energisystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Energy Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Nyckelord
- Lagrangian relaxation
- cost optimization
- wind power integration
- variable renewable electricity
- variation management
- variable splitting
- electricity system modelling
- long-term investment models
- solar power integration
- Cost optimization
- Electricity system modelling
- Lagrangian relaxation
- Long-term investment models
- Solar power integration
- Variable renewable electricity
- Variable splitting
- Variation management
- Wind power integration
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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