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Applicability of a Clustered Unit Commitment Model in Power System Modeling
- Source :
- IEEE Transactions on Power Systems. 33:2195-2204
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- Clustered unit commitment (CUC) formulations have been proposed to provide accurate and fast approximations to the unit commitment (UC) problem. In these formulations, identical or similar plants are grouped into clusters. This way, the binary commitment variables of all the plants within a cluster can be replaced by a single integer variable. This approach has recently been mainly used for tractably integrating flexibility constraints in generation expansion planning problems. However, a thorough general validation is still missing. In addition, these formulations do not provide commitment schedules on a plant-by-plant level and hence cannot be used directly for operating actual systems or markets. A first contribution of this paper is to show that errors can be introduced both due to the problem formulation and the grouping of non-identical units. A case study is presented in which these errors are quantified under different conditions. Overall, the error in approximating the total cost does not exceed 0.06%. A second contribution of this paper is the development of a hybrid approach which sequentially uses a CUC and a traditional UC model. This approach allows to reduce the computational cost of solving the UC problem while providing a guaranteed feasible and near optimal solution. ispartof: IEEE Transactions on Power Systems vol:33 issue:2 pages:2195-2204 status: published
- Subjects :
- Clustered Unit Commitment
Flexibility (engineering)
Engineering
Mathematical optimization
business.industry
Total cost
020209 energy
Long-term planning
Energy Engineering and Power Technology
Binary number
02 engineering and technology
Unit Commitment
Electric power system
Variable (computer science)
Power system simulation
0202 electrical engineering, electronic engineering, information engineering
Cluster (physics)
Electrical and Electronic Engineering
business
Integer (computer science)
Subjects
Details
- ISSN :
- 15580679 and 08858950
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Power Systems
- Accession number :
- edsair.doi.dedup.....3a987cf5f1fc1b16e85b009731b72fa8