Effects of Tightening Unit-level and System-level Constraints in Unit Commitment

Unit Commitment is an important problem faced by independent system operators. It is usually formulated as a Mixed Binary Linear Programming (MBLP) problem, and is believed to be NP hard. To solve UC problems efficiently, an idea is through formulation tightening. If constraints can be transformed t...

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Veröffentlicht in:IEEE Power & Energy Society General Meeting S. 1 - 5
Hauptverfasser: Yan, Bing, Luh, Peter B., Litvinov, Eugene, Zheng, Tongxin, Schiro, Dane, Bragin, Mikhail A., Zhao, Feng, Zhao, Jinye, Lelic, Izudin
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2019
Schlagworte:
convex hull
Convex hulls
Data preprocessing
formulation tightening
Linear programming
mixed binary linear programming
Power systems
Unit commitment
ISSN:1944-9933
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Zusammenfassung:Unit Commitment is an important problem faced by independent system operators. It is usually formulated as a Mixed Binary Linear Programming (MBLP) problem, and is believed to be NP hard. To solve UC problems efficiently, an idea is through formulation tightening. If constraints can be transformed to directly delineate an MBLP problem's convex hull during data preprocessing, then the problem can be solved by using linear programming methods. The resulting formulation can be reused for other data sets, tremendously reducing computational requirements. To achieve the above goal, both unit- and system-level constraints are tightened with synergistic combination in this paper. Unit-level constraints are tightened based on existing cuts and novel "constraint-and-vertex conversion" and vertex projection processes. To tighten system-level constraints, selected cuts are applied and some potentially powerful cuts are identified. Numerical results demonstrate the effectiveness of tightening unit- and system-level constraints.
ISSN:1944-9933
DOI:10.1109/PESGM40551.2019.8973770