Multi-Area Reserve Dimensioning Using Chance-Constrained Optimization

We propose a chance-constrained formulation for the problem of dimensioning frequency restoration reserves on a power transmission network. We cast our problem as a two-stage stochastic mixed integer linear program, and propose a heuristic algorithm for solving the problem. Our model accounts for th...

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Bibliographic Details
Published in:IEEE transactions on power systems 2022-09, Vol.37 (5), p.3982-3994
Main Authors: Papavasiliou, Anthony, Bouso, Alberte, Apelfrojd, Senad, Wik, Ellika, Gueuning, Thomas, Langer, Yves
Format: Article
Language:English
Subjects:
Algorithms
Chance constraints
Europe
Frequency control
Heuristic methods
Integer programming
Mixed integer
multi-area reserve sizing
Optimization
Power system reliability
probabilistic constraints
probabilistic dimensioning
Probabilistic logic
Real-time systems
Reliability
reserve deliverability
reserve requirements
Reserves
Restoration
Sizing
Uncertainty
Zonal flow (meteorology)
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Summary:We propose a chance-constrained formulation for the problem of dimensioning frequency restoration reserves on a power transmission network. We cast our problem as a two-stage stochastic mixed integer linear program, and propose a heuristic algorithm for solving the problem. Our model accounts for the simultaneous sizing of both upward and downward reserves, and uncertainty driven by imbalances, contingencies and available transmission capacity. Our core methodology is further adapted in order to minimize inter-zonal flows and in order to split reserve requirements between automatic and manual frequency restoration reserves. We apply our methodology to the problem of sizing reserves in the four load frequency control areas of the Swedish power system. We demonstrate the benefits of our method in terms of decreasing reserve requirements in the absence of reserve sharing, we analyze the spatial allocation of reserves, and we perform various sensitivity analyses.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2021.3133102