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Robust Unit Commitment With Wind Power and Pumped Storage Hydro
943
Citations
16
References
2011
Year
Distributed Energy SystemUnit CommitmentEngineeringSmart GridEnergy ManagementEnergy OptimizationRenewable Energy StoragePower SystemHydropowerPower System OptimizationSystems EngineeringVirtual Power PlantRobust Optimization ApproachRobust Optimization ModelsRenewable Energy SystemsEnergy System OperationRobust OptimizationPower Systems
Renewable energy penetration creates reliability challenges for grid operators, making system robustness essential as intermittent wind power grows. The study proposes a robust optimization method to generate a cost‑minimizing unit commitment schedule for thermal generators that withstands worst‑case wind power uncertainty. The method models wind uncertainty with an uncertainty set that includes the worst‑case scenario and introduces a conservatism‑control variable to balance protection and cost. The approach improves reliability by accounting for worst‑case wind scenarios and reduces total cost substantially through the inclusion of pumped‑storage units.
As renewable energy increasingly penetrates into power grid systems, new challenges arise for system operators to keep the systems reliable under uncertain circumstances, while ensuring high utilization of renewable energy. With the naturally intermittent renewable energy, such as wind energy, playing more important roles, system robustness becomes a must. In this paper, we propose a robust optimization approach to accommodate wind output uncertainty, with the objective of providing a robust unit commitment schedule for the thermal generators in the day-ahead market that minimizes the total cost under the worst wind power output scenario. Robust optimization models the randomness using an uncertainty set which includes the worst-case scenario, and protects this scenario under the minimal increment of costs. In our approach, the power system will be more reliable because the worst-case scenario has been considered. In addition, we introduce a variable to control the conservatism of our model, by which we can avoid over-protection. By considering pumped-storage units, the total cost is reduced significantly.
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