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Robust Approximate Dynamic Programming for Large-Scale Unit Commitment With Energy Storages
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DOI：10.1109/TASE.2023.3342054.png)
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Abstract
En 中文
The robust unit commitment (UC) is of paramount importance for achieving reliable operations considering the uncertainty of renewable realizations. The typical affine decision rule method and the robust feasible region method may achieve uneconomic dispatches as the dispatch decisions just rely on the current-stage information. Through approximating the future cost-to-go functions, the dual dynamic programming based methods have been shown adaptive to the multistage robust optimization problems, while suffering from high computational complexity. Thus, we propose the robust approximate dynamic programming (RADP) method to promote the computational speed and the economic performance for large-scale robust UC problems. RADP initializes the candidate points for guaranteeing the feasibility of upper bounding the value functions, solves the alternating calculation based bilinear programming to obtain the worst cases, and combines the primal and dual updates for the two-phase robust UC decision-making problem to achieve fast convergence. The finite termination guarantee of the RADP method is verified by the analyses for the multistage robust optimization problems with achieving suboptimal solutions. Numerical tests on 118-bus and 2383-bus transmission systems have demonstrated that RADP can approach the suboptimal economic performance at significantly improved computational efficiency.
Keywords:
Robust unit commitment
feasible upper bounding
robust approximate dynamic programming
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