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Solving Storage-Integrated Long-Term Unit Commitment With Guaranteed Bounds on Sub-Optimality
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DOI：10.1109/TPWRS.2025.3638908.png)
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Abstract
En 中文
Long-term unit commitment (LTUC) plays an important role in power system planning and production simulation, especially when seasonal volatility of renewable generation and ultra-long-term energy storage are taken into account. Solving LTUC exactly is challenging due to the large number of binary variables. This paper proposes a tractable method to obtain a near-optimal solution to LTUC with a guaranteed bound on its sub-optimality. The proposed method first constructs a lower bound by formulating a relaxed unit commitment (UC) problem in which binary variables are replaced by continuous ones, and a family of valid inequalities is introduced to strengthen the relaxation. A general framework for generating such inequalities is developed by exploiting the specific structural properties of single-unit operational constraints. Subsequently, by fixing the seasonal energy storage levels at the optimal solution of the relaxed UC problem, a feasible LTUC solution is constructed through sequential short-term UC optimization with look-ahead augmentation, which provides an upper bound for the true optimum. The sub-optimality is measured by the gap between the lower and upper bounds. Numerical tests demonstrate that the monthly or annual UC problems of practically-sized power systems can be solved on a laptop in hours with an optimality gap of less than 1.5%.
Keywords:
Long-term unit commitment
valid inequality
optimality gap
energy storage
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