We propose a novel computational method for unit commitment UC, which does not require linearized approximation and provides several orders of magnitude performance improvement over current state-of-the-art. The performance improvement is achieved by introducing a heuristic tailored for UC problems. The method can be implemented using existing continuous optimization solvers and adapted for different applications. We demonstrate value of the new method in examples of advanced UC analyses at the scale where use of current state-of-the-art tools is infeasible. We expect that the capability demonstrated in this paper will be critical to address emerging power systems challenges with more volatile large loads, such as data centers, and generation that is composed of larger number of smaller units, including significant behind-the-meter generation.

翻译：我们提出一种用于机组组合（UC）的新型计算方法，该方法无需线性化近似，且相比当前最优技术可实现数个数量级的性能提升。性能提升源于针对机组组合问题设计的启发式策略。该方法可通过现有的连续优化求解器实现，并能根据不同应用场景进行调整。在现有最优工具难以处理的规模下，我们通过先进机组组合分析实例验证了该新方法的实用价值。我们预期，本文所展示的能力对于应对新兴电力系统挑战至关重要，这些挑战包括更易波动的超大负荷（如数据中心）、以及由大量小型机组（含显著的表后发电）构成的发电组合。