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：我们提出了一种新型机组组合（UC）计算方法，该方法无需线性化近似，且相较于当前最先进技术可实现数个数量级的性能提升。该性能提升通过引入针对UC问题量身定制的启发式算法实现。该方法可基于现有连续优化求解器实现，并适配不同应用场景。我们通过当前最先进工具无法胜任的大规模高级UC分析案例，验证了新方法的实用价值。我们预期本文展示的能力对于应对新兴电力系统挑战至关重要，这些挑战包括数据中心等具有更强波动性的大型负荷，以及由更多数量小型机组（含大量表后发电）构成的电源结构。