The rapid growth of data centers increasingly requires data center operators to "bring own generation" to complement the available utility power plants to supply all or part of data center load. This practice sharply increases the number of generators on the bulk power system and shifts operational focus toward fuel costs rather than traditional startup and runtime constraints. Conventional mixed-integer unit commitment formulations are not well suited for systems with thousands of flexible, fast-cycling units. We propose a unit commitment formulation that relaxes binary commitment decisions by allowing generators to be fractionally on, enabling the use of algorithms for continuous solvers. We then use a rounding approach to get a feasible unit commitment. For a 276-unit system, solution time decreases from 10 hours to less than a second, with no accuracy degradation. Our approach scales with no issues to tens of thousands of generators, which allows solving problems on the scale of the major North America interconnections. The bulk of computation is parallel and GPU compatible, enabling further acceleration in future work.

翻译：数据中心的快速增长日益要求运营商"引入自有发电"以补充现有公用发电厂，从而全部或部分满足数据中心负荷需求。这种做法显著增加了大容量电力系统中的发电机数量，并将运行重点从传统的启停与运行约束转向燃料成本。传统的混合整数机组组合模型不适用于包含数千台灵活、快速循环机组的大规模系统。我们提出一种机组组合模型，通过允许发电机以分数形式运行来松弛二元启停决策，从而能够采用连续求解器算法。随后使用取整方法获得可行的机组组合方案。针对包含276台机组的系统，求解时间从10小时缩短至不足1秒，且精度无损失。本方法可无缝扩展至数万台发电机规模，能够求解北美主要互联电网级别的超大规模问题。计算主体部分支持并行处理且与GPU兼容，为未来进一步加速提供了可能。