发表机构
Oak Ridge National Laboratory（橡树岭国家实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对电网约束下大规模本地机组组合问题，提出扩展的松弛-取整机组组合（RRUC）方法，在满足时空MVA约束下快速求得低成本解，运行时间随节点数次二次方增长，性能远超现有求解器。
AI 中文摘要
美国知识经济的近期发展带来了数据中心负荷的显著增长，这对发电产生了两个主要影响。首先，为补偿负荷增长，数据中心被鼓励自带发电机组。其次，为寻找剩余可调度发电资源，公用事业公司正日益转向次输电和配电层面的发电资产。加之负荷增加及由此导致的电网运行条件趋紧，这两种趋势都可能产生在电网约束下对大量本地化发电机组进行机组组合的需求。我们提出了一种松弛-取整机组组合（RRUC）的扩展方法，该方法能够在满足跨时段和空间MVA约束的同时，比传统方法更快地解决更大规模问题的机组组合。我们使用从100到20,000个节点的合成拥塞测试系统展示了RRUC的性能。RRUC始终能找到低成本解，且与问题规模无关，其运行时间随节点数呈次二次方增长。RRUC能在不到1秒内求解100节点系统，在7分钟内求解20,000节点系统。相比之下，一个领先的最先进求解器在15分钟内无法找到100节点系统的可行解。
英文摘要
Recent developments in the US knowledge economy have created a significant growth in datacenter loads, with two major consequences for power generation. First, to compensate for growth in load, datacenters are encouraged to bring their own generating units. Second, in search of the remaining pools of dispatchable generation, utilities are increasingly turning to subtransmission and distribution level generating assets. Coupled with increasing loads and the resulting tighter grid conditions, both trends are likely to create a need to commit a large number of localized generating units under grid constraints. We propose an extension of Relax-and- Round Unit Commitment (RRUC) that is capable of committing generating units for larger problems faster than conventional methods, while staying within intertemporal and spatial MVA constraints. We demonstrate the performance of RRUC using synthetic congestible test systems ranging from 100 to 20,000 buses. RRUC consistently finds low cost solutions, independent of the problem size, and its run time increases sub-quadratically in the number of buses. RRUC can solve the 100 bus system in less than a second and the 20,000 bus system 7 minutes. In contrast, a leading state of the art solver cannot find a feasible solution to the 100 bus system in 15 minutes.
Comments10 pages, 12 figures
