论文标题
通过在线反馈优化为电力系统实时治疗动作
Real-time Curative Actions for Power Systems via Online Feedback Optimization
论文作者
论文摘要
治愈性或补救措施是旨在将电网带到意外事件后的安全操作点的一系列即时动作。这些行动的有效性对于保证治愈性N-1安全至关重要。如今，基于预期的未来网格状态，提前提取了治愈的动作。由于从稳定到挥发性的能源的转变，网格状态将经常发生变化，并且需要越来越多地预先计划。此外，随着从大量生产到许多小型分散能源的转变，需要同时启动更多设备以实现相同的结果。我们建议在发生意外情况后实时计算这些复杂的治疗作用，而不是预先计划。我们展示了如何非常适合此任务的在线反馈优化方法（OFO）。作为对这些功能的初步演示，我们使用了一个（OFO）控制器，在故障后，降低了断路器上的电压差，以使操作员能够重新下降。该测试案例的灵感来自2003年瑞士 - 意大利停电，该停电是由相对较小的事件引起的，随后是无效的治疗作用。 最后，我们识别并讨论了一些开放问题，包括闭环稳定性和模型不匹配的鲁棒性。
Curative or remedial actions are the set of immediate actions intended to bring the power grid to a safe operating point after a contingency. The effectiveness of these actions is essential to guarantee curative N-1 security. Nowadays, curative actions are derived ahead of time, based on the anticipated future grid state. Due to the shift from steady to volatile energy resources, the grid state will frequently change and the curative actions would need to be pre-planned increasingly often. Furthermore, with the shift from large bulk production to many small decentralized energy sources more devices need to be actuated simultaneously to achieve the same outcome. Instead of pre-planning, we propose to calculate these complex curative actions in real-time after the occurrence of a contingency. We show how the method of Online Feedback Optimization (OFO) is well suited for this task. As a preliminary demonstration of these capabilities, we use an (OFO) controller, that after a fault, reduces the voltage difference over a breaker to enable the operators to reclose it. This test case is inspired by the 2003 Swiss-Italian blackout, which was caused by a relatively minor incident followed by ineffective curative actions. Finally, we identify and discuss some open questions, including closed-loop stability and robustness to model mismatch.
