基于数据驱动逻辑回归的孤岛电力系统鲁棒频率约束机组组合
Robust Frequency Constrained UC Using Data Driven Logistic Regression for Island Power Systems
AI总结：
本文针对孤岛电力系统频率响应稀缺问题，提出基于逻辑回归的数据驱动线性频率约束，并结合自适应鲁棒机组组合，在拉帕尔马岛系统中验证其可同时改善频率质量并降低运行成本。
摘要：
在当前的短期电力调度实践中，在线功率备用被用于应对发电不匹配和突发事件。调度过程中既不考虑在线惯量，也不考虑已投运机组的速度。随着不确定可再生能源注入量的不断增加，这种做法开始显得力不从心，尤其是在孤岛电力系统中，一次频率响应本就稀缺，任何突发事件都可能导致较差的频率响应。本文引入一种数据驱动的线性约束，以改善孤岛电力系统故障后的频率质量。通过模拟单一断线故障的系统频率响应，获得一个连贯的初始数据集。然后采用逻辑回归作为预测分析方法，以区分可接受和不可接受的事件。为了将传统方法与所提方法进行比较，并处理可再生能源发电的不确定特性，采用了一种自适应鲁棒机组组合公式。拉帕尔马岛电力系统的结果表明，根据逻辑回归估计中所选的切点，所提方法能够在改善系统频率响应质量的同时降低运行成本。
英文摘要：
In the current practice of short-term power scheduling, online power reserves are used to address generation mismatches and contingencies. Neither online inertia nor the speed of the committed units is considered in the scheduling process. With the increasing injection of uncertain renewable energy sources, this practice is starting to fall short especially in island power systems, where the primary frequency response is already scarce, and any contingency leads to potentially poor frequency response. This paper introduces a data driven linear constraint to improve the post-fault frequency quality in island power systems. A coherent initial data-set is obtained by simulating the system frequency response of single outages. Then logistic regression is employed as a predictive analytic procedure to differentiate the acceptable and unacceptable incidents. To compare the conventional methods with the proposed approach and also to handle the uncertain nature of renewable energy generation, an adaptive robust unit commitment formulation is utilized. Results for the island power system of La Palma show that depending on the chosen cut-point on the logistic regression estimation the proposed method can improve the frequency response quality of the system while reducing the operation costs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
