Fault detection based on k-nearest neighbor (FD-kNN) is one of the most widespread fault detection techniques for industrial processes under complex working conditions, owing to its characteristic of local modeling. However, its state separation ability tends to worsen when the operating data is heterogeneous distribution. To tackle this challenge, a weighted k-nearest neighbor fault detection method based on multistep index and dynamic neighbor scale is proposed. The multistep nearest neighbor index is defined to evaluate the state separation ability, and a weighted k-nearest neighbor fault detection framework is formed by the assigned weights obtained from kernel principal component analysis. On the basis above, a dynamic neighborhood scale correction method and a dynamic threshold setting strategy are proposed to deal with the heterogeneous distribution of operating data and track the abrupt change of the operation state. 10 common faults of wind turbines with complex operation conditions are used to verify the effectiveness of the proposed method.
Aiming at the problems of insufficient power system regulation capacity and lack of flexible resources caused by source-load uncertainty, the flexible resource planning of power systems is studied with the goal of improving flexibility. Uncertainty and flexibility are combined in this article, and a probability index of an insufficiently flexible supply-demand ratio is proposed based on the probability characteristics of flexibility. A bi-level programming model of power system flexibility resources considering the probability of an insufficiently flexible supply demand ratio is constructed. Optimal economics is used as the objective function of the planning layer, and the proposed minimum probability index of the flexible supply-demand ratio is used as the objective function of the operations layer. Economics and flexibility are studied, taking the power system in a certain area in Northeast China as the research object. A flexible resource planning scheme that meets different flexibility expectations is obtained, and the scheme is discussed in detail from the aspects of system flexibility, economic cost, and new energy consumption capacity. The effectiveness of quantitative indicators and planning methods are verified.
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