Coded Quickest Classification for Power Quality Events in Smart Grids

• Main Authors: Chien-Chi Liu, 劉建志
• Other Authors: Shih-Chun Lin
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/m3s5k6

碩士 === 國立臺灣科技大學 === 電子工程系 === 105 === The goal of smart grid is to develop a more reliable, secure, and environmentally friendly power grid. Unfortunately, power quality (PQ) events are much easier to happen due to unstable renewable energy sources in smart grids. We thus focus on the quickest change detection of multiple PQ events, which aims to minimize the detection delays and error probabilities of classifying more than two hypotheses. A group of smart meters in grid is used, where each meter transmits its local decision to a fusion center for making final decisions. For energy saving, the bandwidth between each meter and the fusion center is limited to be one bit. Moreover, some meters may be faulty and misleading the finial decision. To combat these faulty meters under limited bandwidth, a code-based framework for quickest detection is proposed. Our contribution is two-fold. First, new local decision rule based on stochastic ordering theory is proposed, which has lower complexity compared with existing matrix Cumulative Sums (CUSUM) and completing performance. Second, new fusion method based on codebook switching and minimum distance rule is developed, which can significantly lower the error probabilities compared with existing methods.fold.First,new local decision rule based on stochastic ordering theory is proposed, which has lower complexity compared with exist- ing matrix Cumulative Sums(CUSUM)and completing performance.Second, new fusion method based on codebook switching and minimum distance rule is developed, which can signicantly lower the error probabilities compared with existing methods.