Disturbance Detection of a Power Transmission System Based on the Enhanced Canonical Variate Analysis Method

Aiming at the characteristics of dynamic correlation, periodic oscillation, and weak disturbance symptom of power transmission system data, this paper proposes an enhanced canonical variate analysis (CVA) method, called SLCVAkNN, for monitoring the disturbances of power transmission systems. In the proposed method, CVA is first used to extract the dynamic features by analyzing the data correlation and establish a statistical model with two monitoring statistics T2 and Q. Then, in order to handling the periodic oscillation of power data, the two statistics are reconstructed in phase space, and the k-nearest neighbor (kNN) technique is applied to design the statistics nearest neighbor distance DT2 and DQ as the enhanced monitoring indices. Further considering the detection difficulty of weak disturbances with the insignificant symptoms, statistical local analysis (SLA) is integrated to construct the primary and improved residual vectors of the CVA dynamic features, which are capable to prompt the disturbance detection sensitivity. The verification results on the real industrial data show that the SLCVAkNN method can detect the occurrence of power system disturbance more effectively than the traditional data-driven monitoring methods.

Application of Canonical Variate Analysis to Compare Different Groups of Food Industry Companies in Terms of Financial Liquidity and Profitability

Financial liquidity and profitability are two critical phenomena present in the financial economy of a company, whose relations depend on each other and may course in different directions. At the same time, they are an example of the complexity of the problem, which demands a proper approach, allowing one to reconcile two opposing objectives of any enterprise, i.e., maximizing the benefits for the owners and minimizing the risk of losing financial liquidity. Until now, the relationship between liquidity and profitability has not been examined explicitly, using multidimensional methods in particular. Nevertheless, the links between profitability and financial liquidity maintenance ensure the sustainable development of enterprises in different branches. This paper formulates two aims: scientific and practical. The scientific one concerns adopting the canonical variate analysis method to visualize the differences and relationships between food industry companies regarding financial liquidity and profitability. The practical one relates to indicating the relationship between financial liquidity and profitability in different groups of food industry companies. To study the relationships between the selected groups of enterprises and describe them, the liquidity and profitability ratios were utilized, involving canonical variate analysis based on transformation by linear combination and singular value decomposition. The analysis found that the most important feature highlighting the group of the examined entities regarding financial liquidity was the cash conversion cycle. The research results showed the existence of multidirectional relationships between liquidity and profitability. The research indicates that they depend on indicators describing financial dependencies and the industries in which they operate. This led to a much deeper and broader interpretation of the assessment of the financial situation of companies to support their sustainable development.