Settlement Data Risk Identification and Processing of Power Market Based on Evidence Theory

In recent years, China's power market reform has been continuously promoted, and reasonable settlement of trading behavior is an important cornerstone for ensuring the orderly development of the power market. The paper analyzes the data risks faced in the power market settlement, and proposes the method of using DS evidence theory to identify the data risks in the settlement process through multi-evidence fusion decision. The PCA and ICA construct statistics are used as evidence sources. After multiple evidences are combined, abnormal data is identified through reasonable decision-making methods. In addition, based on the calculation results of evidence theory, the paper puts forward the risk processing method of settlement data, and proposes a reconstruction method based on polynomial fitting and historical correlation for the abnormal data with low reliability. The effectiveness of the proposed method is demonstrated by an example. The reconstruction method can obtain more accurate data and can effectively reduce the settlement risk of the power market.