Development of multidimensional sequence operation theory with applications to risk evaluation in power system generation scheduling

作     者：ChongQing Kang&Email:cqkang@*** GaoFeng Yang Qing Xia 

作者机构：State Key Lab of Power Systems Department of Electrical Engineering Tsinghua University Beijing 100084 China Yangjiaping Power Supply Bureau Chongqing Electric Power Corporation Chongqing 400050 China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2008年第51卷第6期

页      面：724-734页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 50777031) Program for New Century Excellent Talents in University (Grant No. NCET-07-0484) the Fok Ying-Tong Education Foundation (Grant No. 104020) 

主　　题：power system multidimensional sequence operation theory vector Hadamard products uncertainty 

摘      要：Sequence operation theory (SOT) is a powerful tool for solving complex probabilistic problems in power system. However, the basic single dimension SOT cannot satisfy the requirement of multi-state; multi-attribute analysis, which is often the case in actual power system practice. To address this problem, multidimensional sequence operation theory (MSOT) is developed. On the basis of previous research, this paper first categorizes the situations by the number of state variables; the number of attribute values,; defines the multidimensional sequence for single state variable; multiple attribute values, as well as the multidimensional sequence for multiple state variables; multiple attribute values. Corresponding to those definitions, four types of operations between two discrete multidimensional sequences are derived respectively. Therefore, the sequence is extended from single dimensional to multidimensional, establishing an integrated theory of multidimensional sequence operation. In particular, the basic single dimension SOT can be viewed as a special case of MSOT with only one state variable; one attribute value. Finally, the paper demonstrates the effectiveness of MSOT through an example of risk evaluation in power system generation scheduling.