Comparison of the fuzzy regression analysis and the least squares regression method to the electrical load estimation
Marek Witold Zalewski
AbstractAn essential point in correct calculations and analysis of power distribution systems is a proper evaluation of loads. The acquisition of this data is complex because of a large number of nodes and their area distribution. As a rule receiving nodes are not equipped with stationary measuring instruments so measurements of loads are performed only sporadically. The theory which enables efficient description of unreliable and inaccurate data, and relationship between them, is the fuzzy set theory. The paper presents possibilities of application of the fuzzy set theory to power distribution system calculations. Unreliable and inaccurate input data were modeling by means of fuzzy numbers. A regression model, expressing the correlation between a substation peak load and a set of customer features (explanatory variables), existing in the substation population, is determined. The fuzzy set approach and standard regression method are compared
|Book||Electrotechnical Conference, 1998. MELECON 98., 9th Mediterranean, vol. 1, 1998|
|Keywords in English||distribution networks, electrical load estimation, fuzzy regression analysis, Fuzzy sets, fuzzy set theory, Instruments, least squares approximations, Least squares methods, least squares regression method, load forecasting, Load modeling, power distribution, power distribution system calculations, power distribution systems, Power system modeling, regression analysis, regression model, set theory, Shape measurement, stationary measuring instruments, statistical analysis, substation peak load, system buses|
|Citation count*||5 (2013-01-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.