Title :
Application of regression analysis for predication of voltage collapse in power systems
Author_Institution :
Electr. Power & Machines Dept., Ain Shams Univ., Cairo
Abstract :
In this paper we present a new application of the Least Error Square (LES) Estimation algorithm for the predication of voltage collapse in a power system using the local measurements of voltage and current of a load bus. Using these measurements a polynomial of order n is assumed for the relation of the load voltage and load current, and hence the kVA. The coefficients of this polynomial are estimated using the LES estimation algorithm. The collapse point is defined as the point where the load draws its maximum volt-ampere from the bus. Having obtained this point the estimated voltage can be obtained using the assumed polynomial. This method of prediction of voltage collapse supercedes the conventional load flow methods by avoiding repeated load flows. The proposed algorithm is tested using the IEEE-30 bus system and compared with the conventional load flow methods.
Keywords :
least squares approximations; load flow; polynomials; power system dynamic stability; regression analysis; IEEE-30 bus system; collapse point; least error square estimation algorithm; load bus; load current; load flow methods; load voltage; polynomial coefficients; power systems; regression analysis; voltage collapse; voltage stability; Current measurement; Estimation error; Load flow; Polynomials; Power measurement; Power system analysis computing; Power system measurements; Regression analysis; System testing; Voltage measurement; Least Error Square; Maximum Load; Regression Analysis; Voltage Collapse; Voltage Stability;
Conference_Titel :
Power System Conference, 2008. MEPCON 2008. 12th International Middle-East
Conference_Location :
Aswan
Print_ISBN :
978-1-4244-1933-3
Electronic_ISBN :
978-1-4244-1934-0
DOI :
10.1109/MEPCON.2008.4562329