caa a22 4500 463206738 CHVBK 20180405153128.0 cr unu---uuuuu 170326e20070901xx s 000 0 eng 10.1007/s00202-006-0047-x doi (NATIONALLICENCE)springer-10.1007/s00202-006-0047-x A genetic-based algorithm for optimal estimation of input-output curve parameters of thermal power plants [Elektronische Daten] [A. AL-Kandari, K. EL-Naggar] This paper presents a new and accurate method for estimating the input-output curve parameters of thermal power plants. These parameters are very important for performing the economic dispatch calculations. The higher the accuracy of the estimated coefficients, the more accurate the results obtained from the economic dispatch calculations. Different models of thermal input-output curve fitting of the thermal units are considered. The problem is formulated as an estimation problem. The goal is to minimize the estimation error. The proposed genetic-based method is used to perform this job. Practical study cases are considered to test the performance of the method. Results obtained are evaluated. Springer-Verlag, 2006 Estimation nationallicence Genetic algorithm nationallicence Economic dispatch nationallicence Fuel cost function nationallicence AL-Kandari A. Electrical Engineering Department, Collage of Technological Studies, Kuwait, Kuwait aut EL-Naggar K. Electrical Engineering Department, Collage of Technological Studies, Kuwait, Kuwait aut Electrical Engineering Springer-Verlag 89/8(2007-09-01), 585-590 0948-7921 89:8<585 2007 89 202 https://doi.org/10.1007/s00202-006-0047-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00202-006-0047-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- AL-Kandari A. Electrical Engineering Department, Collage of Technological Studies, Kuwait, Kuwait aut NATIONALLICENCE 700 1- EL-Naggar K. Electrical Engineering Department, Collage of Technological Studies, Kuwait, Kuwait aut NATIONALLICENCE 773 0- Electrical Engineering Springer-Verlag 89/8(2007-09-01), 585-590 0948-7921 89:8<585 2007 89 202 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer