TITLE:
Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm
AUTHORS:
Le-Le Cui, Yang-Fan Li, Pan Long
KEYWORDS:
Thermal Power Plant, Coal Consumption Curve, Unit, Least Squares Method, Genetic Algorithm, Curve Fitting, Nonlinear Problems
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.3 No.4,
April
19,
2015
ABSTRACT: Coal consumption curve of the thermal power
plant can reflect the function relationship between the coal consumption of
unit and load, which plays a key role for research on unit economic operation
and load optimal dispatch. Now get coal consumption curve is generally obtained
by least square method, but which are static curve and these curves remain
unchanged for a long time, and make them are incompatible with the actual
operation situation of the unit. Furthermore, coal consumption has the
characteristics of typical nonlinear and time varying, sometimes the least
square method does not work for nonlinear complex problems. For these problems,
a method of coal consumption curve fitting of the thermal power plant units
based on genetic algorithm is proposed. The residual analysis method is used
for data detection; quadratic function is employed to the objective function; appropriate
parameters such as initial population size, crossover rate and mutation rate
are set; the unit’s actual coal consumption curves are fitted, and comparing the
proposed method with least squares method, the results indicate that fitting
effect of the former is better than the latter, and further indicate that the
proposed method to do curve fitting can best approximate known data in a
certain significance, and they can real-timely reflect the interdependence
between power output and coal consumption.