07-05-2011, 04:17 PM
INTRODUCTION
Economic dispatch is one of the most important optimization
problems in power system operation and forms the basis of
many application programs. Conventional methods employ
the widely used Lagrangian approach. However in the case of
segmented piece-wise quadratic function, corresponding to the
valve point loading or mixed fuel fired inputs, conventional
approach fails to obtain an optimal solution. In this context,
several approaches have been proposed using non-conventional
optimization approaches, including artificial neural networks
and genetic algorithms. Hopfield Neural Networks have been
successfully used in various optimization problems in different
domains.
Application of Hopfield network to power system economic
dispatch has been earlier proposed by various researchers
differing in the method of handling constraint relations1-7. In
this paper, a new approach to economic dispatch using
Hopfield Neural Network is presented. Important features of
this approach are faster convergence and efficient handling of
equality constraint.
ECONOMIC DISPATCH
Economic dispatch is the important component of power
system optimization. It is defined as the minimization of the
combination of the power generation, which minimizes the
total cost while satisfying the power balance relation. The
problem of economic dispatch can be formulated as
minimization of the cost function subjected to the equality and
inequality constraints.
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