Hopfield Lagrange for short-term hydrothermal scheduling

This paper proposes Hopfield Lagrange (HL) model for optimal scheduling of fixed head and variable head hydrothermal coordination. HL is a combination of Hopfield neural network and Lagrange function. Unlike Hopfield network, HL is not required to define an energy function and map the problem into the Hopfield neural network with connection conductance. HL achieves better solution than Hopfield neural network and linearized coordination equations method and is faster than augmented Lagrange Hopfield (ALH) on two test systems. The proposed model is simple and efficient for the fixed head and variable head hydrothermal scheduling problems.