Abstract
A two-phase optimisation neural network based modelling framework and a solution technique is proposed for solving the economic load dispatch problem in large-scale systems. The method is based on the solution of a set of differential equations obtained from transformation of an augmented Lagrangian energy function. The main objective is to minimise the total cost of generation while meeting the load demand and satisfying a number of constraints like power balance, unit generation limits, maximum ramp-rate limits, network losses and prohibited zone avoidance. It compares the proposed technique with the lambda iteration and genetic algorithm methods while investigating its applicability to large-scale power systems. The technique has shown the potential for achieving improved and feasible results with proper selection of control parameters.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEE Proceedings - Generation, Transmission and Distribution
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
