Cost Minimization of Power System Generation Using Artificial Neural Network (ANN)

Attempts to generate electricity at a minimal cost or economic dispatch (ED) are a problem for many operators in the power industry. The activities involved are very complicated, evolves in time by unpredictable events. Currently the application of Artificial Intelligence methods in this industry has produced tremendous positive results. In this regard, this study developed Rivann software to provide the best load distribution for optimal power generation with minimal fuel cost using artificial neural network (ANN). The approach is validated by using the lagrangian multiplier method. Result obtained from Rivpann show daily cost saving or Netsave derived from optimal distribution of load as against equal distribution of load. The system will assist operators in thermal power plants with the task of planning power generation economically. The result obtained from the application also explains the important role intelligent support systems can play in the management of the electricity generation industry.