A Hopfield Neural Network approach for integrated transmission network expansion planning

This paper presents a metaheuristic algorithm using Hopfield Neural Network (HNN) for predicting the optimum expansion plan for large interconnected transmission system. An integrated optimization function for transmission system planning including combined generation and transmission effects is first developed. The mathematical model used is a DC model, in which the objective function considers the investment in generation and transmission as well as the system operational costs for the planning horizon. HNN are used to obtain an optimum plan for transmission network expansion by mapping the mathematical model mentioned above to the HNN energy function. The new model is tested on both the Garver´s 5 bus system and the IEEE 14 bus system to demonstrate its advantages.