Hopfield neural network computation as an alternative solution for solving economic dispatch in power system

In modern industrialized society, an Economic Dispatch (ED) of power generating units has always been occupied an important position in the electric power industry. This paper presents a Hopfield Neural Network (HNN) computation method to solve ED problem in power systems. HNN computation is expected to be reliable since HNN is essential for its progress. The objective of this paper is to describe how a new method to solve the ED in power system is developed since HNN is the faster alternative method in predicting problem in ED. A new mapping process is formulated and how to obtain the weighting factors is also described in this paper. Then, a simulation algorithm is described to solve the dynamic equation of the HNN. To solve the ED problem, the power mismatch, total fuel cost and the transmission line losses along with their associated weighting factors are defined. The results obtained gives less computational time compared to the Lambda-iteration method. Furthermore, the results also indicate that the HNN computation performs significantly better than conventional method, Lambda-iteration method