A Modified Hopfield Neural Network Method for Equality Constrained State Estimation
نویسندگان
چکیده
Electric power system is a highly complex and non linear system. Its analysis and control in real time environment requires highly sophisticated computational skills. Computations are reaching a limit as far as conventional computer based algorithms are concerned. It is therefore required to find out newer methods which can be easily implemented on dedicated hardware. It is a very difficult task due to complexity of the power system with all its interdependent variables, thus making the neural networks one of the better options for the solution of different issues in operation and control. In this project an attempt has been made to implement ANN’s for State Estimation. A Hopfield neural network model has been developed to test Topological Observability of Power System and it is tested on two different test systems. The results so obtained, are comparable with those results of conventional root based observability determination technique. Further a Hopfield model has been developed to determine State Estimation of power system. State Estimation of 6 bus and IEEE 14 bus system is attempted using this Hopfield neural network.
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