Adaptive load shedding for an industrial petroleum cogeneration system

This paper presents the design of adaptive load-shedding strategy by executing the artificial neural network (ANN) and transient stability analysis for an Industrial cogeneration facility.
► To prepare the training data set for ANN, the transient stability analysis has been performed to solve the minimum load shedding for various operation scenarios without causing tripping problem of cogeneration units. Various training algorithms have been adopted and incorporated into the back-propagation learning algorithm for the feed-forward neural networks.
► By selecting the total power generation, total load demand and frequency decay rate as the input neurons of the ANN, the minimum amount of load shedding is determined to maintain the stability of power system.
► To demonstrate the effectiveness of the ANN minimum load-shedding scheme, the traditional method and the present load shedding schemes of the selected cogeneration system are also applied for comparison and verification of the proposed methodology.

► The transient stability analysis has been performed to solve the minimum load shedding for various operation scenarios without causing tripping problem of cogeneration units.
► The minimum amount of load shedding is determined to maintain the stability of power system.
► The traditional method and the present load shedding schemes of the selected cogeneration system are also applied for comparison and verification of the proposed methodology.