Abstract
This paper proposes a new model in emergency control of load shedding based on the combination of dual Artificial Neural Network to implement the load shedding, restore the power system frequency and prevent the power system blackout. The first Artificial Neural Network (ANN1) quickly recognizes the state with or without load shedding when a short-circuit occurs in the electrical system. The second Artificial Neural Network (ANN2) identifies and controls the selection of load shedding strategies. These load shedding strategies include pre-designed rules which is built on the AHP algorithm to calculate the importance factor of the load units and select the priority of the load shedding. In case the ANN1 results in a load shedding, the load shedding control strategy is immediately implemented. Therefore, the decision making time is much shorter than the under frequency load shedding method. The effectiveness of the proposed method is tested on the IEEE 39-bus system which proves the effectiveness of this method.
Highlights
Short-circuit faults during operation are unpredictable and the time required for troubleshooting is very short
The results show that this method performs faster load shedding than under frequency load shedding (UFLS) methods [11, 12]
Fast recognition process of "Yes" or "No" perform load shedding when a short-circuit incident occurs causes frequency instability in the power system in combination with the established load-control solution based on Analytic Hierarchy Process (AHP) algorithm
Summary
Short-circuit faults during operation are unpredictable and the time required for troubleshooting is very short. Due to the complexity of the power system, in case of the emergency control, such as short circuits on branch and bus bars, these methods have problems with the amount of data, computation time and the processing speed of the algorithm program is relatively slow or the passive load shedding is done after waiting for the frequency below the permitted threshold, causing delays in the load shedding decision. This can lead to an instability of the power system frequency. It helps to quickly make decisions to control load shedding based on ANN2 to restore and maintain the frequency stability of the power system
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