Fast assessment method of power grid risk based on Huffman code and state identification

Abstract

With the development of economy and society, people's requirements for power quality and reliability are gradually increasing, so it is necessary to carry out risk assessment on power system. Monte Carlo method is a common method for power system risk assessment, but there is a contradiction between the calculation speed and accuracy. In order to improve the calculation accuracy, a large number of state samples need to be calculated, which takes a long time, and there are many repetitive states. For this reason, an improved Monte Carlo method based on Huffman code and state identification is proposed, which can significantly improve the efficiency of power grid risk assessment from two aspects. The first is to uniquely identify the system states through Huffman code and record relevant data, so as to avoid recalculation of the same states. The second is the fast and efficient identification of system state based on the shortest weighted path length of Huffman code. The effectiveness of the method is verified by an example, and several factors that may affect the effectiveness of the method are analyzed.