Research On Risk Evaluationg Of Coal-fired Air-cooling Unit For HULUNBEIER

This paper assesses the expansion project of the Hulunbeier coal-fired air-cooling unit, forecasts the medium and long-term power load development of the Northeastern area using gray system forecast technique. Basing on the assessment, this paper also analyzes the necessity the expansion project. This paper identifies risks related to Hulunbeier Coal-fired air-cooling unit expansion project, and builds a coal-fired air-cooling unit expansion project risk evaluation index system according to the index system setup principles.This paper employs the analytic hierarchy process to determine the relevance weight of index system. The relevance weights are used as the input value to initialize the connection weights of BP neural network, and the risk evaluation model is established. Thus the possibility that the BP network fall into the partial minimum point can be greatly reduced; moreover, the BP neural network training speed can be improved.Finally, the effectiveness and utility has been demonstrated by the Empirical risk evaluation of the Hulunbeier coal-fired air-cooling unit expansion project.