Research on Teaching Planning and Teacher Evaluation Integrating Sustainable Development and Renewable Energy Concepts

Abstract

Energy is an essential basis for human survival, social progress and economic development. With the rapid development of China's economy and the acceleration of urbanization, the problem of energy shortage is increasingly serious, and the problem of energy security is prominent. Based on stochastic power flow algorithm, this paper proposes the safety assessment and teaching planning of wind power generation in renewable energy. Firstly, the dynamic safety domain and thermal stability safety domain of wind power systems are proposed in this paper. Within the selected security domain, the key factors that are most likely to lead to the risk of a distribution network are selected by means of entropy-modified analytic hierarchy process (AHP). The incompleteness of the single weighting method is solved, and the total evaluation score of each layer of the index system is calculated from the subjective and objective perspectives to determine the weak link in the occurrence of accidents in the distribution network. The total score is less than 90 points, which is prone to failure risk. Finally, based on the safety index system, PLF is introduced into the uncertainty safety assessment of wind power systems to overcome the inefficiency of traditional uncertainty assessment methods. Methods PLF was used as a means of system state analysis to replace a lot of conventional power flow analysis in uncertain safety assessment, and related safety indexes were defined based on PLF results. The test system ST-PLF is taken as an example to verify the rationality of the proposed method. The results show that the proposed method can effectively realize the static security assessment of the system and identify the potentially vulnerable elements of the system. The evaluation time of the proposed method is 0.73 s, while that of the traditional method is 48.54 s. The evaluation speed of the proposed method is greatly improved, and the time is only 1.55% of that of Monte Carlo method.