Optimal Design of Smart Grid Information Scheduling Algorithm Based on Deep Learning

Due to the rapid growth of smart grid, the application of power grid dispatching system has gradually developed from basic dispatching business to information business applications such as data fusion, heterogeneous system interaction and big data analysis. The overall development direction of power grid now and in the future is smart grid, and the application of relatively emerging cloud technology to power grid system can provide technical support for comprehensive and in-depth innovation of business model and operation mode of power grid enterprises to a certain extent. However, the current power grid dispatching system can not meet the requirements of big data analysis and other information services. Based on the theory of complex science, aiming at the development and preliminary planning of smart grid, this article analyzes the complex characteristics of smart grid management information system (MIS), and proposes a smart grid information scheduling algorithm based on deep learning. The results show that the system has good performance, and can effectively improve the business application level of the system and complete the corresponding scheduling.