Big data in recent years (big data) technology has been highly concerned and valued by academia, industry and governments all over the world. Data has been widely considered to be as important as other resources. This paper first analyzes the application of big data in power grid, and then uses Hadoop technology to design a big data system suitable for power grid enterprise decision-making based on the characteristics of power platform in a province of China Data platform system. This paper constructs the operation environment and uses the big data platform to sample all kinds of power generation and user side data. Based on the platform, the behavior data of power customers are analyzed and processed, which proves that the technology of big data can better serve the company's business innovation and decision support.

P2P online loan platform is a new product with the development of Internet finance. Its new financial way can bring the participant both abundant rewards and high risk. Therefore, there are many risk assessing companies springing up. But common companies just forecast if a P2P online loan platform will be absconding according some characteristics and they can't explain the reason why the platform will be absconding in the future. Instead of the directly forecasting the future status of a platform, the risk of a platform absconding is more objective and the decision makers can completely consider a platform's interest, risk and other factors to make their own decision. After all, 51% risk of absconding is not the same as 91% risk of absconding, when the investors are thinking. In this model, the almost features of platforms including absconding and non-absconding will be considered and be disposed according to the type of the data. The feature candidates will be selected by different angles and methods. The forecast model will calculate risks using the input feature and there is a index in this paper to appraise how the model is good.

Generally speaking, the approaches for power resources in the demand and generation side can be divided into the following three groups: the electricity policy mechanism in the demand side, the way of electricity use side and the generation side. The scheduling mechanism of the electricity price in the demand side, the way of electricity use and the generation side. The joint optimal disposal of power consumption mechanism in the demand side, the accumulation system in the generation side. Further research for those three kinds of optimization problems will be made both at home and abroad. When we talked about the questions about the optimal allocation of electric power resources of the generation side in this passage, we adopted a relatively new electricity situation, that is, to discuss the problem of efficiency power plant generations side engagement in the linkage absorptive of power resources.

One of the important factors and the user side affecting the electric power resources utilization, the way to use the electricity has an important effect on improving the efficiency the power generation side using the electric resources. The way that the user side consumes electric power can be divided into several ways: the large users' direct power purchase transaction, cross-regional power transmission, energy storage system charge, discharge way and so on. Different ways have different operating laws and characteristics. In order to analyze the impact of different ways on the electric power resources use efficiency, this paper established the optimization model that diversified the ways that the user side assists to use the electric power resources, and analyzed the electric power resources utilization optimization problem with the aid of the large users' direct power purchase transaction, power sending and energy storage system, and carried out example simulation by means of examples of data.