Scientific Research Team

Information Security Research Team(Leader:Prof. Wen Mi)

Due to the adoption of computer network and information technology in the smart grid, it is inevitable to bring various inherent defects in information network (such as protocol defects, system vulnerabilities, computer network attacks, etc.). Moreover, smart grid security has three unique characteristics: 1) Most of the equipments in smart grid have weak computing power and lack of extra storage space, so it is difficult to implement the protection function of software. 2) Smart grid belongs to complex network. In addition to communication requirements, it also involves multiple links such as control and transmission etc, and a dedicated communication network protocol. 3) The facilities in smart grid must not be allowed to restart at will or be down for a long time.

In view of the particularity of information security of the smart grid, we have built a power network security laboratory in this experimental environment, which truly demonstrates the information security partition protection measures of China's power system,network isolation and encryption technology,the technical process of attack and defense can be presented in this environment.We have built a smart grid attack and defense test bed project for real-time dynamic display of the smart grid attack and defense process, including the use of power generation, transmission, distribution and power side information security protection technology, its research results can be used in the the smart grid partition defense,data center security protection, system security assessment, real-time detection of unknown viruses and many other technical areas.

For the management of big data in the smart grid, we have introduced a cloud computing platform to build a power cloud computing center, the main research includes power public cloud and power private cloud.The Smart Grid Cloud provides a variety of services to users and power system applications in a transparent manner, dynamically deploying, dynamically allocating/redistributing, real-time monitoring through virtualized computing and storage resource pools, and providing quality of service to users or power system applications. (QoS) required computing services, data storage services, and platform services. In the power cloud, because of the data collected by the terminal equipment and the users (such as industrial power users, commercial power users, residential power users, etc.) provide data storage, sharing and calculation, the data storage and access based on the power cloud is also faced a series of security threats in general cloud computing. At present, there are mainly research on power cloud and power cloud security in the following aspects: 1) identity authentication; 2) access control; 3) privacy protection; 4) data security; 5) security audit; 6) key management; 7) trustworthiness measurement. We are currently conducting research on access control, data security, trustworthiness measurement, privacy protection and other aspects, which are mainly applied in the fields of power data publishing, power user security management, multi-source (multi-source heterogeneous distributed generation) power data security storage and retrieval and other fields.

Power Big Data Research Team (Leader: Prof. Lei Jingsheng)

With the continuous deepening and advancement of smart grid construction, the amount of data generated by grid operation and equipment inspection/monitoring has grown exponentially, which gradually constitutes a large amount of data which is concerned by the information academia nowadays,which requires corresponding storage and rapid processing technology as support. Power network business data can be roughly divided into three categories: first, power network operation and equipment detection or monitoring data; Second, the marketing data of power enterprises, such as transaction price, electricity sold, electricity customers and other data; Third, power enterprise management data.The main reasons for the generation of grid big data include: in order to accurately obtain the running status information of the equipment in real time, more and more collection points; in order to capture various status information and meet the requirements of the upper application system, the sampling frequency of the equipment is getting higher and higher; To truly and completely record every detail of production and operation, fully reflect the process of production and operation, and meet the requirement of real-time change sampling.

Combining the two core lines of power big data reshaping power core value and transforming power development mode, aiming to the 3V3E characteristics of electric power big data, the team studied the electric power data acquisition technology and large power, large power data storage, data cleaning technology power big data management and electric power data analysis methods, heterogeneous data fusion models and related technologies of power big data in power grids and power companies, focusing on breakthroughs in power big data quality control, storage sharing methods, data security, privacy protection Key technologies such as analysis and mining have built a power big data processing system and application system platform to provide strong support for the development of smart grid.