“Based on the distribution network and the physical entity of distribution network automation, integrating sensing measurement, operation control, information communication and other technologies, and supporting the friendly access and demand interaction of distributed generation, microgrid, energy storage and electric vehicles, this is the connotation of current distribution network intelligence. The most basic work of distribution network intelligence is data acquisition and management, and high-quality data can be obtained Accurate perception and control of distribution network system and equipment status. ” Dong xuzhu, chief engineer of China Southern Power Grid Research Institute and distinguished expert of the national “thousand talents plan”, said.
Improving data quality is an eternal topic in the intellectualization of distribution network. Only the real-time monitoring of power supply reliability of distribution network can realize fault early warning, analysis and decision-making, achieve the purpose of self prevention and self recovery of power grid, and realize the optimal operation state of power grid.
Interactivity puts forward higher requirements for data acquisition
In recent years, with the accelerated process of re electrification, high proportion of new energy access, large-scale application of energy storage, and the deep integration of digital technology and power grid technology, the physical characteristics, operation mode and functional form of power grid are undergoing profound changes. Accelerating the construction of an energy Internet with a strong smart grid as the core and a new generation of power system as the basis is an urgent need to improve the efficiency of energy resource allocation.
In particular, with the acceleration of power reform, new urbanization and agricultural modernization, the rapid development of new energy, distributed power generation, electric vehicles and energy storage devices, and the new trend of rapid growth, great change and diversification of terminal power load, the investment focus of power grid in the future will gradually turn to power grid intelligence and distribution network construction, more inclined to the power distribution and consumption side. This also brings opportunities for power transmission and distribution equipment enterprises, especially those integrating primary and secondary equipment.
“The interaction between the power grid and users has been greatly enhanced. In the traditional mode, users are only electric energy receivers and users. However, with the development of demand response, smart home and distributed power generation, electric energy and its accompanying information flow will flow in both directions between the power grid and users in the future, which requires the power grid to become more flexible, controllable and testable. Our system protection laboratory Based on data analysis and modeling, the physical hardware in the loop simulation of the primary and secondary system is realized, which strongly supports the core technology, equipment R & D and talent training of China’s power safety production regulation and operation. ” Li Wei, deputy general manager of Nanrui group stability company, said.
In fact, intelligent data analysis and management of distribution network is the key. In recent years, China is strengthening the scientific research and construction of intelligent data collection and processing of distribution network, and has also made some gratifying achievements. For example, a new generation of distribution automation master station system was put into operation in Changzhou, Jiangsu Province not long ago. The master station system has achieved technical breakthroughs in real-time data processing from one million to ten million, from single area I collection to multi area and multi-source data collection, and from centralized application service to massive data platform service architecture, meeting the dual business requirements of operation monitoring and state control of distribution network.
The new generation of distribution automation master station system is like the “thousand mile eye” and “nerve center” installed for distribution network dispatching. Through real-time big data acquisition and analysis, it can make the distribution network be monitored in real time like the main network. Whether it is daily operation monitoring, dispatching operation or fault disposal, it can quickly and accurately switch the power grid operation mode, isolate the fault power outage area, and significantly improve the power supply reliability in an all-round way.
In the future, advanced technologies such as artificial intelligence will be integrated
With the continuous improvement of the practical level of advanced information and communication technology, the future distribution network will become a dynamic, efficient, convenient and interactive super architecture network that can be used for real-time information and power exchange. Information and communication technology effectively connects the power supply with the needs of customers, comprehensively utilizes a variety of communication modes, realizes effective and reliable information transmission, establishes a panoramic real-time and seamless exchange data model of distribution network, realizes high reliable and real-time communication, and ensures the association, cooperation and interaction between distribution network and customers at all levels.
Therefore, in the future, based on advanced power electronics technology, nano materials and low-power technology, the distribution network can also realize power quality control and reduce system loss.
“At present, we are studying the application of artificial intelligence in power grid, which has covered the fields of power load forecasting, power grid hidden danger fault forecasting in extreme weather, large power grid dispatching simulation and so on.” Shan Xin, system R & D center of NARI Group Research Institute, said that the application of artificial intelligence in transmission and distribution grid has just started and is still in the exploratory stage.
For example, he said, we have handed over the line trip data, typhoon path and tower wind resistance parameters caused by typhoons in East China in recent years to artificial intelligence for learning and comparison. The results show that compared with the traditional algorithm and physical modeling, the accuracy of artificial intelligence “predicting” the line trip probability caused by typhoon is improved by 20%. In the future, with the continuous upgrading of hardware, data and algorithms, the application prospect of artificial intelligence in power grid can be expected.