Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.

Automation in Power Grid Dispatch

A project named ＂A New Generation of Energy Management with Three Dimensional Coordination＂ has recently passed technical appraisal from the Ministry of Education. The project has been developed over the past 15 years by a research team led by Professor Zhang Boming from Tsinghua＇s Department of Electrical Engineering.

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence:mechanisms and applications of cognition,management,and control for complex systems

In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.