基于平行CPSS结构的智慧能源调度机器人及其知识自动化理论

本项目着眼于能源5.0 前瞻性基础理论研究，重点攻关基于信息-物理-社会融合系统（CPSS）的智慧能源调度机器人RoboEC群体及其知识自动化的关键理论方法：研究面向下一代能源电力系统的平行CPSS理想框架及工程可行框架体系；研发基于数据驱动及自校正引导方法的新型高精度镜像仿真方法，实现镜像系统对真实物理系统的趋优引导；研究面向未来能源电力系统集中/分散调度的平行机器学习方法和知识自动化技术，实现RoboEC群体的知识自我探索和群体智慧水平的自动提升；研究平行系统与真实系统的交互协调收敛数学机理及实现CPSS大闭环的系统化设计方法，获得能源、信息、社会三者的深度融合方法和系统化工程设计方法；研发并完善基于平行CPSS架构的RoboEC研究平台，将所研发的RoboEC投入到小规模实际工程运行测试，力争在 “能源4.0”到“能源5.0”的技术发展之路上先行一步。

This project attempts on systematically developing the key theories of “Energy 5.0” based on smart energy robot dispatcher RoboEC, in which the theoretical and application structure of next generation of energy system called CPSS will be thoroughly investigated. In addition, novel high-precision mirror simulation approaches will be developed based on data-driven and self-correction mechanisms, such that an optimal approximation from the mirror system to the physical system can be achieved. Moreover, parallel machine learning and knowledge automation will be comprehensively studied for centralized/decentralized dispatch of future energy power systems, which can effectively achieve a knowledge self-exploration of RoboECs as well as significantly enhance the swarm intelligence. Besides, the convergence property between the coordinated parallel system and real system will be studied in depth, together with the design of global closed-loop CPSS system, so that a highly incorporated and systematic engineering design of energy, information and society can be realized. Lastly, a small-scale experiment project will be used for testing the engineering feasibility of theoretical results with the ambitious aims to make the substantial scientific progress from “Energy 4.0” to “Energy 5.0”.