The weakly-centralized Web-of-Cells based on cyber-physical-social systems integration and group machine learning: Theoretical investigations and key scientific issues analysis

Abstract

The key technology concerning the dispatch and control of the cyber-physical-social systems (CPSS) integration and group machine learning (ML) based Web-of-Cells (WoC) is systematically investigated, aiming to develop an intelligent dispatching system that has a high penetration of distributed generations (DG). Based on practical engineering demands and the weakly-centralized WoC, which is characterized by self-organized co-evolution, high independence, high-efficiency synergy, and autonomous learning, a variety of advanced theoretical tools such as complex network theory, group ML, evolutionary game theory, and CPSS-based parallel system theory have been adopted to address the following key issue: How can we achieve overall optimal dispatching and control decision-making in a class of complex systems relying on a large number of group cells with characteristics of limited information, weak controllability, small capacity, and wide distribution? Starting from this, four basic scientific issues are discussed: 1) a modeling method for a self-organized coupled network of the CPSS integration-based WoC; 2) a stability analysis and stability control system of the self-organized evolution of the WoC; 3) a highly autonomous group intelligent decision (GID) method of an independent cell; 4) multi-cell synergetic evolutionary game and GID theory. Hence, an innovative breakthrough on the intersection of complex network game theory and group ML is expected to be obtained, contributing to the emergence of group knowledge in complex circumstances and a significant improvement in the level of GID. Lastly, based on the theoretical investigation in this paper, explorations on the development of the CPSS platform for the WoC as well as its engineering practice in application are conducted. Furthermore, the in-depth development of the WoC, as well as its anticipated technical challenges, are prospected and analyzed with the hope of applying it on practical smart distribution grid demonstration projects in the future.