With the development of power technology and communication technology, the power grid and power communication network have become interdependent and closely coupled. The load shedding operation of the power grid is an important means to reduce the occurrence of chain faults and ensure the safe and stable operation of the power grid. Based on the transmission of load control services in the communication network, this paper establishes a model for a dual-network coupled cyber physical power system (CPPS). Considering communication edge faults, the associated load capacity of the communication edge and the expected load loss of the power grid are defined. On this basis, the paper proposes a complete information zero-sum game mechanism called “defense attack defense” for communication edge failures, which takes the expected loss of load from the power grid as the benefit. The paper studies the optimal attack and defense game strategies and provides the algorithm implementation process for the three stages of the game. Considering the bandwidth capacity of the communication edge, this paper uses the Dijkstra algorithm or k shortest paths (KSP) algorithm with the cost factor of the communication edge as the weight to plan the main and backup communication channels for multiple load control services. The simulation results show that the game mechanism proposed in this paper can effectively reduce the expected load loss from the power grid and improve the stability of the CPPS.
With the rapid development of Synchronous Digital Hierarchy (SDH) technology, it has been more and more widely used in power communication networks. The power communication network has high requirements on the reliability of data transmission, and the self-healing ring has the advantages of automatic fault recovery, high reliability, flexible networking, and simple implementation, thus becoming an indispensable part of the construction of power communication SDH networks. How to effectively evaluate the self-healing ability of SDH and improve the performance of the transmitted services has become an urgent problem to be solved. In the actual operation of the network, the selfhealing capability of SDH cannot be accurately and effectively evaluated. Therefore, on the Exata simulation platform, the SDH transmission network equipment, network, services and other resources and self-healing behavior are modeled to achieve the SDH. Transmission network "fault occurrence-fault detection-fault recovery" this self-healing process simulation. Finally, a comparative evaluation of the availability of access networks and backbone networks was carried out for a protection network in a certain area, verifying that the channel protection function of SDH self-healing rings can effectively improve the security and reliability of the power grid.
With the large-scale deployment of sensors, both the smart grid and the power communication network should jointly deal with different kinds of big data. The fusion of both networks should bring unpredictable accidents, even leading a catastrophic destruction in our lives. However, data fusion (DF) and coordination treatment for two networks will greatly improve system performance, reduce system complexity, and improve the precision and control ability of both networks. Situation awareness (SA) is the key function for DF and accident avoidance for both networks with different network structures, data types, system mechanisms, and so on. This paper use tensor computing to provide a general data model for heterogeneous and multidimensional big data generated from smart grid and power communication network. A novel data fusion scheme is designed with multidimensional tensors. Deep reinforcement learning (DRL) algorithms are utilized to construct an optimal SA strategy based on tensor big data. A multi-agent actor-critic (MAAC) algorithm is used to achieve an optimal SA policy and improve system performance. The proposed DF and SA schemes based on tensor computing and DRL provide useful guidance for smart grid and power communication networks from theory and practice.
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