Autonomous Collaborative Decision-Making for Power Elastic Optical Network Oriented to Service Reliable Bearing
Chen Yapeng1, Liu Pengju1, Zhou Zhenyu1, Bai Huifeng2, Zhang Jie3
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing 102206 China; 2. Beijing Smart Chip Microelectronics Technology Co. Ltd Beijing 100192 China; 3. State Grid Sichuan Electric Power Research Institute Chengdu 610041 China
Abstract:The power communication backbone network is an important infrastructure to ensure the safe and stable operation of the power system by means of power grid service reliable bearing. However, cross domain, layer and level source-grid-load-storage efficient interaction and multi energy wide interconnection also bring challenges to the service data bearing capacity of the power communication backbone network, where the network is facing increasingly prominent problems such as limited spectrum resources and poor deployment flexibility. Aiming at such problems, this paper proposes an autonomous collaborative decision-making method for power elastic optical network (EON) oriented to service reliable bearing, which integrates new generation information communication technology to upgrade traditional technology applications and provide support for wide area transmission and regulation of electric energy. First, he long-term reliability constraint of different types of power grid services and the optimization problem in the power EON are constructed, optimization goal of which is maximizing weighted network utility considering service priority, spectrum utilization and spectrum fragmentation. Furthermore, due to the randomness of power grid services and the time-varying nature of power EON resources, Lyapunov optimization is introduced to transform the long-term optimization problem and constraints into a series of short-term deterministic optimization problems, where the service reliability constraints deviation awareness is realized through virtual queue drift without any prior statistics and future prediction information. Finally, the coordination between service and resource in power EON is modeled as a three-dimensional matching problem among service requests, paths and frequency slots, which dimension was reduced to a one-to-one matching problem through the aggregation of path and frequency slot. Considering the competition of multi service requests for network resources, the price-based matching algorithm is utilized to achieve the autonomous collaboration between them in a unified time period, so as to ensure the reliable bearing of power services by the power communication network. The simulation results show that compared with the min drift plus penalty-based routing and spectrum allocation algorithm and the first-last exact fit-based routing and spectrum allocation algorithm, the proposed algorithm has better performance in network utility, spectrum utilization improvement, and service reliability guarantee. Specifically, the average network utility increased by 18.45% and 35.71%, the spectrum utilization increased by 33.52% and 54.41%, the cumulative throughput increased by 9.86% and 15.17%, the service request queue backlog decreased by 51.87% and 80.18%, and the virtual queue backlog decreased by 54.50% and 81.45%, which can also meet the high reliable transmission requirements of different priority services. As prospective theoretical research on the integration of electric power and information communication, the research results of this paper can provide a feasible technical scheme for the deployment of the next generation power communication backbone network, improve the service data carrying capacity of the power communication network, and provide a guarantee for the development of large-scale emerging power communication services. In the future research, based on the highly time-varying nature of service and network under the background of new power system construction, the autonomous collaborative decision-making method with lower complexity and stronger adaptability will be further studied.
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