Abstract
Accurate prediction of power business communication bandwidth is the premise for the effectiveness of power communication planning and the fundamental guarantee for regular operation of power businesses. To solve the problem of scientifically and reasonably allocating bandwidth resources in smart parks, communication bandwidth prediction technology of intelligent power distribution service for smart parks is proposed in this paper. First, the characteristics of mixed service data arrival rate of power distribution and communication mixed services in smart parks were analyzed. Poisson process and interrupted Poisson process were used to simulate periodic and sudden business of smart parks to realize accurate simulation of the business arrival process. Then, a service arrival rate model based on the Markov modulation Poisson process was constructed. An active buffer management mechanism was used to dynamically discard data packets according to the set threshold and achieve accurate simulation of the packet loss rate during the arrival of smart park business. At the same time, considering the communication service quality index and bandwidth resource utilization, a business communication bandwidth prediction model of smart parks was established to improve the accuracy of business bandwidth prediction. Finally, a smart power distribution room in a smart park was used as an application scenario to quantitatively analyze the relationship between the communication service quality and bandwidth configuration. According to the predicted bandwidth, the reliability and effectiveness of the proposed method were verified by comparison with the elastic coefficient method.
Highlights
IntroductionA variety of energy forms and types of smart terminals exist in smart parks [1,2,3,4]
A variety of energy forms and types of smart terminals exist in smart parks [1,2,3,4].The power business in smart parks is complex, such as distributed power business, energy consumption monitoring business, control business, etc., which demands higher requirements on edge computing and edge communication capabilities
In [14], a hybrid traffic model that includes self-similar traffic and Poisson traffic was proposed to predict the bandwidth of electricity consumption information collection services, but this method cannot meet the needs of complex communication services in smart park systems
Summary
A variety of energy forms and types of smart terminals exist in smart parks [1,2,3,4]. At the same time, starting from different business characteristics, it accurately simulates the data arrival process of smart power distribution and communication services in smart parks to improve the accuracy of bandwidth prediction. Reliable, economical, and suitable communication methods for business, such as WiFi, EPON, industrial ethernet, 4G/5G wireless public network, etc They support services such as intelligent identification and monitoring of each link of electricity distribution, electricity consumption information collection, distributed energy control, etc. With the expansion of network scale and the continuous development of new power distribution services in smart parks, network traffic has shown strong burstiness and randomness It is difficult for the classic Poisson model to accurately simulate its characteristics. The average reaching rate of MMPP(2), that is, the arrival rate of mixed service data packets, is as follows: λ r2λ1 + r1λ0 (r1 + r2)
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