DQN-based 5G fusion intelligent power distribution network energy management method

Abstract

The invention relates to a 5G fusion intelligent power distribution network energy management method based on DQN, and belongs to the technical field of communication. According to the task unloading method with the energy queue perception based on the DQN, high-dimensional complex environment state information can be effectively processed. And an optimal energy management decision is made through deep reinforcement learning, and effective compromise between cost reduction and efficiency increase of the 5G base station and power supply stability is realized. New energy consumption is promoted, power grid energy supply and demand balance is maintained, and cost reduction and efficiency improvement effects of the 5G base station are improved. The power supply stability performance and the power service differentiation QoS demand can be considered at the same time, and the coupling relation between the information flow and the energy flow is considered, that is, the influence of communication demands such as transmission time delay and bit error rate on the battery state of the energy storage system is considered. An energy storage operator can learn a long-term optimal energy management strategy while guaranteeing the power supply stability of the base station, and the communication requirements of stable and reliable transmission of power service data are met.

Description

technical field [0001] The invention relates to a DQN-based 5G fusion intelligent distribution network energy management method, which belongs to the field of communication technology. Background technique [0002] With the rapid development of 5G mobile communication networks, a large number of energy storage units are widely deployed on large-scale 5G base stations. On the one hand, the abundant energy storage resources provided by 5G play an important role in ensuring the balance of power supply and demand in the distribution network. Provide advanced communication and computing capabilities. On the other hand, the distribution network can provide abundant power resources for the 5G base station, and the coordinated scheduling of the energy of the two will help the 5G base station achieve the goal of cost reduction and efficiency increase. 5G integrated smart distribution network has become a new research hotspot, which puts forward higher requirements for real-time and...

AI Technical Summary

Problems solved by technology

[0004] First, the fluctuation of 5G base station load, the intermittent nature of renewable energy, the huge signaling overhead, and security and privacy issues make it almost impossible for the 5G integrated smart distribution network system to obtain a global state

At the same time, the large increase of 5G base stations and the dynamic changes of the network bring the problem of numerical disaster to the optimization solution of energy management.

[0005] Second, the four resources of “source, network, load, and storage” for energy management decision-making and the optimization decision-making among various subjects are coupled. Therefore, its energy management problem cannot be solved by traditional model-based optimization methods

[0006] Third, in the process of intelligent energy management, we need to pay attention to real-time message transmission, and the reliable operation of base stations requires long-term stable energy supply. Traditional energy management optimization methods often ignore the coupling relationship between energy flow and information flow, and ignore power data. The long-term constraint of stable transmission cannot guarantee the stable power supply capability of the base station

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