Research On The Power Consumption Method Of Mobile Cellular Network Based On Energy Supply And Demand

In recent years,the prelude of a new round of the energy revolution has begun,since the distributed energy resources,which have the properties of low environmental costs,renewability,and world-wide distribution,have been increasingly integrated into the power system.Traditional power systems will face a significant transition to cope with the new changes and challenges.In view of this,micro-grids that are comprised of networked groups of distributed loads and renewable generators become an appealing solution.Micro-grids have the characteristics of flexible location and decentralization,which is well adapted to the distributed power demands and resource distribution,so that the reliability of power supply can be improved effectively.Furthermore,it is very important to coordinate the energy management of power generation and electricity consumption in the micro-grid.On the other hand,cellular networks as power users are consuming more and more energy.The cellular network can flexibly adjust the electricity consumption according to its own demands and external environment,which makes the cellular network play a very important role in the micro-grid.Therefore,energy management will be a fundamental challenge in micro-grid connected cellular networks.Motivated by the above observations,we investigate the energy supply and demand problems of multiple retailers and clusters.First,considering the rapid increase of wireless network traffic,the energy consumption of mobile network operators(MNOs)continues to increase,and the electricity bill has become an important part of the operating expenses of MNOs.The power grid as the power supplier of cellular networks is also developing rapidly.In this paper,we design two levels of bilateral matching algorithm to solve the energy management of micro-grid connected cellular networks.There are multiple retailers and clusters in our system model,which determine the transaction price and trading energy respectively and have a certain influence on the balance of energy supply and demand.Retailers make more profits by adjusting the price of electricity in matching algorithm M-1.At the same time,clusters allocate resources through matching algorithm M-2 and power allocation on the basis of ensuring the quality of users' service.Finally,the performance of the proposed scheme is evaluated by changing various parameters in the simulation.Next,on the basis of the single slot energy interaction between retailers and clusters,we have further extended the research on this topic.Energy storage equipment,as the connection unit of front and rear time slots,has a certain influenceon retailers' behavior decision.In this paper,we research optimizing resource allocation for clusters with multiple time slots in a multi-retailer energy supply scenario.Power retailers update their electricity price by the load,which can reasonably guide the cluster's energy demand strategy in the power market.The simulation results show that the electricity price of retailers will influence and restrict each other,so that it fluctuates within a reasonable range and tends to be stable.The change of electricity price can influence the energy demand of clusters and ultimately lead to the reasonable energy consumption.