Optimal Scheduling Method For Multi-agent In Power Distribution System With 5G Base Stations

In order to adapt to the transformation of the world’s energy structure,smart grid and 5G technology have been vigorously developed.With the large-scale access of 5G base stations to the distribution networks,the energy consumption and cost of communication network will increase sharply.At the same time,the high energy consumption of communication network will increase.The peak load of large distribution network operation has impact on the safe and stable operation of distribution network.5G communication network operators with a large number of distributed adjustable loads and energy storage can participate in distribution network demand response,which is suitable for multi-agent energy optimization scheduling scenarios based on game theory,but the existing research on communication network energy optimization is less considered The collaborative interaction between distribution network operators and communication network operators has not yet established a complete interaction optimization framework and method.In view of the above problems,this paper proposes a multi-agent collaborative optimization control method for distribution network and communication network based on master-slave game.First,according to the basic composition and power consumption characteristics of 5G base stations,construct a 5G base station cluster model considering the energy storage scheduling in the time dimension and the communication load migration in the space dimension;The distribution network energy optimization model and the communication network energy optimization model are established.Secondly,for the multi-regional 5G base station cluster scenario,a multi-agent optimization control framework for power distribution system based on master-slave game is established.The cluster adjusts the power consumption behavior and reduces the peak load of the distribution network;the 5G base station cluster,as a follower,actively adjusts the energy storage charging and discharging strategy and the load migration strategy to respond to the electricity price set by the distribution network operator,and minimizes the cost of electricity consumption;The independence of the power grid and the communication network,using the differential evolution algorithm to solve the two-level optimization problem.Finally,through the example simulation,the distributed solution algorithm is used to optimize the dynamic electricity price in each area of the power distribution system,the 5G base station cluster energy storage charging and discharging strategy,and the load migration strategy,and by setting a comparative example,the multi-agent collaboration proposed in this paper is analyzed.The superiority of the optimization method in terms of peak shaving ability,economic benefits and convergence speed,the collaborative optimization method can effectively adjust the peak load of the distribution network,smooth load fluctuations,improve the safe and stable operation of the distribution system,and at the same time reduce the operating cost of the communication network,providing a new idea for the coordinated development of the power industry and the communication industry.