Do 5G communication base stations have multi-objective cooperative optimization?

This paper develops a method to consider the multi-objective cooperative optimization operation of 5G communication base stations and Active Distribution Network (ADN) and constructs a description model for the operational flexibility of 5G communication base stations.

What are the operational constraints of 5G communication base stations?

The operational constraints of 5G communication base stations studied in this paper mainly include the energy consumption characteristics of the base stations themselves, the communication characteristics, and the operational constraints of their internal energy storage batteries.

Do 5G communication base stations engage in demand response?

In the above model, by encouraging 5G communication base stations to engage in Demand Response (DR), the Renewable Energy Sources (RES), and 5G communication base stations in ADN are concurrently scheduled, and the uncertainty of RES and communication load is described by using interval optimization method.

Where are 5G communication base stations located?

Furthermore, 5G communication base stations with energy storage are located at nodes 6, 8, 15, and 31, each group containing 100 base stations, labeled as groups 1, 2, 3, and 4. The fundamental parameters of the base stations are listed in Table 1.

What are the basic parameters of a base station?

The fundamental parameters of the base stations are listed in Table 1. The energy storage battery for each base station has a rated capacity of 18 kWh, a maximum charge/discharge power of 3 kW, a SOC range from 10% to 90%, and an efficiency of 0.85.

What is the optimal ADN operation of 5G communication base stations?

Under the current technological level and market conditions, due to the natural contradiction between the above-mentioned economy and the realization of carbon emission reduction objectives, the optimal ADN operation of 5G communication base stations can be summarized as a typical multi-objective optimization problem.