A control Strategy for Hybrid Energy Source in Backbone Base Transceiver Station using Artificial Neural Network: A Case Study of Penajam, Indonesia

Abstract

Base transceiver station (BTS) is vital infrastructure in cellular communication. Without BTS, of course, communication cannot occur between cellular network users. Moreover, BTS is a BTS backbone that is a link between BTS. One of the problems with the BTS backbone is that energy sources. Without adequate energy for 24 h, of course, the supply of BTS cannot work. This is a problem in the BTS backbone located in Penajam, Indonesia. Therefore, it is necessary to regulate energy sources using the concept of hybrid energy sources (HES). In this study, the authors simulate the concept of HES by setting the energy source following the real site condition. The energy sources are the grid, diesel generators, and batteries. The control strategy is based on several policies that have been determined by the BTS operators. Due to the complexity of the rules, the strategy is realized into a binary rule. The binary rule is trained into a black box controller in an artificial neural network (ANN) to simplify the control system. From the simulation results obtained, the control system can stabilize energy distribution well, and there was an overshoot of 8.3% of the nominal value of the bus when switching switches to the diesel generator.