APPLICATION TLBO ALGORITHM FOR LORAWAN OF SMART METER FOR RESIDENTIAL ELECTRICITY
In this paper, the main objective is to design a smart meter to measure electricity consumption in households with communications based on LoRaWAN (Long Range Wide Area Network) wireless technology. Two devices have been designed, a Smart Meter for Electrical Energy in Households (SMEEH) and a LoRaWAN Network Supervisor (LNS), which optimises the LoRAWAN parameters using the teaching learning base optimisation (TLBO) algorithm. This algorithm allows obtaining the parameters’ spreading factor (SF), bandwidth (BW), and code rate (CR) so that the minimum value of the packet loss rate (PLR) is reached, and the load profiles of the households are modelled in real time using cloud data storage. The algorithm implemented in the LNS determines the most appropriate parameters of the LoRaWAN by checking data traffic in real time. The data obtained by the household electrical energy measuring system are acquired through sensors. Load profiles of households obtained by measuring the voltage, current, and active power with LoRaWAN using algorithm TLBO are more accurate.