Application of LoRa Network for Data Transmission in Intelligent Smart Grid Systems

As new ways to generate renewable energy cost effectively are being developed, high load devices such as electric vehicles (EVs) are becoming common. EVs require high current and voltage for charging, due to the large size of the batteries and the requirement for fast charging. This has made intelligent smart grids necessary, as traditional grids are incapable of dealing with the disturbances in the grid produced by the load required by these devices. Our paper proposes an intelligent smart grid which is interconnected using LoRa network and uses a long short-term memory (LSTM)-based neural network for processing, forecasting and predicting the disturbances produced in the network. The LoRa modules will be used in a mesh configuration; this will remove the need for a repeater and also give us greater network coverage. A LoRa access point will be placed, which will collect data from the individual modules and send them to the power station. Here, the LSTM algorithm will be applied on the data collected thereby doing the necessary predictions. The use of LoRa has make the system independent of cellular networks and due to its low power consumption, and efficiency have been improved. LSTM algorithm is capable of dealing with not only individual data but also complete time series. It can also deal with missing data, which makes it much more beneficial. Overall, our proposed system can greatly benefit both consumers and electricity companies.