Aggregator to Electric Vehicle LoRaWAN Based Communication Analysis in Vehicle-to-Grid Systems in Smart Cities

Abstract

Recently, there has been growing attention to the power grid management due to the increasing concerns on global warming. With the advancement in electric vehicles (EV) industry and the evolution in batteries, EVs become an important contributor to the grid with capability of bidirectional power exchange with the grid. In this context, Vehicle-to-Grid (V2G) systems enable multiple functionalities between EVs and the corresponding aggregator. Thus, reliable, long-range communication capabilities between aggregator and EVs is compulsory. In this paper, wireless channel analysis for aggregator and electrical vehicle communication using Long-Range Wide Area Network (LoRaWAN) technology in V2G is presented, in order to test a low-cost solution with large coverage and reduced power consumption profile. Wireless channel and system-level measurements have been performed in a real urban scenario between EV's charging station in Pamplona (Spain) and a vehicle in motion using LoRaWAN 868 MHz devices. Wireless channel characterization is performed by implementing a full 3D urban scenario model, including elements such as buildings, vehicles, users and urban infrastructure such as lamp posts and benches. By means of in-house developed 3D Ray Launching algorithm with hybrid simulation capabilities, estimations of received power levels, signal to noise ratio and time domain parameters have been obtained, for the complete volume of the scenario under test in dense urban conditions. V2G end to end communication has been validated by implementing an intra-vehicle Controller Area Network-BUS (CAN BUS) data gathering system connected to the vehicle LoRaWAN transceiver and subsequently, to a cloud-based web service. The results show that the accurate deterministic based radio channel analysis enables to optimize the network design of LoRaWAN networks in a vehicular environment, considering inter-vehicular and infrastructure links, enabling scalable, low cost end to end data exchange for the deployment of ancillary V2G services.

Distribution network energy loss reduction under EV charging schedule

“…The proposed algorithm is implemented based on: (a) prior knowledge of DN's electrical characteristics, battery size and charger for each EV, and daily load curve for each node (provided as a day‐ahead load forecast) and (b) real‐time information about the connection of each EV in its charging station and its SoC upon its arrival. This kind of information could be provided under various IT solutions and communication channels as described in Reference 35. We consider that this information is directly available to the user.…”

RM-ADR: Resource Management Adaptive Data Rate for Mobile Application in LoRaWAN

“…The authors in [ 25 ] presented a CAN-BUS prototype considering a vehicle to grid (V2G) communication based on intra-vehicle data collection and interchange to aggregators. The data were gathered using the CAN-BUS prototype, connected with EDs and GW by connecting web services in a cloud-based NS.…”

Towards Environmental RF-EMF Assessment of mmWave High-Node Density Complex Heterogeneous Environments

“…The proposed in-house 3D-RL algorithm is based on Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). It has been previously validated in different indoor/outdoor complex environments [31,32] for different applications, such as vehicular communications [33,34], Intelligent Transportation Systems (ITS) [35][36][37], interference analysis [38,39], Wireless Local Area Networks (WLAN) [40,41], Wireless Sensor Networks (WSNs) [42,43] or Public Land Mobile Networks (PLMN) [23,24], among others. These applications have been validated for different operating frequencies (from mid-bands to mmWave frequency bands) and different wireless communication system configurations, achieving, in general, a Root Mean Square Error (RMSE) of 3-6 dB, an absolute mean error of 4-5 dB and a Standard Deviation (SD) of 1-7 dB.…”