Cost-aware Data Aggregation and Energy Decentralization with Electrical Vehicles in Microgrids through LTE Links

Microgrids are the building blocks of resilient and sustainable smart cities. In remote areas, well-designed and managed microgrids can operate as standalone mode. Since renewable energy causes more intermittency to the electricity grid, interruptions to the electricity supply due to uncertain weather condition or supply shortage to charge Electrical Vehicles (EVs) in microgrids reveals extra cost especially during the peak hours. EVs can be utilized to stand this temporary circumstances with the help of decentralized services by supplying the excess electricity which is stored in the EV batteries to other microgrids. Dynamic electricity prices which are determined by smart grids are necessary to manage and control this process. The reliability of the communication link between eNodeB’s and EVs plays an important role to ensure successful delivery of the transmitted data during data aggregation process in microgrids. In this paper, the interaction between smart microgrids (i.e. buyer) and electrical vehicles (i.e. seller) for short-term power supply, and formulate a Mixed Integer Linear Programming (MILP) to obtain the best set of EVs in order to obtain cost-aware solution. In addition, considering the EV-microgrid integration over LTE links, we demonstrate the impact of the physical downlink shared channel (PDSCH) throughput performance on the following outputs of the model: total cost, the outstanding energy and the electrical vehicle’s revenue. We simulate the throughput performance in a multiuser multiple-input multiple-output (MU-MIMO) scenario.