Smart Electric Vehicle Charging Through Cloud Monitoring and Management

Abstract

Smart charging system of electric vehicle using cloud based monitoring and management is demonstrated in this work. xEVs (electric plugin hybrid, battery electric vehicles) Charging Management System is crucial for the dynamic demands of charging infrastructure, namely perspectives from automakers, electricity providers, vehicle owners and charging service providers. Through dedicated interface, the developed system is capable of providing real time information to xEVs users regarding nearest charging station with minimum queuing delay, with minimum charging cost through a secured online accessing mechanism for accessing Sate of the Charge (SOC) of the xEV's India Smart Grid Forum (ISGF), New Delhi, India battery being charged. The system not only provide an execution framework for the xEVs users but also provide an optimal energy trading solution to all entities involved in a smart charging infrastructure such as charging station, aggregators, smart grid etc. The work also explains the cloud enabled bidding strategies that look for day-ahead and term-ahead markets. The aggregators will use the smart decisions undertaken by cloud analytics to execute their bidding strategies in way to maximize the profit. Further, the work also assesses the possible cyber security aspects of such architectures along with providing possible solutions.

Dynamic Pricing for Electric Vehicle Charging—A Literature Review

“…An adequate infrastructure for monitoring and metering, for data storage and processing and for the communication between stakeholders like EV drivers, charging providers and distribution system operators, is required. Cloud-based EV charging management systems as proposed by Mierau et al [111] and Saqib et al [112] can represent a scalable solution. Data privacy is playing an increasingly important role.…”

Fog Computing for Internet of Things (IoT)-Aided Smart Grid Architectures

“…This vision is bold but critical to enabling smart living [13]. The new challenges of big data analytics (BDA) posed by SG welcome scientists from both academia and R&Ds to investigate and develop novel and high-performance computing architectures [11]. Due to its multifaceted opportunities and advantages over pure cloud and edge models, FC had received enormous attention from the SG community.…”

“…Fortunately, the FC is there to harness the store and compute resources latent in the underutilized SG resources such as vehicles [31,32], gateways, PMUs, etc. [11]. The fog model complements the cloud computations with dedicated and ad hoc computational resources [33], to be performed on the edge nodes of an IoT-aided SG thereby reducing the networking latency.…”

“…where, the terms inside square braces denotes power consumption at the network while transmitting the byte-stream. The second and third addend in (11) represents power consumption profile for FCNs and cloud servers, respectively. The energy consumption profile of a typical fog node (P comp f…”

A Fog Computing Based Architecture for IoT Services and Applications Development

“…The idea is to allow devices to talk directly to each other without the need to send data all the way to the cloud, enabling real-time decisions to be made and also shielding the IoT application from transmitting massive amount of data to the cloud. The FC objective is also to connect all devices to the cloud with open communication standards [3]. We believe that most IoT services and application are of realtime nature and thus require performing data processing and decision making in a timely manner.…”