Electric vehicle (EV) integration into the distribution system has been a topic of great interest lately due to the potential challenges it poses. Previous works have focused on either centralized charge control or distributed charge control to solve these issues. In this paper, an adaptive voltage feedback controller for an onboard EV charger is proposed that, unlike other proposed methods, does not require any real-time communication between the EV and the utility. This controller compares the system voltage at the point of charging with a preset reference voltage. The EV charging is reduced as the system voltage approaches this reference. The reduced charging rate takes into account the EV battery state of charge (SOC) and the owner's end-of-charge time (ECT) preference. To validate the proposed control structure, extensive simulations are carried out on a distribution system with and without other voltage control mechanisms. The simulation results show that this method can eliminate system voltage violations that would otherwise be caused by EV charging while ensuring fairness among the various EVs even with different system configurations and EV penetration levels. The proposed controller shows a good performance in the presence of other voltage control devices and distributed generation units. Also, it can integrate with Vehicleto-Grid services as a lowest level of hierarchical control.
Integrating a fleet of electric vehicles (EVs) in the distribution system without a communication infrastructure exhibits several issues that need to be handled by electric utilities. Robust autonomous controllers are crucial in this case to manage the charging operation without violating the grid standard limits. This paper proposes a communication-free autonomous charging controller for EVs in distribution systems. The controller is based on fuzzy logic considering both the system voltage profile and the EV's battery state of charge (SOC). The fuzzy inference system is designed to avoid under voltage issues in the grid, flatten the system loading profile and accomplish fair charging among different EVs connected to the system. An 18-bus distribution system driven by the proposed controller was implemented in a simulation environment. The proposed controller performance was investigated under different distribution system operating conditions such as different loading, different levels of EV penetration, system reconfiguration as well as with distributed generation. In all cases, the controller demonstrated faster and better charging performance without violating the standard voltage limits compared to other research reported in the literature.
With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states.
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