Smart Charging Solutions for Hybrid and Electric Vehicles. Группа авторов

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Название Smart Charging Solutions for Hybrid and Electric Vehicles
Автор произведения Группа авторов
Жанр Техническая литература
Серия
Издательство Техническая литература
Год выпуска 0
isbn 9781119771715



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optimal solution considering constraints of both the EV user and the utility grid. The solution can be related to the direction of power flow, electricity cost, allowable charging rate, scheduling of charging and discharging of EVs, and power management. The central control, in a few cases, is supported by the necessary algorithms that process the data. The processing of data includes error check, relevant parameter estimations, data storage, and analysis. Nonetheless, the centralized control system determines solutions or makes decisions considering information from the entire system [9, 10]. A schematic of the centralized controller is shown in Figure 1.5. Each of the entities shown connected by dotted lines depicts communication links.

      1.7.2 Decentralized

Schematic illustration of the decentralized controller in smart charging architecture.

      The simplicity in the implementation of the decentralized controller is leading to an increase in demand. Further, the coherency, like EV operation (spatially distributed), reduces deployment complexity. Further, decentralized control architectures are seemingly practical and scalable, considering their computational complexity [78].

      1.7.3 Comments on Suitability

      The drawbacks and benefits of centralized and decentralized control architecture infer a requirement for maturity in the smart charging system.

Control architecture Merits Demerits
Centralized Better voltage and frequency regulationBetter utilization of network capacityCan be used with provisions for ancillary servicesEase of control and operation inclined towards the PSO System design and deployment are complexDemands huge capital investment in developing robust communication architectureDifficult to scale due to predefined constraints in the optimization problemHigh computational requirements to process and analyze a large amount of dataRobust error correction of data protection is required
Decentralized Ease in the tracking of fault in the systemMore control to the EV users and higher acceptance rateLess capital investment in deploying communication architectureEasily scalableEase of renewable energy integration The impact on the utility grid is tough to determineThe use of EVs as ancillary services is difficult to implement

      EVs are looked upon as a key to unleashing the potential of clean transportation and low-carbon emission electricity. The push for electrification of the transport sector has brought changes in the operations of current utility grids with a rise in the integration of renewable energy sources. Renewable energy sources are spatially distributed in nature; EVs’ mobility and the capability to smart charge and discharge are seen as impactful in integrating renewables to the grid. The outlook of smart charging infrastructure has a wide perspective, which is drawn based on the geography of the land where the infrastructure will be developed, the system analysis time frame, the focus of the impact study, and the society.

      The geography of the land helps decide the type of control architecture to be deployed for smart charging. Apart from control architecture, the availability of renewables is also considered. Consider a remotely located region with hilly terrain. The control architecture for such a region is preferred to be distributed, due to capital investment in developing communication architecture. The availability of renewables introduces another opportunity to develop an isolated grid rather than connecting to a larger grid. Hence, the potential of renewables in generating electricity is analyzed and,