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Smart Coordination Approach for Power Management with PEV Based on Real Time Pricing

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Modelling and Simulation in Science, Technology and Engineering Mathematics (MS-17 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 749))

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Abstract

Plug in Electric Vehicles (PEVs), replacing a considerable share of the nation’s light vehicle recommends the potential of reducing dependence on petroleum fuels together with important economic and environmental benefits. The impact of PEVs will be most significantly felt by the electric power distribution networks. The price-demand characteristics of PEV can assist System Operator (SO) to produce prolific solutions in optimization of the grid. In this pursuit, this paper presents an innovative approach to charge the PEV for sustaining operational standards in power networks in terms of voltage profile, distribution network losses and to maximize energy transferred to PEVs. This paper also enunciates a methodology supported by the unique price elastic characteristics of PEVs to maintain operational standards at minimum cost of generation and with maximum load catering including forecasted PEVs load. The proposed methodology demonstrates a power management strategy using smart coordination approach to (a) design a charging-discharging schedule for the PEVs that maximizes energy delivered to PEV batteries, (b) reduce the peak demand and transmission losses so that grids can avoid the situation of overloading and (c) maintain price equilibrium in power market. Effectively employing this procedure may lead to an operating scenario where an overall benefit of all the power market participants with standard operational status can be ensured and the over-pricing of electricity will be minimized.

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Correspondence to Purbasha Singha .

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Singha, P., Ghosh, D., Koley, S., Sarkar, R., Sen, S. (2019). Smart Coordination Approach for Power Management with PEV Based on Real Time Pricing. In: Chattopadhyay, S., Roy, T., Sengupta, S., Berger-Vachon, C. (eds) Modelling and Simulation in Science, Technology and Engineering Mathematics. MS-17 2017. Advances in Intelligent Systems and Computing, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-74808-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-74808-5_23

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-74808-5

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