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## Optimal location and charging of electric vehicle with wind penetration

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Large number of electric vehicles influences the aggregate power request significantly. Demand estimation is typically intended for the occasionally changing load designs. Though, with the fleet of electric vehicles, daily charging request makes conventional strategies less precise. In this work, prime site for centralized charging of electric vehicles and its charging scheme in a modified IEEE-34 distribution network is planned. To determine the optimum site, an hourly load demand is changed at specified junction nodes and the equivalent voltage sensitivity indexes are calculated. These indexes are derived from the Newton-Raphson load flow analysis in proposed distribution network and aid in choosing appropriate site for charging. Next, in the study, optimum charging of electric vehicles at selected node is conferred based on real-time pricing and wind power output data. The charging based on real-time price would lead to shift in the situations of peak load occurrence in the network. Similarly, charging based on wind power availability would aid in optimizing the customer's benefit in terms of cost. The peak period is shifted to valley period wherein real-time price is low or wind output is high.

Chapter Contents:

• Nomenclature
• 14.1 Introduction
• 14.2 Test system
• 14.3 Sensitivity analysis
• 14.3.1 Node selection
• 14.3.2 System operation algorithm
• 14.4 Stochastic modeling for EVs load demand
• 14.4.1 Charging level and type of EVs analysis
• 14.4.2 Stochastic fuzzy modeling
• 14.4.3 Initial SOC and EVs load profile
• 14.5 Peak load shifting optimization
• 14.5.1 EV charging optimization according to load curve
• 14.5.2 EV charging optimization according to real-time price
• 14.5.3 EV charging optimization according to wind power and RTP
• 14.5.4 Charging/discharging shifting
• 14.6 Conclusion
• References

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