PROJECT TITLE :
Demand Response for Residential Electric Vehicles With Random Usage Patterns in Smart Grids
Electric vehicles (EVs) are expected to become widespread in future years. So, it is foreseen that EVs can become the new high-electricity-consuming appliances within the households. The characteristics of the extra power load that they impose on the distribution grid follow the patterns of individuals's random usage behaviors. In this paper, we get to produce answers to the following question: assigning real-world randomness to the EVs' availability within the households and their charging necessities, how will EVs' demand response (DR) help to reduce the peak power demand and, normally, form the aggregated demand profile of the system? We tend to present a general demand-shaping problem applicable for limit order bids to on a daily basis-ahead (DA) energy market. We propose an algorithm for distributed DR of the EVs to form the daily demand profile or to minimize the height demand. Additionally, we tend to put these issues in a game framework. Extensive simulations show that, for certain sensible distributions of EVs' usage, it is doable to accommodate EVs for all the users in the system and however achieve the same peak demand as when there is no EV in the system while not any changes within the users' commuting behaviors.
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