| Title | Energy trading with dynamic pricing for electric vehicles in a smart city environment |
|---|---|
| ID_Doc | 37195 |
| Authors | Aujla, GS; Kumar, N; Singh, M; Zomaya, AY |
| Title | Energy trading with dynamic pricing for electric vehicles in a smart city environment |
| Year | 2019 |
| Published | |
| Abstract | Smart cities are equipped with latest technologies to provide sustainable and economical services to their citizens. With an increase in carbon emissions, the popularity of electric vehicles (EVs) is a major step towards environment friendly smart cities. However, energy trading with dynamic pricing is one of the major challenges for EVs in a smart city environment. Most of the existing solutions reported in the literature do not consider energy trading with an aim to maximize benefits to EVs in terms of their demand satisfaction. EVs have to pay higher price as they have limited knowledge about the location and pricing policy of the charging stations (CSs). Moreover, they have to wait for long time till the required amount of energy is met from the CSs. To address these issues, a multi-leader multi-follower Stackelberg game for energy trading is proposed by assuming EVs as the consumers and CSs as energy providers. Using this concept, a dynamic pricing scheme known as multi parameter pricing scheme is designed by taking parameters such as - electricity usage, time-of-use, location, and type of EVs. Two cases of Stackelberg Game are considered in the proposal- (i) EVs as leaders and CSs as followers, and (ii) CSs as leaders and EVs as followers. The proposed scheme is evaluated using three types of vehicles with respect to performance metrics such as (a) price of energy (b) utility function and (c) satisfaction factor. The results obtained clearly depict the superior performance of the proposed scheme in comparison to the existing schemes. (C) 2018 Elsevier Inc. All rights reserved. |
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