DocumentCode :
2017213
Title :
A new model to improve the behavior of PIEVs aggregator considering the customers´ motivation
Author :
Shafie-Khah, Miadreza ; Catalao, Joao P. S. ; Parsa Moghaddam, Mohsen ; Sheikh-El-Eslami, Mohammad Kazem
Author_Institution :
Dept. of Electromech. Eng., Univ. Beira Interior (UBI), Covilha, Portugal
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, a new model is developed to improve the behavior of plug-in electric vehicles (PIEVs) aggregator in the short-term and long-term time horizons. In the model, the aggregator maximizes his/her profit and optimizes PIEV owners´ revenue by applying changes in the contract type to ensure their participation and attract new customers in the future. The aggregator optimizes the self-scheduling program and proposes the optimal bidding strategies to the electricity markets, considering EVs constraints. Moreover, the electricity markets are modeled as oligopoly markets, in contrast with previous works that considered perfectly competitive ones. Further, in the proposed model several uncertainties are considered, such as electricity market prices, number of connected PIEVs, the connection duration of PIEVs, amount of energy stored in the batteries, calling the aggregator by ISO for power generation and behavior of market players. The numerical results show the effectiveness of the proposed model.
Keywords :
consumer behaviour; electric vehicles; oligopoly; optimisation; power generation economics; power generation scheduling; power markets; profitability; tendering; ISO; PIEV aggregator; customer motivation; electricity market; market player; oligopoly market; optimal bidding strategy; plug-in electric vehicle; power generation; profit maximization; revenue optimization; self-scheduling program optimization; time horizon; Batteries; Contracts; Electricity supply industry; Numerical models; Oligopoly; Spinning; Uncertainty; Aggregator; bidding strategies; oligopoly market; plug-in electric vehicles; profit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/PTC.2013.6652155
Filename :
6652155
Link To Document :
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