Demand Prediction and Placement Optimization for Electric Vehicle Charging Stations
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3117-3122.
Abstract
Effective placement of charging stations plays a key role in Electric Vehicle (EV) adoption. In the placement problem, given a set of candidate sites, an optimal subset needs to be selected with respect to the concerns of both (a) the charging station service provider, such as the demand at the candidate sites and the budget for deployment, and (b) the EV user, such as charging station reachability and short waiting times at the station. This work addresses these concerns, making the following three novel contributions: (i) a supervised multi-view learning framework using Canonical Correlation Analysis (CCA) for demand prediction at candidate sites, using multiple datasets such as points of interest information, traffic density, and the historical usage at existing charging stations; (ii) a mixed-packing-and-covering optimization framework that models competing concerns of the service provider and EV users; (iii) an iterative heuristic to solve these problems by alternately invoking knapsack and setcover algorithms. The performance of the demand prediction model and the placement optimization heuristic are evaluated using real world data.
@inproceedings{ijcai2016p442,
title = {Demand Prediction and Placement Optimization for Electric Vehicle Charging Stations},
author = {Gopalakrishnan, Ragavendran and Biswas, Arpita and Lightwala, Alefiya and Vasudevan, Skanda and Dutta, Partha and Tripathi, Abhishek},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {3117--3122},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/442},
}
TY - CPAPER TI - Demand Prediction and Placement Optimization for Electric Vehicle Charging Stations AU - Gopalakrishnan, Ragavendran AU - Biswas, Arpita AU - Lightwala, Alefiya AU - Vasudevan, Skanda AU - Dutta, Partha AU - Tripathi, Abhishek T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 3117 EP - 3122 UR - https://ijcai.org/proceedings/2016/442 ER -Copied
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