@inproceedings {pub3464,
	title = {Multi-objective Optimization of Plug-in Electric Vehicle Charging Prices},
	author = {Steffen Limmer AND Tobias Rodemann},
	year = {2017},
	month = {November},
	abstract = {With the increasing penetration of plug-in electric vehicles (PEVs), the operation of public charging
stations becomes a more and more interesting business case. For such a public charging station a 
dynamic pricing scheme can help to react to varying operation costs and to encourage customers 
to extend their charging deadlines. 

We propose a framework for the selection of dynamic prices
with respect to the following three objectives: maximizing the charging station operator{\textquoteright}s profit, 
minimizing the number of customers that decline charging due to too high prices and minimizing the 
number of PEVs that have to be rejected because of missing charging capacities. 

Two variants of the framework are proposed. In the first variant, the objectives are reduced to a single objective and
CMA-ES is used for the optimization. In the second variant, the problem is solved with multi-objective
optimization over NSGA-II in conjunction with desirability functions.

Numerical experiments show that the proposed approach is able to yield a tradeoff between short-term 
profit and the number of declining and rejected PEVs. In this way the social welfare can be increased 
in comparison to choosing prices solely with the objective of maximizing the profit. It can be expected
that this has a positive effect on the long-term profit of the public charging station.},
	publisher = {IEEE},
	booktitle = {Proceedings IEEE SSCI 2017},
	pages = {2853--2860}
}