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3154. A robust optimization approach for the strategic design of EV charging stations

Invited abstract in session MB-35: Stochastic Optimization for Energy Transition, stream Stochastic, Robust and Distributionally Robust Optimization.

Monday, 10:30-12:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Giovanna Miglionico
DIMES, Università della Calabria
2. Patrizia Beraldi
Department of Mechanical, Energy and Management Engineering, University of Calabria
3. Giovanni Giallombardo
DIMES, University of Calabria

Abstract

Although the environmental policies have pushed for the introduction of electric vehicles (EVs), the development of the EV industry is slowed down by the issues related to short driving range and extended recharging time. These challenges underscore the need for increased investment in the charging infrastructure. We consider strategic and operational planning decisions arising in managing plug-in electric vehicle (PEV) charging stations. At a strategic level, the station owner, makes decisions on the capacity of the station infrastructures (PEV-charging piles, renewable generators, and energy storages) and on the retail prices for PEV-charging energy. These decisions depend on the unknown values for the productivity of the renewable resources, for the number of PEV clients and for the wholesale prices. Based on the worst possible outcome for these scenarios the PEV owner would like to make the best operational decisions regarding the quantity of supplementary energy to be produced. We introduce a robust formulation of the problem and solve it by an iterative method designed for solving linearly constrained optimization problems, whose non-smooth nonconvex objective function is defined as the pointwise maximum of finitely many concave functions. We provide some computational results to compare the adopted solution method with those derived from the literature.

Keywords

Status: accepted

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