(Created page with " == Abstract == Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavio...") |
m (Scipediacontent moved page Draft Content 246272581 to Anvari-Moghaddam et al 2017a) |
(No difference)
| |
Latest revision as of 20:48, 3 February 2021
Abstract
Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.
Original document
The different versions of the original document can be found in:
Document information
Published on 01/01/2017
Volume 2017, 2017
DOI: 10.1109/eeeic.2017.7977806
Licence: CC BY-NC-SA license
Share this document
Keywords
claim authorship
Are you one of the authors of this document?