A combinatorial artificial intelligence realtime solution to the unit commitment problem incorporating V2G
 M. M. Hosseini Bioki,
 M. Zareian Jahromi,
 M. Rashidinejad
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Plugin hybrid electric vehicles (PHEVs) have been the center of attention in recent years as they can be utilized to set up a bidirectional connection to a power grid for ancillary services procurement. By incorporating Vehicle to Grid (V2G), this paper proposes a realtime solution to a nonconvex constrained unit commitment (UC) optimization problem considering V2G parking lots as dispersed generation units. V2G parking lots can be considered as virtual power plants that my decrease dependency to small expensive units in a UC problem. In this paper, firstly a probabilistic attendance model of PHEVs in a parking lot is investigated, while expected number of PHEVs as well as the equivalent generation capacity of the parking lot is obtained using a radial basis neural network. Secondly, a particular UC problem considering V2G parking lot is solved using GAANN as a hybrid heuristic method. A realtime estimation of PHEVs number in the V2G parking lot and realtime solution to UC–V2G problem associated with load variation makes this work distinguished, while the proposed method is applied to a standard IEEE 10unit test system with promising results.
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 Title
 A combinatorial artificial intelligence realtime solution to the unit commitment problem incorporating V2G
 Journal

Electrical Engineering
Volume 95, Issue 4 , pp 341355
 Cover Date
 20131201
 DOI
 10.1007/s0020201202635
 Print ISSN
 09487921
 Online ISSN
 14320487
 Publisher
 Springer Berlin Heidelberg
 Additional Links
 Topics
 Keywords

 Unit commitment
 Vehicle to grid
 Parking lots
 Probabilistic model
 Radial basis neural network
 Genetic algorithm
 Industry Sectors
 Authors

 M. M. Hosseini Bioki ^{(1)}
 M. Zareian Jahromi ^{(1)}
 M. Rashidinejad ^{(2)}
 Author Affiliations

 1. Department of Electrical and Computer Engineering, Kerman Graduate University of Technology, Kerman, Iran
 2. Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran