Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids

This paper proposes an efficient planning algorithm for allocating smart electric vehicle (EV) charging stations in remote communities. The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total dema...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2019-09, Vol.10 (5), p.5819-5830
Main Authors: Shaaban, Mostafa F., Mohamed, Sayed, Ismail, Muhammad, Qaraqe, Khalid A., Serpedin, Erchin
Format: Article
Language:English
Subjects:
Algorithms
Charging stations
Classification
Community planning
Computer simulation
Distributed generation
Electric power grids
Electric vehicle charging
Electric vehicle charging stations
Electric vehicles
EV charging stations
Genetic algorithms
Greenhouse effect
Greenhouse gases
hybrid microgrids
islanded microgrids
Load modeling
microgrid planning
Microgrids
Mixed integer
Multiple objective analysis
Planning
Reactive power
remote microgrids
Sorting algorithms
State of charge
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Summary:This paper proposes an efficient planning algorithm for allocating smart electric vehicle (EV) charging stations in remote communities. The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total demand of regular loads and EV charging. The planning algorithm specifies optimal locations and sizes of the EV charging stations and DG units that minimize two conflicting objectives: 1) deployment and operation costs and 2) associated green house gas emissions, while satisfying the microgrid technical constraints. This is achieved by iteratively solving a multi-objective mixed integer non-linear program. An outer sub-problem determines the locations and sizes of the DG units and charging stations using a non-dominated sorting genetic algorithm. Given the allocation and sizing decisions, an inner sub-problem ensures smart, reliable, and eco-friendly operation of the microgrid by solving a non-linear scheduling problem. The proposed algorithm results in a Pareto frontier that captures the tradeoff between the conflicting planning objectives. Simulation studies investigate the performance of the proposed planning algorithm in order to obtain a compromise planning solution.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2019.2891900