Intelligent Energy Management Algorithms for EV-charging Scheduling with Consideration of Multiple EV Charging Modes

Electric vehicles (EVs) are now attracting increasing interest from both industries and countries as an environmentally friendly and energy efficient mode of travel. Therefore, the EV charging and/or discharging issue has become an important challenge and research topic in power systems in recent ye...

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Vydáno v:Energies (Basel) Ročník 12; číslo 2; s. 265
Hlavní autoři: Mao, Tian, Zhang, Xin, Zhou, Baorong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 16.01.2019
Témata:
Algorithms
charging/discharging
Convex analysis
Design
electric vehicle
Electric vehicles
Electricity distribution
energy management
genetic algorithm
Genetic algorithms
Infrastructure
intelligent scatter search
International conferences
Load
Methods
Optimization
Power
Scheduling
Vehicles
United States > US
China
Singapore
ISSN:1996-1073, 1996-1073
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Shrnutí:Electric vehicles (EVs) are now attracting increasing interest from both industries and countries as an environmentally friendly and energy efficient mode of travel. Therefore, the EV charging and/or discharging issue has become an important challenge and research topic in power systems in recent years. An advanced and economic EV charging process, however, should employ smart scheduling, which depends on effective and robust algorithms. To that end, a comprehensive intelligent scatter search (ISS) algorithm within the frame of a basic scatter search has been designed with both unidirectional and bidirectional charging considered. The ISS structure also supports both a flexible and constant charging power rate by respectively employing filter-SQP (sequential quadratic programming) and mixed-integer SQP as local solvers with module control. The detailed design of ISS is presented and the objectives of smoothing the daily load profile and minimizing the charging cost have been tested. Compared with methods based on GS (global search), GA (genetic algorithm), and PSO (particle swarm optimization), the outcome-verified ISS can produce attractive results with a significantly short computational time. Moreover, to handle a large scale EV charging scenario, a hybrid method comprised of a GA and ISS approach has been further developed. Simulation results also verified its prominent performance, plus superbly low computational time.
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ISSN:1996-1073
1996-1073
DOI:10.3390/en12020265