Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

Ecological and economics issues are caused to give careful consideration to electric vehicles (EV) and sustainable power source assets. One of the proposed answers for increment the impact of these assets, is to utilize the electric vehicles potential. The capability of electric vehicles require pla...

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Veröffentlicht in:Journal of ambient intelligence and humanized computing Jg. 11; H. 5; S. 2071 - 2103
Hauptverfasser: Yin, WanJun, Mavaluru, Dinesh, Ahmed, Munir, Abbas, Mazhar, Darvishan, Aida
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2020
Springer Nature B.V
Schlagworte:
Algorithms
Alternative energy sources
Artificial Intelligence
Computational Intelligence
Consumers
Demand side management
Ecological effects
Electric potential
Electric power systems
Electric vehicles
Electricity distribution
Energy consumption
Energy resources
Energy storage
Engineering
Flexibility
Fossil fuels
Hybrid vehicles
Impact strength
Industrial plant emissions
Integer programming
Multiple objective analysis
Optimization
Optimization algorithms
Original Research
Planning
Pollutants
Power management
Power plants
Power sources
Renewable resources
Robotics and Automation
Scheduling
Smart grid
Uncertainty
User Interfaces and Human Computer Interaction
EV
Demand response
Renewables source
Multi-objective scheduling
Optimization
ISSN:1868-5137, 1868-5145
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Zusammenfassung:Ecological and economics issues are caused to give careful consideration to electric vehicles (EV) and sustainable power source assets. One of the proposed answers for increment the impact of these assets, is to utilize the electric vehicles potential. The capability of electric vehicles require planning for Smart Distribution Systems (SDS). Request reaction programs, as a suitable device to utilize endorsers’ potential in ideal administration of the system, gives dynamic nearness of supporters in control framework execution change and these projects, in basic conditions, can give the request prerequisites diminishment, in a brief timeframe. In this work, attempts to presents a multi-objective scheduling of EV based on the sustainable assets in smart grid, cover uncertainty caused by inexhaustible assets and EVs, by considering of the request reaction projects and EV battery stockpiling framework, limit the working expenses and the measure of intensity framework contamination, with enhancing procedures. Improved optimization algorithm is utilized for taking care of the advancing issue. Operating costs dropped much further utilizing monetary model of the demand response and vehicle charge/discharge and smart program in the hours when the load is lower. Effectiveness of proposed method is applied on 33 bus standard power system.
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ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-019-01233-1