Coordinated Scheduling for Improving Uncertain Wind Power Adsorption in Electric Vehicles-Wind Integrated Power Systems by Multiobjective Optimization Approach

Electric vehicles (EVs) and renewable energy, such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, research articles on the operation performance of the EV-wind integrated power system are important. This article proposes a coordinated schedu...

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Bibliographic Details
Published in:IEEE transactions on industry applications Vol. 56; no. 3; pp. 2238 - 2250
Main Authors: Li, Yuanzheng, Ni, Zhixian, Zhao, Tianyang, Yu, Minghui, Liu, Yun, Wu, Lei, Zhao, Yong
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive algorithms
Adsorption
Alternative energy sources
Computer simulation
Coordinated scheduling model
Cost effectiveness
Electric power systems
Electric vehicles
electric vehicles (EVs)
Emission analysis
Emissions control
Energy conservation
Evolutionary computation
Generators
Mathematical programming
multiobjective optimization
Multiple objective analysis
Optimization
Power systems
Scheduling
Sociology
Statistics
Sustainable development
Thermal loading
uncertainty
Wind power
Wind power generation
Wind turbines
ISSN:0093-9994, 1939-9367
Online Access:Get full text
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Summary:Electric vehicles (EVs) and renewable energy, such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, research articles on the operation performance of the EV-wind integrated power system are important. This article proposes a coordinated scheduling model, which aims to improve the wind power adsorption while considering the energy conservation and emission reduction of thermal generators. Besides, to conduct a comprehensive investigation among these multiple objectives, we formulate the coordinated scheduling model as a multiobjective optimization problem. Then, a multiobjective optimization algorithm based on a parameter adaptive differential evolution is proposed to solve this problem. Simulation results based on a modified Midwestern USA power system verify that the proposed scheduling model could reveal the relationship among multiple objectives, and the integration of EVs can improve the wind power adsorption and cost effectiveness of the power system.
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ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2020.2976909