TY - JOUR
T1 - Coordinated Scheduling for Improving Uncertain Wind Power Adsorption in Electric Vehicles - Wind Integrated Power Systems by Multiobjective Optimization Approach
AU - Li, Yuanzheng
AU - Ni, Zhixian
AU - Zhao, Tianyang
AU - Yu, Minghui
AU - Liu, Yun
AU - Wu, Lei
AU - Zhao, Yong
N1 - Publisher Copyright:
© 1972-2012 IEEE.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
KW - Coordinated scheduling model
KW - electric vehicles (EVs)
KW - multiobjective optimization
KW - uncertainty
KW - wind power
UR - http://www.scopus.com/inward/record.url?scp=85084181883&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084181883&partnerID=8YFLogxK
U2 - 10.1109/TIA.2020.2976909
DO - 10.1109/TIA.2020.2976909
M3 - Article
AN - SCOPUS:85084181883
SN - 0093-9994
VL - 56
SP - 2238
EP - 2250
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 3
M1 - 9016077
ER -