MESSAI.iO

AI summary

100% confidence

International MES research in renewable-energy with focus on renewable-integration, transportation. Electric vehicles (EVs) and renewable energy, such as wind power, have been widely utilized to meet the sustainable deve...

Generated by MESSAI extraction pipeline · review against source PDF

Extraction

Reported parameters

No values extracted from this paper yet.

No 3D model is mapped to this paper yet. Parameter ranges above still place reported values on the literature distribution.

Abstract

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.

Keywords

Wind powerMulti-objective optimizationScheduling (production processes)Renewable energyElectric power systemDifferential evolution

Identifiers

DOI
10.1109/TIA.2020.2976909
Journal
IEEE Transactions on Industry Applications
Year
2020