Optimization Method for Energy Network Consumption Considering Marketing Objectives of Energy Vehicles

Authors

  • Nan Jiao Business School of College of Humanities & Information Changchun University of Technology, Changchun, 130122, China, Department of Global Business Administration of Shinhan University, Gyeonggi-do, Uijeongbu City, 11644, South Korea
  • Kewei Zhang Chassis Development Department of FAW Jiefang Commercial Vehicle Development Institute, Changchun, 130000, China
  • Hang Su Business School of College of Humanities & Information Changchun University of Technology, Changchun, 130122, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.40562

Keywords:

New energy vehicles, worker exposure, energy storage, consumption, battery, charging station, marketing

Abstract

As new energy vehicles continue to advance rapidly, a large number of charging stations and new energy generation systems have been established in various regions based on marketing goals. This study proposes an energy network consumption model based on energy integration strategy to address the effective consumption of intermittent and fluctuating energy in the power grid. By integrating different types of charging stations and intelligently adjusting prices at different time periods based on actual electricity consumption, the model accelerates energy consumption. The experiment outcomes indicate that the new model increases electricity consumption from 7208 kWh to 11240 kWh, reduces abandoned electricity from 4059 kWh to 27 kWh, and increases the profit of charging stations from 3604 yuan to 5620 yuan. In practical applications in a certain area, user consumption has decreased by 33.52%. From this, he new model can absorb energy networks and reduce resource waste. The research not only enhances the steadiness and economy of the energy network, but also reduces the charging cost for users, providing a new technology for promoting the development of new energy vehicles and improving the grid’s ability to absorb renewable energy.

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Author Biographies

Nan Jiao, Business School of College of Humanities & Information Changchun University of Technology, Changchun, 130122, China, Department of Global Business Administration of Shinhan University, Gyeonggi-do, Uijeongbu City, 11644, South Korea

Nan Jiao obtained her Master’s degree in Curriculum and Teaching Theory from Northeast Normal University in 2019. She is a doctoral student at Sinhan University in South Korea. Currently serving as a faculty member in the Business School of College of Humanities & Information Changchun University of Technology, she was awarded the professional title of Lecturer in E-Commerce in 2022. Her research focuses on e-commerce and management studies.

Kewei Zhang, Chassis Development Department of FAW Jiefang Commercial Vehicle Development Institute, Changchun, 130000, China

Kewei Zhang Obtained a Bachelor of Engineering from Harbin Institute of Technology (2017) and Obtained a Master’s degree in Mechanical Engineering from Shandong University (2020). Presently, he is working as a chassis testing engineer in the Chassis Development Department of FAW Jiefang Company, Commercial Vehicle Development Institute. He is mainly responsible for the testing and verification of commercial vehicle chassis products. He obtained the titles of Assistant Engineer (2021) and Intermediate Engineer (2023).

Hang Su, Business School of College of Humanities & Information Changchun University of Technology, Changchun, 130122, China

Hang Su obtained his Ph.D. in Management Science and Engineering from Jilin University in 2006. Currently, he serves as a professor and the dean of the Business School of College of Humanities & Information Changchun University of Technology. He is a graduate supervisor. His research interests lie in marketing.

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Published

2025-12-16

How to Cite

Jiao, N. ., Zhang, K. ., & Su, H. . (2025). Optimization Method for Energy Network Consumption Considering Marketing Objectives of Energy Vehicles. Distributed Generation &Amp; Alternative Energy Journal, 40(05-06), 923–946. https://doi.org/10.13052/dgaej2156-3306.40562

Issue

Section

Approaches on Intelligent Algorithms for Sustainable and Renewable Energy System