This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Open AccessArticle
Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids
by
Faa-Jeng Lin
Faa-Jeng Lin 1,
Su-Ying Lu
Su-Ying Lu 1,2,
Ming-Che Hu
Ming-Che Hu 3,* and
Yen-Haw Chen
Yen-Haw Chen 2
1
Department of Electrical Engineering, National Central University, Taoyuan 320, Taiwan
2
Research Division 1, Taiwan Institute of Economic Research, Taipei 104, Taiwan
3
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 106, Taiwan
*
Author to whom correspondence should be addressed.
Energies 2024, 17(15), 3726; https://doi.org/10.3390/en17153726 (registering DOI)
Submission received: 14 June 2024
/
Revised: 15 July 2024
/
Accepted: 26 July 2024
/
Published: 28 July 2024
Abstract
This study combines the Nash–Cournot competition model and the stochastic optimization model to examine the impact of electric vehicle (EV) quantity fluctuations on microgrid operations, aiming to optimize energy usage in a competitive electricity market. Integrating distributed energy resources and bidirectional charging, microgrids offer a novel approach for energy optimization, aiding in renewable energy generation, peak demand management, and emission reduction. Empirical evidence highlights benefits in Taiwan’s electricity market and net-zero emissions target by 2050, with a case study demonstrating enhanced local renewable energy generation due to EVs and microgrid integration. As the number of EVs increases, electricity sales from microgrids decline, but electricity purchases remain stable. The degree of electricity liberalization also influences the supply and demand dynamics of the electricity market. Microgrids selling electricity only to the main grid increases total power consumption by 65.55 million MWh, reducing the market share of the state-owned utility (Taipower). Conversely, allowing retailers to purchase from microgrids increases total consumption by 30.87 million MWh with a slight market share decrease for Taipower. This study contributes to providing an adaptable and flexible general model for future studies to modify and expand based on different scenarios and variables to shape energy and environmental policies.
Share and Cite
MDPI and ACS Style
Lin, F.-J.; Lu, S.-Y.; Hu, M.-C.; Chen, Y.-H.
Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids. Energies 2024, 17, 3726.
https://doi.org/10.3390/en17153726
AMA Style
Lin F-J, Lu S-Y, Hu M-C, Chen Y-H.
Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids. Energies. 2024; 17(15):3726.
https://doi.org/10.3390/en17153726
Chicago/Turabian Style
Lin, Faa-Jeng, Su-Ying Lu, Ming-Che Hu, and Yen-Haw Chen.
2024. "Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids" Energies 17, no. 15: 3726.
https://doi.org/10.3390/en17153726
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details
here.
Article Metrics
Article metric data becomes available approximately 24 hours after publication online.