Welcome to the InfoSci Platform
Vehicle-to-Grid and Electric Vehicle-Integrated Demand Response Management

Vehicle-to-Grid and Electric Vehicle-Integrated Demand Response Management

Bavly Hanna
Copyright: © 2023 |Pages: 19
ISBN13: 9781668466315|ISBN10: 1668466317|ISBN13 Softcover: 9781668466322|EISBN13: 9781668466339
DOI: 10.4018/978-1-6684-6631-5.ch012
Cite Chapter Cite Chapter

MLA

Hanna, Bavly. "Vehicle-to-Grid and Electric Vehicle-Integrated Demand Response Management." Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles, edited by S. Angalaeswari, et al., IGI Global, 2023, pp. 250-268. https://doi.org/10.4018/978-1-6684-6631-5.ch012

APA

Hanna, B. (2023). Vehicle-to-Grid and Electric Vehicle-Integrated Demand Response Management. In S. Angalaeswari, T. Deepa, & L. Kumar (Eds.), Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles (pp. 250-268). IGI Global. https://doi.org/10.4018/978-1-6684-6631-5.ch012

Chicago

Hanna, Bavly. "Vehicle-to-Grid and Electric Vehicle-Integrated Demand Response Management." In Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles, edited by S. Angalaeswari, T. Deepa, and L. Ashok Kumar, 250-268. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6631-5.ch012

Export Reference

Mendeley
Favorite

Abstract

The safe and efficient functioning of microgrids (MGs) has always depended on the best scheduling of MGs with renewable uncertainty. Electric vehicles (EVs) can back-feed power to the electrical grid to provide a variety of ancillary services, including demand response (DR), peak-load management, voltage support, and frequency regulation. This technology also enables EV holders to reduce their energy costs and make money through price arbitrage. Vehicle-to-grid (V2G) technology is developing quickly, and research is being done to improve its usability and use. The benefits of V2G include ancillary services, active power support, reactive power compensation, and promoting the use of renewable energy sources. In contrast, the challenges of V2G include battery degradation, effects on distribution equipment, elevated investment cost, and social obstacles.There are three main algorithms to optimize EV DR management: the artificial neural network, machine learning, and nature-inspired algorithm. The successful V2G-based DR strategies for energy management are covered in this chapter.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.