Electrification of transportation: A hybrid Benders/SDDP algorithm for optimal charging station trading
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00377469" target="_blank" >RIV/68407700:21230/24:00377469 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/24:00377469
Result on the web
<a href="https://doi.org/10.1016/j.ijhydene.2024.09.345" target="_blank" >https://doi.org/10.1016/j.ijhydene.2024.09.345</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijhydene.2024.09.345" target="_blank" >10.1016/j.ijhydene.2024.09.345</a>
Alternative languages
Result language
angličtina
Original language name
Electrification of transportation: A hybrid Benders/SDDP algorithm for optimal charging station trading
Original language description
This paper examines the electrification of transportation as a response to environmental challenges caused by fossil fuels, exploring the potential of battery electric vehicles and hydrogen fuel cell vehicles as alternative solutions. However, a significant barrier to their widespread adoption is the limited availability of charging infrastructure. Therefore, this study proposes the development of comprehensive charging stations capable of accommodating both battery and hydrogen vehicles to address this challenge. The energy is purchased from the day-ahead and intraday auction-based electricity markets, where the electricity price is subject to uncertainty. Therefore, a two-stage stochastic programming model is formulated while the price scenarios are generated utilizing a k-means clustering algorithm. Given the complexity of the proposed model, an efficient solution approach is developed through the hybridization of the Benders decomposition algorithm and stochastic dual dynamic programming. In the Benders master problem, day-ahead bidding variables are determined, whereas the Benders sub-problem addresses intraday bidding and charging station scheduling variables, employing stochastic dual dynamic programming to tackle its intractability. Additionally, we transform the mixed integer linear program model of the second stage problem into a linear program, confirming its validity through KKT conditions. Our model provides practical insights for making informed decisions in electricity markets based on sequential auctions. While the bidding curves submitted to the day-ahead market remain unaffected by scenarios, those submitted to the intra-day market show dependence on fluctuations in day-ahead market prices. 2024 Hydrogen Energy Publications LLC.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Hydrogen Energy
ISSN
0360-3199
e-ISSN
1879-3487
Volume of the periodical
89
Issue of the periodical within the volume
November
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
15
Pages from-to
1060-1074
UT code for WoS article
001331440700001
EID of the result in the Scopus database
2-s2.0-85205337567