Optimal clustering-based operation of smart railway stations considering uncertainties of renewable energy sources and regenerative braking energies
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F22%3A43965799" target="_blank" >RIV/49777513:23220/22:43965799 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S037877962200801X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S037877962200801X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.epsr.2022.108744" target="_blank" >10.1016/j.epsr.2022.108744</a>
Alternative languages
Result language
angličtina
Original language name
Optimal clustering-based operation of smart railway stations considering uncertainties of renewable energy sources and regenerative braking energies
Original language description
The smart railway stations (SRSs), as prosumer microgrids, are considered active users in smart grids. By utilizing regenerative braking energy (RBE) and renewable energy resources (RERs) along with energy storage systems (ESSs), these SRSs can participate in the prosumer market. The uncertainties of RERs in SRSs due to meteorological factors have been studied in the literature. However, there is a research gap in developing a stochastic method for optimized operating of SRSs considering the RBE uncertainties besides the RER, load, and number of passengers’ uncertainties. In this paper, a new probabilistic clustering-based framework for the optimal operation of SRSs is presented. By applying Monte Carlo Simulations (MCS), several scenarios are generated and then clustered by the k-means algorithm. The introduced method is applied to an actual SRS in Tehran Urban and Suburban Railway Operation Company. The test results of the MCS, deterministic, and proposed scenario-based approaches are compared to illustrate the proposed method. Test results imply that the related error of the scenario-based method under the real-time pricing can be less than 4.4%, while the computation time significantly decreases. Furthermore, sensitivity analysis is done to determine how the exchanging power constraints and ESS capacity might influence the SRS operation.
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
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ELECTRIC POWER SYSTEMS RESEARCH
ISSN
0378-7796
e-ISSN
1873-2046
Volume of the periodical
213
Issue of the periodical within the volume
December 2022
Country of publishing house
CH - SWITZERLAND
Number of pages
15
Pages from-to
1-15
UT code for WoS article
000863067700002
EID of the result in the Scopus database
2-s2.0-85136575590