Název:	Optimal clustering-based operation of smart railway stations considering uncertainties of renewable energy sources and regenerative braking energies
Autoři:	Akbari, Saeed Hashemi Dezaki, Hamed Fazel, Seyed Saeed
Citace zdrojového dokumentu:	AKBARI, S. HASHEMI DEZAKI, H. FAZEL, SS. Optimal clustering-based operation of smart railway stations considering uncertainties of renewable energy sources and regenerative braking energies. ELECTRIC POWER SYSTEMS RESEARCH, 2022, roč. 213, č. December 2022, s. 1-15. ISSN: 0378-7796
Datum vydání:	2022
Nakladatel:	Elsevier
Typ dokumentu:	článek article
URI:	2-s2.0-85136575590 http://hdl.handle.net/11025/50440
ISSN:	0378-7796
Klíčová slova v dalším jazyce:	energy management system (EMS);k-means algorithm;regenerative braking energy (RBE);renewable energy resources (RERs);smart railway station (SRS);uncertainty
Abstrakt v dalším jazyce:	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.
Práva:	Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Elsevier
Vyskytuje se v kolekcích:	Články / Articles (RICE) OBD

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