Automotive Science and Engineering
Iran University of Science & Technology
Fri, May 30, 2025
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Volume 15, Issue 2 (6-2025)
ASE 2025, 15(2): 4667-4677 |
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sobbouhi A, Mozaffari M. Reliability Assessment and Congestion Management of Power System with Electric Vehicles and Uncertain Renewable Resources. ASE 2025; 15 (2) :4667-4677
URL: http://ijae.iust.ac.ir/article-1-702-en.html
URL: http://ijae.iust.ac.ir/article-1-702-en.html
Shahid Beheshti University
Abstract: (393 Views)
The high penetration of renewable energy sources (RES) makes the power system unreliable due to its uncertain nature. In this paper, the quantifying impact of electric vehicles (EV) charging and discharging on power system reliability and relieving the congestion is analyzed. The proposed reliability assessment is formulated by considering generation and demand interruption costs for N-1 contingency criteria. The proposed algorithm manages the optimal scheduling of EV to mitigate the uncertainties associated with RES and relieving the congestion. The impact of EV charging and discharging on expected energy not supplied (EENS) and expected interruption cost (ECOST) for generating companies (GENCOs), transmission companies (TRANSCOs), customers, and entire power system are calculated. The charging station of EV is selected by the trade-o_ between investment cost of EV and percentage change in EENS and ECOST value for the entire power system, GENCOs, TRANSCOs, and customers. The effectiveness of the proposed approach is tested on the modified IEEE RTS 24 bus system. The impact of EV charging stations on system reliability has been evaluated by quantifying the EENS and the ECOST across all available EV capacities. The results clearly demonstrate the improvement of system reliability and minimize the objective function consisting of generator re-dispatch and load curtailment considering N-1 contingency in the face of uncertainties of wind and solar generation sources by considering EV. The results show that EV can improve the reliability by about 40%. The problem is modeled in GAMS environment and solved using CONOPT as a nonlinear programming (NLP) solver.
Type of Study: Research |
Subject:
Storage systems (battery, ultracapacitor, flywheel, etc)
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