Optimal electric vehicles charging scheduling for energy and reserve markets considering wind uncertainty and generator contingency

Summary Decarburization of electrical systems encourage high wind power into electric power systems and the electrification of transport sectors through electric vehicles (EVs). The increasing penetration of uncertain wind power generation and transportation networks via EV charging stations has int...

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Published in:International journal of energy research Vol. 46; no. 4; pp. 4516 - 4539
Main Authors: Gupta, Pranda Prasanta, Kalkhambkar, Vaiju, Sharma, Kailash Chand, Jain, Prerna, Bhakar, Rohit
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Inc 25.03.2022
Subjects:
bender's decomposition
Contingency
Contingency ranking
Decarburization
Electric power
Electric power generation
Electric power sources
Electric power systems
electric vehicle
Electric vehicle charging
Electric vehicles
Electricity
Electricity distribution
Energy
Energy reserves
generator response
Operating costs
Optimization
Outages
Ranking
Scheduling
Security
stochastic security‐constrained unit commitment
transportation network
Transportation networks
Uncertainty
Unit commitment
Vehicles
Wind power
Wind power generation
wind uncertainty
ISSN:0363-907X, 1099-114X
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Summary:Summary Decarburization of electrical systems encourage high wind power into electric power systems and the electrification of transport sectors through electric vehicles (EVs). The increasing penetration of uncertain wind power generation and transportation networks via EV charging stations has introduced challenges for system operators to manage power systems and market operations. In this context, this paper presents a stochastic AC security‐constrained unit commitment (SCUC) model to clear day‐ahead energy and reserve markets considering transportation–electricity networks through EV charging stations in the presence of uncertain wind power and generator contingency. Pre‐contingency ranking is a common strategy for reducing the time of the SCUC problem, but it provides high‐impact outages. To address this issue, generator outages ranked first are identified using the post‐contingency generator response ranking approach. The main contribution of this paper is the development of a structure with the most effective outages in the presence of uncertain wind power and transportation networks. The stochastic optimization approach is modeled through scenarios with corresponding probabilities to manage the wind uncertainty. The computationally complex proposed model is solved by a prominent bender decomposition approach. Case studies are shown on a modified IEEE 118‐bus system with 26 nodes and 74 connected links of the electricity transportation network. The results show that optimal EV travel scheduling can optimize the transportation network and a sufficient energy reserve, confirming the security of the power system with minimum operating cost.
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ISSN:0363-907X
1099-114X
DOI:10.1002/er.7446