Multi-Objective Security Constrained Unit Commitment via Hybrid Evolutionary Algorithms-Reference-Cited by-同舟云学术

Multi-Objective Security Constrained Unit Commitment via Hybrid Evolutionary Algorithms

Published:2024 Issue: Volume:12 Page:6698-6718
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ali Aamir¹^ORCID,Shah Arslan¹,Keerio Muhammad Usman¹,Mugheri Noor Hussain¹^ORCID,Abbas Ghulam²^ORCID,Touti Ezzeddine³,Hatatah Mohammed⁴,Yousef Amr⁵^ORCID,Bouzguenda Mounir⁶

Affiliation:

1. Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, Pakistan

2. School of Electrical Engineering, Southeast University, Nanjing, China

3. Department of Electrical Engineering, College of Engineering, Northern Border University, Arar, Saudi Arabia

4. Department of Electrical Engineering, Al-Baha University, Alaqiq, Saudi Arabia

5. Department of Electrical Engineering, College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia

6. Department of Electrical Engineering, King Faisal University, Al-Ahsa, Saudi Arabia

Funder

Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10385080.pdf?arnumber=10385080

Reference57 articles.

1. A Comprehensive Review of Security-constrained Unit Commitment

2. Stochastic Optimization for Unit Commitment—A Review

3. Unit Commitment—A Bibliographical Survey

4. Optimal site and size of FACTS devices with the integration of uncertain wind generation on a solution of stochastic multi-objective optimal power flow problem

5. Profit-based unit commitment problem: A review of models, methods, challenges, and future directions

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