LAPSE:2023.33441
Published Article

LAPSE:2023.33441
A New Chaotic Artificial Bee Colony for the Risk-Constrained Economic Emission Dispatch Problem Incorporating Wind Power
April 21, 2023
Abstract
Due to the rapid increase in the consumption of electrical energy and the instability of fossil fuel prices, renewable energy, such as wind power (WP), has become increasingly economically competitive compared to other conventional energy production methods. However, the intermittent nature of wind energy creates certain challenges to the power network operation. The combined economic environmental dispatch (CEED) including WP is one of the most fundamental challenges in power system operation. Within this context, this paper presents a new attempt to solve the probabilistic CEED problem with WP penetration. The optimal WP to be incorporated in the grid is determined in such a way that the system security is within acceptable limits. The system security is described by various fuzzy membership functions in terms of the probability that power balance cannot be met. These membership functions are formulated based on the dispatcher’s attitude. This probabilistic and non-convex CEED problem is solved using a new technique combining chaos theory and artificial bee colony (ABC) technique. In this improved version of ABC (IABC), chaotic maps are used to generate initial solutions, and the random numbers involved in the standard ABC are substituted by chaotic sequences. The effectiveness of IABC is tested on two groups of benchmark functions and practical cases. The impacts of dispatcher’s attitude and risk level are investigated in the simulation section.
Due to the rapid increase in the consumption of electrical energy and the instability of fossil fuel prices, renewable energy, such as wind power (WP), has become increasingly economically competitive compared to other conventional energy production methods. However, the intermittent nature of wind energy creates certain challenges to the power network operation. The combined economic environmental dispatch (CEED) including WP is one of the most fundamental challenges in power system operation. Within this context, this paper presents a new attempt to solve the probabilistic CEED problem with WP penetration. The optimal WP to be incorporated in the grid is determined in such a way that the system security is within acceptable limits. The system security is described by various fuzzy membership functions in terms of the probability that power balance cannot be met. These membership functions are formulated based on the dispatcher’s attitude. This probabilistic and non-convex CEED problem is solved using a new technique combining chaos theory and artificial bee colony (ABC) technique. In this improved version of ABC (IABC), chaotic maps are used to generate initial solutions, and the random numbers involved in the standard ABC are substituted by chaotic sequences. The effectiveness of IABC is tested on two groups of benchmark functions and practical cases. The impacts of dispatcher’s attitude and risk level are investigated in the simulation section.
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Keywords
artificial bee colony, chance constraint problem, chaotic sequences, economic emission dispatch, risk level, security level
Subject
Suggested Citation
Alshammari ME, Ramli MAM, Mehedi IM. A New Chaotic Artificial Bee Colony for the Risk-Constrained Economic Emission Dispatch Problem Incorporating Wind Power. (2023). LAPSE:2023.33441
Author Affiliations
Alshammari ME: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Ramli MAM: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia [ORCID]
Mehedi IM: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia [ORCID]
Ramli MAM: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia [ORCID]
Mehedi IM: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia [ORCID]
Journal Name
Energies
Volume
14
Issue
13
First Page
4014
Year
2021
Publication Date
2021-07-03
ISSN
1996-1073
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Original Submission
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PII: en14134014, Publication Type: Journal Article
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LAPSE:2023.33441
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https://doi.org/10.3390/en14134014
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Apr 21, 2023
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