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A New Chaotic Artificial Bee Colony for the Risk-Constrained Economic Emission Dispatch Problem Incorporating Wind Power

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  • Motaeb Eid Alshammari

    (Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Makbul A. M. Ramli

    (Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Ibrahim M. Mehedi

    (Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

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.

Suggested Citation

  • Motaeb Eid Alshammari & Makbul A. M. Ramli & Ibrahim M. Mehedi, 2021. "A New Chaotic Artificial Bee Colony for the Risk-Constrained Economic Emission Dispatch Problem Incorporating Wind Power," Energies, MDPI, vol. 14(13), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:4014-:d:588012
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    References listed on IDEAS

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    4. Motaeb Eid Alshammari & Makbul A. M. Ramli & Ibrahim M. Mehedi, 2020. "An Elitist Multi-Objective Particle Swarm Optimization Algorithm for Sustainable Dynamic Economic Emission Dispatch Integrating Wind Farms," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
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    Cited by:

    1. Motaeb Eid Alshammari & Makbul A. M. Ramli & Ibrahim M. Mehedi, 2022. "Hybrid Chaotic Maps-Based Artificial Bee Colony for Solving Wind Energy-Integrated Power Dispatch Problem," Energies, MDPI, vol. 15(13), pages 1-26, June.
    2. Benyekhlef Larouci & Ahmed Nour El Islam Ayad & Hisham Alharbi & Turki E. A. Alharbi & Houari Boudjella & Abdelkader Si Tayeb & Sherif S. M. Ghoneim & Saad A. Mohamed Abdelwahab, 2022. "Investigation on New Metaheuristic Algorithms for Solving Dynamic Combined Economic Environmental Dispatch Problems," Sustainability, MDPI, vol. 14(9), pages 1-27, May.

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