A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

Ren, Huiting; Hou, Xuemei; Jia, Zhichun; Mashhadi, Arsam

doi:10.1049/rpg2.12744

Cited by 3 publications

(1 citation statement)

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“…[18]. Furthermore, numerous optimization approaches, such as genetic algorithms [19]- [21], chaotic map-based chameleon Swarm Algorithm [22], the Sunflower (SFO) algorithm [23], Artificial Rabbits Optimizer [24], the Cuttlefish optimization algorithm [25], the particle swarm optimization (PSO) [26]- [29], particle swarm optimizationgravitational search algorithm [30], Artificial Fish Swarm Algorithm [31], and improved Mutation particle swarm optimization [32]. Many of these approaches possess both advantages and challenges [33].…”

Section: A Problem Statementmentioning

confidence: 99%

Adaptive-Width Generalized Correntropy Diffusion Algorithm for Robust Control Strategy of Microgrid Autonomous Operation

Hussien,

Hasanien,

Qais

et al. 2023

IEEE Access

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This study introduces a new method for achieving the robust performance of an isolated microgrid (MG) using an adaptive-width generalized correntropy diffusion algorithm (AWGC-DA). In the approach, the width of the kernel is adjustable, allowing the program to reject misleading input from attackers; the technique may identify attackers using a simple identification rule. The Response Surface Methodology is utilized in combination with three optimization algorithms: the Coot bird metaheuristic optimizer (COOT), the sunflower optimization (SFO), and the particle swarm optimization (PSO) to improve the technique's effectiveness. To assess the effectiveness of the new technique, a standard microgrid is tested under three different scenarios: (1) disconnected from the utility grid (autonomous status); (2) variations in load while in autonomous status; and (3) a three-phase fault while in autonomous status. In addition, numerous simulations are performed using the PSCAD/EMTDC software to verify the efficacy of the proposed technique. The main contribution of this study is to enhance the system transients by minimizing the overshoots, steady state error, and settling time which increases the efficacy of the autonomous MG process. Finally, to demonstrate its validity, the performance of the suggested approach is compared to that of other methods, including the LMSRE-based adaptive control, EBS-ABA, COOT, SFO, and PSO algorithms. The results confirm that the AWGC-DA method outperforms the other methods regarding the system's transient response.

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Section: A Problem Statementmentioning

confidence: 99%

Adaptive-Width Generalized Correntropy Diffusion Algorithm for Robust Control Strategy of Microgrid Autonomous Operation

Hussien,

Hasanien,

Qais

et al. 2023

IEEE Access

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A comprehensive survey of artificial intelligence-based techniques for performance enhancement of solid oxide fuel cells: Test cases with debates

Ashraf,

Draz

2024

Artif Intell Rev

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Since installing solid oxide fuel cells (SOFCs)-based systems suffers from high expenses, accurate and reliable modeling is heavily demanded to detect any design issue prior to the system establishment. However, such mathematical models comprise certain unknowns that should be properly estimated to effectively describe the actual operation of SOFCs. Accordingly, due to their recent promising achievements, a tremendous number of metaheuristic optimizers (MHOs) have been utilized to handle this task. Hence, this effort targets providing a novel thorough review of the most recent MHOs applied to define the ungiven parameters of SOFCs stacks. Specifically, among over 300 attempts, only 175 articles are reported, where thirty up-to-date MHOs from the last five years are comprehensively illustrated. Particularly, the discussed MHOs are classified according to their behavior into; evolutionary-based, physics-based, swarm-based, and nature-based algorithms. Each is touched with a brief of their inspiration, features, merits, and demerits, along with their results in SOFC parameters determination. Furthermore, an overall platform is constructed where the reader can easily investigate each algorithm individually in terms of its governing factors, besides, the simulation circumstances related to the studied SOFC test cases. Over and above, numerical simulations are also introduced for commercial SOFCs’ stacks to evaluate the proposed MHOs-based methodology. Moreover, the mathematical formulation of various assessment criteria is systematically presented. After all, some perspectives and observations are provided in the conclusion to pave the way for further analyses and innovations.

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Techno‐economic optimization framework of renewable hybrid photovoltaic/wind turbine/fuel cell energy system using artificial rabbits algorithm

Menesy,

Almomin,

Sultan

et al. 2024

IET Renewable Power Gen

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In order to maximize the electricity supply from clean energy sources, the goal of the smart power system is to unite all renewable energy sources. The goal of the present study is to use three optimization techniques, artificial rabbits optimization algorithm (ARO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA), to reduce the cost of electricity (COE) while improving the reliability of the power supply for rural areas. While using the same control variables for the optimization methods and load profile, various hybrid system configurations are explored. Photovoltaic, wind turbine, fuel cell, and electrolyser systems are all involved in the proposed hybrid renewable system. The ARO methodology is more effective than the GWO, WOA, and PSO procedures in terms of net present cost (NPC) and cost of energy (COE) generation, according to data comparing the three optimization techniques with the traditional Particle Swarm Optimization (PSO) method. The proposed ARO reached a value of COE of 0.4412$/kWh compared to 0.4438$/kWh for GWO, 0.4443$/kWh for WOA, and 0.44378$/kWh for PSO.

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A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

Cited by 3 publications

References 50 publications

Adaptive-Width Generalized Correntropy Diffusion Algorithm for Robust Control Strategy of Microgrid Autonomous Operation

Adaptive-Width Generalized Correntropy Diffusion Algorithm for Robust Control Strategy of Microgrid Autonomous Operation

A comprehensive survey of artificial intelligence-based techniques for performance enhancement of solid oxide fuel cells: Test cases with debates

Techno‐economic optimization framework of renewable hybrid photovoltaic/wind turbine/fuel cell energy system using artificial rabbits algorithm

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