Article
Mathematics
Mokhtar Said, Ali M. El-Rifaie, Mohamed A. Tolba, Essam H. Houssein, Sanchari Deb
Summary: Economic Load Dispatch is a critical issue in power engineering, aiming to minimize production costs and reduce emissions. The Chameleon Swarm Algorithm showed promising performance in addressing this problem.
Article
Multidisciplinary Sciences
Ijaz Ahmed, Um-E-Habiba Alvi, Abdul Basit, Tayyaba Khursheed, Alwena Alvi, Keum-Shik Hong, Muhammad Rehan
Summary: In this paper, a novel soft computing optimization technique is proposed for solving the dynamic economic dispatch problem (DEDP) of complex non-convex machines with several constraints. The proposed hybrid method GA-SQP converges to achieve the best optimal solution in a confined environment in a limited number of simulations, demonstrating applicability and adequacy over conventional methods.
Article
Multidisciplinary Sciences
Khaldon Ahmed Qaid, Aziah Khamis, Chin Kim Gan
Summary: An optimal economic dispatch model is proposed for networked microgrids using particle swarm optimization. The model aims to minimize load shedding and operation costs. The model is evaluated using two IEEE 9-bus test systems and the results show a reduction in operation costs and load shedding for the networked microgrids. The findings also suggest that networked operation and power sharing strategies improve the performance of the microgrids.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Energy & Fuels
Miel Sharf, Iliya Romm, Michael Palman, Daniel Zelazo, Beni Cukurel
Summary: This work addresses the economic dispatch problem for a single micro gas turbine and presents a robust optimization-based approach to handle the uncertainty of power and heat demands. Two different choices of uncertainty sets are considered, and the problems are transformed into robust shortest-path problems. Efficient algorithms for solving these problems are provided.
Article
Computer Science, Artificial Intelligence
Subhamay Basu, Mousumi Basu
Summary: This manuscript introduces a modified student psychology-based optimization (MSPBO) algorithm for the convoluted economic dispatch problem. Simulation results demonstrate that the suggested MSPBO algorithm is capable of delivering better outcomes.
APPLIED ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Qisong Song, Liya Yu, Shaobo Li, Naohiko Hanajima, Xingxing Zhang, Ruiqiang Pu
Summary: In this study, particle swarm optimization (PSO) algorithm and ant colony optimization (ACO) algorithm were optimized to improve the comprehensive performance of energy dispatching between different sites. A new improved PSO-ACO algorithm was proposed based on hybrid algorithm to address the issue of poor energy dispatching efficiency between sites. The algorithm introduced multiobjective performance indicators, vitality factor, transformation of PSO routes into ant colony enhancement pheromone, angle guidance function, and high-quality pheromone update rule to enhance the optimization capability and convergence speed. Simulation experiments were conducted to compare the algorithm with other methods, and the results demonstrated that the improved PSO-ACO algorithm achieved shorter routes, lower time consumption, and higher security in energy dispatching optimization.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Mohammad Amin Akbari, Mohsen Zare, Rasoul Azizipanah-abarghooee, Seyedali Mirjalili, Mohamed Deriche
Summary: Motivated by cheetah hunting strategies, this paper proposes a nature-inspired algorithm called the cheetah optimizer (CO), which is shown to outperform other algorithms in extensive testing on benchmark functions and engineering problems.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Multidisciplinary
Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Sharif Naser Makhadmeh, Iyad Abu Doush, Raed Abu Zitar, Samah Alshathri, Mohamed Abd Elaziz
Summary: This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer for solving economic load dispatch (ELD) problems. The proposed method achieves significant performance in various ELD cases and can be considered as an efficient alternative for solving ELD problems.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Zhongda Chu, Subhash Lakshminarayana, Balarko Chaudhuri, Fei Teng
Summary: This paper investigates optimal mitigation strategy against large-scale load-altering attacks (LAAs) on IoT enabled high-wattage electrical appliances. The proposed Cyber-Resilient Economic Dispatch (CRED) concept coordinates the frequency droop control gains of Inverter-Based Resources (IBRs) to mitigate the destabilizing effect of LAAs while minimizing the overall operational cost.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Multidisciplinary
Hilmy Awad, Yasser Fathi Nassar, Ahmed Hafez, Mohamed K. Sherbiny, Alaa. F. M. Ali
Summary: This article proposes a rooftop photovoltaic system for fulfilling the load demand of Assuit University, and explores its economic and technical feasibility. Particle Swarm Optimization is used to determine the optimal quantity of photovoltaic modules, and robust load forecasting models are developed. The results demonstrate the economic efficacy of the proposed system and the advantages of Particle Swarm Optimization in sizing.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Thermodynamics
Shengping Xu, Guojiang Xiong, Ali Wagdy Mohamed, Houssem R. E. H. Bouchekara
Summary: This paper presents an improved comprehensive learning particle swarm optimization (CLPSO) named FV-ICLPSO to solve the optimization problem of economic dispatch in power systems. The proposed method demonstrates a significant advantage in convergence speed and is validated in multiple practical cases.
Article
Thermodynamics
Ali Saleh Aziz, Mohammad Faridun Naim Tajuddin, Moaid K. Hussain, Mohd Rafi Adzman, Nur Hafizah Ghazali, Makbul A. M. Ramli, Tekai Eddine Khalil Zidane
Summary: A new dispatch strategy based on the HOMER-MATLAB Link Controller is proposed to overcome the limitations of the default HOMER strategies. The results show that the proposed strategy offers the best economic and environmental performance.
Article
Thermodynamics
Wenqiang Yang, Xinxin Zhu, Qinge Xiao, Zhile Yang
Summary: This paper proposes an improved version of the multi-objective marine predator algorithm (IMOMPA) for solving the optimization of multi-objective dynamic economic-grid fluctuation dispatch (MODEGD). The IMOMPA algorithm improves population diversity, convergence speed, and global search ability. Numerical experiments on benchmark functions and generation units demonstrate the superiority of the IMOMPA algorithm, and plug-in electric vehicles (PEVs) connected to the grid (V2G) can help mitigate grid fluctuations.
Article
Thermodynamics
Maryam Parvin, Hossein Yousefi, Younes Noorollahi
Summary: This study applied a multi-objective particle swarm optimization algorithm to three renewable micro grid configurations in Shiraz, Iran. The results showed that the simultaneous utilization of wind and solar energy was more beneficial, especially when considering carbon tax policies or renewable energy incentives for future applications.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Umair Ahmad Salaria, Muhammad Ilyas Menhas, Sohaib Manzoor
Summary: Power companies are interested in making strategic decisions to maintain profitable energy systems; Economic Load Dispatch is a complex decision-making process, where metaheuristic methods like PSO can be used to address the complexity; The proposed GPSO-w and QPGPSO-w methods showed excellent performance in solving the ELD problem.
