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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index
Published 2023“…Electric power plant loads; Learning algorithms; MATLAB; Multiobjective optimization; Optimization; Reactive power; Back tracking; Backtracking search algorithms; Identification method; Load-shedding; Multi-objective functions; Power flow simulation; System contingencies; Under voltage load shedding; Electric load shedding…”
Conference Paper -
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Optimal allocation of battery energy storage system using whale optimization algorithm
Published 2023Conference Paper -
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A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system
Published 2021“…This algorithm will help an IMG system to operate its generation systems optimally and economically along with PV generation unit. …”
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5
An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…The conventional PID controller is developed using MLSL optimization algorithm including the LFC loop to minimize the frequency deviation and regulate the power exchange because of the load disturbance changes in area1 and area2. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
text::Thesis -
7
Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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8
Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables
Published 2025Subjects:Article -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The HFPSO technique hybridizes the Firefly Optimization (FFO) algorithm and the Particle Swarm Optimization (PSO) method to improve the exploitation and exploration strategies and enhance the convergence rate. …”
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11
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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12
Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications
Published 2023“…Battery management systems; Charging (batteries); Controllers; Fuzzy logic; Fuzzy sets; Learning algorithms; Loading; Membership functions; Optimization; Particle swarm optimization (PSO); Secondary batteries; Backtracking search algorithms; Battery energy storage; Battery energy storage systems; Fuzzy controllers; Fuzzy logic control system; Fuzzy membership function; Micro grid; State of charge; Battery storage…”
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Optimum battery depth of discharge for off-grid solar PV/battery system
Published 2023“…Electric load loss; Genetic algorithms; Multiobjective optimization; Optimization; Secondary batteries; Battery systems; Cost of energies; Depth of discharges; Multi-objective optimization models; Non dominated sorting genetic algorithm (NSGA II); NSGA-II; Off-grid system; Solar PV systems; Loss of load probability…”
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Optimal load shedding in power system using back tracking search algorithm
Published 2024text::Final Year Project -
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Distributed generation allocation to reduce losses and improve voltage profile genetic algorithm: article
Published 2010“…This paper presents a method for the optimal allocation of Distributed generation in distribution systems. …”
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Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement
Published 2017“…The load flow algorithms from MATPOWER, harmonic load flow and method of fault position has been integrated in MATLAB environment to solve the multi-objective function. …”
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17
Application of genetic algorithm for optimal voltage control of the power system / Mohd Supian Yahya
Published 1998“…This project uses genetic algorithm (GA) for optimal voltage control of the power system and automatically will minimum a system loss. …”
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18
Energy Management in Integrated Microgrids: An Optimal Schedule Controller Utilizing Gradient Descent Algorithm
Published 2024“…Weather data, including wind, solar, fuel, and battery status, is integrated into the BGD algorithm for optimizing ON and OFF schedules. The results demonstrate a significant 46.3% reduction in energy consumption achieved by the BGD algorithm, contributing to the advancement of optimization algorithms for sustainable energy management. …”
Conference Paper -
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A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System
Published 2025Subjects:Conference paper -
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Optimal power flow solutions for power system operations using moth-flame optimization algorithm
Published 2021“…The comparison proves that MFO offers a better result compared to the other selected methods. In IEEE 30-bus test system, MFO outperform the other optimization methods with 967.589961$/h compared to 971.411400 $/h, 983.738069$/h, 975.346233$/h, 985.198050$/h, 1035.537820$/h for Improved Grey Wolf Optimizer (IGWO), Grey Wolf Optimizer (GWO), Ant Loin Optimizer (ALO), Whale Optimization Algorithm (WOA), and Sine Cosine Algorithm (SCA) respectively. …”
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