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1
Swarm Evolutionary Programming Method for Optimal Under-Frequency Load Shedding Scheme
Published 2017“…This thesis proposed a new method of incorporating swarm features into the optimization algorithm of Classical Evolutionary Programming (CEP) to derive optimal settings for the UFLS scheme. …”
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2
Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation
Published 2016“…Therefore, to overcome this situation, in this work, particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) algorithms were employed in a LFC of twoarea power system to optimise the performance of the PID controller. …”
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Investigation of load variant under power distribution network reconfiguration using EPSO algorithm
Published 2024“…Due to that reason, this study proposes the Evolutionary Particle Swarm Optimization (EPSO) algorithm which is a hybrid optimization technique that combines the principles of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) to solve optimization problems by reducing the power losses under Distribution Network Reconfiguration (DNR). …”
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
Published 2015“…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
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5
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025Subjects:Article -
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Voltage constrained optimal power flow based using genetic algorithm
Published 2015“…Active power generator, generator-buses voltages, transformer tap and injection capacitor are used as control parameters. Effectiveness of the proposed method was tested on IEEE 30 bus system and it has been compared to other optimization of power fl ow using other methods, for example the Evolutionary Programming (EP), Differential Evolution (DE) and Particle Swarm Optimization (PSO) methods. …”
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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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9
A 33kV distribution network feeder reconfiguration by Using REPSO for voltage profile improvement
Published 2014“…It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. …”
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10
Multi-Objective PSO with Passive Congregation for Load Balancing Problem
Published 2023“…Efficient load balancing can minimize the simulation time of HLA and this optimization can be done using the multi-objective evolutionary algorithms (MOEA). …”
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…Particle swarm optimization (PSO), evolutionary particle swarm optimization (EPSO), and ant colony optimization (ACO) algorithms were applied to optimize the simultaneous LM strategies of peak clipping, valley filling and load shifting in order to minimize the energy consumption and maximum demand costs, and improve economic indexes such as load factor and building economic efficiency response. …”
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12
A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
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Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li
Published 2018“…Also, using MEPSO-TVAC algorithm, the performance of AGC by using two PID controllers is better in terms of rise time and settling time than using one PID controller. …”
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14
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…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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Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system
Published 2013“…AI methods mainly include Artificial Neural Network (ANN), Expert System (ES), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). …”
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16
Electricity distribution network for low and medium voltages based on evolutionary approach optimization
Published 2015“…The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran
Published 2018“…The chosen optimization techniques in this work include evolutionary programming (EP), particle swarm optimization (PSO), gravitational Search Algorithm (GSA), and firefly algorithm (FA). …”
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19
An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions
Published 2024Subjects:Conference Paper -
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Particle swarm optimization technique for optimal economic load dispatch / Muhammad Hilmi Nordin
Published 2014“…In this proposal paper, an optimization technique called the Particle Swarm Optimization (PSO) technique that is a meta-heuristic optimization technique, are proposed to solve the economic load dispatch problem. …”
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