Search Results - (( loading optimization method algorithm ) OR ( parameter application system algorithm ))
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1
An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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2
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…Result shows that the CFA is the best optimization method due to its robustness and consistency. …”
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5
Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…The post-islanding frequency stability is maintained by optimizing the Load Frequency Control‘s parameters. …”
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6
Application of genetic algorithm for optimal voltage control of the power system / Mohd Supian Yahya
Published 1998“…Newton-raphson method is used for load flow calculation and determining the power losses. …”
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7
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Optimization of electrical wiring design in buildings using particle swarm optimization and genetic algorithm / Tuan Ahmad Fauzi Tuan Abdullah
Published 2017“…In this project, the main objective is to optimize the electrical distribution system design in buildings using optimization methods, which are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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10
Load dispatch optimization of open cycle industrial gas turbine plant incorporating operational, maintenance and environmental parameters
Published 2006“…The objective of this work is to develop a multi-objective optimization model and optimization algorithm for load dispatching optimization of open cycle gas turbine plant that not only consider operational parameters, but also incorporates maintenance and environmental parameters. …”
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11
Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li
Published 2018“…Comparison of the performance by using the proposed algorithm and other algorithms was made to identify which algorithm is better in controlling the performance of the AGC. …”
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13
Voltage constrained optimal power flow based using genetic algorithm
Published 2015“…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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14
An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
Published 2011“…This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). …”
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Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi
Published 2018“…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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16
An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach
Published 2017“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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Genetic algorithm for design optimization of 3-phase semi-conductor rectifier power transformers
Published 2007“…This paper presents the optimal design of a 3-phase rectifier power transformer supplying a dc load by Genetic Algorithm (GA). …”
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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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Alternative method for economic dispatch utilizing grey wolf optimizer
Published 2015“…In addition, the flexibility of this algorithm is a merit to solve different problems by only setting few parameters such as number of population and number of iteration without any special changes in the structure of the algorithm. …”
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