Search Results - (( loading optimization system algorithm ) OR ( using evolutionary method algorithm ))

A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System by Shukor S.F.A., Musirin I., Hamid Z.A., Senthil Kumar A.V., Mansor M.H., Salimin R.H.

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Immune multistage evolutionary programming (IMEP) for optimal load shedding approach for loss minimization / Muhammad Faris Baharuddin by Baharuddin, Muhammad Faris

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Swarm Evolutionary Programming Method for Optimal Under-Frequency Load Shedding Scheme by Lu, Michelle

“…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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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Multi -Objective Economic Dispatch Using Evolutionary Programming by Noor Azlan Bin Adnan

“…The designated algorithm of MOEP used MATLAB to run the simulations. …”

Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. …”
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Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation by Illias, Hazlee Azil, Zahari, A.F.M., Mokhlis, Hazlie

“…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 by Sulaima, Mohamad Fani, Wong, Kok Loong, Bohari, Zul Hasrizal, Mohd Nasir, Mohamad Na'im

“…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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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…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. …”

Optimal finite- time prescribed performance of servo pneumatic positioning with PID control tuning using an evolutionary mating algorithm by Addie Irawan, Hashim, M. H., Sulaiman, Mohd Iskandar Putra, Azahar

“…This paper presents an optimum tuning on finite-time prescribed performance with PID (FT-PPC-PID) controller using the Evolutionary Mating Algorithm (EMA) approach for a pneumatic servo system’s (PSS) rod-piston positioning. …”
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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 by Hanapi, Suhadiyana

“…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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Voltage constrained optimal power flow based using genetic algorithm by Yassir Asnawi, Teuku Hasannuddin

“…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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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm by Kahourzade, S., Mahmoudi, A., Mokhlis, Hazlie

“…To solve the multi-objective OPF problem, Pareto optimal method is used to form the Pareto optimal set. …”
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A decomposition/aggregation method for solving electrical power dispatch problems by Mansor M.H., Irving M.R., Taylor G.A.

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Optimal DG Placement and Sizing for Voltage Stability Improvement Using Backtracking Search Algorithm by Ruhaizad, Ishak, Azah, Mohamed, Abdalla, Ahmed N., Mohd Zamri, Che Wanik

“…A new evolutionary algorithm known as backtracking search algorithm (BSA) is opted in solving the optimization problem. …”
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A hybrid optimization technique for solving economic emission load dispatch problems by Aisyah binti Nordin

Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

“…Automatic Generation Control (AGC) is used for regulating the electrical power supply in two-area power system and changing the system frequency and tie-line load. …”
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Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system by Nur Zahirah, Mohd Ali

“…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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Multi-Objective PSO with Passive Congregation for Load Balancing Problem by Marufuzzaman M., Timu M.A., Sarkar J., Islam A., Rahman L.F., Sidek L.M.

“…Efficient load balancing can minimize the simulation time of HLA and this optimization can be done using the multi-objective evolutionary algorithms (MOEA). …”