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Wyszukujesz frazę "evolution algorithm" wg kryterium: Temat

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    Tytuł:
    Improved Differential Evolution Algorithm to solve multi-objective of optimal power flow problem
    Autorzy:
    Al-Kaabi, Murtadha
    Hasheme, Jaleel Al
    Al-Bahrani, Layth
    Powiązania:
    https://bibliotekanauki.pl/articles/2135728.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Multi-objective Improved Differential Evolution Algorithm
    MOIDEA
    optimal power flow
    OPF
    set of Pareto front solutions
    multi-objective function problems
    fuel costs considering emissions
    fuel costs considering real power losses
    fuel costs considering voltage deviation
    Opis:
    This article presents a new efficient optimization technique namely the Multi- Objective Improved Differential Evolution Algorithm (MOIDEA) to solve the multiobjective optimal power flow problem in power systems. The main features of the Differential Evolution (DE) algorithm are simple, easy, and efficient, but sometimes, it is prone to stagnation in the local optima. This paper has proposed many improvements, in the exploration and exploitation processes, to enhance the performance of DE for solving optimal power flow (OPF) problems. The main contributions of the DE algorithm are i) the crossover rate will be changing randomly and continuously for each iteration, ii) all probabilities that have been ignored in the crossover process have been taken, and iii) in selection operation, the mathematical calculations of the mutation process have been taken. Four conflicting objective functions simultaneously have been applied to select the Pareto optimal front for the multi-objective OPF. Fuzzy set theory has been used to extract the best compromise solution. These objective functions that have been considered for setting control variables of the power system are total fuel cost (TFC), total emission (TE), real power losses (RPL), and voltage profile (VP) improvement. The IEEE 30-bus standard system has been used to validate the effectiveness and superiority of the approach proposed based on MATLAB software. Finally, to demonstrate the effectiveness and capability of the MOIDEA, the results obtained by this method will be compared with other recent methods.
    Źródło:
    Archives of Electrical Engineering; 2022, 71, 3; 641--657
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Novel optimization method for mobile magnetostatic shield and test applications
    Autorzy:
    Ralf, Patrick Alexander
    Kreischer, Christian
    Powiązania:
    https://bibliotekanauki.pl/articles/2135737.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    differential evolution
    evolutionary algorithm
    magnetostatic passive shielding
    mobile application
    optimization
    spherical shells
    Opis:
    This article provides an optimized solution to the problem of passive shielding against static magnetic fields with any number of spherical shells. It is known, that the shielding factor of a layered structure increases in contrast to a single shell with the same overall thickness. For the reduction of weight and cost by given material parameters and available space the best system for the layer positions has to be found. Because classic magnetically shielded rooms are very heavy, this system will be used to develop a transportable Zero-Gauss-Chamber. To handle this problem, a new way was developed, in which for the first time the solution with regard to shielding and weight was optimized. Therefore, a solution for the most general case of spherical shells was chosen with an adapted boundary condition. This solution was expanded to an arbitrary number of layers and permeabilities. With this analytic solution a differential evolution algorithm is able to find the best partition of the shells. These optimized solutions are verified by numerical solutions made by the Finite Element Method (FEM). After that the solutions of different raw data are determined and investigated.
    Źródło:
    Archives of Electrical Engineering; 2022, 71, 3; 627--639
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation
    Autorzy:
    Pandiarajan, K.
    Babulal, C. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/141059.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    non-dominated sorting genetic algorithm
    generation rescheduling
    particle swarm optimization (PSO)
    differential evolution
    overload index
    Opis:
    This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem
    Źródło:
    Archives of Electrical Engineering; 2014, 63, 3; 367-384
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices
    Autorzy:
    Bhattacharyya, B.
    Gupta, V. K.
    Kumar, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/141459.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    FACTS devices
    line power flow
    FACTS devices & its optimal locations
    genetic algorithm
    differential evolution technique
    Opis:
    The problem of improving the voltage profile and reducing power loss in electrical networks must be solved in an optimal manner. This paper deals with comparative study of Genetic Algorithm (GA) and Differential Evolution (DE) based algorithm for the optimal allocation of multiple FACTS (Flexible AC Transmission System) devices in an interconnected power system for the economic operation as well as to enhance loadability of lines. Proper placement of FACTS devices like Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC) and controlling reactive generations of the generators and transformer tap settings simultaneously improves the system performance greatly using the proposed approach. These GA & DE based methods are applied on standard IEEE 30 bus system. The system is reactively loaded starting from base to 200% of base load. FACTS devices are installed in the different locations of the power system and system performance is observed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. GA and DE based algorithm is then applied to find the amount of magnitudes of the FACTS devices. Finally the comparison between these two techniques for the placement of FACTS devices are presented.
    Źródło:
    Archives of Electrical Engineering; 2013, 62, 4; 541-552
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The On-line Evolutionary Method for Soft Fault Diagnosis in Diode-transistor Circuits
    Autorzy:
    Korzybski, M.
    Ossowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/226980.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    electric circuit diagnosis
    soft faults
    multiple faults
    evolutionary computation
    gene expression programming
    genetic algorithm
    differential evolution
    Opis:
    The paper is devoted to diagnostic method enabling us to perform all the three levels of fault investigations - detection, localization and identification. It is designed for analog diode-transistor circuits, in which the circuit’s state is defined by the DC sources’ values causing elements operating points and the harmonic components with small amplitudes being calculated in accordance with small-signal circuit analysis rules. Geneexpression programming (GEP), differential evolution (DE) and genetic algorithms (GA) are a mathematical background of the proposed algorithms. Time consumed by diagnostic process rises rapidly with the increasing number of possible faulty circuit elements in case of using any of mentioned algorithms. The conncept of using two different circuit models with partly different elements allows us to decrease a number of possibly faulty elements in each circuit because some of possibly faulty elements are absent in one of two investigated circuits.
    Źródło:
    International Journal of Electronics and Telecommunications; 2015, 61, 1; 109-115
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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