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    Wyświetlanie 1-8 z 8
    Tytuł:
    New solutions to a multi-objective benchmark problem of induction heating: an application of computational biogeography and evolutionary algorithms
    Autorzy:
    Di Barba, P.
    Dughiero, F.
    Forzan, M.
    Mognaschi, M. E.
    Sieni, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/140925.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    induction heating
    multi-physics analysis
    multi-objective optimization
    benchmark
    Opis:
    In induction heating the design of the inductor implies the solution of coupled electromagnetic and thermal fields, along with the use of optimal design procedures to identify the best possible device or process. The benchmark model proposed, a graphite disk heated by means of induction, is optimized using different optimization algorithms. The design aim requires to achieve a prescribed and uniform temperature distribution in the workpiece maximizing the system efficiency.
    Źródło:
    Archives of Electrical Engineering; 2018, 67, 1; 139-149
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Genetic algorithm as a tool for multi-objective optimization of permanent magnet disc motor
    Autorzy:
    Cvetkovski, G.
    Petkovska, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/141012.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    design optimisation
    electric vehicle
    genetic algorithm
    multi-objective optimisation
    permanent magnet disc motor
    Opis:
    The analysed permanent magnet disc motor (PMDM) is used for direct wheel drive in an electric vehicle. Therefore there are several objectives that could be tackled in the design procedure, such as an increased efficiency, reduced iron weight, reduced copper weight or reduced weight of the permanent magnets (reduced rotor weight). In this paper the optimal design of PMDM using a multi-objective genetic algorithm optimisation procedure is performed. A comparative analysis of the optimal motor solution and its parameters in relation to the prototype is presented.
    Źródło:
    Archives of Electrical Engineering; 2016, 65, 2; 285-294
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller
    Autorzy:
    Suresh, C. V.
    Sivanguraju, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/141441.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    generalized unified power flow controller
    optimal reactive power dispatch
    social welfare
    multi-objective optimization
    Opis:
    In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC). This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
    Źródło:
    Archives of Electrical Engineering; 2015, 64, 3; 405-426
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-objective coordination optimisation method for DGs and EVs in distribution networks
    Autorzy:
    Tang, Huiling
    Wu, Jiekang
    Powiązania:
    https://bibliotekanauki.pl/articles/141087.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    charging and discharging of electric vehicles
    distribution networks
    distributed generation
    multi-objective coordination optimisation
    SAPSO
    Opis:
    The loss of power and voltage can affect distribution networks that have a significant number of distributed power resources and electric vehicles. The present study focuses on a hybrid method to model multi-objective coordination optimisation problems for distributed power generation and charging and discharging of electric vehicles in a distribution system. An improved simulated annealing based particle swarm optimisation (SAPSO) algorithm is employed to solve the proposed multi-objective optimisation problem with two objective functions including the minimal power loss index and minimal voltage deviation index. The proposed method is simulated on IEEE 33-node distribution systems and IEEE-118 nodes large scale distribution systems to demonstrate the performance and effectiveness of the technique. The simulation results indicate that the power loss and node voltage deviation are significantly reduced via the coordination optimisation of the power of distributed generations and charging and discharging power of electric vehicles.With the methodology supposed in this paper, thousands of EVs can be accessed to the distribution network in a slow charging mode.
    Źródło:
    Archives of Electrical Engineering; 2019, 68, 1; 15-32
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    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:
    Multi-objective dynamic economic dispatch using Fruit Fly Optimization method
    Autorzy:
    Arsyad, Haripuddin
    Suyuti, Ansar
    Said, Sri Mawar
    Akil, Yusri Syam
    Powiązania:
    https://bibliotekanauki.pl/articles/1841297.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    dynamic economic dispatch
    Fruit Fly Optimization method
    multi-objective
    dynamiczna wysyłka ekonomiczna
    Metoda optymalizacji muszki owocowej
    wielocelowy
    Opis:
    An essential task of the interconnected power system is about how to optimize power plants during operation time which is known as economic dispatch. In this study, the Fruit Fly Optimization method is proposed to solve problems of dynamic economic dispatch in an electrical power system. To measure the performance of the method, a simulation was conducted for two different electric systems of the existing Sulselbar 150 kV thermal power plant system in Indonesia with two objective functions, namely fuel costs and active power transmission losses, aswell as the 30-bus IEEE standard system with five objective functions namely fuel costs, transmission losses (active and reactive power), a reactive power reserve margin, and an emission index by considering a power generation limit and ramp rates as the constraints. Under tested cases, the simulation results have shown that the Fruit Fly Optimization method can solve the problems of dynamic economic dispatch better than other existing optimization methods. It is indicated by all values of the objective functions that are lowest for the Fruit Fly Optimization method. Moreover, the obtained computational time is sufficiently fast to get the best solution.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 2; 351-366
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Scaling laws for the FE solutions of induction machines
    Autorzy:
    Nell, Martin
    Lenz, Jonas
    Hameyer, Kay
    Powiązania:
    https://bibliotekanauki.pl/articles/141030.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    evolutionary strategy
    finite element method analysis
    induction machine
    induction motor
    loss calculation
    multi-objective optimization
    scaling laws
    Opis:
    In this paper a scaling approach for the solution of 2D FE models of electric machines is proposed. This allows a geometrical and stator and rotor resistance scaling as well as a rewinding of a squirrel cage induction machine enabling an efficient numerical optimization. The 2D FEM solutions of a reference machine are calculated by a model based hybrid numeric induction machine simulation approach. In contrast to already known scaling procedures for synchronous machines the FEM solutions of the induction machine are scaled in the stator-current-rotor-frequency-plane and then transformed to the torque-speed-map. This gives the possibility to use a new time scaling factor that is necessary to keep a constant field distribution. The scaling procedure is validated by the finite element method and used in a numerical optimization process for the sizing of an electric vehicle traction drive considering the gear ratio. The results show that the scaling procedure is very accurate, computational very efficient and suitable for the use in machine design optimization.
    Źródło:
    Archives of Electrical Engineering; 2019, 68, 3; 677-695
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
    Autorzy:
    Khoshayand, Hossein Ali
    Wattanapongsakorn, Naruemon
    Mahdavian, Mehdi
    Ganji, Ehsan
    Powiązania:
    https://bibliotekanauki.pl/articles/2202555.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    backward-forward load distribution
    fuzzy logic
    iterative search algorithm
    multi-objective optimization
    shortest distance from the origin
    weighted sum
    Opis:
    One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
    Źródło:
    Archives of Electrical Engineering; 2023, 72, 1; 253--271
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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