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Number of results: 8
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Abstract

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.

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Authors and Affiliations

Chintalapudi Venkata Suresh
Sirigiri Sivangaraju
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Abstract

The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
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Authors and Affiliations

Łukasz Knypiński
1
ORCID: ORCID

  1. Poznan University of Technology, Institute of Electrical Engineering and Electronics, Piotrowo 3a, 60-965 Poznan, Poland
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Abstract

Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.
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Authors and Affiliations

Chenghui Qiu
1
Chongtian Wu
1
Xiaolu Yuan
1
Linxu Wu
1
Jiaming Yang
1
Hong Shi
1
ORCID: ORCID

  1. College of Energy & Power Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, 212003, P.R. China
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Abstract

The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal

levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal

with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary

manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process

variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the

responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present

manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO)

and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple

outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and

MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.

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Authors and Affiliations

G.C.M. Patel
P. Krishna
P.R. Vundavilli
M.B. Parappagoudar
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Abstract

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.

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Authors and Affiliations

Martin Nell
Jonas Lenz
Kay Hameyer
ORCID: ORCID
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Abstract

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.
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Authors and Affiliations

Hossein Ali Khoshayand
1
ORCID: ORCID
Naruemon Wattanapongsakorn
2
ORCID: ORCID
Mehdi Mahdavian
1
ORCID: ORCID
Ehsan Ganji
1
ORCID: ORCID

  1. Department of Electrical Engineering, Naein Branch, Islamic Azad University, Iran
  2. Department of Computer Engineering, King Mongkut’s University of Technology, Thonburi, 126 Prachautid Road, Bangmod, Bangkok 10140, Thailand

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