The power distribution networks supply nonlinear consumers which causes a distorted and unbalanced state. A repercussion of these states is represented by the increase of active power losses. Even if the symmetrical s...
详细信息
ISBN:
(纸本)9781509061303
The power distribution networks supply nonlinear consumers which causes a distorted and unbalanced state. A repercussion of these states is represented by the increase of active power losses. Even if the symmetrical sinusoidal state is initially considered for the power losses, in reality this often leads to power lines overloading, especially for the neutral. The existing method for power losses computation in distribution networks with distorted operating state is very difficult to use. The paper investigates the additional power losses for a real distribution network, considering three representative scenarios, close to real operation states. The aim is to present an accurate approach for evaluating the effects of harmonic current flows on the feeder power losses. In order to validate the proposed methodology, a study case is provided. The additional power losses due to the distorted state, for all conductor cross section of the Romanian low voltage power networks are computed.
This paper presents a model-based distributed fault diagnosis approach for electro-hydraulic suspension system by using the diagnostic hybrid bond graph（DHBG） technique and bat algorithm（BA）. Electro-hydraulic sus...
详细信息
This paper presents a model-based distributed fault diagnosis approach for electro-hydraulic suspension system by using the diagnostic hybrid bond graph（DHBG） technique and bat algorithm（BA）. Electro-hydraulic suspension system is a complex nonlinear system and if the centralized diagnosis approach is used, some problems, like poor scalability and high computationally cost, exist. To overcome these problems, a distributed approach is developed where the DHBG model of global system is decomposed into several local submodels by temporal causal graph technology. In each submodel, the distributed analytical redundancy relations are derived from the DHBG of submodel and the distributed fault signature matrix is constructed to isolate the possible faults set（PFS）. For fault estimation, the BA is used to find out the true fault parameters from *** results validate the developed distributed fault diagnosis method in Electro-hydraulic suspension system is effective.
Breast malignancy is one of dangerous illness among the women community and premature detection may facilitate to provide the appropriate treatment to diminish/eliminate breast cancer. Digital Mammogram (DM) is a comm...
详细信息
ISBN:
(纸本)9781538644737
Breast malignancy is one of dangerous illness among the women community and premature detection may facilitate to provide the appropriate treatment to diminish/eliminate breast cancer. Digital Mammogram (DM) is a commonly approved imaging scheme to record and scrutinize the breast cancer. This paper implements a novel hybrid approach based on the combination Otsu's multi-thresholding and Water Shed Segmentation (WSS) to mine the suspicious sections from the DM. Initially, the multi-level thresholding using the bat algorithm (BA) driven Otsu with a bi-, tri- and four-level thresholding is implemented to pre-process the DM. Afterward, a marker controlled WSS is implemented to mine the infected division of DM. The mined section is then evaluated using the Haralick texture feature in order to know the severity of the disease by examining its texture feature. In this paper, DM dataset with dense, medium, low and normal breast regions are analyzed independently with the proposed approach. The experimental result of this paper confirms that, proposed method is very proficient in extracting the breast malignancy from the considered DM database.
Glow Swarm Optimization(GSO) and Particle Swarm Optimization(PSO) algorithms are proposed in this paper for optimal tuning of PI controllers for Load Frequency Controller(LFC) design. To visualize the effectiveness of...
详细信息
ISBN:
(纸本)9781509046218
Glow Swarm Optimization(GSO) and Particle Swarm Optimization(PSO) algorithms are proposed in this paper for optimal tuning of PI controllers for Load Frequency Controller(LFC) design. To visualize the effectiveness of the proposed method, a two area interconnected power system is considered as a test system. To prove the robustness of the proposed controller and to stabilize the frequency of oscillations, the design process takes a large range of operating conditions and system nonlinearities in to account. The simulation results emphasis on the superiority of GSO algorithm over bat and Simulated Annealing (SA) in tuning PI controller parameters with the help of different performance indices. The result analysis demonstrate that the proposed algorithm achieves robust performance for different load perturbations in second as well as both areas as compared to bat and SA approaches.
In order to solve the problem of particle dilution in traditional particle filter（PF） estimation of Ni-Cd Alkaline battery state of charge（SOC）, a bat algorithm optimized particle filter was proposed to estimate S...
详细信息
In order to solve the problem of particle dilution in traditional particle filter（PF） estimation of Ni-Cd Alkaline battery state of charge（SOC）, a bat algorithm optimized particle filter was proposed to estimate SOC. The particles are represented as bat individuals, and the predatory process of bat population is simulated to solve the problem of particle dilution in particle filter technology;the theoretical model of battery state space is constructed by combining the second-order Thevenin battery model,and the related parameters of battery are identified;the SOC is estimated by using BA-PF algorithm and standard PF algorithm under pulse current condition. The experimental results show that, compared with the traditional PF algorithm, the SOC estimation accuracy of Ni-Cd alkaline battery based on BA-PF is less than 2%, and it has good adaptability and stability for nonlinear and non-Gaussian characteristics of Ni-Cd alkaline battery.
This paper considers two-dimensional non-guillotine rectangular bin packing problem with multiple objectives in which small rectangular parts are to be arranged optimally on a large rectangular sheet. The optimization...
详细信息
This paper considers two-dimensional non-guillotine rectangular bin packing problem with multiple objectives in which small rectangular parts are to be arranged optimally on a large rectangular sheet. The optimization of rectangular parts is attained with respect to three objectives involving maximization of (1) utilization factor, minimization of (2) due dates of rectangles and (3) number of cuts. Three nature based metaheuristic algorithms - Cuckoo Search, bat algorithm and Flower Pollination algorithm - have been used to solve the multi-objective packing problem. The purpose of this work is to consider multiple industrial objectives for improving the overall production process and to explore the potential of the recent metaheuristic techniques. Benchmark test data compare the performance of recent approaches with the popular approaches and also of the different objectives used. Different performance metrics analyze the behavior/performance of the proposed technique. Experimental results obtained in this work prove the effectiveness of the recent metaheuristic techniques used. Also, it was observed that considering multiple and independent factors as objectives for the production process does not degrade the overall performance and they do not necessarily conflict with each other.
This paper applies cuckoo search and bat metaheuristic algorithms to solve two-dimensional non-guillotine rectangle packing problem. These algorithms have not been found to be used before in the literature to solve th...
详细信息
This paper applies cuckoo search and bat metaheuristic algorithms to solve two-dimensional non-guillotine rectangle packing problem. These algorithms have not been found to be used before in the literature to solve this important industrial problem. The purpose of this work is to explore the potential of these new metaheuristic methods and to check whether they can contribute in enhancing the performance of this problem. Standard benchmark test data has been used to solve the problem. The performance of these algorithms was measured and compared with genetic algorithm and tabu search techniques which can be found to be used widely in the literature to solve this problem. Good optimal solutions were obtained from all the techniques and the new metaheuristic algorithms performed better than genetic algorithm and tabu search. It was seen that cuckoo search algorithm excels in performance as compared to the other techniques.
暂无评论