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  • 1
    Publication Date: 2018-06-27
    Description: The integration of distributed generation (DG) resources is growing day by day in electricity grids. There are many reasons which persuade the operators to utilize DGs such as restrictions on the construction and development of transmission lines and distribution network, transition of traditional power systems to restructured electricity markets, the competitive conditions in wholesale and retail markets, the implication of economic and environmental issues in the production of electrical energy, increasing the system reliability and customer satisfactory level. The reliability improvement capability of power systems by utilization of these units has attracted the attention of many electrical engineering experts and power system planners and operators. Reliability plays a prominent role in the satisfaction of all power industry participants, especially the consumers of the electricity. In this paper, the effect of distributed generation units on the power system reliability has been investigated.  Therefore, the virus colony search (VCS) algorithm is employed to determine the optimal placement and size of distributed generators subject to improve the reliability indices. The simulation is carried out on a 34-bus IEEE test network. The optimization results are also compared with the results of both genetic algorithm (GA), particle swarm optimization (PSO) algorithm, differential evolution (DE) algorithm, multi-objective particle swarm optimization (MOPSO) algorithm, modified shuffled frog leaping algorithm (MSFLA), gravitational search algorithm (GSA), biogeography-based optimization (BBO) algorithm, hybrid big bang-big crunch (HBB-BC) algorithm and glowworm swarm optimization (GSO) algorithm.
    Electronic ISSN: 1309-0127
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Technology
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  • 2
  • 3
    Publication Date: 2021-05-19
    Description: Frequently,the development of quantitative traits in livestock based on breeding programs has been more important.In spite of higher selection response in fish than in farm animal, it is no progress in fish breeding programs in some regions such as IRAN, because of little information of genetic variation of stock, disconstructed or undesigned base population, the deterioration of genetic resourse and don’t well informed educated researchers,extension workers and aquaculturists in breeding theory and its practical issues. At first step,in Yasouj Coldwater Fishes Breeding Research Center, in order to conducting combined selection program in rainbow trout broodstock as base population and their offsprings in mixed age parents,150 female and male broods with higher mean weight were selected,striped in 6 stage and eggs were incubated.One-year Fishes(45000 pcs.) of the six groups with higher mean weight in 5 stage were selected(438 pcs.) and remainder was discarded. Before selection, a few fishes of six aged-groups as control group were cultured apart. Difference(p〈0.05) induced between mean weight of the selected groups and with control group was because of age difference in them and of no deletion in control group(don’t throw out small individuals) by selection.The whole groups don’t have significant difference (p〉0.05) in FCR and FER. Based on results, it isn’t told that difference between experimental and control groups is a result of genetic improvement of growth rate trait induced of selection process in one generation and the continue of this program for several generations in order to reveal the development of a quantitative trait is unevitable and mating of selected broods(438 fish) in a crossbreeding program and the selection of offsprings is essential.
    Description: Iranian Fisheries Science Research Institute
    Description: Published
    Keywords: Rainbow trout ; Breeding ; Selection ; Broodstock ; Genetic variation ; Genetic ; Growth Rate ; Generation
    Repository Name: AquaDocs
    Type: Report , Refereed
    Format: 26pp.
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  • 4
    Publication Date: 2021-07-16
    Description: Frequently,the development of quantitative traits in livestock based on breeding programs has been more important. In spite of higher selection response in fish than in farm animal, it is no progress in fish breeding programs in some regions such as IRAN, because of little information of genetic variation of stock, disconstructed or undesigned base population, the deterioration of genetic resourse and don’t well informed educated researchers, extension workers and aquaculturist in breeding theory and its practical issues. At first step, in Yasouj Coldwater Fishes Breeding Research Center, in order to conducting combined selection program in rainbow trout broodstock as base population and their off springs in mixed age parents,150 female and male broods with higher mean weight were selected, striped in 6 stage and eggs were incubated. One-year Fishes(45000 pcs.) of the six groups with higher mean weight in 5 stage were selected(438 pcs.) and remainder was discarded. Before selection, a few fishes of six aged-groups as control group were cultured apart. Difference (p〈0.05) induced between mean weight of the selected groups and with control group was because of age difference in them and of no deletion in control group(don’t throw out small individuals) by selection. The whole groups don’t have significant difference (p〉0.05) in FCR and FER. Based on results, it isn’t told that difference between experimental and control groups is a result of genetic improvement of growth rate trait induced of selection process in one generation and the continue of this program for several generations in order to reveal the development of a quantitative trait is unevitable and mating of selected broods (438 fish) in a crossbreeding program and the selection of off springs is essential.
    Keywords: Aquaculture ; Iran ; Yasouj ; Rainbow trout ; Breeding ; Selection ; Broodstock ; Genetic variation ; Genetic ; Growth Rate ; Generation
    Repository Name: AquaDocs
    Type: monograph
    Format: application/pdf
    Format: application/pdf
    Format: 26
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