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Composites with different configuration of fiber (E-Glass) and metal (Aluminium) laminates were fabricated and tested for grasping optimum hybrid structure. GLARE (Glass laminate aluminium reinforced epoxy) is a unique composite recently being used by wide engineering domains like defense body and vehicle armors, aerospace, marine and structural applications. The GLARE hybrid composites are manufactured by adding very thin layer of aluminium sheets (surface treated) on the surface of unidirectional E-Glass fiber fabrics in presence of epoxy polymer. Firstly three hybrid GLARE laminates were fabricated with different volume fractions. Consequently, impact and flexural behaviors are measured by izod, charpy impact and flexural tests for all volume configurations. Impact resistance of such hybrid laminate is intensively great. The results depicts that the linear metal volume fraction (MVF) increment on fiber metal laminates greatly increases impact energy absorption capacity of composites and little difference in flexural modulus. Finally the fractured surfaces were analyzed by optical microscope.

Introduction. The renewable integrated microgrid has considered several distributed energy sources namely photovoltaic power plant, thermal generators, wind power plant and combined heat and power source. Economic dispatch problem is a complex operation due to large dimension of power systems. The objective function becomes non linear due to the inclusion of many constraints. Hourly demand of a commercial area is taken into consideration for performing economic dispatch and five combinations are considered to find the best optimal solution to meet the demand. The novelty of the proposed work consists of a Sparrow Search Algorithm is used to solve economic load dispatch problem to get the better convergence and accuracy in power generation with minimum cost. Purpose. Economic dispatch is performed for the renewable integrated microgrid, in order to determine the optimal output of all the distributed energy sources present in the microgrid to meet the load demand at minimum possible cost. Methods. Sparrow Search Algorithm is compared with other algorithms like Particle Swarm Optimization, Genetic Algorithm and has been proved to be more efficient than Particle Swarm Optimization, Genetic Algorithm and Conventional Lagrange method. Results. The five combinations are generation without solar power supply system and Combined Heat and Power source, generation without solar and wind power supply systems, generation including all the distributed energy sources, generation without wind power supply system and Combined Heat and Power source, generation without thermal generators. Practical value. The proposed optimization algorithm has been very supportive to determine the optimal power generation with minimal fuel to meet the large demand in commercial area.