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International Journal of Civil, Mechanical and Energy Science

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Optimum designing of a Transformer Considering Lay out Constraints by Penalty-Based Method using Hybrid Big Bang-Big Crunch Approach( Vol-2,Issue-1,January 2016 )


Hesam Parvaneh, Mostafa Sedighizadeh


Transformer, Transformer design, Optimization, Hybrid big bang big crunch algorithm. Particle swarm optimization algorithm.


Optimum designing of power electrical equipment and devices play a leading role in attaining optimal performance and price of equipments in electric power industry. Optimum transformer design considering multiple constraints is acquired using optimal determination of geometric parameters of transformer with respect to its magnetic and electric properties. As it is well known, every optimization problem requires an objective function to be minimized. In this paper optimum transformer design problem comprises minimization of transformers mean core mass and its windings by satisfying multiple constraints according to transformers ratings and international standards using a penalty-based method. Hybrid big bang-big crunch algorithm is applied to solve the optimization problem and results are compared to other methods. Proposed method has provided a reliable optimization solution and has guaranteed access to a global optimum. Simulation result indicates that using the proposed algorithm, transformer parameters such as core mass, efficiency and dimensions are remarkably improved. Moreover simulation time using this algorithm is quit less in comparison to other approaches.

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