A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG

Abstract

In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.

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A. Baziar, A. Kavoosi-Fard and J. Zare, "A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG," Journal of Intelligent Learning Systems and Applications, Vol. 5 No. 1, 2013, pp. 11-18. doi: 10.4236/jilsa.2013.51002.

Conflicts of Interest

The authors declare no conflicts of interest.

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