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Optimal energy management of micro grid connected system: a hybrid approach

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Abstract

This dissertation proposes a hybrid technique for the optimal operation of microgrid (MG) connected sources through minimization of cost and better usage of MG connected sources. The MG connected sources are Wind Turbine (WT), Photovoltaic array (PV), Fuel Cell (FC), Micro Turbine (MT), Diesel Generator (DG) and battery storage. The proposed technique is the hybrid wrapper of Artificial Neural Network (ANN) with Artificial Bee Colony (ABC) and the Firefly Algorithm (FA). The proposed strategy is utilized to manage the power flow between the energy sources and the grid. At first, ANN technique predicts the load demand, based on the predicted load demand, ABC optimizes the MG configuration. Finally, FA technique helps to minimize the fuel cost, operation and maintenance (OM) cost. By then, the proposed technique is implemented in the MATLAB/Simulink working platform and compared with existing techniques such as Online Management (OM), ABC, ABC-ABC and ABC-Gravitational Search (GS). The maximum generated power of PV, WT, MT, FC, DG and battery is 5.9 kW, 5.9 kW, 4 kW, 4 kW, 6 kW and 0.5 kW. The total cost of ABC, ABC-ABC, ABC-GS and proposed technique is about 4.1$/hr, 3.9$/hr, 3.3$/hr and 2.7$/hr. The comparison results demonstrate that the proposed technique has less cost effective based on their load demand.

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  1. University Institute of Technology, Burdwan University, Burdwan, India

    Kallol Roy

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Roy, K. Optimal energy management of micro grid connected system: a hybrid approach. J Ambient Intell Human Comput 13, 2343–2354 (2022). https://doi.org/10.1007/s12652-022-03776-2

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  • DOI: https://doi.org/10.1007/s12652-022-03776-2

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