The day to day transformations in the environment like global warming and the pollution made us to think about the alternative resources to fossil fuels. The main intension is to use clean and Longley available resources for power generation. This paper presents the design of the microgrid system based on renewable sources like wind, solar and fuel cell stack. This paper also presents the design of the maximum power point tracking system which tracks the maximum power point for the varying climatic conditions. The maximum power point tracking systemhas designed with two different types of controllers like artificial neural network and model predictive controllers gives the fast dynamic response and high efficiency have been used in the integrated microgrid system. This paper also presents the three inputs single output cascaded boost converter gives the boosted output voltage is also used in the microgrid system to avoid the three individual converters for each source to reduce the cost and size of the system. The battery storage systemwith battery management is also incorporated in the microgrid system to maintain continuity power supply to the load. This battery management system helps to store the excessivegenerated power in the battery and also helps to supply the power from battery to the load when generated power falls below the load power. This paper also presents the comparison of performances of the artificial neural network and model predictive controllers in terms of efficiency, ripples, dynamic response and static response. The entire microgrid system was simulated and the results are verified using MATLAB Simulink.
Volume 12 | Issue 2
Pages: 1907-1921
DOI: 10.5373/JARDCS/V12I2/S20201234