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Control and Management of Fuel Cell Micro-grid Using Optimal Model Predictive Controller

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Advances in Intelligent Computing and Communication

Abstract

In the present days, the renewable energy generation is increasing exponentially as per the demand. But in the distribution it is not economical and convenient to supply energy to a particular area separately. Thus, the renewable sources should be integrated with conventional grid, which is still a challenging task. It is because of the nonlinearity and fluctuating nature of the sustainable sources like PV and fuel cell. Here in this paper, a micro-grid (MG) is designed with PV and polymer exchange fuel cell as distributed energy resources (DER) and the MG is integrating with conventional grid with an online load. Since most of the loads are nonlinear, it can cause a power quality issue called harmonics distortion which may cause huge damage to the system. To address the above problem, an optimized model predictive controller is introduced in shunt active power filter to improve the robustness of controller. To validate the strength of the controller, the system is introduced with high reactive nonlinear load. All the results and model are simulated in MATLAB/Simulink environment.

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Correspondence to Lalit Mohan Satapathy .

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Nayak, A.S., Satpathy, A., Satapathy, L.M., Nayak, N. (2021). Control and Management of Fuel Cell Micro-grid Using Optimal Model Predictive Controller. In: Das, S., Mohanty, M.N. (eds) Advances in Intelligent Computing and Communication. Lecture Notes in Networks and Systems, vol 202. Springer, Singapore. https://doi.org/10.1007/978-981-16-0695-3_54

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