Abstract: This study presents power flow management in a stand alone mode-connected hybrid power system comprising of solar system and energy storage system fuel cell/battery using controller between the energy resources. The proposed controller is focused with structure in order to manage the power flow. The Maximum Power Point Tracking (MPPT) design is achieved by using adaptive neuro-fuzzy inference system control design with respect to variation of solar insolation and temperature. To optimize the battery managing of charge and discharge of the current flow in the battery it is accomplished by advance fuzzy logic controller. Finally, in the design of local control is done in order to adjust the fuel cell/battery set points. The comparison of adaptive neuro-fuzzy inference system with standard PI based controller is demonstrated through series of simulation results with variation of solar irradiance and at various load resistance. This hybrid topology of the controller design exhibited excellent results under various operating conditions which obviously reflect the robustness with respect to parameter variation. Thus, its concluded the proposed model augmented by the control strategy improves management of power flow in a stand alone system connected hybrid power system.
Modem Narayana and Soumya R. Mohanty, 2018. Power Flow Managing in a Stand Alone Hybrid Power System. Journal of Engineering and Applied Sciences, 13: 3892-3899.