Power flow control and management strategy applied to DC nanogrids based on Gaussian distribution function.
Power Management System, Cooperative Control, Sliding Mode Control, Energy Storage Systems, Renewable Energy Sources, DC Nanogrid, Control System, Electric Power System.
The increase in world energy demand, combined with the government's search for
lower emission of polluting gases, emitted by fossil fuels, has driven the insertion of
Renewable Energy Sources (RES) in the Electric Power System (EPS). These sources can be
connected as Distributed Generation (DG) systems, which can be organized by Microgrids, or,
on a smaller scale, Nanogrids (residential systems or small operations in remote regions).
Generally, FERs have an intermittent generation profile because they depend on
meteorological conditions. Thus, an Energy Storage Systems (ESS) can be used to maintain
energy balance. To operate properly, Nanogrids need an efficient and reliable control system.
Therefore, this work implement a DC Nanogrid, with a Photovoltaic (PV) generation system, a
Lead-Acid battery-based ESS and loads. This DC nanogrid is connected to a DC grid. The use of
the DC configuration is justified by the nature of the elements used in this nanogrid. To control
the SAE terminal voltage, a sliding mode control system is used, due to the complexity of
modeling such system. To perform the proper control of the power flow, a power
management system (PMS) is used in a cooperative control scheme that changes the reference
values of the converters local controllers. This function is based on the energy balance equation and on a Gaussian inference function. The SAE operates to provide energy balance. The effectiveness of the proposed method is validated by the simulation results.