Power Flow Control of UIPC Using Neural Networks in AC-DC Grid Connected Hybrid Micro grids

Abstract

Linking AC-DC microgrids in framework-related mixed microgrids may be improved by 
using a modified interphase power regulator, according to this study (UIPC). A normal matrix-related 
half-breed microgrid with an AC microgrid and a DC microgrid is the framework being studied. 
These microgrids are connected through a UIPC that has been modified rather than the same 
associated power converters. Change the current UIPC structure, which employs three force 
converters in each stage, to a reduced number of intensity converters for power trade control across 
AC-DC microgrids, the major goal of this work. Rather of having a power converter (LPC) for each 
stage, the redesigned structure use a bus power converter (BPC) to control the DC supply voltage. 
Because they can function in either capacitance mode (CM) or inductance mode (IN), LPCs, which 
feature DC transports, connect the AC microgrid to the main network (IM). A "fluffy rationale 
regulator" is utilized in the LPC control scheme. The H sifting process is used to broaden the fluffy 
derivation framework in order to eliminate errors in the development of enrollment capacity. Through 
the BPC, the DC microgrid distributes DC power to the LPCs. The LPCs' DC interface voltage 
changes in every circumstance since the DC microgrid power is supplied by a PV framework. Thus, 
another nonlinear unsettling influence onlooker (NDO-MS-SMC) approach for DC side management 
of the BPC is produced to settle the DC connect variances as a follow-up commitment to settle the DC 
connect variations Neural Networks are also used to assess the system's response.
A network controller replaces the current fuzzy controller. According to the simulation 
results, the enhanced UIPC's proposed power stream management method for mixed microgrids is a 
good fit.