Battery Energy Management System for DC Micro Grids with AI Controller
Abstract : This paper presents the design and implementation of an energy management system (EMS) with fuzzy control for a dc microgrid system. Modeling, analysis, and control of distributed and energy storage devices with MATLAB/Simulink are proposed.
To improve the life cycle of the battery, fuzzy control manages the desired state of charge. A fuzzy network has been designed to control the operating mode the battery to monitor values of all subsystems in the dc microgrid system.
Existing system has high efficiency but doesn’t have proper control strategies
Power converted by rectifying an ac source with power factor correction is act as a backup.
To use renewable energy more efficiency
DC electricity should be supplied to these loads
Existing system does not have EMS monitoring
SOC parameter is not maintained properly
There is no equilibrium of power supply
The dc micro grid system is composed of solar power wind power generation, lithium ion battery, dc load and ac/dc convertor with EMS monitoring and control system
The proposed EMF was commanded with RS-485/zigbee network for data communication and delivery of energy distribution instruction
The design concept of the study was to increase the useful life of lithium battery and to include to charge and over discharge production mechanism and control the green source energy management
Fuel cell was used effective
Fuzzy theory was first proposed in 1965 by Lotfi. A. Zadeh, an American scholar of automatic control, as a tool of quantitative expression for concepts that could not be clearly defined. A fuzzy control system is based on fuzzy-logic thinking in the design of how a controller works.
The so-called fuzzy logic is to establish a buffer zone between the traditional zero and one, with logic segments of none-zero and none one possible. It allows awider and more flexible space in logic deduction for the expression of conceptual ideas and experience.
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