Real-Time Energy Management for DC Microgrids Using Artificial Intelligence

Abstract

Microgrids are defined as an interconnection of several renewable energy sources in order to provide the load power demand at any time. Due to the intermittence of renewable energy sources, storage systems are necessary, and they are generally used as a backup system. Indeed, to manage the power flows along the entire microgrid, an energy management strategy (EMS) is necessary. This paper describes a microgrid energy management system, which is composed of solar panels and wind turbines as renewable sources, Li-ion batteries, electrical grids as backup sources, and AC/DC loads. The proposed EMS is based on the maximum extraction of energy from the renewable sources, by making them operate under Maximum Power Point Tracking (MPPT) mode; both of those MPPT algorithms are implemented with a multi-agent system (MAS). In addition, management of the stored energy is performed through the optimal control of battery charging and discharging using artificial neural network controllers (ANNCs). The main objective of this system is to maintain the power balance in the microgrid and to provide a configurable and a flexible control for the different scenarios of all kinds of variations. All the system’s components were modeled in MATLAB/Simulink, the MAS system was developed using Java Agent Development Framework (JADE), and Multi-Agent Control using Simulink with Jade extension (MACSIMJX) was used to insure the communication between Simulink and JADE.

Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers

“…However, no study has been carried out using ANNs to control DC/DC converters or to use ANNs to govern DC microgrids. In [27], a preliminary investigation was published on creating an ANN-based DC/DC converter control system and combining it with a droop mechanism to regulate a freestanding DC microgrid. The wind speed was estimated in real time using a back-propagation ANN in [28].…”

Microgrid energy management system for smart home using multi-agent system

“…The bidirectional DC/DC converter allows power to be transferred in either direction between the battery and the DC Bus. They are increasingly being employed as a connection between the battery and microgrid system to control battery charging and discharging because of their capacity to reverse the direction of current flow, and power, while keeping the voltage polarity at either end unchanged [25].…”

Microgrid energy management and monitoring systems: A comprehensive review

“…Various control techniques outlined in Figure 2 (Albarakati et al, 2021) present MG control types typically employed in MG to improve MG's power and operations. The microgrid control regulates reactive power and MG output voltage.…”

“…Comparisons related procedures(De Santis et al, 2017;Albarakati et al, 2021)]. Adaptive PID ControllerDe Santis et al (2017) Voltage and courant An adaptive PID controller's gain parameter is determined through optimal tuning Simple to implement; does not necessitate system dynamics to be realized; There are only three variables to optimize Adaptive Sliding Mode Controller Hussein and Shamekh, (2019) Voltage and frequency; power quality control Changing the control structure allows the approach to track the system output within predetermined limitations.…”