Accurate power-sharing, voltage regulation, and SOC regulation for LVDC microgrid with hybrid energy storage system using artificial neural network

ABSTRACT

In this paper, an artificial neural network-based control strategy is proposed for low voltage DC microgrid (LVDC microgrid) with a hybrid energy storage system (HESS) to improve power-sharing between battery and supercapacitor (SC) to suit the demand-generation imbalance, maintain state-of-charge (SOC) within boundaries and thereby to regulate the dc bus voltage. The conventional controller cannot track the SCs current rapidly with the high-frequency component that will place dynamic stress on the battery, further resulting in shorter battery life. The significant advantage is that in the proposed control strategy, redirections of unwaged battery currents to SCs for fast compensations enhance battery life span. The proposed control strategy effectiveness was investigated by simulations, including a comparison of overshoot/undershoot and settling time in dc bus voltage with a conventional control strategy. The results have been experimentally verified by hardware-in-loop (HIL) on a field-programmable gate array (FPGA)-based real-time simulator.

KEYWORDS:

• LVDC microgrid
• Artificial Neural Network (ANN)
• hybrid energy storage system
• state of charge
• voltage regulation

Acknowledgments

The authors express their heartily thankful to the Ministry of Human Resource Development, Government of India, for granting financial support throughout this research work.