Hybrid Model Predictive Control Framework for Efficient Operation of a Five-Port Converter Interfaced DC Microgrid
Arghya Mallick (TU Delft - Mechanical Engineering)
Atanu Mondal (Indian Institute of Technology Kharagpur)
Ashish R. Hota (Indian Institute of Technology Kharagpur)
Debaprasad Kastha (Indian Institute of Technology Kharagpur)
Prabodh Bajpai (Indian Institute of Technology Kanpur)
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Abstract
In this article, a hybrid model predictive control (MPC) based novel energy management framework for a dc microgrid is proposed to efficiently manage power sharing among photovoltaic (PV) source, battery, fuel cell, and supercapacitor while meeting critical load demand and satisfying operational constraints. In particular, the proposed framework mitigates certain practical operational challenges of the fuel cell and the electrolyzer, as laid down by the manufacturers. Instead of using multiple converters, a multiport converter topology is utilized for integrating the distributed energy resources (DERs) due to fewer conversion stages, compact size, cost-effectiveness, and ease of control. For smooth operation of the multiport converter, a hierarchical control unit is developed to coordinate with the hybrid MPC based supervisory controller and proportional - integral (PI) compensator based local controllers. Finally, a 2 kW laboratory prototype of the five-port converter is integrated with real DERs. The efficacy of the proposed energy management framework is demonstrated through experimental case studies which are designed to create challenging scenarios, such as large power mismatch due to stochastic PV generation and load.