Finite-set model predictive control for hybrid energy storage systems using single-inductor dual-input single-output converters in DC microgrids

• Main Author: Tan, Sze Meng
• Other Authors: Gooi Hoay Beng
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/74566
• Institution: Nanyang Technological University

In recent years, there have been an increasing adoption of hybrid energy storage system (HESS) which consists of different types of energy storages (ESs) to handle load energy demand with different criteria. At the same time, it is recommended to incorporate the increasingly popular renewable energy supplies such as solar energy in HESS, in order to overcome renewable energy’s limited capacity and to promote efficient energy usage. This final year project proposes a bidirectional single-inductor dual-input single-output (BSIDISO) converter for the integration of HESS which consists of two ESs with complementary characteristics in a DC microgrid. On top of that, a model predictive control (MPC) based controller is developed to regulate the BSI-DISO converter for efficient charging/discharging operation in HESS depending on their characteristics. Ultimately, the DC bus voltage of the DC microgrid is maintained at a desired voltage value constantly, without being affected much by both the fluctuation of renewable power generation, as well as the variable load consumption. By sharing a single-inductor converter among the ESs, the number of circuit components, topology complexity and cost can be reduced significantly. In this report, the workability and effectiveness of the proposed system are validated through hardware-in-loop (HIL) experimental studies and the experimental results are being analysed in details.