SS6: Advanced Model Predictive Control of Grid-Integrated Power Converters and Drives

Abstract:

Model predictive control (MPC) has been broadly applied for many decades. The use of MPC offers immediate merits: intuitive implementation, no need for linear regulators and modulators, convenient inclusion of nonlinearities and constraints, etc. In particular, with the increasing availability of fast microprocessors, MPC has become a very attractive and powerful alternative to classic controllers of power converters and drives. The core idea of MPC is the use of the system model to predict the future behaviour of controlled variables and the selection of the best actuation based on certain optimization criteria. MPC takes into account the discrete nature of power converters and has high flexibility in control implementation. Under the accelerated transition of the power grid from a centralized system to a distributed infrastructure, the high-performance power converters empowered by advanced MPC strategies offers a range of grid-supporting functions to address the urgent issues of future smart grids. This session aims to provide a timely opportunity for scientists, researchers and practising engineers to disseminate their latest discoveries in MPC applications in grid-integrated power converters and drives.

Rationale:

In future power grids, the increasing use of power-electronics-based systems has put a high demand on new control strategies that provide voluntary grid-supporting functions. Many of these functions enforce operating limits and constraints to cope with the stringent grid codes and regulations, which cannot be sufficiently done by the hardware only but also need to be addressed by the control system. This dramatic change in the role of power-electronics-based systems has driven the development of advanced control methods to ensure their seamless integration with power grids. Under this trend, MPC is a promising solution, as it can readily incorporate the nonlinear characteristic of power electronics systems and the grid-oriented control constraints in the control design.

Topics of this special session include, but are not limited to the following:

  • Model predictive control applied to grid-integrated power converters: AC/DC, DC/AC, multilevel converters, matrix converters, etc.
  • Model predictive control applied to renewable energy: doubly fed induction generators (DFIGs), permanent magnet synchronous generators (PMSGs), photovoltaic systems, etc.
  • Model predictive control applied to grid-integrated storage systems
  • Model predictive control applied to smart load control
  • Observer-based sensorless model predictive control
  • Robust model predictive control
  • Design and implementation issues of model predictive control: cost function design, delay compensation, model inaccuracy compensation, etc
  • Artificial intelligence in predictive control design

Organizers:
Shuo YAN, Senior Lecturer, RMIT University, Email: shuo.yan@rmit.edu.au, Tel: (+852) 66793493

Dr Shuo YAN (S’13-M’16) received his B.Eng. at University of South China, Heng’yang, China, in 2007, M.Eng. at Southeast University, Nan’jing, China, in 2010, and Ph.D. at The University of Hong Kong, Hong Kong SAR, in 2016, all in electrical engineering. He worked as a postdoctoral fellow in power electronics and control at The University of Hong Kong from 2016 to 2019. Presently, he is a senior lecturer and program manager at RMIT University, Australia. His current research interests include power electronics and control, smart grids, and renewable energy. Dr YAN is an associate editor of e-Prime, Advances in Electrical Engineering, Electronics and Energy.

Jialong QU, Research Fellow, Nanyang Technological University, Email: jialong.qu@ntu.edu.sg, Tel: (+65) 98608345

Dr. Jialong Qu (S’18-M’21) received the B.S. degree and M.Eng. degrees in electrical engineering and its automation from the Harbin Institute of Technology, Harbin, China, in 2014 and 2016, respectively, and the Ph.D. degree in electrical and electronics engineering from the University of Hong Kong, Hong Kong SAR, in 2020. He is currently a research fellow with Experimental Power Grid Centre, ERI@N, NTU. His research interests include power electronics, motor drives, wireless power transfer technology and its applications, and energy storage system.