Model predictive control—Based distributed control algorithm for bidirectional interlinking converter in hybrid microgrids

Abstract

Summary A hybrid AC/DC microgrid takes advantages of both DC and AC microgrids with distributed generation (DG) units in both the respective grids connected through a bidirectional interlinking converter (BIC). Control of hybrid AC/DC microgrid presents a significant research and engineering challenge and hence needs increased research efforts. Existing control algorithms restrict individual controllers to control only designated parameters. This paper proposes MPC‐based distributed control algorithm that will analyze grid conditions, and it would designate BIC to regulate the highest deviated parameter (AC/DC voltage or current) in all nonlinear conditions by performing multivariable optimization using variable control scheme in MPC. Other parameters would be controlled by individual controllers as per their capability. MPC being a nonlinear control technique having an excellent dynamic response and constraint inclusion feature has advantage as compared to other linear and nonlinear techniques. The performance of the proposed algorithm has been compared against other techniques and proved in MATLAB/SIMULINK simulation.

Model predictive control of consensus-based energy management system for DC microgrid

“…Hence, the input current of the AC/DC converter acting as GFE DG [32] is: Future values of current and voltage are calculated from previous values of (k−1)th sampling interval, using Euler approximation:…”

Optimized Nonlinear Integral Backstepping Controller for DC–DC Three-Level Boost Converters

“…In [10], a conventional controller based on feedback and PID has been used. Conventional controllers are easy to implement, but they are just suitable for linear systems and give slow response to disturbances [11]. A sliding mode controller for the voltage control of DC-DC buck-and-boost converters has been introduced in [12] and [13].…”