Abstract

Abstract
PV-based renewable energy systems are integrated in microgrids (MGs) throughout power electronic converters. During external disturbances of abrupt load variation and PV generation fluctuation, controllers play the most key role in regulating the system performance. In this paper, a proposed combination control method of model predictive control (MPC) and sliding mode control (SMC) for moderating the power converters is presented. The interlinking inverter is controlled via applying MPC while DC-DC converter is controlled by SMC. MPC is well known as most reliable and modern approach for non-linear systems to compensate noise and handle modeling inaccuracies for efficient load voltage profile. On the other hand, SMC is considered as the most stable controller with highly robust operation for DC-DC converters. Intermittency nature of renewable energy systems and abrupt load variation have a severe impact on load voltage quality. Keeping in view the sophisticated control attributes of MPC and SMC, inner and outer control loops with primary droop control are designed for interlinking converter by using MPC while SMC is designed for the DC-DC boost converter. Controller performance is analyzed through simulations with fluctuating generation, and variable loads. Unlike conventional cascaded PI controller, proposed MPC strategy is simple, robust with fast dynamic response.

Abstract
Future power system depends on penetrating more renewable energy to fulfill the drastic increase in energy demand with reduced carbon emission. Wind energy integration is increasing in worldwide each year. To efficiently investigate a quality voltage for AC loads under wind speed variations, a combined control strategy is proposed in this paper. It consists of PI and model predictive control (MPC) for the three-phase rectifier and interlinking inverter, respectively. The controlled rectifier ensures a constant DC-bus voltage under variable wind speed, while MPC is used to control output AC load voltage under abrupt load changes. Unlike traditional controllers, MPC does not require PI controllers for inner current and outer voltage loop or complex modulation steps. The discrete state-space model of VSI, LC filter, and load currents are used to predict future trends of load voltage for each of eight switching states. The control strategy selects the optimal switching state that reduces the error difference between reference and predicted load voltage. The proposed scheme is tested under perturbation of generation and load parameters. The proposed MPC strategy is compared with the conventional method-based PI controllers. The presented results ensure the effectiveness of the proposed approach with 0.67% THD for the AC output voltage.

Abstract

Abstract

Abstract
Renewable energy resources are integrated into microgrid through power converters. During abnormal situations like PV intermittency and load variations, the controller plays the most key role. In this paper, a combined control method is proposed and it consists of model predictive control (MPC) and sliding mode control (SMC) for power converters. The voltage source inverter (VSI) is controlled by using MPC, while the DC-DC boost converter is controlled by using SMC. Discrete state space model of interlinking inverter, LC-filter and load is used to predict the future trend of load voltage for each of the eight switching states. On the other hand, the detailed SMC model for boost converter is analyzed for fast convergence rate with finite-time convergence and chattering free signals. A comparison between the proposed control method and the control method based on PID is presented to illustrate the superiority of the proposed method. The performance of the proposed control strategy is verified by the simulation results. The controller performance is analyzed under different scenarios including fluctuating generation and variable loads. Unlike conventional PID controllers, the proposed strategy is simple and robust with a fast-dynamic response.