Next Article in Journal
Riding Comfort Evaluation Based on Longitudinal Acceleration for Urban Rail Transit—Mathematical Models and Experiments in Beijing Subway
Next Article in Special Issue
A Sustainable Distributed Building Integrated Photo-Voltaic System Architecture with a Single Radial Movement Optimization Based MPPT Controller
Previous Article in Journal
Rising Inequality and Entrepreneurship during Economic Downturn: An Analysis of Opportunity and Necessity Entrepreneurship in Spain
Previous Article in Special Issue
Smart Wifi Thermostat-Enabled Thermal Comfort Control in Residences
Open AccessArticle

Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability

1
Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 Munich, Germany
2
Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut 71516, Egypt
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(11), 4542; https://doi.org/10.3390/su12114542
Received: 8 May 2020 / Revised: 27 May 2020 / Accepted: 28 May 2020 / Published: 3 June 2020
(This article belongs to the Special Issue Intelligent Mechatronic and Renewable Energy Systems)
Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest due to the predicted lack of conventional sources over the coming years. That shortage is not the only concern, as environmental issues add to this concern also. Thus, this study proposes two-stage PV grid connected system, which is supported with extended Kalman filter (EKF) for parameter estimation. In the first stage, maximum power point tracking (MPPT) for the boost converter is accomplished using new MPPT method in which the switching state of the converter is directly generated after the measurement stage, so it is called direct switching MPPT technique. This technique is compared with the conventional finite control set model predictive control (FCS-MPC) method, where the design of the cost function is based on minimizing the error between the reference and the actual current. The reference current is obtained by employing perturb and observe (P&O) method. In the second stage, the two-level inverter is controlled by means of model predictive control (MPC) with reduced computation burden. Further, to overcome the parameter variations, which is a very common problem in MPC applications, an extended Kalman filter is utilized to eliminate the control algorithm’s dependency on the parameters by providing an efficient estimation. After the inverter, an RL filter is inserted to guarantee the quality of the currents injected into the grid. Finally, the system is validated using Matlab under different operating conditions of atmospheric variation and parameter changes. View Full-Text
Keywords: direct switching MPPT; extended Kalman filter; grid connection; model predictive control; MPPT; PV systems direct switching MPPT; extended Kalman filter; grid connection; model predictive control; MPPT; PV systems
Show Figures

Figure 1

MDPI and ACS Style

Ahmed, M.; Abdelrahem, M.; Kennel, R. Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability. Sustainability 2020, 12, 4542.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop