Nonlinear controller for stand-alone PV system

Photovoltaic (PV) system generates energy that varies with the variation in environmental conditions such as temperature and solar radiation. To cope up with the ever increasing demand of energy, the PV system must operate at maximum power point (MPP), which changes with load as well as weather conditions. This paper proposes a nonlinear backstepping controller to harvest maximum power from a PV array using DC-DC buck converter. A regression plane is formulated after collecting the data of the PV array from its characteristic curves to provide the reference voltage to track MPP. Asymptotic stability of the system is proved using Lyapunov stability criteria. The simulation results validate the rapid tracking and efficient performance of the controller. For further validation of the results, it also provides a comparison of the proposed controller with conventional perturb and observe (P&O) and fuzzy logic-based controller (FLBC) under abrupt changes in environmental conditions.

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Design and Analysis of Non-linear Controller for a Standalone PV System using Lyapunov Stability Theory

Journal of Solar Energy Engineering ◽

10.1115/1.4051584 ◽

2021 ◽

pp. 1-22

Author(s):

Narendra Kumar ◽

Aman Sharma

Keyword(s):

Lyapunov Stability ◽

Stability Theory ◽

Sliding Mode ◽

Equilibrium Points ◽

Lyapunov Stability Theory ◽

Maximum Power ◽

Hill Climbing ◽

Sliding Mode Controller ◽

Nonlinear Controller ◽

Pv System

Abstract This paper presents Lyapunov Stability Theory based Nonlinear Controller Design for a Standalone PV System. The comparative analysis of different nonlinear controllers is also carried out . Due to the nonlinear characteristics of photovoltaic systems, conventional Hill-Climbing methods like Perturbate and Observe and Incremental Conductance do not show reliable tracking of Maximum Power under various uncertainties. Therefore, these methods require nonlinear tools to meet the control objectives and design specifications. Out of various nonlinear controlling techniques, the one presented in this paper is the Sliding Mode Approach for Maximum Power Point Tracking (MPPT). In context of Lyapunov Stability Theory, sliding mode approach uses a switching manifold. In this approach, the system trajectories are made to follow the sliding surface and to remain there forever to ensure the stability of equilibrium points. Two types of Sliding Mode controllers have been simulated namely Conventional - Sliding Mode Controller (CSMC) and Terminal - Sliding Mode Controller (TSMC). The results are analyzed and compared scientifically on various performance parameters including, duty cycle ratio, ideal and PV output power and time taken for error convergence, under varying dynamic conditions. All the control algorithms are developed in MATLAB/Simulink.

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Nonlinear Controller of Solar PV System for Water Pumping and Irrigation Applications

2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) ◽

10.1109/wits.2019.8723736 ◽

2019 ◽

Author(s):

M. Madark ◽

A. Ba-Razzouk ◽

E. Abdelmounim ◽

M. El Malah

Keyword(s):

Solar Pv ◽

Nonlinear Controller ◽

Pv System ◽

Water Pumping ◽

Solar Pv System

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RBF neural network based backstepping terminal sliding mode MPPT control technique for PV system

PLoS ONE ◽

10.1371/journal.pone.0249705 ◽

2021 ◽

Vol 16 (4) ◽

pp. e0249705

Author(s):

Zain Ahmad Khan ◽

Laiq Khan ◽

Saghir Ahmad ◽

Sidra Mumtaz ◽

Muhammad Jafar ◽

...

Keyword(s):

Neural Network ◽

Finite Time ◽

Sliding Mode ◽

Maximum Power ◽

Control Technique ◽

Maximum Efficiency ◽

Nonlinear Controller ◽

Pv System ◽

Terminal Sliding Mode ◽

Controller Performance

The energy demand in the world has increased rapidly in the last few decades. This demand is arising the need for alternative energy resources. Solar energy is the most eminent energy resource which is completely free from pollution and fuel. However, the problem occurs when it comes to efficiency under different atmospheric conditions such as varying temperature and solar irradiance. To achieve its maximum efficiency, an algorithm of maximum power point tracking (MPPT) is needed to fetch maximum power from the photovoltaic (PV) system. In this article, a nonlinear backstepping terminal sliding mode control (BTSMC) is proposed for maximum power extraction. The system is finite-time stable and its stability is validated through the Lyapunov function. A DC-DC buck-boost converter is used to deliver PV power to the load. For the proposed controller, reference voltages are generated by a radial basis function neural network (RBF NN). The proposed controller performance is tested using the MATLAB/Simulink tool. Furthermore, the controller performance is compared with the perturb and observe (P&O) MPPT algorithm, Proportional Integral Derivative (PID) controller and backstepping MPPT nonlinear controller. The results validate that the proposed controller offers better tracking and fast convergence in finite time under rapidly varying conditions of the environment.

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