Aranzazu D. Martin

Backstepping Control of Smart Grid-Connected Distributed Photovoltaic Power Supplies for Telecom Equipment

Backstepping controllers are obtained for distributed hybrid photovoltaic (PV) power supplies of telecommunication equipment. Grid-connected PV-based power supply units may contain dc-dc buck-boost converters linked to single-phase inverters. This distributed energy resource operated within the self-consumption concept can aid in the peak-shaving strategy of ac smart grids. New backstepping control laws are obtained for the single-phase inverter and for the buck-boost converter feeding a telecom equipment/battery while sourcing the PV excess power to the smart grid or to grid supply the telecom system. The backstepping approach is robust and able to cope with the grid nonlinearity and uncertainties providing dc input current and voltage controllers for the buck-boost converter to track the PV panel maximum power point, regulating the PV output dc voltage to extract maximum power; unity power factor sinusoidal ac smart grid inverter currents and constant dc-link voltages suited for telecom equipment; and inverter bidirectional power transfer. Experimental results are obtained from a lab setup controlled by one inexpensive dsPIC running the sampling, the backstepping and modulator algorithms. Results show the controllers guarantee maximum power transfer to the telecom equipment/ac grid, ensuring steady dc-link voltage while absorbing/injecting low harmonic distortion current into the smart grid.

MPPT algorithms comparison in PV systems: P&O, PI, neuro-fuzzy and backstepping controls

This paper presents a comparative analysis of control methods to extract the maximum power and to track the maximum power point (MPP) from photovoltaic (PV) systems under changeable environmental conditions. The PV system consists of a solar module and a DC/DC converter, in this case a buck-boost converter, connected to a load. The maximum power point tracking (MPPT) algorithms compared are the perturb and observe (P&O) method, the PI control, a neuro-fuzzy and fuzzy technique and finally a backstepping control. The parameters considered for the comparison are the efficiency of the MPPT algorithm taking into account the extracted power from the PV system, steady and dynamic response of the system under changeable conditions such as the temperature and the irradiance and the signals ripple. The methods have been compared and the algorithm with the best results has been implemented in an experimental platform.

Sinteza backstepping regulatora za praćenje maksimalne proizvodnje energije u fotonaponskim sustavima

This work presents a new control method to track the maximum power point of a grid-connected photovoltaic (PV) system. A backstepping controller is designed to be applied to a buck-boost DC-DC converter in order to achieve an optimal PV array output voltage. This nonlinear control is based on Lyapunov functions assuring the local stability of the system. Control reference voltages are initially estimated by a regression plane, avoiding local maximum and adjusted with a modified perturb and observe method (P&O). Thus, the maximum power extraction of the generating system is guaranteed. Finally, a DC-AC converter is controlled to supply AC current in the point of common coupling (PCC) of the electrical network. The performance of the developed system has been analyzed by means a simulation platform in Matlab/Simulink helped by SymPowerSystem Blockset. Results testify the validity of the designed control method.

Adaptive backstepping control of a DC-DC converter in photovoltaic systems

This paper presents a new nonlinear control method to regulate the voltage at the output of a DC-DC converter so as to achieve the maximum power point (MPP) of a photovoltaic (PV) system. The proposed adaptive backstepping controller of the system, based on Lyapunov functions to ensure locally stability, is applied to a buck-boost converter. A regression plane is used to initialize reference voltages and to make a modified perturb and observe method (P&O) faster, avoiding local maximum. Therefore, the maximum power extraction of the PV system is guaranteed. This system is grid-connected, thus, a DC-AC converter is connected to the buck-boost converter. The inverter supplies AC current in the point of common coupling (PCC) of the electrical network. The performance of the developed system has been analyzed by means a simulation platform in Matlab/Simulink.

Neuro-fuzzy control of a grid-connected photovoltaic system with power quality improvement

This paper presents a Photovoltaic Active Power Line Conditioner, a device designed to extract the maximum power of a photovoltaic (PV) system and to compensate the nonlinear and unbalanced loads of the electrical power systems. The grid-connected PV systems require DC-DC and DC-AC power converters to maximize the generated PV power and to inject an AC current to the network. In this work, a neuro-fuzzy system to achieve the Maximum Power Point (MPP) and a fuzzy logic control loop to ensure the Maximum Power Point Tracking (MPPT) of the PV system connected at DC side are designed. The DC-AC power converter control strategy includes an active compensation of the non-linear and unbalanced loads connected to the electrical system. The performance of the PV conditioner with the neuro-fuzzy control designed has been analyzed through a simulation platform.

Backstepping Control of a Buck-Boost Converter in an Experimental PV-System

This paper presents a nonlinear method to control a DC-DC converter and track the Maximum Power Point (MPP) of a Photovoltaic (PV) system. A backstepping controller is proposed to regulate the voltage at the input of a buck-boost converter by means of Lyapunov functions. To make the control initially faster and avoid local maximum, a regression plane is used to estimate the reference voltages that must be obtained to achieve the MPP and guarantee the maximum power extraction, modifying the conventional Perturb and Observe (P&O) method. An experimental platform has been designed to verify the validity and performance of the proposed control method. In this platform, a buck-boost converter has been built to extract the maximum power of commercial solar modules under different environmental conditions.

Improvement of shunt active power filter compensation through switching output reactances

The increase in non-linear loads in the electrical network deteriorates the voltage waveform quality. One of the most used methods to correct the quality lack is to use shunt, series or mixed topologies of active power filters. Mixed filters can compensate loads that generate voltage harmonics and current harmonics, but the economic investment is high. Commercial shunt filters are more widespread due to their design, modularity and cost; although their non-linear load tracking capability is limited. The aim of this work is to improve the shunt active filter reference tracking, designing a variable reactance at the filter output. The validity of the proposed design is analyzed through a Matlab-Simulink platform.