Current Converter with Two-Loop Maximum Power Tracking Control for Solar Arrays

An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

Renewable energy is being used to lessen the consumption of fossil fuels. Solar energy is a common source of renewable energy. Solar energy is the most promising source of energy due to its long-term sustainability and availability. The output power of solar panels is strongly influenced by the intensity of sunlight and the temperature of the solar panels. Maximum Power Point Tracking (MPPT) control, which aims to optimize the output power of solar panels, is commonly used to increase the efficiency of solar panels. However, MPPT control often causes overvoltage disturbance in systems directly connected to the load. To limit the output power of solar panels, additional Constant Power Generation (CPG) control is required. In this research, a solar panel system will be created to supply submersible DC pumps without any energy storage devices. DC-DC SEPIC Converter is designed with MPPT control combined with CPG control to limit the output power of the converter using the Adaptive Neuro-Fuzzy Inference System method by 150 watts. When the output power of the solar panel is less than the power limit, then MPPT mode will work. While CPG mode works when the PV output power is greater than the limit power. The results of this research showed that the system can provide optimal power generated by solar panels in MPPT mode by increasing efficiency by up to 33.04% and CPG mode can limit power to 150 Watts to avoid overvoltage disturbance at load.

An efficient maximum power point tracking (MPPT) controller is a crucial part of solar photovoltaic (PV) system, which can handle the non-linear characteristics of a solar PV array. In this study, a proposed solar PV system with boost converter and dc load is modeled and compared according to the operating characteristics (i.e. voltage, current, power and efficiency under varying solar irradiance and cell temperature) using five conventional and modern MPPT techniques. The proposed solar PV system and MPPT controllers are modeled and simulated in MATLAB Simulink platform. Among these five MPPT controllers, artificial neural network (ANN) MPPT controller provides the highest efficiency of 97.55% and produces less voltage and power fluctuations. The novelty of this paper is that it focuses on the key characteristics and simulated results of the five MPPT techniques to make a comparison between them.

A maximum power point tracking (MPPT) controller was used to make the photovoltaic (PV) module operate at its maximum power point (MPP) under changing temperature and sunlight irradiance. Under partially shaded conditions, the characteristic power–voltage (P–V) curve of the PV modules will have more than one maximum power point, at least one local maximum power point and a global maximum power point. Conventional MPPT controllers may control the PV module array at the local maximum power point rather than the global maximum power point. MPPT control can be also implemented by using soft computing methods (SCM), which can handle the partial shade problem. However, to improve the robustness and speed of the MPPT controller, a hybrid MPPT controller has been proposed that combines two SCMs, the Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Matlab was used in a simulation of a GA-ACO MPPT controller where four SunPower SPR-305NE-WHT-D PV modules with a maximum power of 305.226 W connected in series were used under conditions of partial shade to investigate the performance of the proposed MPPT controller. The results obtained were analyzed and compared with others obtained under perturb and observe (P&O) MPPT and conventional ACO MPPT controllers were observed.

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Solar Photovoltaic (PV) energy is becoming an increasingly important part of the world's renewable energy. In order to develop technology for efficient energy conversion from a solar PV system, this paper studies typical Maximum Power Point Tracking (MPPT) control techniques used in solar PV industry and then proposes a close-loop and adaptive MPPT method for reliable and rapid extraction of solar PV power. The paper emphasizes especially on how the proposed and conventional adaptive MPPT methods perform under highly variable weather and solar irradiation conditions in a digital control environment. A computer simulation system is developed by using SimPowerSystems and Opal-RT real-time simulation technology which allows for fast and efficient investigations of the MPPT algorithms under high switching frequency conditions for power converters. A hardware experiment system is built to validate and compare the proposed and conventional MPPT techniques in a more practical condition. Advantages, disadvantages and properties of different MPPT methods are compared and studied, evaluated.

This paper presents a maximum power point tracking (MPPT) controller employing a modified hill top algorithm implemented using embedded microcontroller for solar photovoltaic (PV) module. The proposed MPPT algorithm has high efficiency compared to conventional hill top algorithm in terms of transferring power from source to load. The designed controller regulates the output voltage through control of the DC-DC boost converter under varying environmental conditions. The comparative result for hill top and modified hill top algorithm based on the proposed MPPT controller has been obtained through the simulation studies in PSCAD/EMTDC software. The validity of the proposed modified hill top algorithm has been obtained through experimental implementation of the MPPT controller on a solar PV module driving a load.

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

Photovoltaic power systems normally use maximum power point tracking (MPPT) to continuously deliver the highest possible power to the load when changes in insolation and temperature occur. This overcomes the problem of mismatch between the solar cells and the given load. The solar array is normally treated as a voltage source, but it is treated as a current source in this paper. A simple method of tracking the maximum power point (MPP) and forcing the PV power system to operate near this point is also presented. The effect of the negative impedance of power converters on the MPPT process is also considered. As to the system equivalent circuit model, the principle of energy conservation is used to develop large- and small-signal models and the transfer function. By using this model, the drawbacks of the state-space-averaging method can be overcome. A TI320C25 digital signal processor (DSP) was used to implement the proposed MPPT controller; simulations and experimental results show its excellent performance.

In this paper, a control scheme for wind energy conversion systems (WECS) with induction generator is presented that is composed of a copper loss minimization (CLM) controller and a maximum power point tracking (MPPT) controller. The CLM is accomplished by controlling the excitation current of the induction generator and the MPPT control is attained by controlling the rotational speed of the wind turbine. The suggested control scheme can be easily implemented because, neither the measurement of the wind speed nor the knowledge of the wind turbine characteristics are required. Moreover, it exhibits fast dynamic response and thus, it can follow the fast dynamics of the wind. The generator is connected to the power grid by means of two vector controlled back-to-back converters. Experimental results are presented to validate the cooperation of the CLM controller with the MPPT controller.

A novel control strategy for mode seamless switching of PV converter in DC microgrid based on double integral sliding mode control

This study presents a maximum power point tracking (MPPT) method and controller for a multi-channel ( N -channel) photovoltaic solar system. The N -channel single-sensor MPPT (SS-MPPT) controller is able to track the maximum power point (MPP) of each solar panel using only one output current sensor in the N -channels. Compared with a conventional N -channel MPPT system which requires N voltage sensors, N current sensors, 2 N analogue-to-digital converters (ADCs) (or an ADC with 2 N channels) and N -MPPT controllers along with the associated conditioning circuitries, the proposed method only requires one sensor, one ADC and one MPPT controller. In the proposed N -channel SS-MPPT controller, the MPPT for each channel is achieved by tracking the maxima of the output (load) current (resulting in the maxima of the system output power) using the Perturb and Observe algorithm and the maxima of each channel power via channel output current difference optimisation. Two algorithms which can be used to realise the SS-MPPT controller are discussed and compared. The concept and operation of the SS-MPPT controller is presented, analysed and verified by results obtained from a proof-of-concept experimental prototype.

The purpose of this paper is to discuss a modeling and control of stand- alone photovoltaic system using voltage mode control maximum power point tracking (MPPT) method. The PV module was modeled based on the parameters obtained from a commercial PV data sheet while voltage mode control was modeled using simulink block model. A DC-DC boost converter was chosen to step-up and regulates the input DC voltage of the PV module. The voltage mode control (VMC) maximum power point tracking model was simulated and compared with perturb and observe (P&O) maximum power point tracker in order to validate the performance of output results. Results showed that the voltage mode control maximum power point tracking model yields the similar performance as produced by the photovoltaic system controlled by perturb and observe maximum power point tracking algorithm. The simulation is made to analyze the voltage, current and power generated under the changing irradiant and temperature condition. As a conclusion, the voltage mode control technique is possible to implement which yields the similar performance as the results from conventional MPPT method.

Compared with typical current controlled PV inverters, voltage controlled PV inverters based on droop control are easier to achieve seamless transfer between the stand-alone mode and the grid-connected mode. This paper achieves both seamless transfer and the maximum power point (MPP) tracking (MPPT) by adjusting droop curves dynamically, combining MPPT and P-f droop control. The DC voltage is difficult to control during grid connecting which will affect both the stability of the system and the MPPT efficiency. To solve this problem, a control method is proposed which includes an active power inner loop and a DC voltage outer loop. At last simulation and experimental results validate the proposed control strategy and show that DC voltage response is fast and stable. Both seamless transfer and MPPT operation modes are realized.

When the battery or supercapacitor is connected to the output of a PV system, the conventional voltage equation expressing its mathematical model usually must be replaced by the current relationship to study the maximum power point tracking (MPPT) control theory. However, hitherto, there is a lack of an attempt to disclose the current constraint relationships at the maximum power point (MPP), which leads to the potential risk of MPPT failure. To solve this problem, in this paper, the MPPT constraint conditions on the basis of currents are built and then a new MPPT control strategy is proposed. In this strategy, a linearized model parameter of a PV cell is used as the bridge to find the current relationships. On the basis of them, some expressions involving the duty cycle are built to directly calculate the control signal of the MPPT controller. Meanwhile, an implementation method is designed to match this proposed MPPT strategy. Finally, some simulation experiments are conducted. The simulation results verify that the proposed MPPT constraint expressions are accurate and workable and that the proposed MPPT strategy and its implementation process are feasible and available. In addition, the simulation results also show that the proposed MPPT strategy has a better MPPT speed and the same MPPT accuracy when the P&O method and fuzzy algorithm are compared. By this work, the MPPT constraint conditions based on current relationships are first found, representing a breakthrough in disclosing the inherent relationships between different currents when the PV system is operating around the MPP.