DC power optimizer for PV modules using SEPIC converter

PurposeTo analyze the operating performance of a fuzzy logic control (FLC) based solar energy conversion modular system controlled by a digital signal processor (DSP) microcontroller.Design/methodology/approachA range of published works relevant to the solar energy conversion modular systems are evaluated and their limitations are indicated in the first section of the paper. The circuit diagram of the panel‐boost converter system is described in the second section. In the third section, a neural network model is suggested for the photovoltaic panel and the model is created in the MATLAB/SIMULINK and then combined with other blocks existing in the system. The design of the FLC method is described in section 4. The simulation and experimental results corresponding to the control of the duty‐cycle of the converter to set the operating point of the solar panel at the maximum power point (MPP) are given in sections 5 and 6, respectively. Section 7, summarizes the results and conclusions of the study.FindingsThe paper suggests a simple dc‐dc boost converter controlled by FLC method. The proposed converter model can be used to obtain maximum power from a photovoltaic panel.Research limitations/implicationsIn preparing this paper, the resources books existing in the library of our university and the resources relative to the solar energy conversion and FLC published in English language and reachable through the internet were researched.Practical implicationsThe paper suggests a neural network model for a solar panel, which can be used in the simulation of the solar energy panel‐boost converter system. The solar energy panel‐boost converter system proposed in this study can be used by the researchers who are working in the solar energy conversion area.Originality/valueThe suggestion of a neural network model for a solar panel and creation of this model in the MATLAB/SIMULINK environment provides researchers to simulate and to analyze the performance of the solar energy panel‐boost converter system using the MATLAB/SIMULINK simulation program. In addition, since the control approach proposed in this paper does not require the information on temperature and solar irradiance that affect the maximum output power, can effectively find the MPP of the solar panel.

"Photovoltaic panel maximum power point tracker". As the name implied, it is a photovoltaic system that uses the photovoltaic array as a source of electrical power supply and since every photovoltaic (PV) array has an optimum operating point, called the maximum power point, which varies depending on cell temperature, the insolation level and array voltage. A maximum power point tracker (MPPT) is needed to operate the PV array at its maximum power point. The objective of this paper is to build MPPT to charge a 12-volts lead acid battery by using a (TBP1275) 74 - watts PV panel. A technique for efficiency extracting the maximum output power from a solar panel under varying meteorological conditions is presented. The methodology is based on connecting a pulse width modulated dc/dc SEPIC converter, which is controlled by a micro controller based unit. The main difference between the method used in the proposed MPPT systems and other technique used in the past is that PV array output power is used to directly control the dc/dc converter thus reducing the complexity of the system. The resulting system has high efficiency, low cost and can be easily modified. This approach ensured maximum power transfer under all conditions by using micro controller for calculation. The tracking capability of the proposed technique has been verified experimentally with a 74 W solar panel at different insolation levels.

The position of MPP of a solar panel changes with changes in weather conditions such as radiation, temperature and partial Shadow. In such a situation, several local MPPs and one GMPP are created in the P-V curve, and the common methods of MPPT(P&O, IC,…) have converged due to the failure to recognise the local MPP. They cause a lot of losses to the photovoltaic system. Therefore, in this article, it has been tried to provide a new method of particle swarm optimisation with variable coefficients, which in combination with the perturb and observe method can reach the GMPP in the fastest possible time. In this proposed method, we first reach the convergence of the GMPP using the VCPSO method, and after converging to it, we go to the P&O method and use P&O until significant changes are made in the system, and if observed Variations To re-examine the GMPP, we return to the VCPSO algorithm. The results of the simulation of the efficiency of the proposed method show that this method was able to reach the GMPP in the shortest time, and the efficiency of the photovoltaic system increases and the effects of partial shading are reduced.

As energy demand is increasing rapidly, our deployment must be tending towards Renewable Energy Sources (RES), in order to meet the demand. Photovoltaic (PV) is one of the most focused RES due to plenty than other sources. Before serving to the load, the generated power by solar array is treated electronically and this process is called 'power conditioning'. In power conditioning, two major functions are frequently discussed i.e. DC-AC conversion and maximum power point tracking (MPPT). In order to supply the maximum power to the load, it is desired to operate the solar array at its maximum power point (MPP). Maximum Power Point Tracker automatically and electronically matches the load with the array. There are various techniques to determine the maximum power point. In this paper, one soft computing technique is discussed for this purpose i.e. Fuzzy Logic. With the fuzzy logic based control technique, the duty cycle of the boost converter is controlled in order to obtain the maximum power from PV array. Fuzzy logic controller (FLC) based MPPT system is implemented to the grid through multilevel inverter (MLI).

Solar panels are a renewable energy power plant that uses sunlight as its main energy source. The power generated by solar panels are determined by the size of the solar panels, solar radiation and temperature. The power of the solar panels is also determined by the output voltage of the solar panels. To get the maximum output power at any time, it is necessary to adjust the output voltage of the solar panel. This study proposes controlling the maximum output power of solar panels, also known as maximum power point tracking (MPPT) by adjusting the output voltage of the solar panels using a buck converter. The buck converter output voltage regulation at the maximum power point of the solar panel is designed with the Perturbation and Observation (PO) algorithm which is implemented using an Arduino Mega 2560. This MPPT control system is applied to 4x50 Watt-Peak (WP) solar panels which are connected in parallel. The experimental results show that the proposed MPPT control system with the PO algorithm has worked well as expected. This can be seen from the output power generated by the solar panels already around the maximum power point at any change in solar radiation and temperature.

This paper involves an incremental conductance Maximum Power Point Tracking (MPPT) algorithm for solar panel output. MPPT, or Maximum Power Point Tracking, is a charge controller algorithm that is used to extract the maximum available power from a PV module under particular conditions. Maximum power point (or peak power voltage) refers to the voltage at which a PV module may output the most power. Maximum power is affected by solar radiation, ambient temperature, and the temperature of the solar cell. The output of the solar PV array is connected to DC-DC boost converter. To verify the effectiveness of the algorithm, the MATLAB/SIMULINK results are presented.

The implementation of the maximum power extraction function from solar panels is an important energy task, which can significantly increase the energy efficiency of solar energy. It is shown that the maximum power point that a solar panel can deliver depends on many parameters, such as current consumption, temperature, and illumination. In addition, solar panels have the property of degradation of the generated power over the years of operation. Thus, at a particular moment in time, the value of the maximum solar power can be obtained either by creating a complete multidimensional mathematical model and using temperature sensors, light sensors, and a timer for the operation of the solar panel from the moment of its production. The implementation of this function is possible by using pulsed semiconductor converters with pulse-width modulation by changing the duty cycle of pulse-width modulation from 0 to 1 and empirically determining the value of the maximum power that a solar panel can deliver and work at a given point while maintaining the required PWM duty cycle. Computer simulation was carried out, it confirmed the possibility of determining the point of maximum power by using a step-down pulse converter.

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

The aim of this paper is the design of an automatic voltage regulator device for regulating the load voltage supplied by solar cells array (SCA). The device contains DC control circuit (DCCC) and automatic voltage regulating circuit. This circuit senses any deviation of load voltage from that at maximum power point (MPP) of SCA. As the voltage deviated away from the voltage at MPP, the circuit changes its state. Then, the operation of the circuit at this instant changes the performance of DCCC triggering circuit. Consequently, the (DCCC) will return back the load voltage deviated to that equal to the voltage at MPP. Through this paper the proposed construction of the automatic control voltage device is illustrated. Its design procedures as will as its performance are investigated. The proper operation of the proposed regulator shows that it’s very suitable for coupling with photovoltaic power systems and agricultural loads (DC Irrigation pump). In the present paper, a novel circuit, referred to as the generation control circuit (GCC), which enables maximum power to be obtained from all of the PV modules even if some of the modules are prevented from receiving light. The proposed circuit enables the individual PV modules to operate effectively at the maximum power point tracking, irrespective of the series connected PV module system. In addition, the total generated power is shown experimentally to increase for the experimental set-up used in the present study.

The photovoltaic generator exhibits a nonlinear v - i characteristic and its maximum power point varies with solar insolation. An intermediate converter is required to match the photovoltaic generator to the load and to operate the solar cell array at maximum power point. In this paper, a feedforward current sensorless maximum power point tracking scheme is developed for the interleaved dual boost converter-supplied photovoltaic system using only solar cell array information. For a given solar insolation, the tracking algorithm adjusts the solar cell array voltage to a value corresponding to the maximum power point. This is done by the feedforward loop, by comparing the instantaneous array voltage and a reference voltage corresponding to the maximum power point. The reference voltage for the feedforward loop is obtained by an off-line trained neural network. Experimental data is used for off-line training of the neural network, employing a back-propagation algorithm. A PI controller generates the control signal in real time for the PWM modulator and adjusts the duty ratio of the converter. The proposed current sensorless peak power tracking effectiveness is demonstrated through simulation and experimental results.

Under partially shaded conditions, series connection of PV modules results in the flow of lowest current in the PV string, thus reducing the power output. To maximize power output, it is necessary to ensure that maximum possible current flows in the string. This needs current equalization across the modules. To achieve this, a converter is connected in parallel with each PV module. This converter provides the extra (equalization) current in parallel with the shaded module to make the string current equal to the maximum string current, i.e. the current corresponding to the least shaded PV module. The equalization current supports the PV module to have its voltage regulated at a value that corresponds to its MPP (Maximum Power Point) voltage. However, the existing current equalization schemes use approximate maximum power point voltage and not an exact one. This paper proposes an improvement over the existing schemes by using synchronous fly-back converters to regulate the exact MPP voltage across PV modules in a partially shaded PV array. Unlike existing schemes that operate on similar principle, the proposed scheme makes no assumptions and ensures that each module is regulated at its exact MPP voltage i.e. exact MPP of individual PV module is tracked.

In this work, a Fuzzy Logic Control (FLC) based MPPT technique is proposed to improve the performance of a stand-alone solar energy system. The Fuzzy logic controller is used as an intelligent way of tracking the maximum power point (MPP). The Taguchi method is adopted in this study to analyze multiple operating conditions of solar PV array. Solar PV output changes with Atmospheric conditions. The change in PV Current and Power are measured and fed to the Fuzzy logic controller as input. The Fuzzy controller is designed with 25 fuzzy rules and the Mamdani fuzzy inference is performed to obtain the aggregation which will be defuzzified by Center of gravity method. Based on the change in PV Current and Power, the Fuzzy logic controller generate the duty cycle for the boost converter (DC-DC converter). The variation of the duty cycle is from 0 to 1. The signal of change in duty ratio from the Fuzzy logic MPPT algorithm is fed to the PWM for switching the IGBT to dynamically update the duty cycle of the boost converter for extracting the maximum power from the solar PV array. A stand-alone Photovoltaic system with a boost converter is simulated in MATLAB Simulink to demonstrate the results and applicability of the proposed method.

Maximum Power Point Tracking of solar photovoltaic cell using Perturb & Observe and fuzzy logic controller algorithm for boost converter and quadratic boost converter

Comparison of the input filter effect to PV panel by SEPIC MPPT converter

Solar power converters were used to convert the electrical energy from solar arrays to a stable and reliable power source. The object of this paper is to analyze and design DC/DC power converters of different types in a PV power system to investigate the performance of such converters. A simple method which combines discrete time control and a PI compensator is used to track the maximum power points (MPPs) of the solar array. The system is kept to operate close to the MPPs, thus the maximum possible power transfer from the solar array is achieved. The implementation of the proposed power converter system was based on a digital signal processor. Experimental tests were carried out for buck, boost and buck-boost power converters using a simple maximum power point tracking algorithm. The efficiencies for the system with different power converters are compared and presented.