Performance comparison between PWM and MPPT charge controllers

This paper aims to obtain suitable control for the Standalone Photo Voltaic (SAPV) system to meet consumer demands in weather conditions. A SAPV system is developed with a solar array with Maximum Power Point Tracking (MPPT), a Boost converter, and an inverter. This system uses controllers for maximum power output tracking, constant DC output of the Boost converter, and constant output voltage and frequency with Pulse Width Modulation (PWM) control mode. MPPT, boost converter, and inverter controller parameters are designed and tuned, respectively. Proportional gain (Kp) and Integral gain (Ki) values and the Sliding Mode Method (SMC) tune the controller parameters. The innovative aspect of this work is to propose a standalone PV system with controllers based only on the sliding mode control approach. Moreover, the current controller provides an output current of high quality with a THD of 1.6 %. Effectiveness and robustness of the proposed scheme modeled and simulated under OPAL-RT real-time Software in Loop (SIL) platform with MATLAB Simulink under fast variations of irradiance and temperature. Various analyses have been carried out for examining the proposed Sliding Mode Controller-based standalone photovoltaic system.

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.

Photovoltaic (PV) solar systems with series-connected module integrated converters (MICs) are receiving increased attention because of their ability to create high output voltage while performing local maximum power point tracking (MPPT) control for individual solar panels, which is a solution for partial shading effects in PV systems at panel level. To eliminate the partial shading effects in PV system more effectively, sub-MICs are utilized at the cell level or grouped cell level within a PV solar panel. This study presents the results of a series-output-connection MPPT (SOC-MPPT) controller for sub-MIC architecture using a single sensor at the output and a single digital MPPT controller (sub-MIC SOC-MPPT controller and architecture). The sub-MIC SOC-MPPT controller and architecture are investigated based on boost type sub-MICs. Experimental results under steady-state and transient conditions are presented to verify the performance of the controller and the effectiveness of the architecture.

An off-grid photovoltaic (PV) system's PV array is connected with a charge controller as the first power conversion stage. The average efficiency of the power stage of charge controllers is around 90%. Supercapacitor (SC) battery hybrid PV system is a novel PV system that utilizes some of the wasted energy of a typical system and enhances the system's efficiency up to 98%. However, the feasibility of maximum power point tracking (MPPT) for this system is yet to be validated. This paper presents a comparative study to adapt MPPT for the proposed system consisting of a series-connected SC bank with PV array and step-down DC-DC converter. The step-down converter is used as the impedance matching network. Different solar irradiance profiles were emulated to check the feasibility and efficiency of MPPT. Experimentally, it was shown that the typical MPPT could be adapted to the proposed PV system with very high MPPT efficiency.

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.

Soft switching maximum power point tracker with resonant switch in PV system

With the growing demand for renewable energy, solar photovoltaic (PV) systems have gained popularity as a reliable source of clean electricity. However, the performance of these systems can be limited by factors such as suboptimal maximum power point tracking (MPPT) algorithms. In order to improve the power generation efficiency of PV systems, it is important to evaluate the performance of dynamic MPPT algorithms that can adapt to varying operating conditions. Traditionally, such evaluations have been time consuming and expensive, often requiring extensive testing and measurement equipment. In this paper, we propose a novel approach to evaluate dynamic MPPT performance very quickly and simply using PSIM software. This approach enables accurate and efficient evaluation of MPPT performance under a wide range of operating conditions, while minimizing the cost and time involved in traditional testing methods. When applying the proposed method to a 3.7 kW inverter using the traditional perturbation and observation (P and O) method, we found that the highest average efficiency was 98.92% at an MPPT control period of 0.1s and a voltage perturbation of 1 V. This evaluation technique provides valuable insights into the design and optimization of more efficient MPPT control algorithms, leading to improved power generation efficiency and increased adoption of solar PV systems.

Photovoltaic traffic light system is a significant application of renewable energy source. The development of the system is an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic (PV) modules still have relatively low conversion efficiency, an alternative control of maximum power point tracking (MPPT) method is applied to the traffic light system. MPPT is intended to catch up the maximum power at daytime in order to charge the battery at the maximum rate in which the power from the battery is intended to be used at night time or cloudy day. MPPT is actually a DC-DC converter that can step up or down voltage in order to achieve the maximum power using Pulse Width Modulation (PWM) control. From experiment, we obtained the voltage of operation using MPPT is at 16.454 V, this value has error of 2.6%, if we compared with maximum power point voltage of PV module that is 16.9 V. Based on this result it can be said that this MPPT control works successfully to deliver the power from PV module to battery maximally.

Solar Photo-voltaic (PV) arrays have non-linear characteristics with distinctive maximum power point (MPP) which relies on ecological conditions such as solar radiation and ambient temperature. In order to obtain continuous maximum power (MP) from PV arrays under varying ecological conditions, maximum power point tracking (MPPT) control methods are employed. MPPT is utilized to extract MP from the solar-PV array; high-performance soft computing techniques can be used. In this paper, the proposed hybrid MPPT algorithm is used in the solar-PV system with variable climatic conditions. The performance of the proposed hybrid MPPT algorithm with different membership functions is analyzed to optimize the MPP. Simulation results establish that with the application of MPPT controller such as Perturb and Observe, Fuzzy Logic and a proposed hybrid MPPT for the solar-PV system, the proposed hybrid MPPT controller provides more accurate performance and also reduces the fluctuation about the MPP as compared to other MPPT techniques.

This paper proposes a dynamic maximum power point tracking (MPPT) controller for a solar photovoltaic (SPV) system with a battery charging circuit. The voltage and current, and consequently the maximum available power of SPV panels vary based on environmental conditions. To operate SPV system at maximum power point under different weather conditions, a cascaded (PI-PD) controller with PSO gain scheduling is suggested in this paper. Also, the FOPI control is applied to an accurate dynamic model of the buck converter to function as a charge controller. For tuning the FOPI controller parameters, a stochastic inertia weight GWO algorithm is employed which maintains an appropriate balance between detection and hunting strategies, and gives the fittest wolf position during iterations. The proposed algorithm is compared with the original GWO algorithm to show its superiority. The accuracy of the proposed cascaded controller used in the SPV system to find MPP ranges from 96.05% to 98.87%. The goal of this study is to operate the SPV panel at maximum power point under variable atmospheric conditions to increase efficiency at a lower cost. It also provides appropriate current and voltage for faster battery charging, thereby increasing the life span of the battery. The system is implemented and analyzed in MATLAB/Simulink, and results are validated.

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.

An improved adaptable step-size P&O MPPT approach for standalone photovoltaic systems with battery station

Renewable energy is becoming more popular every day. This is mainly attributed to threats that fossil fuels pose towards the climate change, and also the fact that they are scarce. Thus, solutions such as solar energy are among the top trending alternatives to the fossil fuels. However, one of the main issues with solar energy, particularly with its most popular technique, the photovoltaic solar arrays, is that they are not efficient when it comes to their ratio of power to cost. In order to address this problem, we propose a voltage regulation system that enhances photovoltaic system. The main feature of this system is that it uses a DC-DC converter that regulates the power using specific voltage inputs. Combining this system with Maximum Power Point Tracking (MPPT), the efficiency of the photovoltaic panels to reach its maximum capacity. The voltage is regulated using a buck and boost converter. In order to simulate the environment, MATLAB SIMULINK is used for developing and implementing the system, as well as applying the algorithms related to the fuzzy logic controller for Pulse Width Modulation (PWM) signal generation on the converter. The results indicated that using fuzzy logic technique is an effective method for the increasing the photovoltaic system power to cost efficiency. Other than being a novel technique, the fuzzy logic strategy is also robust and adaptable, which allows it to be combined with a multitude of systems.

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.

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.