A Comparative Study between Single-loop and Dual-loop Tracking Control Schemes for MPPT of Solar Tracking System

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 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.

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.

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.

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.

Photovoltaic (PV) grid-connected system is the development trend of photovoltaic systems. According to the PV grid-connected system characteristics, analyzes the maximum power point tracking(MPPT) control strategy based on two-stage power conversion architecture, proposed a novel MPPT control algorithm, it can achieve the maximum power point tracking by only detect one parameter-the inverter output current. In the Matlab/Simulink simulation environment, building the system model and simulation based on the control scheme, the system can find the maximum power point quickly and steadily, compared with the widely used MPPT algorithm simulation result, proved the correctness and feasibility of control scheme, has practical value.

In this paper, a prototype fuzzy logic based maximum power point tracking (MPPT) controller for photovoltaic (PV) systems is presented. The prototype is a boost converter controlled by dSpace® using DS 1104 boar to control current will be extracted from PV. The current is related to maximum power at the moment. That is the implementation MPPT. This paper show comparison result MPPT using FLC and conventional method (Perturbation and observation) in Matlab simulation. Simulation is done to verify and justify the controller before hardware implementation. A prototype hardware implementation is carried out for 5 KW case to manifest in real system.

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.

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.

Recently, real-time simulation of renewable energy sources are indispensible for evaluating the performance of the maximum power point tracking (MPPT) controller, especially in the photovoltaic (PV) system in order to reduce cost in the testing phase. Nowadays, real time PV simulators are obtained by using analog and/or digital components. In this paper, a real-time simulation of a PV system with a boost converter was proposed using only the digital signal processor (DSP) processor with two DC voltage sources to emulate the temperature and irradiation in the PV system. AMATLAB/ Simulink environment was used to develop the real-time PV system with a boost converter into a C-program and build it into a DSP controller TMS320F28335. Besides, the performance of the real-time DSP-based PV was tested in different temperature and irradiation conditions to observe the P-V and V-I characteristics. Further, the performance of the PV with a boost converter was tested at different temperatures and irradiations using MPPT algorithms. This scheme was tested through simulation and the results were validated with that of standard conditions given in the PV data sheets. Implementation of this project helped to attract more researchers to study renewable energy applications without real sources. This might facilitate the study of PV systems in a real-time scenario and the evaluation of what should be expected for PV modules available in the market.

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.

This paper presents a photovoltaic system with maximum power point tracking facility. Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. The system consists of a photovoltaic solar module connected to a DC–DC buck–boost converter and load. The adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) controller is used to track the maximum power. DC–DC boost converter and space vector modulation-based inverter are used to provide the required supply to the load. The proposed ANFIS-based MPPT improves the system efficiency even at abnormal weather conditions. Here a lot of reduction in torque and current ripple contents is obtained with the help of ANFIS-based MPPT for an asynchronous motor drive. Also, the better performance of an asynchronous motor drive is analyzed with the comparison of conventional and proposed MPPT controller using MATLAB simulation along with experimental implementation. The experimental implementation of MPPT with hardware setup is done using dSPACE real-time controller. Data acquisition and codes of the successfully simulated model can be linked and loaded directly to the dSPACE DS-1104 controller for real-time hardware operation. The simulation and the practical results represent that the proposed system tracked the maximum power accurately and successfully under different working conditions. Practical validations are also carried out and are represented.

African vulture optimized RNN algorithm maximum power point tracking (MPPT) controller for photovoltaic (PV) system

This paper develops a novel maximum power point tracking (MPPT) control strategy for nonlinear photovoltaic (PV) systems. The MPPT control problem of the considered PV systems is first formulated in the framework of fuzzy descriptor systems. Then, based on the new formulation, a fuzzy sliding mode control (FSMC) law is constructed to drive the state trajectories into a desired sliding surface within the finite-time T* with T* < T. Moreover, sufficient conditions are derived to ensure the reachable set boundings of the closed-loop PV control systems in the finite-time intervals [0,T*] and [T*,T]. A simulation example is given to show the effectiveness of the proposed design method.

Photovoltaic (PV) systems have witnessed a rapid increment, the yield mainly relies on the working condition. In most cases, it is hard to obtain the optimal yield. Therefore, Maximum Power Point Tracking (MPPT) controllers witness much attention as an important optimization field of PV systems. These controllers employ different algorithms and they vary in their efficiency, performance, modernity, complexity, and tracking speed. MPPT controllers have witnessed a rapid improvement, they can be generally classified as conventional and advanced methods. Conventional methods are relatively simple but they can't distinguish between the local and global peaks if partial shading occurs, therefore, their efficiency is relatively low. Advanced tracking methods are widely used due to their superior efficiency. Due to the limitation of the singular conventional and advanced methods, hybrid methods find their way to solve these limitations. Selecting the finest MPPT method is still an open issue, this issue can be solved by implementing a survey of the applied methods. This study gives a concise classification and evaluation review of all the applied MPPT methods. This study also provides an accessible reference to undertake mass research works in MPPT in the near future.