A Novel Intelligent Neural Network Techniques of UPQC with Integrated Solar PV System for Power Quality Enhancement

A Novel, Intelligent control of a Unified Power Quality Conditioner (UPQC), coupled with a Photovoltaic (PV) system, is proposed in this work. It enhances the decarbonizes clean energy generation and maintains Power Quality (PQ) to the grid. In PV integrated UPQC, Crow Search Algorithm (CSA) assisted Perturb and Observation (P&O) Maximum Power Point Tracking (MPPT) technique. A d-q theory-based control is employed with the assistance of a Proportional Integral (PI) controller for controlling the working of UPQC and maintaining the power quality. The dynamic working of the PV-based UPQC is evaluated based on simulation outcomes attained from MATLAB

A Novel Intelligent Neural Network Techniques of UPQC with Integrated Solar PV System for Power Quality Enhancement

A Novel, Intelligent control of a Unified Power Quality Conditioner (UPQC), coupled with a Photovoltaic (PV) system, is proposed in this work. It enhances the decarbonizes clean energy generation and maintains Power Quality (PQ) to the grid. In PV integrated UPQC, Crow Search Algorithm (CSA) assisted Perturb and Observation (P&O) Maximum Power Point Tracking (MPPT) technique. A d-q theory-based control is employed with the assistance of a Proportional Integral (PI) controller for controlling the working of UPQC and maintaining the power quality. The dynamic working of the PV-based UPQC is evaluated based on simulation outcomes attained from MATLAB

A single measurement of combined direct and indirect MPPT algorithm for mismatch PV module application / Mohd Najib Mohd Hussain

The use of module integrated converter (MIC) topologies for photovoltaic (PV) system is to harvest the maximum power point of PV module from solar irradiance. MIC is a promising method to keep the electrical power output from PV module at maximum capacity through maximum power point tracking (MPPT) algorithm during full-sun and mismatch module occurrence. This thesis focussed on the development of PV module integrated with positive output (PO) buck-boost converter by intelligent control of MPPT technique. A novel of combination direct and indirect (CoDId) MPPT algorithm is implemented for solving mismatch losses from existing PV system by employing the implementation of system identification approach. System identification is established via utilization of multi-input single-output (MISO) model and incorporation with simple iteration scheme. The main intention of this study is to develop a single sensor measurement of instantaneous output current from PV system in order to track maximum power point of the PV module. The signal from the sensor is then applied for power switching devices of the PO buckboost converter by the attained maximum power point current from CoDID MPPT method

Cascade sliding mode maximum power point tracking controller for photovoltaic systems

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands. Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances

A Review on Fuzzy-GA based Controller for Power Flow Control in Grid Connected PV System

Now-a-days Renewable Energy Sources became an alternative to meet the increasing load demand because they are environmental friendly and also available abundant in nature. Among the Renewable Energy Sources, the Photo Voltaic (PV) System is gaining more attention due abundant availability of solar energy. The Maximum Power Point Tracking Technique is used to extract maximum power from the Photo Voltaic (PV) Array. When there is a need to transfer bulk amount of power from PV Array to Power Grid, the power quality issues, especially the real and reactive power flow problems, are a major concern. In this paper a novel control technique was proposed to control the power flow and to deal with power quality issues that arise when PV Array is integrated with power grid. It consists of a Fuzzy-GA based Cascaded Controller fed Flexible AC Transmission System device, namely Unified Power Flow Controller, for effective control of real and reactive power flow in grid connected photovoltaic system. The output of the Fuzzy Logic Controller is a control vector which is fine tuned by using Genetic Algorithm approach

70% decrease of hot-spotted photovoltaic modules output power loss using novel MPPT algorithm

The phenomenon of 'hot-spotting' within photovoltaic (PV) panels, where a mismatched cell/cells heats up, leads to reliability and efficiency issues. In this brief, a novel maximum power point tracking (MPPT) algorithm is developed to compensate for hot-spotted PV module effects, thus increasing the output power and improving reliability. The MPPT algorithm implements two mitigation processes; the first to identify the optimum power-voltage curve to track the global maximum power point (GMPP). The second process is to manipulate the output power toward the GMPP through the control of the perturbation step size. In order to verify the appropriateness of the proposed algorithm, multiple hot-spotted PV modules were tested under various environmental conditions. Significantly, the algorithm reduces the hot-spotted PV modules output power loss by at least 70% under all irradiance transition scenarios, slow, medium, and fast

Photovoltaic Emulation System and Maximum Power Point Tracking Algorithm Under Partial Shading Conditions

In this thesis, a novel photovoltaic (PV) emulator and the state-of-art learning–based real-time hybrid maximum power point tracking (MPPT) algorithms have been presented. Real-time research on PV systems is a challenging task because it requires a precise PV emulator that can faithfully reproduce the nonlinear properties of a PV array. The prime objective of the constructed emulator based on integration of unilluminated solar panels with external current sources is to overcome the constraints such as the need for wide surrounding space, high installation cost, and lack of control over the environmental conditions. In addition, the proposed PV emulator is able to simulate the electrical characteristics of the PV system under uniform irradiation as well as partially shading conditions (PSC). Moreover, the application of MPPT technology in PV systems under PSC conditions is challenging. Under complex environmental conditions, the power-voltage (P-V) characteristic curve of a PV system is likely to contain both local global maximum power points (LMPPs) and global maximum power points (GMPP). The MPPT algorithm applied to a PV system should have minimal steady-state oscillations to reduce power losses while accurately searching for the GMPP. The proposed MPPT algorithms resolved the drawbacks of the conventional MPPT method that have poor transient response, high continuous steady-state oscillation, and inefficient tracking performance of maximum power point voltage in the presence of partial shading. The intended algorithms have been verified using MATLAB/Simulink and the proposed PV emulator by applying comparative analysis with the traditional MPPT algorithms. In addition, the performance of the proposed MPPT algorithms and control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-Time-Interface (RTI) 1007 processor board and DS2004 A/D and CP4002 Digital I/O boards. The results indicate that the algorithm is effective in reducing power losses and faster in tracking the speed of the maximum power point with less oscillation under partial shading conditions. In addition, excellent dynamic characteristics of the proposed emulator have been proven to be an ideal tool for testing PV inverters and various maximum power point tracking (MPPT) algorithms for commercial applications and university studies

A Real-Time Implementation of Novel and Stable Variable Step Size MPPT

This paper presents a complete study of a standalone photovoltaic (PV) system including a maximum power tracker (MPPT) driving a DC boost converter to feed a resistive load. Here, a new MPPT approach using a modification on the original perturb and observe (P&O) algorithm is proposed; the improved algorithm is founded on a variable step size (VSZ). This novel algorithm is realized and efficiently implemented in the PV system. The proposed VSZ algorithm is compared both in simulation and in real time to the P&O algorithm. The stability analysis for the VSZ algorithm is performed using Lyapunov’s stability theory. In this paper, a detailed study and explanation of the modified P&O MPPT controller is presented to ensure high PV system performance. The proposed algorithm is practically implemented using a DSP1104 for real-time testing. Significant results are achieved, proving the validity of the proposed PV system control scheme. The obtained results show that the proposed VSZ succeeds at harvesting the maximum power point (MPP), as the amount of harvested power using VSZ is three times greater than the power extracted without the tracking algorithm. The VSZ reveals improved performance compared to the conventional P&O algorithm in term of dynamic response, signal quality and stability

Power Ramp-Rate Control via power regulation for storageless grid-connected photovoltaic systems

Photovoltaic Power Ramp-Rate Control (PRRC) constitutes a key ancillary service for future power systems. Although its implementation through the installation of storage systems or irradiance sensors has been widely investigated, fewer studies have explored the power curtailment approach. The latter lacks efficiency, as it voluntarily produces power discharges, yet it is a cost-effective solution in terms of capital expenditures. This paper proposes a novel storageless and sensorless photovoltaic PRRC for grid-connected applications in which the photovoltaic power, rather than the voltage, is the controlled magnitude. The aforementioned contribution makes the effective tracking of the power ramp-rate limit possible compared to the existing methods in the literature. The method is assisted by a real-time curve-fitting algorithm that estimates the Maximum Power Point while operating suboptimally. Thus, no direct temperature or irradiance measurement systems are needed. The validation of the proposed PRRC strategy has been tested by simulation and compared to another approach available in the literature, considering real-field highly variable irradiance data. Experimental validation of the proposed strategy has been performed in real time via Controller Hardware-in-the-Loop.Agencia Estatal de Investigación PID2019-108966RB-I0

Design and Implementation of a Micro-Inverter for Photovoltaic Applications

The objective of this work is to design and build a novel topology of a micro-inverter to directly convert DC power from a photovoltaic module to AC power. In the proposed micro-inverter, a structure with two power stages, which are DC/DC and then DC/AC converters, is used. A novel MPPT algorithm is implemented and evaluated in the DC/DC converter to optimize the solar panel energy production. The new method operates with an efficiency of 97.9%, which is a 1% improvement on the standard method, and a response time of In this research, the following approach is taken. A literature review was conducted, to identify potential converter topologies. A topology for both converters was selected by comparison of performance through simulations. Maximum Power Point Tracking algorithms were also investigated, to select an appropriate control scheme. A design for two converters was then performed, leading to a prototype for experimental verificatio