Internal model based current control for grid integrated solar photovoltaic

In this paper, single stage conversion method is used for integration of the Solar Photo Voltaic (SPV) with the utility grid. Three phase voltage source converter is used to extract the maximum power from the PV source as well as to integrate the SPV to the grid. The power produced by SPV changes with change in solar irradiance, hence, a Maximum Power Point Tracking (MPPT) scheme is used to obtain the maximum power at a particular irradiance. The Fizzy Logic Control (FLC) and Adaptive Network based Fuzzy Inference System (ANFIS) are proposed for the DC link voltage control. The power produced by the SPV is used to supply the local load demand, and the extra power, if any, is fed to the utility grid or the deficit power is supplied by the grid. The proposed control scheme is validated using Matlab/Simulink under different irradiance values.

This paper presents the energy management in a solar PV based charging station integrated with battery energy storage system (BESS). The provision of optional exchange of power by the DC grid with the utility grid has been created here. Power flow through the utility grid is controlled using a voltage source converter (VSC). The loads considered are the Electric Vehicles (EVs) batteries. Load demand was met by the maximum power obtained from the solar PV (Photo Voltaic) using Maximum Power Point Tracking (MPPT) controller. An automated control of energy flow among solar PV, BESS and load battery is proposed using DC-DC converters. The dip in DC microgrid voltage, because of excess load demand beyond the available combined maximum power from solar PV and BESS, is compensated by delivering deficient power from utility grid. PSCAD simulation results are presented here to validate the proposed scheme.

Solar Photovoltaic (SPV) offers alternative sources of energy which is in general pollution free, environment friendly, sustainable and unlimited in nature. The concerns of environment due to green house gases and global warming force research communities to develop a smart power system that has capability to integrate Solar Photovoltaic with the power grid. There are many challenges in integrating SPV generation with the grid like efficiency, power quality, stability, cost of the energy conversion, load management, reliability etc. Moreover, power quality problems at distribution level like harmonics, unbalanced supply, unbalanced loads, reactive power, load management etc. affect the operation of grid connected SPV systems. Single stage grid connected PV systems has the advantage of use of a single VSC for MPPT (Maximum Power Point Tracking) and inverter operation. The proposed grid interfaced SPV generating system consists of a SPV array, VSC (Voltage Source Converter), three-phase grid and linear/nonlinear loads. The SPV energy is injected in to the DC bus of VSC during sunshine hours. The DC bus voltage of a three- phase VSC is regulated for MPPT from the PV array. Secondly, this system serves to provide harmonics elimination, load balancing, power factor correction (PFC) and regulating the terminal voltage at the PCC (Point of Common Coupling). In this paper, a SRF (Synchronous Reference Frame) based control of a single stage dual purpose grid connected SPV system is proposed and simulation based on MATLAB and Simpower System Blockset demonstrates the dual purpose of the system.

The proposed work deals with the implementation of a control approach for an active power transfer between solar photovoltaic (PV) array and grid/ load alongwith power quality improvement by eliminating harmonics and compensating reactive power required by the load in the distribution system. The PV array is directly connected across the DC link of a voltage source converter (VSC). The power is transferred to the grid/ load through VSC, which performs the function of distribution static compensator (DSTATCOM) by injecting compensating currents in the proposed system. The PV array is operated at maximum power by employing the usage of perturb and observe (P&O) maximum power point tracking (MPPT) approach in order to extract the available maximum power from the solar PV array. A feed-forward term for the solar PV array power, is incorporated for the enhancement of dynamic response. The prominence of the control algorithm lies in the efficient switching of VSC, by generating reference grid currents, which are obtained through indirect current control technique. The recursive digital filter is utilized for processing the load currents and extracting the active power component of the load currents. Therefore, the active power component of load currents obtained, are used for generating the reference grid currents in the proposed system. A prototype of the system is developed in the laboratory and its performance is studied for varying loads, changing solar insolation, and voltage swell and voltage sag conditions.

Due to the Randomness and fluctuation of the photovoltaic (PV) system, Maximum Power Point Tracking (MPPT) algorithm is employed to ensure the maximum power extraction from PV arrays, when it is connected to the grid. The previous studies have indicated that the MPPT algorithm is one of the main causes of interharmonics emission in PV systems. The MPPT algorithm parameters such as perturbation step size inevitably have a strong impact on the interharmonics in the current injected to the grid. In general, a smaller MPPT perturbation step size will reduce the interharmonics emission level, but it will result in poor tracking performance of the MPPT algorithm. Thus, there is a trade-off between the MPPT efficiency and the interharmonics emission in PV system. In this paper, an interharmonics suppression scheme with variable step size MPPT algorithm was proposed. In the suppression scheme, two voltage values near by the MPPT voltage and two tracking step size are preset. When the dc-link voltage of PV is between the two preset voltage values, it means that the PV power near its MPP and the smaller perturbation step size implemented in the MPPT algorithm. Otherwise, the bigger perturbation step size is employed. It can greatly reduce interharmonics emission level and maintain the MPPT efficiency. Simulations have been carried out to verify the effectiveness of the suppression scheme.

Purpose Silicon photovoltaics technology has drawbacks of high cost and power conversion efficiency. In order to extract the maximum output power of the module, maximum power point (MPP) is used by implying the nonlinear behavior of I-V characteristics. Different techniques are used regarding maximum power point tracking (MPPT). The paper aims to review the techniques of MPPT used in PV systems and review the comparison between Perturb and Observe (P&O) method and incremental conductance (IC) method that are used to track the maximum power and gives a comparative review of all those techniques. Design/methodology/approach A study of MPPT techniques for photovoltaic (PV) systems is presented. Matlab Simulink is used to find the MPP using P&O simulation along with IC simulation at a steady temperature and irradiance. Findings MATLAB simulations are used to implement the P&O method and IC method, which includes a PV cell connected to an MPPT-controlled boost converter. The simulation results demonstrate the accuracy of the PV model as well as the functional value of the algorithms, which has improved tracking efficiency and dynamic characteristics. P&O solution gave 94% performance when configured. P&O controller has a better time response process. As compared to the P&O method of tracking, the incremental conductance response rate was significantly slower. Originality/value In PV systems, MPPT techniques are used to optimize the PV array output power by continuously tracking the MPP under a variety of operating conditions, including cell temperature and irradiation level.

K-Nearest Neighbors hybrid method for maximum power point tracking under partial shading for photovoltaic power systems

A maximum power point tracking (MPPT) DC/DC converter for a photovoltaic (PV) system is an important component in a PV system. The converter is used to convert the value of DC voltage produced by PV panels to a value accepted by the inverter for on-grid, or battery for off-grid system. In addition, the MPPT is used to extract and maintain the solar PV to its maximum power in all conditions. However, the values of components used in literature of MPPT DC/DC converter for a specific PV module cannot be applied for different capacity. Although sets of equations are given in literature to determine the values of inductor and capacitor used in the circuit, the calculated values do not produce the desired output in most cases because of unclear explanation. The validation of input parameters of the converter is also not properly presented for different solar irradiance and temperature. The efficiency of the converter is still low. Hence, this paper presents step-by-step process on how to design a MPPT DC/DC boost converter in MATLAB/Simulink environment. The incremental conductance method is used as MPPT algorithm to control the duty cycle of the converter. Then, a thorough analysis is done by simulating the developed model under different solar irradiance and temperature. Simulation results are then compared with the theoretical values from I-V and P-V curves of the selected PV modules. The results show that the proposed MPPT DC/DC converter is able to extract maximum power from PV modules and the output power produced by the converter also indicates that the converter has a high efficiency at 99.7% in all selected values of solar irradiance and temperature.

This paper describes the model matching controller design using Internal Model Control (IMC) controller and the approach of multiobjective optimization based Genetic Algorithm (GA) is used to optimize the value of tuning parameter lambda (λ) of an IMC controller to have more improved robustness and performance for a First Order Plus Time Delay (FOPTD) model. IMC controller is fairly robust towards the uncertainty and can be implemented in any plant process. IMC Controller is using single tuning parameter lambda (λ) which is capable to have trade off between servo-regulator problems from a performance and robustness point of view. GA is an optimization technique useful to minimize or maximize the objective function. Simulation results confirm the effectiveness of multiobjective optimization based GA approach for designing IMC controller to have better servo-regulator trade-off.

Energy crises and the growth of the energy demand have increased the interest in utilizing unconventional power sources. Thus, renewable energy sources have become a topic of interest to mitigate rising energy concerns and cope with increased electricity demand. With remarkable merits including cleanness and abundance, photovoltaic (PV) solar energy systems are a key to solving these issues. The employed inverters should effectively utilize the maximum available power from the PV solar system and transfer this power to the utility grid without posing any further limitations. However, the unequal power generation of different PV systems caused by partial shading (PS) and other PV panel degradation factors leads to a reduction in generation capacity. One of the relatively new solutions to mitigate the mismatch concerns between the PV modules and sub-modules is to extract the maximum power of each sub-module individually. The main objective of this paper is to present a comprehensive review of such PV grid-connected inverters topologies associated with sub-module connection and control. It will classify the PV grid-tied inverters in accordance with the level where the maximum power point tracking (MPPT) system is implemented. A special focus has been placed on sub-module microinverters (MI) in terms of circuit topologies, conversion efficiency, and controller design. This paper provides a comprehensive analysis of employing the distributed MPPT (DMPPT) approach to maximize the power generation of PV systems by mitigating the mismatch issues inside the PV module. The circuit topology, PV system configuration, and MPPT algorithms used for applying DMPPT solutions in PV SMs are discussed in detail in this study.

Solar photovoltaic (PV) system contributes a significant role in meeting power requirements and helps the decentralization of power generation and distribution. The output of the individual photovoltaic module depends on local temperature and irradiance. Since the variation of these parameters depends on the environmental factors, it is difficult to obtain maximum power in all instances. The maximum power point tracking (MPPT) technique is used for tracking the maximum power available at a particular instant. This paper presents the maximum power extraction from a photovoltaic system using Artificial Intelligence (AI) techniques. AI based methods provide a fast dynamic response with high accuracy and mitigate the effects of partial shading. A comparative study is performed for various AI based MPPT techniques such as Fuzzy, Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS). PV module output is interfaced with the resistive load through the Z-Source inverter (ZSI). The ZSI boost the input voltage and provides an AC output voltage. The AI based MPPT techniques have been investigated with conventional Z-source Inverter (ZSI) and Switched Inductor Z-Source inverter (SL-ZSI). A simple boost control technique is employed to control, both conventional and SL Z-source inverter. The performance of the system is verified using MATLAB Simulink.

Photovoltaic (PV) systems provide a number of challenges, one of the most critical of which is determining how to extract the maximum amount of usable power from the PV system even when the system is running in conditions of fast change in irradiance. This study aims to demonstrate a novel hybrid approach to maximum power point tracking (MPPT), which is built on the grey wolf optimization algorithm (GWO) and modified perturb and observe (MP&O) techniques. The second goal of this method is to provide a robust MPPT method with minimum losses in the MPP point of the PV module. This technique is based on the connection of a single KC200GT PV module. The KC200GT PV module is connected to the DC bus via DC/DC boost converter to raise the voltage and implement the MPPT algorithm. After that, the PV system was integrated to supply a new multilevel inverter (MLI) with a reduced number of switches. Additionally, the MATLAB/Simulink environment was used to demonstrate and evaluate the efficacy of the proposed MPPT approach. Complex fast changes in solar irradiation are applied to the module to verify the feasibility and efficacy of the hybrid method by comparing its performance to that of the P&O, and MP&O algorithms. The obtained results demonstrated that the hybrid GWO-MP&O MPPT method achieved an excellent level of efficacy in terms of MPP accuracy, convergence speed (0.05 sec), and overall tracking efficiency (99.7%) compared to other approaches. Keywords: Grey Wolf Optimizer, maximum power point, boost converter, photovoltaic system, multilevel inverter, perturb and observe. https://doi.org/10.55463/issn.1674-2974.50.2.7

The current publication is directed to achieve a high-performance stand-alone PV system having the capability of tracking maximum output power, providing fixed output DC voltage, and attaining efficient system utilization, under different irradiation levels. A new maximum power point tracking (MPPT) approach integrating the incremental conductance algorithm and fuzzy logic control, and enhanced with PI-controller, was proposed to track maximum power. To provide fixed output DC voltage and approaching full system utilization, the PV system is equipped with a battery bank, electrolyzer; as a dump load, and buck-boost converter, with two controllers. The results of the proposed MPPT technique; modified incremental conductance (MINC), are compared with the corresponding results of three prevalently implemented MPPT algorithms: perturbed and observed (P&O), modified variable step-size P&O (VSZ-PO) and the ordinarily incremental conductance (INC). The highest output power, best tracking efficiency and best output power response are achieved by utilizing the proposed MPPT method. The results of the output voltage response and electrolizer on/off states confirm the ability of the PV scheme to provide fixed DC voltage and attain efficient system utilization, under varying irradiances.

The solar photovoltaic (PV)‐based microgrid is one of the most ideal renewable energy resources. This paper presents a utility grid intertie multi‐PV‐inverter‐based microgrid (MG) control for the solar rooftop application. The main and ancillary voltage source converters (VSCs) DC links are assimilated with PV arrays of independent maximum power point tracking (MPPT) algorithms for the economical and efficacious single‐stage configuration. At the point of common coupling (PCC), parallel VSCs arrangement increases the MG's power rating with distinctive local loads. In normal circumstances, the current control methodology is employed by the main VSC under the grid‐interactive mode. Conversely, in some grid contingency conditions under the isolated mode, its control transfers to the voltage control, which regulates the frequency and the voltage at PCC and acts like a grid‐forming inverter. The ancillary VSC operation is implemented with the current control algorithm. The main VSC supplies the active power towards the grid and accomplishes the load requirement, whereas the ancillary VSC retains its load demand in a grid‐interactive mode and also regulates the load requirement in an islanded mode of operation. The utilization of feed‐forward components for PV arrays powers in the VSCs current control techniques improves the MG dynamic performance. The seamless mode transfer performance of the main VSC is implemented via a power electronics switch. The MATLAB software is used to model a microgrid and its performance is analysed via RT‐LAB in real time through the OPAL‐RT (OP4510) controller for various scenarios, that is, varying solar insolation, load alterations and unbalanced non‐linear loads. The utilization of the modified Kwong's algorithm‐based current control enhances the power quality such as harmonics current elimination and improvement in the power factor. The voltage profile of PCC voltages is enhanced via using a modified Kwong's algorithm‐based filter in the voltage controller. The modified Kwong's algorithm has fast convergence, reduces misadjustments and gives very good performance compared to the least‐mean‐square (LMS) and Kwong's approaches. The total harmonic distortion (THD) of grid currents and PCC voltages THD in an isolated mode is found according to the limits of the IEEE‐519 standard.

In this paper, a new approach for the design of PID based Internal model control (IMC) controller is proposed. The proposed design scheme incorporates model order reduction technique and an advanced state space control technique, i.e., linear quadratic regulator (LQR) in the classical IMC control scheme. A systematic algorithm is developed for determining the tuning parameters. Subsequently, the IMC controller is converted into a proportional-integral-derivative (PID) type controller. Further, the proposed scheme is applied for single area load frequency control of the power system. The proposed approach is compared with the existing techniques. The simulation results indicate that the proposed control scheme shows an improved disturbance rejection capability and better transient response in comparison to existing design techniques.