Hybrid Modular Multilevel Converter Based Single-Phase Grid Connected Photovoltaic System

This paper presents the application of “ripple correlation control (RCC)” maximum power point tracking (MPPT) algorithm for photovoltaic (PV) system employing dc-dc Cuk converter to maximize the output power of PV module. Soft switching commutation of the main and auxiliary switches at zerovoltage using active clamp technique allows the operation of the Cuk converter at very high switching frequencies with reduced size of reactive elements and electromagnetic interference. The combination of auxiliary switch, clamp capacitor and resonant inductor is used to exploit the advantage of high efficiency with zero switching losses. RCC technique uses the high frequency signal ripple, which makes it to converge asymptotically to the maximum power point independent of module configuration and parameters. The operating modes of converter for different switching time intervals are analyzed and design considerations are presented. The simulated performance of the converter with RCC MPPT over conventional MPPT algorithms is presented. The MPPT methods are compared on the basis of the time taken to track the maximum power point (MPP), steady state oscillations about MPP and dependence on array parameters. To evaluate the viability of ZVS Cuk converter with RCC MPPT, the entire system is simulated using MATLAB/SIMULINK platform for an 87 Wp solar PV system.

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.

In this work, a simulation study and comparative analysis of conventional Maximum Power Point Tracking (MPPT) technique, i.e., Incremental Conductance (IC) with nonlinear technique, i.e., Ripple Correlation Control (RCC), has been done. Photovoltaic (PV) array and the DC/DC boost converter along with MPPT control strategy have been implemented and simulations analysis has been presented for both the techniques for various solar irradiance levels at 25 °C temperature. The system has been designed to achieve 450 V and 10 kW output at 1000 W/m2 irradiation, which is attained through a DC/DC boost converter. Simulation results show that the IC technique’s output is very much affected by oscillations under steady-state and varying environmental conditions, which affects the system’s stability; whereas, RCC removes all ripples from voltage, current, and power outputs in steady-state and upto some extent in transient state, due to its inherent ripple removal feature. However, during transitions RCC also exhibits underdamped response, but it is minimum as compared to other MPPT techniques.KeywordsPhotovoltaic (PV)DC/DC Boost converterMaximum Power Point Tracking (MPPT)IrradianceRipplesIncremental Conductance (IC)Ripple Correlation Control (RCC)

This paper introduces a novel curvature-based ripple correlation control (RCC) technique for maximum power point tracking (MPPT) in photovoltaic (PV) systems. Ripple correlation control has become a prominent MPPT method due to its straightforward implementation, high accuracy, and quick asymptotic convergence. It effectively tracks the maximum power point (MPP) of PV systems amidst swift changes in solar irradiance and temperature. The curvature of the power-voltage curve provides essential insights into the power output behavior of PV panels in response to voltage fluctuations. Specifically, the curvature offers a critical indication of the system's proximity to the MPP. This information is crucial for optimizing the control gain of the ripple correlation controller to enhance both dynamic and steady-state performance. The simulation and experimental results corroborate the theory proposed in this paper and validate its contributions.

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.

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 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.

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.

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.

This paper presents the application of the "ripple correlation control (RCC)" maximum power point tracking (MPPT) algorithm for Stand-Alone photovoltaic (PV) system employing dc-dc Cuk converter to maximize the output power of PV module. The combination of auxiliary switch, clamp capacitor and resonant inductor is used to exploit the advantage of minimum voltage stress across the semiconductors at switching transitions due to clamping action. RCC technique uses the high frequency signal ripple, which is inherent in power converters to converge asymptotically to the maximum power point independent of module configuration and parameters. The operating modes of converter for different switching time intervals are analyzed and design considerations are presented. To evaluate the feasibility of ZVS Cuk converter with MPPT, simulation is carried out using MATLAB/SIMULINK platform for an 87 Wp solar PV system and the simulated performance results are presented.

Harsh outdoor operating circumstances of photovoltaic (PV) array leads to non-uniform aging phenomenon among PV panels which in turn reduces the life span of the PV modules and the energy efficiency of the whole array. Under non-uniform aging conditions for series-parallel (SP) connected PV modules, the characteristics of the entire PV array are deformed resulting in multiple peaks where one of them is the global peak. The appearance of such multiple peaks can mislead traditional maximum power point tracking (MPPT) techniques to get trapped at local peaks, which leads to misleading power losses. This paper proposes a current collector optimizer (CCO) topology to extract maximum power from a non-uniform aged PV array. By using CCO topology, the PV array characteristics have a unique maximum power point (MPP) which easy to follow by a simple MPPT algorithm. Consequently, the proposed topology does not suffer from misleading power losses. Besides, the CCO topology requires offline rearrangement of aged modules to obtain the optimal maximum power. A comparative study is conducted to demonstrate the efficacy of the proposed topology. Ultimately, the paper presents an offline algorithm for rearranging erratic aged CCO modules to extract the optimum power from large-scale PV arrays.

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.

The escalating demands and increasing awareness for the environment, resulted in deployment of Photovoltaic (PV) system as a viable option. PV system are widely installed for numerous applications. However, the challenges in tracking the maximum power with intermittent atmospheric condition and varying load is significant. Maximum Power Point Tracking (MPPT) algorithms are employed and based on their convergence speed, control of external variations and oscillation, the output power efficiency, and other significant factors viz. the algorithm complexity and implementation cost, novel MPPT approach are preferable than the conventional approach. This paper presents an artificial intelligence-based optimization controller for MPPT in a PV system under varying load and irradiance conditions. Comparative analysis of Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) based MPPT is simulated and analysed. The PV system consisting of PV array and boost converter with MPPT controller feeds the DC load. The power conversion and panel efficiency are the significant factors to determine the effectiveness of tracking maximum power point. The simulation results show the performance of these controllers on the PV panel output power and the load side output power under changing loads and irradiance. In addition, the comparison of PV panel efficiency of ANN and PSO based MPPT techniques w.r.t changing loads is carried out. Based on the above analysis, PSO based MPPT algorithm marginally outperforms the ANN based MPPT algorithm. Further, the implementation of hybrid MPPT (ANN &PSO) for higher accuracy and tracking capability can be carried out as future work.

On-chip integrated power management MPPT controller utilizing cell-level architecture for PV solar system

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.