Performance analysis of the tracking of the global extreme on multimodal patterns using the Asymptotic Perturbed Extremum Seeking Control scheme

This paper presents the capability of the Asymptotic Perturbed Extremum Seeking Control (aPESC) scheme to track the Global Extreme on multimodal patterns. The multimodal patterns are simulated based on power characteristics generated by a photovoltaic (PV) array under Partial Shading Conditions (PSCs). The aPESC scheme is tested to evaluate the performance of locating, searching and tracking of the Global Maximum Power Point (GMPP). The following performance indicators such as the searching resolution, tracking accuracy, tracking efficiency, and tracking speed are used to compare the performance of the GMPP tracking (GMPPT) algorithms. The aPESCH1 scheme proposed has been implemented in MATLAB/Simulink package to evaluate the performance indicators mentioned above. The results prove that the proposed aPESCH1 scheme is effective and simple to be implemented.     

Designing and modelling of the asymptotic perturbed extremum seeking control scheme for tracking the global extreme

This paper presents the designing and modeling of the Asymptotic Perturbed Extremum Seeking Control (aPESC) scheme that is capable to locate and track the Global Extremes on the multimodal patterns. The multimodal patterns may appear on power generated by a photovoltaic (PV) array under Partial Shading Conditions (PSCs), but also on net power generated by a Fuel Cell (FC) system. The proposed aPESC scheme uses a scanning technique to determine the GMPP on different multimodal patterns based on two components of the searching signal: (1) the scanning signal locates the LMPP by sweeping the PV pattern based on a asymptotic dither modulated by the first harmonic of the PV power and controlled by the dither gain (k₂); (2) the tracking signal finds and tracks accurately the GMPP based on similar loop used in PESC schemes proposed in the literature that is controlled by the loop gain (k₁). These tuning parameters are designed based on the averaged model of this aPESC scheme. Also, the averaged scheme and local averaged loop of the aPESCH1 scheme are used to estimate the searching gradient and analyze the closed ESC loop stability. The design methodology is tested on generic multimodal patterns and then is validated considering a PV system and a FC system.     

一种改进型的太阳能最大功率点跟踪控制与仿真

从实际应用角度出发,论述了采用改进间歇扫描跟踪的方法进行最大功率点跟踪控制的过程,并通过仿真实验验证其可行性和有效性,从而达到了较好利用太阳能的目的。     

Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions

Influenced by partial shade, PV module aging or fault, there are multiple peaks on PV array's output power–voltage (P–V) characteristic curve. Conventional maximum power point tracking (MPPT) methods are effective for single peak P–V characteristic under uniform solar irradiation, but they may fail in global MPP tracking under multi-peak P–V characteristics. Existing methods in literature for this problem are still unsatisfactory in terms of effectiveness, complexity and speed. In this paper, we first analyze the mathematical model of PV array that is suitable for simulation of complex partial shade situation. Then an adaptive MPPT (AMPPT) method is proposed, which can find real global maximum power point (MPP) for different partial shade conditions. When output characteristic of PV array varies, AMPPT will adjust tracking strategies to search for global peak area (GPA). Then it is easy for conventional MPPT to track the global MPP in GPA. Simulation and experimental results verify that the proposed AMPPT method is able to find real global MPP accurately, quickly and smoothly for complex multi-peak P–V characteristics. Comparison analysis results demonstrate that AMPPT is more effective for most shade types.     

Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method

This paper proposes maximum photovoltaic power tracking (MPPT) for the photovoltaic (PV) array using the fractional-order incremental conductance method (FOICM). Since the PV array has low conversion efficiency, and the output power of PV array depends on the operation environments, such as various solar radiation, environment temperature, and weather conditions. Maximum charging power can be increased to a battery using a MPPT algorithm. The energy conversion of the absorbed solar light and cell temperature is directly transferred to the semiconductor, but electricity conduction has anomalous diffusion phenomena in inhomogeneous material. FOICM can provide a dynamic mathematical model to describe non-linear characteristics. The fractional-order incremental change as dynamic variable is used to adjust the PV array voltage toward the maximum power point. For a small-scale PV conversion system, the proposed method is validated by simulation with different operation environments. Compared with traditional methods, experimental results demonstrate the short tracking time and the practicality in MPPT of PV array.     

A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems

Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximise the output power of a photovoltaic array. Whilst several techniques have been designed, Perturb and Observe (P&O) is widely used for MPPT due to its low cost and simple implementation. Fuzzy logic (FL) is another common technique that achieves vastly improved performance for MPPT technique in terms of response speed and low fluctuation about the maximum power point. However, major issues of the conventional FL-MPPT are a drift problem associated with changing irradiance and complex implementation when compared with the P&O-MPPT. In this paper, a novel MPPT technique based on FL control and P&O algorithm is presented. The proposed method incorporates the advantages of the P&O-MPPT to account for slow and fast changes in solar irradiance and the reduced processing time for the FL-MPPT to address complex engineering problems when the membership functions are few. To evaluate the performance, the P&O-MPPT, FL-MPPT and the proposed method are simulated by a MATLAB-SIMULINK model for a grid-connected PV system. The EN 50530 standard test is used to calculate the efficiency of the proposed method under varying weather conditions. The simulation results demonstrate that the proposed technique accurately tracks the maximum power point and avoids the drift problem, whilst achieving efficiencies of greater than 99.6%.     

Design of a robust and efficient power electronic interface for the grid integration of solar photovoltaic generation systems

Nowadays, the penetration of photovoltaic (PV) solar power generation in distributed generation (DG) systems is growing rapidly. This condition imposes new requirements to the operation and management of the distribution grid, especially when high integration levels are achieved. Under this scenario, the power electronics technology plays a vital role in ensuring an effective grid integration of the PV system, since it is subject to requirements related not only to the variable source itself but also to its effects on the stability and operation of the electric grid. This paper proposes an enhanced interface for the grid connection of solar PV generation systems. The topology employed consists of a three-level cascaded Z-source inverter that allows the flexible, efficient and reliable generation of high quality electric power from the PV plant. A full detailed model is described and its control scheme is designed. The dynamic performance of the designed architecture is verified by computer simulations.     

A novel MPPT controller based PEMFC system for electric vehicle applications with interleaved SEPIC converter

The Proton Exchange Membrane Fuel Cells (PEMFCs) are one of the most effective and optimistic renewable energy source and they are extensively used in automotive applications. In the past, many researchers focused on solving the issues of extracting maximum power from fuel cell, controlling the speed and reducing the torque ripple of Brushless DC (BLDC) motor for fuel cell based Electric Vehicle (EV) systems. However, it is challenging to fine-tuning the gain parameters in the existing works MPPT approach and extracting maximum amount of energy. Additionally, it has limitations like unregulated voltage, problems of large overshoot, slow tracking speed, output power fluctuation, computational complexity and intricate modeling. Thus, the proposed work aims to create a revolutionary methodology called Unified Firefly Ersatz Neural Network (UFENN) - Maximum Power Point Tracking (MPPT). The UFENN is a kind of optimization-based machine learning technique that was created for efficiently optimizing the parameters to extract the maximum energy from the fuel cells. Furthermore, in order to control the output voltage with the least amount of power loss, an Interleaved SEPIC converter is also used in this work. During performance analysis, an extensive simulation results have been taken for validating the results of the proposed scheme by using various evaluation indicators.     

A robust hybrid method for maximum power point tracking in photovoltaic systems

In this paper a new hybrid method for maximum power point tracking in PV systems has been proposed. This method combines offline and online methods in order to estimate duty cycle of converter in maximum power point. In the offline phase, temperature and radiation intensity are the inputs of the system to estimate the approximate maximum power based on analytical equations of solar cell. These equations which give the relation of maximum power with temperature and irradiation can be derived from characteristics of cell provided by manufacturer or experiments. Afterwards the duty cycle of converter would be estimated using circuit equations of measured Thevenin model of the load and battery. Measuring Thevenin equation results in robustness of method respecting variations of load and battery. In the online phase, the classic perturbation and observation (P&O) method will be utilized for fine tuning and tracking of maximum power point. The proposed method has been simulated in MATLAB/SIMULINK workspace and compared with some other MPPT methods. The results reveal that this hybrid method outperforms other methods in term of performance and speed of tracking.     

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

Due to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% and 31% depending on the PV technology.     

Analytical model for predicting the performance of photovoltaic array coupled with a wind turbine in a stand-alone renewable energy system based on hydrogen

We present the results of an analysis of the performance of a photovoltaic array that complement the power output of a wind turbine generator in a stand-alone renewable energy system based on hydrogen production for long-term energy storage. The procedure for estimating hourly solar radiation, for a clear sunny day, from the daily average solar insolation is also given. The photovoltaic array power output and its effective contribution to the load as well as to the energy storage have been determined by using the solar radiation usability concept. The excess and deficit of electrical energy produced from the renewable energy sources, with respect to the load, govern the effective energy management of the system and dictate the operation of an electrolyser and a fuel cell generator. This performance analysis is necessary to determine the effective contribution from the photovoltaic array and the wind turbine generator and their contribution to the load as well as for energy storage.