A novel shading loss mitigation method in high density photovoltaic modules using Sovereign Butterfly Optimization for enhanced performance

This paper presents a power pulsation decoupling strategy for a two-stage single-phase photovoltaic (PV) inverter with film capacitor, which has small capacitance and large voltage ripple. Such large voltage ripple at DC bus is propagated to the PV array and decreases the maximum power point tracking (MPPT) efficiency. To maintain the MPPT efficiency, a new small-signal model which considers the DC bus voltage ripple is derived. Based on the model, a new boost current controller is developed and it consists of two parts: a PI controller to control DC component and a repetitive controller to suppress the harmonic component caused by the DC bus voltage ripple. Simulation results show that the proposed controllers have drastically reduced the double frequency voltage of the PV array, which improves the MPPT efficiency of the PV array. Experimental result further verified the effectiveness of the controller, the measured MPPT efficiency was increased from 97.06% to 99.9%.

A multi-input single inductor dual-output boost converter for multi-junction photo-voltaic (MJ-PV) energy harvesting is presented. The fast maximum power point (MPP) tracking of each photo-voltaic (PV) sub-cell for irradiation change and the high MPP tracking (MPPT) efficiency are obtained using a dual-loop MPPT control. The implemented discontinuous conduction mode (DCM) of converter operation minimizes cross-regulation among MJ-PV sub-cells. A dual-output path provides regulation at load and stores the extra harvested energy to a battery. A prototype board with the proposed system is implemented. The achieved peak power efficiency is 83% and the MPPT efficiency is 95%. This system can also be used for cell-level parallel-connected PV solar system.

Partial shading condition (PSC) has a bad effect not only on the shaded PV modules/arrays itself but also on the output power generated from the partially shaded photovoltaic (PSPV) system. It reduces the output power generated from the photovoltaic (PV) system and contributes in hot spot problem that may lead to thermal breakdown of shaded PV modules. Under PSC, multiple peaks, one global peak (GP) and many other local peaks (LPs) are generated in the P–V curve. This chapter concentrates on alleviating the partial shading effects and extracting the global maximum power available from the PSPV system. This has been achieved using the suitable and the best PV system design topologies and the efficient maximum power point tracker (MPPT) techniques in tracking the GP under PSC. Therefore, it is concluded that the partial shading (PS) mitigation techniques can be classified into PV system design topologies and MPPT techniques to not only alleviate the PS effects of the PSPV system but also to extract the GP. The PV system design topologies consist of the bypass and blocking diodes, PV system architectures, PV array configuration and PV array reconfiguration, whereas the MPPT techniques concentrate the most efficient heuristic MPPT in tracking the GP under PSC.

This paper presents the comparative analysis of most commonly used Maximum Power Point Tracking (MPPT) techniques viz Open Circuit Voltage (OCV), Perturb and Observe (PnO) and Incremental Conductance (INC) methods that are capable of extracting maximum power from the PV generation system with Soft Switched Interleaved Flyback(SSIFB) converter. The OCV technique is an indirect MPPT method that tracks the Maximum Power Point (MPP) using empirical data or mathematical expressions with numerical corrections and approximations. The direct methods such as PnO and INC techniques measure the actual instantaneous values of PV voltage and PV current to seek the MPP. The steady state performance of each of the MPPT algorithms on PV-SSIFB system under different solar irradiations is compared in terms of accuracy, MPPT efficiency and tracking speed. MATLAB/SIMULINK software is used to simulate and investigate the suitability and limitations of the PV — SSIFB system implemented with MPPT algorithm. The simulation results prove that the OCV MPPT method provides an effective MPP tracking at low irradiations and INC MPPT method offers the better steady state performance at medium and higher irradiations.

Photovoltaic (PV) system losses from inverter maximum power point tracking (MPPT) errors are a persistent source of uncertainty in PV performance modeling. MPPT efficiency comprises both static MPPT efficiency, which quantifies the array power captured under stable conditions, and dynamic MPPT efficiency, which applies under changing irradiance and temperature. Array-level I–V curve modeling can constrain both static and dynamic MPPT efficiency values for large-scale PV systems. We model static MPPT efficiency values as a function of the deviation in operating voltage from the maximum power point. We also estimate dynamic MPPT efficiency by introducing an MPPT time lag into performance models run for a variety of locations, time scales, and system designs. The results suggest that static and dynamic MPPT losses are likely minimal for modern inverters.

Compared with typical current controlled PV inverters, voltage controlled PV inverters based on droop control are easier to achieve seamless transfer between the stand-alone mode and the grid-connected mode. This paper achieves both seamless transfer and the maximum power point (MPP) tracking (MPPT) by adjusting droop curves dynamically, combining MPPT and P-f droop control. The DC voltage is difficult to control during grid connecting which will affect both the stability of the system and the MPPT efficiency. To solve this problem, a control method is proposed which includes an active power inner loop and a DC voltage outer loop. At last simulation and experimental results validate the proposed control strategy and show that DC voltage response is fast and stable. Both seamless transfer and MPPT operation modes are realized.

This paper presents a Maximum Power Point Tracking(MPPT) based Model Predictive Control (MPC) approach to obtain high accuracy and fast dynamic response. The tracking capability of the base algorithm is improved by the combination of two-methods. The proposed control approach tested on a three-phase grid-connected inverter that fed by PV panel group. Switching signals of the inverter are generated by the MPC algorithm. Reference current of the MPC algorithm determined by Perturb and Observe MPPT method. Thus, power flow is controlled by the MPC algorithm based on MPPT. Power flow, MPPT efficiency and THD analyzes are examined in a simulation that performed by using MATLAB/Simulink environment. Especially, the effectiveness of the proposed approach has been tested under varying irradiation and cloudy conditions. Besides the MPPT analyzes, current tracking capability of the MPC algorithm is examined under dynamic transition conditions. Results show that, MPPT efficiency of the proposed control approach is 98%.

This work deals with single-stage three-phase grid-connected Photovoltaic (PV) systems with a focus on developing an efficient Maximum Power Point Tracking (MPPT) technique under partial shading conditions. As partially shaded PV arrays exhibit a multi-modal behavior on their Power-Voltage (P-V) characteristics with a number of possible patterns, the MPPT strategy under such conditions is a complex and challenging task. An Extremum-Seeking Control (ESC) based method is proposed in this paper to track the global power peak under non-uniform irradiance conditions. It relies on the measurements of power and estimation of the power gradient to iteratively determine the segment of the P-V characteristics in which the global peak lies, without converging at the other local maxima. The proposed method is compared to the sequential ESC-based MPPT method presented in the literature. Different test scenarios of partial shading show that the proposed method can reach the global peak with a faster convergence rate and higher tracking efficiency than conventional approaches.

This paper introduces a humpback whale hunting behavior inspired whale optimization with differential evolution (WODE) technique-based tracking algorithm for the maximum power point tracking in the dynamic as well as the steady-state conditions of a partially shaded solar photovoltaic (PV) system. This “WODE” technique is used for quick and oscillation-free tracking of the global best peak position in a few steps. The unique advantage of this algorithm for maximum power point tracking in partially shaded condition is as, it is free from common and generalized problems of other evolutionary techniques, like longer convergence duration, a large number of search particles, steady-state oscillation, heavy computational burden, etc., which creates power loss and oscillations in output. This hybrid algorithm is tested in MATLAB simulation and verified on a developed hardware of the solar PV system, which consists of multiple peaks in voltage-power curve. Moreover, the tracking ability is compared with the state-of-the-art methods. The satisfactory steady-state and dynamic performances of the new hybrid technique under variable irradiance and temperature levels show the superiority over the state-of-the-art control methods.

Characterization of thermoelectric generators (TEG) is widely discussed and equipment has been built that can perform such analysis. One method is often used to perform such characterization: constant temperature with variable thermal power input. Maximum power point tracking (MPPT) methods for TEG systems are mostly tested under steady-state conditions for different constant input temperatures. However, for most TEG applications, the input temperature gradient changes, exposing the MPPT to variable tracking conditions. An example is the exhaust pipe on hybrid vehicles, for which, because of the intermittent operation of the internal combustion engine, the TEG and its MPPT controller are exposed to a cyclic temperature profile. Furthermore, there are no guidelines on how fast the MPPT must be under such dynamic conditions. In the work discussed in this paper, temperature gradients for TEG integrated in several applications were evaluated; the results showed temperature variation up to 5°C/s for TEG systems. Electrical characterization of a calcium–manganese oxide TEG was performed at steady-state for different input temperatures and a maximum temperature of 401°C. By using electrical data from characterization of the oxide module, a solar array simulator was emulated to perform as a TEG. A trapezoidal temperature profile with different gradients was used on the TEG simulator to evaluate the dynamic MPPT efficiency. It is known that the perturb and observe (P&O) algorithm may have difficulty accurately tracking under rapidly changing conditions. To solve this problem, a compromise must be found between the magnitude of the increment and the sampling frequency of the control algorithm. The standard P&O performance was evaluated experimentally by using different temperature gradients for different MPPT sampling frequencies, and efficiency values are provided for all cases. The results showed that a tracking speed of 2.5 Hz can be successfully implemented on a TEG system to provide ∼95% MPPT efficiency when the input temperature is changing at 5°C/s.

This paper discusses about the photovoltaic (PV) system novel non-iterative maximum power point tracking algorithm with faster converging speed under varying solar irradiation level. PV system is a scattered renewable energy resource and a safe environmental energy source. However, the PV power oscillates around MPP value due to the fluctuations of temperature and insolation effects, leading to nonlinear maximum power tracking issues. For each change in atmospheric condition, output of the PV system changes necessitating the need to search for new maximum power conditions. An efficient maximum power point tracking (MPPT) device that improves the power transmitting efficiency along with a suitable high frequency direct current (DC) to DC power converter device are required for efficient operation. Finally, a comparison is made between existing MPPT algorithms and proposed novel non-iterative MPPT algorithm. The proposed MPPT system show that the overall tracking speed of the proposed MPPT is 5.6 times, 3.8 times faster than perturb and observe (P&O) method and INC method respectively. During the variation of irradiance, the power loss is reduced by 18.84% and 11.29% in comparison with P&O and INC method. The proposed method also minimizes the steady state oscillations.

Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking

To increase the output efficiency of a photovoltaic (PV) system, it is important to apply an efficient maximum power point tracking (MPPT) technique. This paper describes the analysis, the design and the experimental implementation of the tracking methods for a standalone PV system, using two approaches. The first one is the constant voltage (CV) MPPT method based on the optimum voltage, which was deduced experimentally, and considered as a reference value to extract the optimum power. The second one is the increment conductance (Inc-Cond) MPPT method based on the calculation of the power derivative extracted by the installation. The output controller can adjust the duty ratio to the optimum value. This optimum duty ratio is the input of a DC/DC boost converter which feeds a set of Moto-pump via a DC/AC inverter. This paper presents the details of the two approaches implemented, based on the system performance characteristics. Contributions are made in several aspects of the system, including converter design, system simulation, controller programming, and experimental setup. The MPPT control algorithms implemented extract the maximum power point (MPP), with satisfactory performance and without steady-state oscillation. MATLAB/Simulink and dSpace DS1104 are used to conduct studies and implement algorithms. The two proposed methods have been validated by implementing the performance of the PV pumping systems installed on the roof of the research laboratory in INSAT Tunisia. Experimental results verify the feasibility and the improved functionality of the system.

Maximum power point (MPP) tracking algorithms have always been at the forefront in photovoltaic (PV) systems to counter the nonlinearity caused by PV arrays and, thereby, harvest maximum power. There are several MPP trackers, including fixed and variable step size. The application of a fixed step-size MPP tracker leads to steady-state power oscillations around MPP. On the other hand, a conventional variable step-size MPP tracker employs a constant multiplying factor to increase the convergence rate; however, its response is found to be sluggish under PV parameters’ uncertainties. Therefore, in this article, an optimized fractional nonlinear synergetic controller (FNSC) driven MPP tracker is proposed to meticulously detect the true MPP. The proposed optimized FNSC provides a large dynamic range and ensures minimal sustained power oscillations around MPP even under unequal irradiances. The algorithm based on fractional calculus utilizes macrovariables for improving the performance of the proposed FNSC under steady-state and dynamic operating conditions. The effectiveness of the proposed optimized FNSC is verified using OPAL-RT (OP5700). The outcomes of this study validate the practicability of an FNSC-driven MPP tracker to guarantee less MPP tracking time. The MPP tracking time recorded with the proposed FNSC during steady-state and dynamic conditions is less than 21.80 and 20.80 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ms</i> , respectively. Besides, it guarantees 99.7% tracking efficiency and, thereby, outperforms the existing MPP trackers.

Green energy endows the utmost environmental benefits, which include electric power produced from photovoltaic (PV) systems. The minimal conversion efficiency of PV systems (9–17%) decelerates the share in the energy market. One of the solutions to increase efficiency is efficient maximum power point tracking (MPPT) through precise controls. Within the available MPPT algorithms, the perturb and observe (P&O) is prominent due to its simplicity. However, its drawbacks slow down its usage. Most of the proposals involved in overcoming these drawbacks are hybrid nature, which increases the complexity. Alternately, this paper proposes shift and search (S&S) modified P&O algorithm, which not only retains the simplicity but also eliminates all the drawbacks of conventional algorithms with improved tracking efficiency. It is unique in its approach by having independent control over the steady state oscillations and the fast convergence, results in improved tracking efficiency. The performances of the proposed algorithm are validated in the simulation platform. Besides, the superiorities are verified by comparing with traditional and drift free P&O algorithms. The improved MPPT efficiency of the proposed technique aids in extracting the maximum power from solar energy.