Digital Maximum Power Point Tracking Research Articles

Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems.

Design of crosstalk aware energy harvesting system-on-chip

A crosstalk noise aware design methodology is developed, suitable for advanced energy harvesting systems-on-chip (SoCs). The proposed methodology enables accurate substrate crosstalk modeling via process characterization, Python based layout extraction and RC modeling, providing a reliable design flow for robust integrated circuits (IC) implementation. The SoC’s noise coupling performance degradation is accurately estimated, co-calculating the impact of the package and printed-circuit-board (PCB) design. The proposed design flow is seamlessly integrated into the standard design suite. An energy harvesting SoC is used as a product level vehicle. The system is developed in a 0.18 μm CMOS process. The noise aggressor is a digital Maximum Power Point Tracking (MPPT) block, while the noise victim is a DC-DC boost converter and the input voltage sensor. The proposed crosstalk design flow effectively captures the hardware efficiency values, with 14.6% maximum deviation from experimental results, while the standard methodology presents high deviation up to 51.08%.

A high‐efficiency power management unit with wide dynamic range for RF energy harvesting system

AbstractA high‐efficiency power management unit (PMU) with wide dynamic range for radio frequency (RF) energy harvesting system is proposed in this paper. A digital zero current switching (ZCS) and a digital maximum power point tracking (MPPT) circuits are adopted. A sub‐threshold current reference circuit and a subthreshold voltage detection circuit are proposed to reduce the power consumption of always‐on control circuits and improve the conversion efficiency at low input power. A dual‐oscillator is designed to extend the frequency range and widen the input power range with optimized power consumption under low‐end band and high‐end band, respectively. Switch size and on‐time are adjusted according to the input power, which optimizes the conversion efficiency in a wide power range. Proposed PMU is implemented in a standard 180 nm CMOS process. The post‐layout simulation results show that proposed PMU can achieve cold‐start at the input voltage of 280 mV, the power consumption to maintain the PMU is only 9.6 nW. The input power range of the PMU is 11 nW–677 μW. When the input power is 50 nW, a power conversion efficiency (PCE) of 65% is achieved, and the peak PCE can reach 93% at 23.5 μW.

Fully-integrated switched-capacitor voltage boost converter with digital maximum power point tracking for low-voltage energy harvesting

This paper proposes a fully-integrated switched-capacitor voltage boost converter with a digital maximum power point tracking (MPPT) control circuit for low-voltage and low-power energy harvesting. The proposed digital MPPT control circuit converts the analog voltage information of a PV cell into digital values and extracts the maximum power regardless of the harvester conditions and load current. Measurement results demonstrated that our proposed circuit can track the maximum power point of a PV cell successfully. The maximum voltage conversion ratio of our circuit was 5.6. The proposed power management system generated a 2.58 V output voltage from a 0.46 V input voltage. The maximum power conversion efficiency was 63.6%.

Photovoltaic system optimization by new maximum power point tracking (MPPT) models based on analog components under harsh condition

Abstract Photovoltaic (PV) energy has become a promising energy source because the demand for electrical energy from renewable energy sources is increasing worldwide in recent decades. Due to efficiency issues, the Maximum Power Point Tracking (MPPT) has been developed to optimize the solar panel’s performance. This paper presents an MPPT model, made up of the analog component, which overcomes traditional MPPT methods’ weakness via the Perturb and observes (P&O) technique. In this case, the PV system includes a PV array, a DC/DC boost converter, a battery, and a load. The proposed method was precisely built and simulated using the Powersim, MATLAB Simulink, and SimCoupler Module. The components of the analog MPPT system were designed practically in detail. The experiment was carried out by using European Efficiency Test 50530, and the results showed the proposed model has higher efficiency over the digital MPPT technique, about 99.99% as maximum. Moreover, MPPT methods were tested under steady-state, irradiation variation, and space conditions to verify the system’s potential capability with PV module Solbian 52L.

Fully Integrated Autonomous Interface With Maximum Power Point Tracking for Energy Harvesting TEGs With High Power Capacity

In this article, a novel fully autonomous and integrated power management interface circuit is introduced for energy harvesting using thermoelectric generators (TEGs) to supply power to Internet of Thing nodes. The circuit consists of a self-starting dc-dc converter based on a dual-phase charge pump with LC-tank oscillator, a digital MPPT unit, and a 1-V LDO regulator. The novel maximum power point tracking (MPPT) algorithm avoids open-circuit state, and accommodates varying input power and ultra-low voltage conditions. Validation data from the fabricated test-chip in 180 nm standard CMOS technology indicates the circuit start-up voltage is as low as 170 mV. The maximum output power capacity is 0.5 mW, which is the highest noted in the literature for a fully integrated solution. The high output power at low cost is achieved with a peak system efficiency of 30%. The relatively low efficiency is expected, since the focus of the design is high power capacity at low cost. The MPPT algorithm reaches 98% maximum accuracy for a source output resistance of 40 Ω, which is typical for wearable TEG modules.

Application of modified classical numerical methods for DMPPT on Buck and Boost converters

Application of Classical Numerical Methods (CNM) for Digital maximum power point tracking (DMPPT) confronts many issues. The issues highlighted in this paper include limited range of operation, PV array dependence and accuracy of the initial guess. In order to address such shortcomings of CNM for DMPPT, Hybrid Techniques (HT) have been proposed. The HT are a combination of the modified incremental conductance method (MINC) and various modified CNM. An overview of the considered MCNM, which are applied to the photovoltaic (PV) application, has also been provided. The HT not only address the issues confronted by the CNM, but also improve the transient response time and remove the steady state oscillations for the conventional MPPT technique. In addition, for DMPPT the DC-DC converter topology under consideration cannot be treated as a black box, by ignoring the effects of the converter topology and control dynamics. Here, a theoretical analysis has been provided to ascertain the optimum performance of DMPPT applications on various DC-DC converter designs. To measure the effectiveness of the proposed HT, Boost, 2-Stage Switch Capacitor Based (2-SSC) Boost, and Optimum Buck Converters (OBC) have been employed. Simulation and experimental results are provided to validate the effectiveness of the proposed HT.

Implementation in Arduino of MPPT Using Variable Step Size P&O Algorithm in PV Installations

In order to maximize the electric energy production of a photovoltaic generator (PVG), the maximum power point tracking (MPPT) methods are usually used in photovoltaic systems. The principle of these techniques is to operate the PVG to the maximum power point (MPP), which depends on the environmental factors, such as solar irradiance and ambient temperature, ensuring the optimal power transfer between PVG and load. In this paper, we present the implementation of two digital MPPT commands using the Arduino Mega type. The two proposed MPPT controls are based on the algorithm of perturb and observe (P&O), the first one with fixed perturbation step and the second one with two perturbations step varying with some conditions. The experimental results show that the P&O algorithm with variable step perturbation gives good results compared to the P&O algorithm with fixed perturbation step in terms of the time response and the oscillations around the MPP.

Modeling and Analysis of a Fast and Robust Module-Integrated Analog Photovoltaic MPP Tracker

Analog circuitry-based photovoltaic (PV) maximum power point (MPP) tracking (MPPT) technique is attractive due to its low cost and capability of easy integration with normal dc–dc switching converters. However, realization of classical digital MPPT algorithms using analog circuitries is a challenging task. It necessarily requires to store the information of module voltage/current and power in order to find the desired MPP. While at the same time, improper design of digital MPPT controllers may cause poor tracking performances or limit cycle oscillations to manifest, which are generally seen as being undesirable. This paper proposes a fast and robust analog PV MPP tracker without imposing any external control or perturbation. The fast dynamic performances with absolute robustness are ensured here by integrating the concepts of Utkin's equivalent sliding mode control law and fast-scale stability analysis of actual switched converter systems. Moreover, the superiority of the proposed MPP tracker (in terms of high-tracking performances) over classical ones, and its impact in series-connected converters configuration are analytically demonstrated through the procedure developed in this paper. Finally, the analytical results have been validated by means of simulations and experiments.

Design and implementation of a digital MPPT controller for a photovoltaic panel

This paper proposes a simplified design and hardware implementation of a digital maximum power point tracking (MPPT) controller for a photovoltaic (PV) panel using PIC microcontroller 16F877A embedded technology. The 3 most well-known algorithms, perturb & observe, hill-climbing, and incremental conductance, are considered and analyzed from a practical implementation point of view. The control board was developed using simple circuits and tested under resistive load conditions lower than the load of the maximum power point. The MPPT controller proved its effectiveness, providing maximum power to the load under changing weather conditions.

MPPT Control and Architecture for PV Solar Panel with Sub-Module Integrated Converters

Photovoltaic (PV) solar systems with series-connected module integrated converters (MICs) are receiving increased attention because of their ability to create high output voltage while performing local maximum power point tracking (MPPT) control for individual solar panels, which is a solution for partial shading effects in PV systems at panel level. To eliminate the partial shading effects in PV system more effectively, sub-MICs are utilized at the cell level or grouped cell level within a PV solar panel. This study presents the results of a series-output-connection MPPT (SOC-MPPT) controller for sub-MIC architecture using a single sensor at the output and a single digital MPPT controller (sub-MIC SOC-MPPT controller and architecture). The sub-MIC SOC-MPPT controller and architecture are investigated based on boost type sub-MICs. Experimental results under steady-state and transient conditions are presented to verify the performance of the controller and the effectiveness of the architecture.

Neural-network-based maximum power point tracking methods for photovoltaic systems operating under fast changing environments

Photovoltaic (PV) generation systems (PGSs) have become an attractive option among renewable energy sources because they are clean, maintenance-free and environmental friendly. For PGSs, a simple and fast maximum power point tracking (MPPT) algorithm is essential. Although the static tracking efficiency of conventional MPPT method is usually high, it drops noticeably in case of rapidly changing irradiance conditions. In this paper, two fast and accurate digital MPPT methods for fast changing environments are proposed. By using piecewise line segments or cubic equation to approximate the maximum power point (MPP) locus, two high-speed, low-complexity MPPT techniques can be developed. To make the developed system more convenient for common PGS users, neural network (NN)-based program which can be used to calculate the parameters of the emulated MPP locus is also developed and embedded into the proposed digital MPPT system. Theoretical derivation and detailed design procedure will be provided in this paper. The advantages of the proposed system include low computation requirement, fast tracking speed and high static/dynamic tracking efficiencies. To validate the effectiveness and correctness of the proposed methods, simulation and experimental results of a 230W PV system will also be provided.

Analysis of Classical Root-Finding Methods Applied to Digital Maximum Power Point Tracking for Sustainable Photovoltaic Energy Generation

This paper examines the application of various classical root-finding methods to digital maximum power point tracking (DMPPT). An overview of root-finding methods such as the Newton Raphson method, Secant method, bisection method, regula falsi method, and a proposed modified regula falsi method (MRFM) applied to photovoltaic (PV) applications is presented. These methods are compared among themselves. Some of their features are also compared with other commonly used maximum power point (MPP) tracking methods. Issues found when implementing these root-finding methods based on continuous variables in a digital domain are explored. Some of these discussed issues include numerical stability, digital implementation of differential operators, and quantization error. Convergence speed is also explored. The analysis is used to provide practical insights into the design of a DMPPT based on classical root-finding algorithms. A new DMPPT based on an MRFM is proposed and used as the basis for the discussion. It is shown that this proposed method is faster than the other discussed methods that ensure convergence to the MPP. The discussion is approached from a practical perspective and also includes theoretical analysis to support the observations. Extensive simulation and experimental results with hardware prototypes verify the analysis.