Hill-climbing Maximum Power Point Tracking Research Articles

Optimizing solar energy efficiency with an improved hill-climbing maximum power point tracking control approach: hardware implementation

Abstract This article implements maximum power point tracking (MPPT) based on the improved hill-climbing algorithm for photovoltaic (PV) systems feeding resistive loads. A direct current-to-direct current boost converter is inserted between the PV system and the load to achieve matching. The converter is managed using MPPT based on the hill-climbing algorithm. The objective of this paper is to optimize the code program to achieve the best compromise between accuracy and rapidity by implementing this algorithm using a microcontroller. Two PV systems are tested under identical meteorological conditions. In the first, an improved hill-climbing MPPT controller is used whereas, in the second, the conventional version is employed. The experimental results obtained show a significant enhancement in terms of speed for the improved algorithm with a value of 0.4 s for the response time and 3% for the oscillation power; those values remain satisfactory in terms of precision of the algorithm compared with the conventional system studied and the compared algorithm from the literature.

A Classical Approach for MPPT Extraction in Hybrid Energy Systems

A novel approach for Maximum Power Point Tracking (MPPT) extraction using the Hill Climbing method in hybrid solar and wind energy systems. MPPT is essential for optimizing the energy harvesting efficiency of sustainable energy sources, the integration of multiple sources poses unique challenges. The proposed Hill Climbing algorithm is applied to both solar photovoltaic (PV) panels and wind turbines, enabling efficient tracking of the Maximum Power Points (MPPs) under varying environmental circumstances. This article investigates the performance of the Hill Climbing MPPT method through simulation and experimental validation in a hybrid energy system. The algorithm's adaptability to the dynamic nature of solar irradiance and wind speed is analyzed, demonstrating its capability to rapidly converge to the MPPs for both solar and wind components. The integration of Hill Climbing MPPT for both sources enhances the overall energy harvesting efficiency of the hybrid system. The Hill Climbing MPPT method offers a robust and unified solution for hybrid solar and wind energy systems, providing improved performance and simplicity of implementation. The findings contribute to advancing the optimization of renewable energy systems by addressing the challenges associated with the simultaneous utilization of solar and wind resources.

A comparison of FLC MPPT techniques and HC MPPT techniques for photovoltaic systems

This study aims to examine the behaviour of various maximum power point tracking (MPPT) methods used with PV systems. The methodologies of hill climbing (HC) and fuzzy logic controller (FLC) are assessed in this paper. PV module and DC/DC boost converter models were simulated using PSIM and Simulink software with various MPPT strategies. The PSIM and Simulink software programmes were founder throughout the FLC MPPT method’s development. To employ each software for specific system components, the co-simulation was conducted. The effectiveness of the various MPPT approaches was assessed in response to rapidly varying weather conditions. The results show that for most of the tested MPPT approaches’ usual working ranges, FLC outperforms the HC MPPT approach in transient behavior and constant.

A Novel Isolated Intelligent Adjustable Buck-Boost Converter with Hill Climbing MPPT Algorithm for Solar Power Systems

This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy that is suitable for regenerative energy systems with unsteady output voltages. It also serves as a reliable voltage source for loads such as battery systems, microgrids, etc. In addition, the hill climbing (HC) maximum power point tracking (MPPT) algorithm can be utilized with this innovative IIABB converter to capture the MPP and then enhance system performance. In this converter, five inductors (LA, LB, LC, LD, and LE) and four power MOSFETs (SA, SB, SC, and SD) are used in the proposed novel isolated intelligent adjustable buck-boost (IIABB) converter to adjust the applied voltage across the load side. It also has a constant, stable output voltage. The new IIABB converter is simulated and verified using MATLAB R2021b, and the performances of the proposed IIABB converter and conventional SEPIC converter are compared. The solar photovoltaic module output voltages of 20 V, 30 V, and 40 V are given as inputs to the proposed IIABB converter, and the total output voltage of the proposed converter is 48 V. In the new IIABB converter, the duty cycle of the power MOSFET has a small variation. The proposed IIABB converter has an efficiency of 92~99%. On the other hand, in the conventional SEPIC converter, the duty cycle of a power MOSFET varies greatly depending on the relationship between the output and input voltage, which deteriorates the efficiency of the converter. As a result, this research contributes to the development of a novel type of IIABB converter that may be employed in renewable energy systems to considerably increase system performance and reduce the cost and size of the system.

−11 to 7 dBm Power Range, Triple Band RF Energy Harvesting System With 99.9% Peak Tracking Efficiency and Improved PCE

This paper presents a triple-band radio frequency (RF) energy harvesting system with 99.99% peak tracking efficiency and the triple band rectifier achieves the 4.6% improvement in the power conversion efficiency (PCE). The proposed system has a power range of −11 to 7 dBm with the three bands targeted on 900, 1900, and 2400 MHz. In this paper, the voltage and power characteristics of the triple-band rectifier at each band are extracted as raw data by measurement. The DC-DC boost converter is applied to achieve the maximum power point tracking (MPPT), which exploits the hill-climbing MPPT method. The method is implemented with register logics and power calculator. The converter’s voltage range of 0.1V to 2V is achieved, and the converter facilitates to achieve the highest tracking efficiency of 99.99%, 98.57%, 99.85% at each bands. The performance is verified through experimental results showing PCE improvement and over 87% tracking efficiency in a wide power range at triple bands. The triple-band rectifier with transmission line is fabricated on FR-4 substrate with active area 35.7 cm2, and the DC-DC boost converter with MPPT is implemented in a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.18~\mu \text{m}$ </tex-math></inline-formula> CMOS process with an active area of 0.94 mm2.

Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

The real implementation of the maximum power point tracking (MPPT) controllers for the photovoltaic (PV) systems is still a big challenge for researchers working in this field. Often, they use simulation tools to assess the performance of their MPPT algorithms before actual implementation. In this context, this paper aims to propose a trusted simulation of a PV system designed under Proteus software. The proposed PV simulator can be used to verify and evaluate the performance of MPPT algorithms with a closer approximation to the real implementation. The main advantage of this model that it contains a real microcontroller, as can be found in reality, so that same code for the MPPT algorithm used in the simulation will be used in real implementation. In contrast, when using (Powersim Software) PSIM or Matlab/Simulink, the code of the algorithm must be rewritten once the real experiment begins, because these tools don’t provide a microcontroller or an electronic board in which our algorithm can be implemented and tested in the same way as the real experiment. After this section, a modified Hill-Climbing (HC) algorithm is introduced. The proposed algorithm can avoid the drift problem posed by conventional HC under a fast variation in insolation. The simulation results show that this method presents good performance in terms of efficiency (99.21%) and response time (10 ms), which improved by 1.2% and 70 ms respectively compared to the conventional HC algorithm.

PNKLMF-Based Neural Network Control and Learning-Based HC MPPT Technique for Multiobjective Grid Integrated Solar PV Based Distributed Generating System

In this paper, a novel power normalized kernel least mean fourth algorithm based neural network (NN) control (PNKLMF-NN) technique and learning-based hill climbing (L-HC) maximum power point tracking (MPPT) algorithm are proposed for grid-integrated solar photovoltaic (PV) system. Here three-phase single-stage topology of a grid-integrated PV system is used for feeding the nonlinear/linear load at the point of common coupling. A single layer neuron structure is used for active load component (ALC) extraction from distorted load current. During ALC extraction, PNKLMF-NN control very precisely attenuates harmonics components, noise, dc offset, bias, notches, and distortions from the nonlinear current, which improves the power quality under normal as well as under abnormal conditions. This single layer PNKLMF-NN control has a very simple architecture, which reduces the computational burden and complexity. Therefore, it is easy in implementation. Moreover, proposed L-HC is the improved form of hill climbing (HC) algorithm, where inherent problems of traditional HC algorithm, such as steady-state oscillation, slow dynamic responses, and fixed step size issues, are successfully mitigated. The prime objective of proposed PNKLMF-NN control is to meet the active power requirement of the loads from generated solar PV power and excess power fed into the grid. However, when generated PV power is less than the required load power, then PNKLMF-NN control meets the load by taking extra required power from the grid. During these processes, power quality is maintained at the grid. Moreover, when solar irradiation is zero, voltage source converter (VSC) acts as distribution static compensator (DSTATCOM), which enhances the utilization factor of the system. The proposed techniques are modeled and their performances are verified experimentally on a developed prototype in adverse conditions, which test results have satisfied the objectives of the proposed system and the IEEE-519 standard.

Real-Time Experimental Assessment of Hill Climbing MPPT Algorithm Enhanced by Estimating a Duty Cycle for PV System

Better functioning of maximum power point tracking (MPPT) can significantly increase the energy efficiency of photovoltaic systems. This process is provided by MPPT algorithms. Such as fractional open-circuit voltage, perturb and observe, fractional short-circuit current, hill climbing, incremental conductance, fuzzy logic controller, neural network controller, just to name a few. The hill climbing algorithm uses the duty cycle of the boot converter as a retraction parameter when the MPPT task is performed. However, this technique has disadvantages in terms of the stability of the system during periods of constant radiation. To overcome this disadvantage, A MPPT technique based on the estimation of the boost converter duty cycle associated with the conventional hill climbing, fractional open-circuit voltage and fractional short-circuit current algorithm is proposed. A comprehensive description of the experimental implementation hardware and software platforms is presented. On the basis of the measured data, the enhanced algorithm was compared to the conventional hill climbing MPPT technique according to various criteria, showing the disadvantages and advantages of each. Experimental results show advantage of the enhanced algorithm compared to the conventional hill climbing MPPT technique in time response attenuation (0.25s versus 0.6s), little oscillations (0.5 W versus 2.5 W), power loss reductions and better maximum power point tracking accuracy (98.45 W versus 92.75 W) of the enhanced algorithm compared to the conventional hill climbing MPPT technique.

AN IMPROVED PERTURB AND OBSERVE MPPT ALGORITHM WITH VARIABLE STEP

Abstract The algorithm for maximum power point tracking (MPPT) using a fixed is widely used because of its simplicity and easyness to implement. This paper presents an improvement consisting in a variable step (VS) applied to the standard Hill Climbing MPPT technique to improve both accuracy and tracking speed. Drawbacks will still be encountered in VS tracking algorithms, between response time and power oscillation.

Comparision of Perturb and Observer and Incremental Conductance MPPT Based Solar Tracking System.

This paper presents a detailed analysis of the two most well-known hill-climbing maximum power point tracking (MPPT) algorithms: the perturb-and-observe (P&O) and incremental conductance (INC). The purpose of the analysis is to clarify some common misconceptions in the literature regarding these two trackers, therefore helping the selection process of MPPT Keywords—Perturb and Observer, Incremental Conductance, Microcontroller, DC Servo motor. Maximum Power Point Tracking (MPPT) I. In tro d uct io n A photovoltaic system is a system which uses one or more solar panels to convert solar energy into electricity. The solar cell is the basic unit of a PV system. An individual solar cell produces direct current and power typically between 1 and 2 W, hardly enough to power most applications. It consists of multiple components, including the photovoltaic modules, mechanical and electrical connections and mountings and means of regulating and or modifying the electrical output. PV cells are made of semiconductor materials, such as silicon (2). For solar cells, a thin semiconductor wafer is specially treated to form an electric field, positive on one side and negative on the other.

A comprehensive comparison of different MPPT techniques for photovoltaic systems

This paper aimed to study the behavior of different maximum power point tracking (MPPT) techniques applied to PV systems. In this work, techniques such as hill climbing (HC), incremental conductance (INC), perturb-and-observe (P&O), and fuzzy logic controller (FLC) are assessed. A model of PV module and DC/DC boost converter with the different techniques of MPPTs was simulated using PSIM and Simulink software. Co-simulation between PSIM and Simulink software packages is used to establish FLC MPPT technique. The co-simulation is done to take advantage of each program to handle certain part of the system. The response of the different MPPT techniques is evaluated in rapidly changing weather conditions. The results indicate that, FLC performed best among compared MPPT techniques followed by P&O, INC, and, HC MPPT techniques in both dynamic response and steady-state in most of the normal operating range.

On the Perturb-and-Observe and Incremental Conductance MPPT Methods for PV Systems

This paper presents a detailed analysis of the two most well-known hill-climbing maximum power point tracking (MPPT) algorithms: the perturb-and-observe (P&O) and incremental conductance (INC). The purpose of the analysis is to clarify some common misconceptions in the literature regarding these two trackers, therefore helping the selection process for a suitable MPPT for both researchers and industry. The two methods are thoroughly analyzed both from a mathematical and practical implementation point of view. Their mathematical analysis reveals that there is no difference between the two. This has been confirmed by experimental tests according to the EN 50530 standard, resulting in a deviation between their efficiencies of 0.13% in dynamic and as low as 0.02% under static conditions. The results show that despite the common opinion in the literature, the P&O and INC are equivalent.

Effect of Measurement Noise and Bias on Hill-Climbing MPPT Algorithms

Erroneous measurement of solar array voltage and current degrades the performance of hill-climbing, maximum power point tracking (MPPT) systems. This degradation is observed as a reduced climbing rate, erroneous settling point, and/or random operating point excursions. The effect of measurement bias and noise on MPPT performance is analyzed. Tracking problems are then classified according to their cause, which allows for easier debugging of a faulty tracker. The effectiveness of several error-mitigating techniques is then studied, and recommendations are given accordingly. Conclusions of the analysis are then experimentally verified.