Simple Maximum Power Point Tracking Algorithm Research Articles

Optimized hill climbing algorithm for an islanded solar photovoltaic system

Conventional energy generation technologies face unreliability due to the depletion of fossil fuels, soaring energy prices, greenhouse gas emissions, and continuously increasing energy demand. As a result, researchers are searching for reliable, cheap, and environmentally friendly renewable energy technologies. Solar photovoltaic (PV) technology, which directly converts sunlight into electricity, is the most attractive sustainable energy source due to the sun's ubiquitous presence. However, the non-linear behaviour of solar PV demands maximum power point tracking (MPPT) to ensure optimal power production. Although Hill Climbing (HC) is a simple, cheap, and efficient MPPT algorithm, it has a drawback of steady-state oscillations around MPP under uniform weather conditions. To overcome this weakness, we propose some modifications in the tracking structure of the HC algorithm. The proposed optimized HC (OHC) algorithm achieves zero steady-state oscillations without compromising the strength of the conventional HC algorithm. We applied both algorithms to an off-grid PV system under constant and changing weather conditions, and the results demonstrate the superiority of the proposed OHC algorithm over the conventional HC algorithm.

Wind energy management of a standalone system operating at maximum power point

In this paper, the management and control of a standalone wind energy system versus variations of wind speed and load are investigated. The system includes a wind turbine coupled to a variable-speed permanent magnet synchronous generator (PMSG), rectifier, boost converter, power inverter, and an energy storage system (ESS). The ESS is a very important part to achieve system stability and support the maximum power point tracking (MPPT) operation. A simple off-line MPPT algorithm is introduced that can be accomplished using the boost converter. The system dynamic model is derived then the control and energy management algorithms are introduced to improve the system performance. The MATLAB platform has been utilized to simulate the proposed system under different disturbances in the load power and wind speed. The results show perfect management of the system energy, good performance of the DC link voltage, stable load voltage, and load frequency.

Implementation of Modified Incremental Conductance MPPT A lgorithm in Grid Connected PV System Under Dynamic Climatic Conditions

Background: The main goal of the grid-connected Photo Voltaic (PV) system is to extract maximum power from the array with reduced loss by using an appropriate MPPT method. Methods: A boost converter topology with linear INCMPPT algorithm is used to provide maximum power of 100 kW from the solar PV array to the grid. The integral regulator in the modified algorithm minimizes the error and guarantees exact control of the duty cycle of the DC-DC converter to produce constant DC voltage 500V with a minimum error of 2V. This proposed methodology perfectly matches with the optimal design of the DC-AC converter (inverter) for grid integration. A three-level IGBT-based voltage source inverter and filters are designed to supply pure AC voltage to the existing 100 kW grid. Detailed simulation work is completed using MATLAB/ Simulink software to prove the effectiveness of the proposed algorithm under various temperature (25-50◦C) and irradiance (200-1000W/m2) levels. Findings: The proposed MPPT algorithm is simple and effective in reducing the error required for the duty cycle correction from 0.45 to 0.518 and eliminating the oscillations at MPP. By using this methodology, the output voltage of the boost converter is adjusted to match the reference value. The simulation results reveal the better performance of the grid-connected PV system with the modified incremental conductance MPPT method. This modified INC MPPT algorithm exactly controls the duty cycle of the boost converter to provide better settling time and low ripples in the grid parameters. Novelty: This article provides a simple and effective improved incremental conductance (INC) MPPT algorithm to minimize the tracking error (1.5%). No additional tuning and selection of parameters, computational burden and memory are required for the implementation of the proposed control algorithm. Keywords: Gridconnected photovoltaic (PV) system; Maximum power point tracking (MPPT); Voltage Source Inverter (VSI); Boost converter; Incremental conductance (INC)

Submodule based MPPT with synchronous buck converter under dynamic partial shading conditions

In order to obtain more power from photovoltaic (PV) modules under mismatching operating conditions, the submodule-based MPPT technique is an important solution. In this technique, since the power-voltage (P-V) curve of a submodule cannot be multi-peaked, the maximum power point (MPP) tracking (MPPT) is easily achieved through a DC-DC converter connected to each submodule. Since the P-V curve cannot be in a multi-peaked form, the maximum power can be obtained with a simple MPPT algorithm. For this reason, perturb & observe (P&O) algorithm can be chosen. In this study, the behaviour of a submodule-based MPPT with synchronous buck converter (SBC) is investigated for dynamic shading conditions. In addition, submodule-based MPPT and module-based MPPT technique were compared and the comparison was confirmed by simulation studies that submodule-based MPPT performed better. In this context, simulation studies were carried out for different shading conditions. According to the simulation results, the submodule-based MPPT approach achieves greater efficiencies to the module-based MPPT. In some simulations, when the module-based MPPT technique is used, the operation at the local MPP has been realized. In such cases, more advanced algorithms are needed. However, a simple algorithm is sufficient in submodule-based MPPT. The only disadvantage of this MPPT is the high hardware cost. However, the increase in efficiency obtained is at a level that can easily tolerate this cost.

Unity Efficiency and Zero-Oscillations Based MPPT for Photovoltaic Systems

Maximum power point tracking (MPPT) is essential for photovoltaic systems to ensure a maximum power extraction from PV panels. However, some issues such as oscillations, power loss and other technical aspects still unsolved. This paper presents and discusses a new MPPT algorithm with zero-oscillations and unity efficiency in transient and steady-states. This algorithm leads to track the maximum power point under extreme operating conditions. The proposed MPPT method is based on the simple adaptive linear neuron. In addition, its implementation is achieved without any additional control loop, which resulted in a simple control. In order to validate the proposal effectiveness, both simulation and experiment tests are carried out under variable irradiance and load. Comparison between the developed MPPT and the conventional perturb and observe algorithm is also performed. Obtained results show that with the proposed method, unity efficiency is reached and oscillations are fully removed in the transient and steady-states. The originality of this work is the design of a simple and efficient MPPT algorithm based on the ADALINE with unity efficiency and zero-oscillations. Moreover, the proposal is verified using a real PV system under irradiance and load changes.

Current collector optimizer topology to extract maximum power from non-uniform aged PV array

Centralized inverter technology is one of the most common architectures of the PV installation, which interfaces a large number of PV panels that configured in series-parallel (SP) combination to the grid. However, the power generated from centralized inverter architecture based on SP array topology is significantly reduced under the non-uniform aging condition. Non-uniform aging of PV panels is a common problem in the PV generation plants, as they often operate under harsh outdoor environmental conditions for a long service period. Due to the elevated price of replacing aged PV panels with new ones, it is preferable to improve the power extracted from aged PV systems. This paper proposes a circuit-based topology known as current collector optimizer (CCO) topology to enhance the performance of centralized inverter technology under the uneven aging condition of PV modules. According to the results, the maximum power extracted from the non-uniform aging PV array is substantially increased by using the CCO topology compared to the conventional SP array topology with bypass diodes. With CCOs, the PV array characteristics have a unique maximum power point (MPP) which can be easily followed by a simple MPP tracking algorithm, subsequently, the CCO topology does not suffer from misleading power losses. The proposed topology requires offline rearrangement of aged modules to obtain the optimum power if only the degradation rate of short-circuit current is used to assess the aging process. Furthermore, the CCO topology operates close to optimum power if the degradation rate of open-circuit voltage is taken into account.

A new simple MPPT algorithm to track MPP under partial shading for solar photovoltaic systems

ABSTRACTExtraction of electrical power from solar photovoltaic (PV) systems under nonuniform irradiance such as partial shading (PSC) or fast transient conditions (FTC) is the most challenging task for the solar PV researchers. Inaccurate detection of PSC or FTC affects the efficiency of maximum power point tracking (MPPT) algorithms. As multiple peaks are found in the P–V curve, searching of the global peak among local peaks and stabilizing the output voltage is a typical task for an MPPT algorithm during PSC or FTC. Particularly for small isolated PV systems, the output system voltage stability is of more concern than power efficiency during PSC. Here, a Modified Perturb and Observation (P&O) (MP&O) MPPT algorithm is proposed for accurate detection of PSC, which stabilizes the system output voltage without compromising with power efficiency. For accurate detection of PSC, the MP&O MPPT algorithm uses irradiance (Ir(k)) and generated PV power (P(k)) as an input parameter and regulates the step size (dD) of the boost converter duty cycle (D). A PV system is simulated in MATLAB/Simulink and the performance of the proposed algorithm is also investigated using dSPACE controller, solar PV emulator and a SiC Mosfet switch under PSC. The accuracy to detect PSC or FTC of this algorithm is found satisfactory with fast tracking speed.

Оптимальное извлечение энергии из неоднородно стареющего фотоэлектрического массива с использованием сумматора тока

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.

Simple adaptive incremental conductance MPPT algorithm using improved control model

In order to achieve maximum power point tracking (MPPT) of the photovoltaic system, many algorithms have been proposed such as incremental conductance (IncCond) MPPT algorithms with a fixed step size or a variable step size. However, most of the proposed algorithms track the maximum power points (MPPs) with an inaccurate response, sustained oscillation, low tracking efficiency, and the loss of energy under fast changing solar irradiation. This paper presents a simple adaptive incremental conductance MPPT algorithm, which uses the variable step size with an improved step model and an improved control strategy to track the MPPs in an adaptive way. The novelty of the proposed method is the combination of the two step models, appropriate error permitted, and precise direction control. The proposed IncCond MPPT algorithm is simulated in MATLAB Simulink, and the capability of an adaptive, fast, accurate response, and high efficiency of MPP tracking with no steady-state oscillation is validated by comparing to a conventional IncCond MPPT algorithm with a fixed step size and improved IncCond MPPT algorithm with a variable step size under fast changing solar irradiation. The high performance of the proposed method compared to the two methods mentioned before is also validated when solar irradiation increases at a different speed.

Design and analysis of artificial bee-colony-based MPPT algorithm for DFIG-based wind energy conversion systems

ABSTRACTIn this article, the proposed maximum power point tracking (MPPT) method is designed by taking rotor speed as an optimization problem, which is solved by artificial bee colony (ABC) algorithm to generate the maximum power output. The main advantage of this algorithm is that its optimal solution is independent of the initial positions and requirement of lesser number of control parameters, which leads to simple and robust MPPT algorithm than other algorithm. Furthermore, the hill climb search and particle swarm optimization-based MPPT algorithm are also discussed and the results obtained by these are compared to verify the effectiveness of proposed algorithm. Simulations for MPPT control along with doubly fed induction-generator-based wind energy conversion system is carried out in MATLAB/Simulink environment. Three statistical methods are used to evaluate the accuracy of each MPPT algorithm. All results are analyzed and compared under randomly selected wind as well as real wind speed configuration. Comparison of both numerical and simulation results under two different varying wind speed conditions strongly suggest that the proposed ABC-based MPPT algorithm is superior than other two MPPT algorithms.

An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification

Maximum power point tracking (MPPT) for photovoltaic (PV) arrays is essential to optimize conversion efficiency under variable and nonuniform irradiance conditions. Unfortunately, conventional MPPT algorithms such as perturb and observe (P&O), incremental conductance, and current sweep method need to iterate command current or voltage and frequently operate power converters with associated losses. Under partial overcast conditions, tracking the real MPP in multipeakP-IorP-Vcurve model becomes highly challenging, with associated increase in search time and converter operation, leading to unnecessary power being lost in the MPP tracking process. In this paper, the noted drawbacks in MPPT-controlled converters are addressed. In order to separate the search algorithms from converter operation, a model parameter identification approach is presented to estimate insolation conditions of each PV panel and build a real-time overallP-Icurve of PV arrays. Subsequently a simple but effective global MPPT algorithm is proposed to track the MPP in the overallP-Icurve obtained from the identified PV array model, ensuring that the converter works at the MPP. The novel MPPT is ultrafast, resulting in conserved power in the tracking process. Finally, simulations in different scenarios are executed to validate the novel scheme’s effectiveness and advantages.

A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading

This article presents a novel MPPT (maximum power point tracking) algorithm, based on a modified GA (genetic algorithm). When photovoltaic systems are affected by partial shading, a GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. A new GMPPT algorithm is proposed in this article: a P&O (perturb and observe) algorithm is integrated inside the GA function and creates a single algorithm. By embedding a simple MPPT algorithm (P&O) inside the structure of the GA, the population size and the number of iterations are decreased, thus finding the MPP (maximum power point) in a shorter time. The algorithm parameters (population size, number of genes, and number of iterations) are optimized and the final solution is provided. A macromodel is used to average the real DC–DC converter and reduce the computation burden of the simulator, thus reducing the simulation time. The control part and the GMPPT algorithm were implemented on a DSP (digital signal processor) and tested on an experimental small scale photovoltaic system. A description of this algorithm and its performances are detailed in this article, verified through simulation and experimental results.

Development of adaptive perturb and observe‐fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter

This study presents an adaptive perturb and observe (P&O)-fuzzy control maximum power point tracking (MPPT) for photovoltaic (PV) boost dc–dc converter. P&O is known as a very simple MPPT algorithm and used widely. Fuzzy logic is also simple to be developed and provides fast response. The proposed technique combines both of their advantages. It should improve MPPT performance especially with existing of noise. For evaluation and comparison analysis, conventional P&O and fuzzy logic control algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with PV module of Kyocera KD210GH-2PU connected to PV boost dc–dc converter. For hardware implementation, the proposed adaptive P&O-fuzzy control MPPT was programmed in TMS320F28335 digital signal processing board. The other two conventional MPPT methods were also programmed for comparison purpose. Performance assessment covers overshoot, time response, maximum power ratio, oscillation and stability as described further in this study. From the results and analysis, the adaptive P&O-fuzzy control MPPT shows the best performance with fast time response, less overshoot and more stable operation. It has high maximum power ratio as compared to the other two conventional MPPT algorithms especially with existing of noise in the system at low irradiance.