Fractional Open Circuit Voltage Research Articles

Next-Generation MPPT: neural network-driven optimization for superior solar performance

This paper presents a novel smart Maximum Power Point Tracking (MPPT) method based on a Neural Network Controller (NNC) to enhance solar power efficiency and mitigate significant oscillations. Traditional MPPT techniques, including perturbation and observation, fixed and variable incremental conductance methods, and fractional open circuit voltage, often suffer from slow response to sudden environmental changes (temperature and irradiation), inaccurate tracking, lack of prediction abilities, and complex structures. These drawbacks lead to power loss, reduced effectiveness of photovoltaic (PV) systems and raised broadband oscillations. To address these issues, we propose an intelligent MPPT strategy utilizing NNC. The NNC inputs are the error and derived error (E&ΔE) between the reference and actual inputs, with the duty cycle (D) as the target output. The proposed algorithm demonstrates an efficiency of approximately 0.75% compared to 0.63% for the P&O method. Simulation and experimental validation results confirm the NNC strategy's effectiveness, robustness, and efficiency, providing a thorough system analysis.

Global MPPT controllers for enhancing dynamic performance of photovoltaic systems under partial shading condition

This research focuses on the development and evaluation of global maximum power point tracking MPPT controllers for enhancing the dynamic performance of Photovoltaic (PV) systems under partial shading conditions. Three different controllers, namely Proportional-Integral (PI), Fractional-Order PI (FOPI), and Fuzzy Logic Controllers (FLC), are studied in conjunction with a modified Incremental Conductance (IC) and Fractional Open-Circuit Voltage (FOCV) algorithms. The proposed controllers with a novel optimization algorithm called Atom Search Optimization Algorithm (ASOA) are compared with classical control. The objective is to investigate the effectiveness of the global MPPT controllers in achieving higher tracking accuracy, faster convergence, and improved stability under varying shading conditions. The study involves extensive simulations using a representative PV system model subjected to different shading scenarios. The results demonstrate that the proposed global MPPT controllers with the ASOA algorithm, when integrated with the modified MPPT algorithms, outperform the classical control techniques in terms of dynamic performance and response to partial shading conditions. The suggested ASOA-based fuzzy IC MPPT controllers can reach the MPP more quickly with a shorter settling time and a better tracking response. Furthermore, with a reduced settling time of about 1.9 % and an average power harvesting efficiency of over 97.9 %, ASOA-based fuzzy IC MPPT controllers offer the best harvesting characteristics. The controller exhibits superior tracking accuracy and stability, mitigating the effects of shading-induced multiple peaks in the P-V curve.

Comparative Analysis of Mppt Techniques for Grid Tie Solar Pv Applications

For effective energy harvesting, photovoltaic (PV) systems must produce their maximum amount of power. This is especially true for grid-tie applications, where the objective is to feed generated power into the grid. The different Maximum Power Point Tracking (MPPT) methods used in grid-tie solar PV systems are compared in this paper. In order to guarantee that PV arrays function at their maximum power point in a variety of environmental circumstances, MPPT algorithms are essential. A DC-DC boost converter is also used for interfacing the load and photovoltaic module. Result is simulated in MATLAB/Simulink environment, and all the condition is kept same for both techniques in simulation for the best outcomes of this comparative study. The efficiency, accuracy, convergence speed, and implementation complexity of several MPPT techniques—Perturb and Observe (P&O), Incremental Conductance (INC), Fractional Open Circuit Voltage (FOCV), and Particle Swarm Optimization (PSO)—are assessed and contrasted in this study. The performance of each technique under various operating conditions is demonstrated through MATLAB/Simulink simulation results, which help in the selection of the optimal MPPT method for grid-tie solar PV applications.

Piezoelectric energy harvesting interface with fast open-circuit voltage sampling

This paper presents a piezoelectric energy harvesting interface with fast open-circuit voltage (VOC) sampling and a wide operating frequency range. The fractional open-circuit voltage (FOCV) method is the primary method for maximum power point tracking (MPPT) in energy harvesting systems, due to its easy implementation and relatively low cost. For this method to be efficient, it is necessary to shorten the time required for VOC sampling. To minimize power loss due to VOC sampling, a novel technique is proposed that is capable of sampling the VOC within a time shorter than half a cycle by using an adaptive tracking pulse instead of conventional fixed ones. We also present a peak detector design technique that can operate across a broad frequency spectrum and adapt to diverse vibration scenarios. The proposed technique reduces the duty cycle of the tracking pulse to 0.42%, which is 3.7 times smaller than the conventional 1.56%. The proposed circuit, designed using a 0.35μm complementary metal oxide semiconductor (CMOS) process, consumes just 94nA at 100Hz, 3V VOC, and a 1kΩ load. In a 2~4V VOC range and a 15~500Hz frequency range, the MPPT efficiency exceeds 95%, peaking at 99.9%, and the power efficiency remains over 93%, reaching a maximum of 97.7%.

Implementing Different MPPT Algorithm For Solar Charge Controller

In this paper, MPPT methods such as Perturb and Observe (P and O), Incremental Conductance and Fractional open Circuit Voltage method has been studied. Also, two converter topology, Buck and Synchronous buck converter has been Studied. Hardware implementation of the solar charge controller is done based on the software simulation data and results. Hardware is developed for 1kW system and 48V, 100Ah battery is going to be charged with it. Two MPPT method with synchronous buck converter has been implemented in hardware. This designed hardware has been tested with different irradiance condition. This proposed system can be used in golf cart to make it a stand-alone system with taking care of all protection measures.

Analysis of Open Circuit Voltage MPPT Method with Analytical Analysis with Perturb and Observe (P&O) MPPT Method in PV Systems

This study conducts a comprehensive comparison between two prominent Maximum Power Point Tracking (MPPT) techniques employed in solar energy systems: the Perturb and Observe (P&O) method and the Analytical Solution Fractional Open Circuit Voltage (ASFOCV) method. To assess the effectiveness of these MPPT approaches, a simulation study was conducted using four SHARP NDQ295 model photovoltaic panels, configured as two panels in series and two in parallel. Both the P&O and ASFOCV MPPT methods were evaluated under various scenarios of radiation levels and temperature changes. The results unequivocally demonstrate the superior performance of the ASFOCV MPPT method over the P&O MPPT method. The ASFOCV method notably enhanced converter output power by up to 5% when compared to the P&O method, leading to more efficient energy production. Furthermore, the ASFOCV method exhibited rapid stabilization of output voltage during abrupt weather changes, outperforming the P&O method in this regard. This study underscores the potential of the ASFOCV MPPT method to enhance the efficiency of solar energy systems and its adaptability to fluctuating environmental conditions. Future research endeavors could focus on mitigating the ASFOCV method’s sensitivity to temperature variations and conducting real-world applications to further investigate its performance under practical circumstances.

Adaptive energy harvesting approach for smart wearables towards human-induced stochastic oscillations

Harvesting diverse renewable energy sources from humans offers an effective approach to achieving cleaner production and sustainable development. The integration of self-powered smart wearables enables continuous power supply for long-term operation of outdoor civilian and military electronics, especially in situations with limited access to conventional power sources. Resonant energy harvesting schemes working at the dominant frequencies of human movement can trigger large mechanical oscillations and significantly enhance the generation of electrical power. This study presents the development of a nonlinear two-degree-of-freedom (2DOF) resonant energy harvesting system with a maximum power point tracking (MPPT) algorithm that adapts to individual human differences and stochastic motion patterns. Through an analysis of the system characteristics based on equivalent circuit modeling, it is found that the electrical damping of the harvester plays a crucial role in determining the actual power output, and the relationship between its optimal value and the oscillation frequency is unique. Thereby, an energy harvesting circuit with an adaptive MPPT algorithm is developed to optimize the electrical damping in real time by applying a novel Perturb and Observe technique based on the average power over each time period. In addition, a variable-step search method and a special convergence judgment are proposed to enhance the tracking speed. The sensitivity analysis of algorithm parameters indicates that the time period and power tolerance need to be reasonably selected to strike a balance between search speed and accuracy. The results of constant motion pattern tests show that the proposed algorithm with a variable-step search method exhibits superior search speed and accuracy over fixed-step configurations. The results of variable motion pattern tests reveal an increase in the actual system power output of up to 194% compared to the conventional fractional open-circuit voltage (FOCV) algorithm. Finally, the system adaptability test is conducted to validate the MPPT efficiency in four resonant systems. The results showcase an impressive MPPT efficiency of 93%–99%, demonstrating its reliability and robustness in various application scenarios.

A Feasible MPPT Algorithm for the DC/DC Boost Converter

One of the most promising forms of renewable energy is solar energy. However, efficient exploitation of this energy form is a topic of great interest, especially in obtaining the maximum amount of power from the solar photovoltaic (PV) system under changing environmental conditions. To solve this problem, it is necessary to propose an optimal algorithm. Therefore, this paper presents a feasible maximum power point tracking (MPPT) technique for DC/DC boost converters applied in load-connected stand-alone PV systems to extract the maximum available power. This proposed method is based on the combination of the modified perturb and observe (P&O) and fractional open circuit voltage (FOCV) algorithms. The effectiveness of the proposed technique is verified via time-domain simulation of the load-connected stand-alone PV system using PSIM software. The simulation results show a tracking efficiency with an average value of 99.85%, 99.87%, and 99.96% for tracking the MPP under varying loads, irradiation, and simultaneously varying temperature, load, and irradiation, respectively. In addition, tracking time is always stable at 0.02 sec for changing weather conditions in the large range. Therefore, the results of the proposed method indicate advantages compared to the conventional method.

Experimental Validation of a Fast-Tracking FOCV-MPPT Circuit for a Wave Energy Converter Embedded into an Oceanic Drifter

Wave Energy Converters (WECs) are an ideal solution for expanding the autonomy of surface sensor platforms such as oceanic drifters. To extract the maximum amount of energy from these fast-varying sources, a fast maximum power point tracking (MPPT) technique is required. Previous studies have examined power management units (PMU) with fast MPPT circuits, but none of them have demonstrated their feasibility in a real-world scenario. In this study, the performance of a fast-tracking fractional open circuit voltage (FOCV)-MPPT circuit (sampling period TMPPT of 48 ms) is compared with a commercial slow-tracking PMU (TMPPT of 16 s) in a monitored sea area while using a small-scale, pendulum-type WEC. A specific low-power relaxation oscillator circuit is designed to control the fast MPPT circuit. The results demonstrate that by speeding up the sampling frequency of the MPPT circuit, the harvested energy can be increased by a factor of three.

Effect of the Sampling Parameters in FOCV-MPPT Circuits for Fast-Varying EH Sources

The fractional open-circuit voltage (FOCV) method is extensively used in low-power energy harvesting (EH) sources to extract maximum power. For fast-varying EH sources, a fast sampling rate is required. This work theoretically analyzes the influence of the sampling time and period on the harvested power of sinusoidal EH sources. In addition, the circuit limitations to achieve a fast sampling rate are presented and circuits to deal with them proposed and implemented. Furthermore, one of the circuits is based on a novel pseudoFOCV method and achieves the fastest sampling rate. Experimental tests are performed with a 2 Hz, 1 to 3 V sinusoidal source having an output resistance of 127 Ω, and the results are shown to agree with theoretical predictions. It is shown that the harvested power increases with the sampling rate when the sampling time is negligible (sampling 15 times faster than the source frequency extracts around 99% of the maximum), and for fixed sampling times, there is an optimum sampling rate where the harvested power is maximum. The first result is generic and valid for methods other than the FOCV. Tests were also performed with a small-scale wave energy converter placed in a linear shaker emulating a sea environment. Harvested power increases by 25% with respect using a commercial FOCV unit with a low sampling rate.

An improved sliding mode control–based GMPPT algorithm for photovoltaic system

In this paper, an improved fixed-frequency-based integral sliding mode controller is designed and applied to a stand-alone photovoltaic (PV) system to obtain the desired reference signal for the maximum power point tracking. The proposed technique is designed with the modified sliding surface and sigmoidal function-based control law which improves the transient and steady-state performance of the PV system under uniform and partial shading conditions. Moreover, the cost of the proposed technique is further reduced by predicting the inductor current without employing a current sensor. In addition, the varying tuning factor strategy is used to further reduce the undershoot and overshoot issues during the tracking process. The desired voltage reference signal is provided by the online fractional open-circuit voltage algorithm. Furthermore, the proposed sliding mode control technique is integrated with the 0.8 Voc model-based algorithm to obtain the global maximum power point. To check the effectiveness and fair analysis, the proposed technique is tested in MATLAB/Simulink environment under partial shading conditions, and its results are compared with the recently developed double integral derivative sliding mode control technique. The suggested technique is also tested experimentally on a 245 W PV module, in conjunction with a boost converter. The simulation and experimental findings reveal that the proposed technique outperforms the double integral derivative sliding mode control technique in terms of steady-state and transient performance, tracking speed, and transient efficiency.

An improved genetic algorithm based fractional open circuit voltage MPPT for solar PV systems

To extract the maximum power from solar PV, maximum power point tracking (MPPT) controllers are needed to operate the PV arrays at their maximum power point under varying environmental conditions. Fractional Open Circuit Voltage (FOCV) is a simple, cost-effective, and easy to implement MPPT technique. However, it suffers from the discontinuous power supply and low tracking efficiency. To overcome these drawbacks, a new hybrid MPPT technique based on the Genetic Algorithm (GA) and FOCV is proposed. The proposed technique is based on a single decision variable, reducing the complexity and convergence time of the algorithm. MATLAB/Simulink is used to test the robustness of the proposed technique under uniform and non-uniform irradiance conditions. The performance is compared to the Perturb & Observe, Incremental Conductance, and other hybrid MPPT techniques. Furthermore, the efficacy of the proposed technique is also assessed against a commercial PV system’s power output over one day. The results demonstrate that the proposed GA-FOCV technique improves the efficiency of the conventional FOCV method by almost 3%, exhibiting an average tracking efficiency of 99.96% and tracking speed of around 0.07 s with minimal steady-state oscillations. Additionally, the proposed technique can also efficiently track the global MPP under partial shading conditions and offers faster tracking speed, higher efficiency, and fewer oscillations than other hybrid MPPT techniques.

An maximum power point tracking interface circuit for low-voltage DC-type energy harvesting sources

This paper presents a maximum power point tracking (MPPT) interface circuit for low-voltage DC-type energy harvesting sources such as light and thermal energy. Most energy harvesting systems used in miniature-sized sensor systems require start-up circuits because the output voltages of small-sized energy transducers are very low and not enough to directly power electronic systems. The proposed interface circuit is driven directly by the low output voltages of small size energy transducers, eliminating the need for complex start-up circuitry. A simple MPPT controller with the fractional open-circuit voltage (FOCV) method is designed and fabricated in a 65-nm complementary metal oxide semiconductor (CMOS) process. Measurement results show that the designed circuit can track the MPP voltage even in the presence of the open-circuit voltage fluctuations and can operate properly at operating voltages as low as 0.3 V. The interface circuit achieves a peak power efficiency of 97.1% and an MPPT accuracy of over 98.3%.

An Enhanced P&O MPPT Algorithm for PV Systems with Fast Dynamic and Steady-State Response under Real Irradiance and Temperature Conditions

This paper presents an enhanced perturb and observe (P&O) method for reconciling the trade-off problem between the dynamic response and steady-state oscillations in maximum power point tracking (MPPT). The constraint of having to sacrifice either the dynamic response or the steady-state oscillations has been solved. The method uses the relationship between the open-circuit voltage and maximum power voltage from the fractional open-circuit voltage (FOCV) MPPT method to establish a valid, reduced, and confined search space within which an enhanced P&O via dynamic adaptive step size terminates the search for the maximum power point. The feasibility of the proposed method has been validated by comparing its performance with the conventional P&O algorithm. It was noted that the proposed method increased the operational efficiency of the PV module to 99.89%, reduced the tracking time to 1.8 ms, and preserved the good steady-state response with a power attenuation of less than 0.10 W or relative 0.16% under MATLAB environment. An experimental setup was used to collect real irradiance and temperature data which was used in real-time simulations. The enhanced P&O method was able to resist abrupt changes in irradiance and temperature as it effectively and efficiently followed the maximum power point (MPP). Finally, to appreciate the supremacy of the proposed method, it was compared to nineteen different MPPT methods from literature. The comparison showed that the enhanced P&O MPPT method is highly efficient and effective for MPPT in photovoltaic (PV) generation systems.

Hybrid sensor-aided direct duty cycle control approach for maximum power point tracking in two-stage photovoltaic systems

A novel maximum power point tracking (MPPT) approach for two-stage photovoltaic (PV) systems is proposed, which is a hybridization of Perturb & Observe (P&O) with a modified version of the Fractional Open Circuit Voltage (FOCV) algorithm. Differently from other hybrid algorithms which merge P&O with FOCV or Fractional Short Circuit Current (FSCC), the proposed algorithm enables direct duty cycle control (DDCC), which significantly reduces efficiency losses due to steady-state oscillations. Also unlike similar methods, it provides a mechanism for tracking the global maximum power point during partial shading (PS). Validation of the proposed method is carried out via computer simulations and a practical experiment, whose results show that it yields superior performance compared to commonly used MPPT algorithms and, on more detailed analysis, improves standard P&O efficiency by a large margin (up to 15% at uniform irradiance and 27% during PS). Furthermore, it outperforms a similar hybrid, but non-DDCC, algorithm by up to 7% in efficiency.

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on.

Design of an MPPT Technique for the Indirect Measurement of the Open-Circuit Voltage Applied to Thermoelectric Generators

This paper presents the design of a maximum power point-tracking (MPPT) technique for DC–DC converters that are used in energy-harvesting systems based on thermoelectric generators. This technique is based on the analysis of the characteristics of the converter to measure the open-circuit voltage indirectly. The main contribution of this article is that the algorithm measures the voltage at the maximum power point without the need to disconnect the source of the circuit, as happens when the fractional open-circuit voltage (FOCV) technique is used. The algorithm is based on a predetermined initial duty cycle, which is applied to the circuit, and the input voltage and input current are read. With these values, the open-circuit voltage and short-circuit current are calculated with equations obtained from the circuit. Then, it calculates the duty cycle at the maximum power point and applies it to the circuit. If this duty cycle does not obtain the maximum power from the circuit, the algorithm starts a second stage based on fuzzy logic to calculate an increase or decrease in the duty cycle. The designed technique was evaluated using a topology based on a DC–DC flyback converter variant and was compared with the P&O technique and obtained better results. The designed technique provides between 3.9% and 5.6% more power to the load than the P&O technique in a 20 W system.

Semi-pilot cell based maximum power point tracking and coordinated current control based PMSM drive for standalone solar water pumping system

The increasing water demand of rural areas without much utility integration can be well met with solar water pumping system. The system encompasses a high gain boost converter (HBC) with bootstrap inductive and capacitive elements and Space Vector Modulation (SVM) based inverter to drive the Permanent Magnet Synchronous Motor (PMSM)-Pump Assembly. A suitable maximum power point tracking (MPPT) method is needed to extract maximum power and to produce pulses for HBC during intermittent PV supply This work proposes Semi Pilot Cell based Fractional Open Circuit Voltage (SPC-FOCV) MPPT in which the pilot cell is involved in power production rather than being involved only in open circuit information extraction. A coordinated current control with cascaded outer speed loop and inner current loop for SVM inverter is adopted to address the dynamic operations of the system with better response. The power extracted from solar PV is boosted through HBC and is used to drive the PMSM-Pump​ assembly. Suitability of the system is validated under varying irradiation through a prototype developed in the laboratory and utilizing P30F4011 and Xilinx based FPGA for controlling the system. The results seem to claim the working efficacy of the system under various irradiation conditions.

Perovskite PV Energy Harvesting System for Uninterrupted IoT Device Applications

The performance of perovskite solar cells (PSCs) has been improved throughout the years. These photovoltaic (PV) cells can be used to power Internet of Things (IoT) devices for indoor applications. A perovskite PV energy harvesting system with a stand-by battery that continuously powers an IoT device is developed in this work. The battery is required to complement the PSCs when the latter have difficulties in power delivery during low or no irradiance. The performance of the energy harvesting circuit as well as the battery charge and discharge scenarios are investigated. Voltage matching between the PSC and the battery is achieved by a boost converter. The PSC energy harvesting system uses fractional open-circuit voltage (FOCV) based maximum power point tracking (MPPT), which utilizes a Sample and Hold (S&H) circuit. The FOCV technique is based on a comparison of the perovskite PV open circuit voltages and the maximum power points. For each irradiance level, the maximum power point is unique, and this work uses a light-dependent resistor (LDR) to adjust the scaling constant in MPPT. Case studies include various scenarios under 1000 lux fluorescent light and 1 sun irradiance as well as a consideration of different battery states.

Design of Efficient Off-Grid Solar Photovoltaic Water Pumping System Based on Improved Fractional Open Circuit Voltage MPPT Technique

The main application of off-grid solar photovoltaic (SPV) systems is water extraction in rural areas where access to the grid is restricted. In this application, photovoltaic (PV) and pump system regulation are crucial to increase its overall efficiency. In this context, this work presents a simple and efficient off-grid SPV water pumping system (SPVWPS). The designed system is based on a DC-DC boost converter, a three-phase DC-AC inverter, and a three-phase induction motor (IM) coupled to the centrifugal pump. The proposed solution is operated using a control strategy that associates an improved fractional open-circuit voltage (FOCV) method for maximum power point tracking (MPPT) and closed-loop scalar control. This association avoids the use of a speed sensor/encoder and a current sensor for the IM. Finally, the effectiveness of the proposed off-grid SPVWPS and its control system for both steady-state and dynamic conditions of insolation change is verified using a 1KVA rated prototype. The relevance of the drive is also checked in various operating conditions and is found to be adequate for pumping water. Moreover, the proposed method guarantees a fast response, less oscillations around the MPP, a system efficiency of 99%, and a high flow rate due to the extraction of maximum power.