Photovoltaic Energy Harvesting Research Articles

Sub-nA photovoltaic energy harvesting circuit for miniaturized battery-less sensor edges

Abstract In this letter, we report on the photovoltaic energy harvesting circuit for miniaturized, battery-less sensor devices. To accumulate nanowatt power from ultra-small photovoltaic cells, it is essential to reduce the minimum operating current of the energy harvesting circuit. To reduce the minimum operating current, we propose a dual-capacitance voltage monitor (DCVM) which can overcome the issue of the voltage drop caused by the shoot-through current for switching. We designed the energy harvesting circuit including the DCVM in a 180nm CMOS standard process, and successfully demonstrate the minimum operating current of 1 nA.

Improving photovoltaic energy harvesting systems with hybrid fuzzy logic-PI MPPT optimized by PSO under normal and partial shading conditions

Improving photovoltaic energy harvesting systems with hybrid fuzzy logic-PI MPPT optimized by PSO under normal and partial shading conditions

Fabrication and evaluation of a CMOS-based energy harvesting chip integrating photovoltaic and thermoelectric energy harvesters

This study explores the development of an energy harvesting chip (EHC) using a complementary metal oxide semiconductor (CMOS) process, addressing the need for efficient micro-scale energy harvesters in modern electronics. The EHC integrates a thermoelectric energy harvester (TEH) and a photovoltaic energy harvester (PEH) to maximize energy conversion efficiency. A key challenge in TEH design is enhancing power output, which is addressed by suspending the cold ends of 41 thermocouples within the TEH structure through post-processing. Experimental methods were employed to assess the performance of the TEH, revealing an output voltage of 21.4 mV and a maximum output power of 9.32 nW under a 3 K temperature difference. The TEH demonstrated a voltage factor of 8.9 mV/(mm2·K) and a power factor of 1.3 nW/(mm2·K2). The PEH was designed with novel patterned p-n junctions, integrating lightly doped n-type regions with interdigitated p-type doping to increase junction density, resulting in high conversion efficiency. The experimental results confirm the effectiveness of the EHC design, showcasing its potential in energy harvesting applications.

Resilient Reinforcement Learning for Voltage Control in an Islanded DC Microgrid Integrating Data-Driven Piezoelectric

This research study presents a resilient control scheme for an islanded DC microgrid (DC MG) integrating solar photovoltaic (PV), battery storage (BESS), and piezoelectric (PE) energy harvesting modules. The microgrid (MG) case study represents an energy hub designed to provide electricity for lighting systems in transportation, roads, and other infrastructure. To enhance practicality, the PE is modeled using the real data captured from a traffic simulator. The proposed reinforcement learning (RL) method was tested against four severe and unexpected failure scenarios, including short circuit at the load side, sudden and severe change of load, open circuit, and converter failure. The performance of the controller was quantitatively compared with a conventional PI controller. The results show marginal improvement in one scenario and significant improvement in the other three, suggesting that the proposed scheme is a robust candidate for microgrids with high levels of uncertainty, such as those involving solar and PE harvesters.

Photovoltaic energy harvesting booster under partially shaded conditions using MPPT based sand cat swarm optimizer

Photovoltaic (PV) systems perform a vital role in addressing the worldwide energy crisis and fulfilling the escalating energy demand. The variability in irradiance, temperature, and unpredictable weather conditions possess a direct impact on the productivity of PV systems. Furthermore, the existence of partially shaded conditions intensifies the complexity of PV systems, resulting in significant power degradation. These conditions present significant challenges for PV systems to achieve maximum power output and produce optimal energy. To address the prevailing challenges, this study introduces a maximum power point tracking (MPPT) control methodology utilizing a sand cat swarm optimizer (SCSO). This ingenious strategy adapts the sand cat hunting style. The investigation centers on optimizing energy harvesting in PV systems, with a specific emphasis on enhancing precision, rapid convergence, and minimizing oscillations. The suggested SCSO performance is evaluated under a variety of weather situations, including both instances of partially shaded and uniform irradiance. The SCSO results are juxtaposed with other existing bio-inspired algorithms, such as grey wolf optimization (GWO), particle swarm optimization (PSO), and tunicate swarm algorithm (TSA). The proposed SCSO technique achieves 99.94 % tracking accuracy on average and shows superior performance, with faster tracking response and less power oscillation. Moreover, the proposed SCSO generates significantly more energy than the rest compared algorithms. The performance of the suggested method is further validated through a hardware-based experimental assessment, demonstrating an optimal level of tracking performance.

Transparent metal-oxide photovoltaics for energy harvesting and storage for sustainable platforms

A transparent photovoltaic (TPV) energy harvesting method would provide more degrees of freedom for deployment on windows, buildings, vehicles, and surfaces with less soil dependency. This study designs a TPV-integrated energy storage system (capacitor charger) as a sustainable energy platform. The TPV device comprises a metal-oxide junction with a thin Si layer to enhance light utilization across a broad spectrum. Wide-bandgap metal-oxide-based materials absorb high-energy ultraviolet (UV) photons, while the Si layer captures longer wavelength lights due to the lower bandgap. The TPV structure (FTO/NiO/p+-Si/a-Si/n+-Si/AZO/ITO) exhibits an average visible transparency of 37 % and a power conversion efficiency of 4.97 % under 405 nm UV light illumination. The excellent electrical characteristics with a short-circuit current density of 10.1 mA/cm2 and open-circuit voltage value of 0.79 V allow TPVs to serve as a power source for rapidly charging capacitor banks in the energy storage unit. This PV-linked capacitor energy system can illuminate LED lamps, suggesting an on-site sustainable energy platform. The proposed Si-embedded TPV demonstrates electric power generation across broad wavelengths, enabling the bi-directional PV utilization of sunlight and indoor light sources for energy harvesting both day and night.

A Time-Based Direct MPPT Technique for Low-Power Photovoltaic Energy Harvesting

A Time-Based Direct MPPT Technique for Low-Power Photovoltaic Energy Harvesting

A Study of High Gain DC-DC Boost Converters for Renewable Energy Sources

This paper presents a comprehensive investigation into the various topologies of DC-DC boost converters which are designed for optimal integration with RES like photovoltaic (PV) systems. Photovoltaic applications demand efficient energy harvesting and management to maximize the conversion of solar energy into electrical power. The DC-DC topologies include switched coupled inductor, basic coupled inductor, coupled capacitor with coupled inductor with a snubber circuit, active clamp, high step-up and three-winding dual switches are considered for study. Each topology is analyzed in terms of its suitability for PV applications, considering factors such as efficiency, voltage gain, and reliability. The basic coupled inductor topology is explored as a reference point, providing a foundation for understanding the subsequent advanced configurations. This work explores and compares several prominent boost converter configurations, incorporating advanced techniques to enhance overall performance and efficiency for RES applications.

A Low-Voltage Self-Starting Boost Converter Using MPPT with Pulse Multiplication for Energy Harvesting

A single-inductor, low-voltage, three-step self-starting boost converter is proposed for photovoltaic (PV) energy harvesting. In order to enhance energy transfer efficiency, a variable-step Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) scheme has been devised based on a novel pulse multiplication technique. Upon overcoming the speed and accuracy limitations, the maximum power point (MPP) of the PV model is accurately tracked. In the boost converter, the average inductor current is utilized to implement closed-loop control of the MPPT loop, enhancing the stability of the tracking process and enabling efficient energy transmission. Finally, the boost converter is implemented using a 0.18 μm CMOS process, which is capable of self-starting and maintaining stable operations at input voltages ranging from 90 mV to 300 mV, achieving a peak efficiency of 93%.

Analysing the Effects of Thin Object Shading on PV Sources: A Dual Approach Combining Outdoor and Laboratory Solar Simulator Experimentation

The impact of shading has been a prominent subject of discourse within the realm of photovoltaic (PV) energy harvesting and is recognized as a significant detriment to the system’s overall efficiency. Nevertheless, prevailing investigations, which predominantly focus on the hard shading originating from building structures and vegetation, singularly address the umbra shadow phenomenon while overlooking the complexity of shadow properties and their varying intensities. In this context, this present research aims to analyze the impact of shading caused by thin objects, wherein shadow formation deviates from a singular-intensity umbra to a blend of umbra and penumbra, exhibiting diverse intensities. In the initial experimental approach, outdoor trials produced statistically significant findings, identifying both the distance and thickness of shading objects as primary determinants influencing the impact of thin object shading on the power output of PV systems. Furthermore, the analysis of the results revealed that under the specified parameters and assumptions, when considering a thin object with a thickness-to-distance ratio of 2.3 mm/225 cm, the resulting power loss of 1.65% is statistically insignificant. Remarkably, laboratory investigations unveiled a notable correlation between penumbra and power loss, contrasting with outdoor experimentation results. The findings highlight the distinction between indoor and outdoor methodologies, stemming from discrepancies in shadow formation characteristics, thereby emphasizing the necessity of acknowledging and comprehending these variations.

Light-Emitting Diodes for Energy Harvesting

Energy harvesting is gaining substantial relevance in the realm of ultra-low-power electronics and Internet-of-Things devices with limited access to classic power sources. Several harvesting approaches are available, depending on the energy source; among them, photovoltaic devices benefit from the highest energy density. However, the inclusion of a dedicated photovoltaic cell in a low-power system may result in increased costs and complexity, thus hampering economic sustainability. Conversely, electronic apparatuses often make use of light-emitting-diodes (LEDs), which could be effectively employed as photovoltaic energy harvesters whenever not actively generating photons. Here, we explore the potentials of commercially available LEDs for energy harvesting and determine their quantum efficiency. We examine the correlation of the latter with the spectral response and the available light, demonstrating that visible-wavelength diode emitters can yield very high conversions in the photovoltaic mode. We report measured quantum efficiencies as high as 39% under low-intensity (100 µW/cm2) fluorescent illumination.

Enhanced power supply circuitry with long duration and high‐efficiency charging for indoor photovoltaic energy harvesting internet of things end device

AbstractLight is a popular choice as an indoor energy source for Internet of Things (IoT) end devices. However, indoor light sources are intermittent, which can disrupt the operation of IoT end devices, potentially leading to safety concerns or inaccurate data. Therefore, there is a growing need to develop a long‐duration power supply for IoT end devices. The energy from ambient light is harnessed to charge a supercapacitor through an energy manager chip. This supercapacitor serves as the power source for IoT nodes when the ambient light is unavailable. Nevertheless, as the voltage of the supercapacitor drops below the operating threshold, the IoT end node will eventually shut down. This paper proposes a circuit that utilizes a Joule Thief circuit, booster converter, and capacitor stack‐up circuit to extract the remaining energy from the supercapacitor and boost the voltage, thereby extending the operational lifespan of IoT end nodes. Additionally, capacitor stack‐up circuits significantly enhance charging efficiency. PSpice design and simulations confirm circuit feasibility. High‐efficiency charging and long‐duration IoT nodes suggest replacing traditional batteries with supercapacitors, reducing environmental impact.

Intrinsically Multistable Soft Actuator Driven by Mixed-Mode Snap-Through Instabilities.

Actuators utilizing snap-through instabilities are widely investigated for high-performance fast actuators and shape reconfigurable structures owing to their rapid response and limited reliance on continuous energy input. However, prevailing approaches typically involve a combination of multiple bistable actuator units and achieving multistability within a single actuator unit still remains an open challenge. Here, a soft actuator is presented that uses shape memory alloy (SMA) and mixed-mode elastic instabilities to achieve intrinsically multistable shape reconfiguration. The multistable actuator unit consists of six stable states, including two pure bendingstates and four bend-twist states. The actuator is composed of a pre-stretched elastic membrane placed between two elastomeric frames embedded with SMA coils. By controlling the sequence and duration of SMA activation, the actuator is capable of rapid transition between all six stable states within hundreds of milliseconds. Principles of energy minimization are used to identify actuation sequences for various types of stable state transitions. Bendingand twisting angles corresponding to various prestretch ratios are recorded based on parameterizations of the actuator's geometry. To demonstrate its application in practical conditions, the multistable actuator is used to perform visual inspection in a confined space, light source tracking during photovoltaic energy harvesting, and agilecrawling.

Simulation and forecasting of power by energy harvesting method in photovoltaic panels using artificial neural network

Heat is an important efficiency reducing factor in photovoltaic systems. Although many studies in the literature are related to the removal of waste heat from photovoltaic panels, the disadvantages such as installation and maintenance of cooling systems should not be forgotten. A study has shown that with a new approach, energy can be produced with the method of energy harvesting from waste heat. The results of the study were limited to a geographical region and climatic conditions in Aksaray, Turkey. In this article, the results of the study, which was limited to a region, were extended using the finite element method analysis and the artificial neural network model. Ten different cases were determined and temperature gradient was found by finite element analysis. The forecasting algorithm was developed with artificial neural network and estimates the harvestable power based on the temperature gradient. The accuracy of the algorithm was tested with the MSE and nRMSE statistical metrics which were calculated as 59.1423 mW and 13.6189 %, respectively. The training data accuracy of the network was 0.93987 and the combined accuracy was 0.94364. The results of this study are important to be a reference for researchers who want to establish a photovoltaic panel energy harvesting system.

A Photovoltaic Energy Harvester/Image Sensor Platform With Event Detection Capability in 180 nm

A Photovoltaic Energy Harvester/Image Sensor Platform With Event Detection Capability in 180 nm

Building Blocks of Photovoltaic Energy Harvesting Systems [Women-In-Circuits Column

Building Blocks of Photovoltaic Energy Harvesting Systems [Women-In-Circuits Column

A High Temperature Harvestorer Based on a Photovoltaic Cell and an Oxygen Ion Battery

A High Temperature Harvestorer Based on a Photovoltaic Cell and an Oxygen Ion Battery

Optimization of Building integrated photovoltaic and thermoelectric hybrid energy harvesting system for different climatic regions

As energy saving emerges as a critical factor for the sustainable development of humankind, the importance of Zero-Energy Buildings (ZEB) is gradually increasing. Therefore, much research is being conducted on high-efficiency renewable energy technologies that can be applied in urban areas. However, increasing the efficiency of BIPV were proposed and studied because of the need for the renewable energy source. Such as using phase change material (PCM), heat fin, wavelength selection, PV surface temperature decreasing or using a thermoelectric generator (TEG), and convection cooling utilizing the waste heat from the PV. In most previous studies, the performance when each method was analyzed through experiments or simulations. However, the design analysis for maximum performance still needs to be conducted. Therefore, a BIPV combined with a PCM and TEG (BIPV-TEG-PCM) design is analyzed in this study. Herein, the three variables (phase change temperature of the PCM, heat fin spacing in the PCM container, and TEG arrangement) were analyzed through computational fluid dynamics (CFD)-based simulations. Moreover, through multi-objective optimization, the BIPV-TEG-PCM system of the optimal design was derived. Analysis results of the appropriate melting temperature of PCM, heat fin interval, and arrangement of TEG for the proposed system are 40 °C, 12.4 mm, and 187 mm, respectively.

Modeling and Design of Cold-Start Charge Pumps for Photovoltaic Energy Harvesters

Modeling and Design of Cold-Start Charge Pumps for Photovoltaic Energy Harvesters

Maximum output power point tracking for photovoltaic energy harvesting systems: Mathematical model and circuit implementation

Maximizing the power transferred to the load is a key feature in any energy harvesting system. Contrary to traditional approaches, this paper mathematically demonstrates that performing a maximum power point tracking on the power delivered to the load instead of on the photogenerated power allows to harvest up to 25% more power due to setting less demanding operating conditions. A circuit implementation of a system that successfully maximizes its output by exclusively taking measurements of the output voltage is designed and demonstrated using a 180 nm commercial CMOS process. The system operates at μW range and achieves a peak power conversion efficiency of 79.04% at 30.74 μW output.