Results for “Power Development” — Page 80

DOE OSTI2022

NPP Simulators for Coupled Thermal and Electric Power Dispatch

The Light Water Reactor Sustainability (LWRS) program within the United States Department of Energy supports extending the operation of the U.S. commercial nuclear power plant (NPP) fleet. Within the LWRS program, the Flexible Plant Operation and Generation (FPOG) Pathway works to diversify the revenue streams of light water reactors (LWRs) by opening opportunities for the co-generation of non-electric products in addition to supplying electrical power to the grid. Recent events have added greater motivation to these efforts. For example, the recent Inflation Reduction Act (IRA) passed by the U.S. federal government offers substantial tax incentives for producing clean hydrogen, the technology readiness level of dispatchable and high-efficiency hydrogen production has dramatically increased in a short time, and societal response to world climate change is driving a transition away from fossil fuels. Producing hydrogen with maximum efficiency using nuclear power requires dispatching both electrical and thermal power from the nuclear plant to the hydrogen plant, so testing concepts of operations for combined electrical and thermal power dispatch (TPD) from an NNP to a hydrogen plant is of interest. This report documents achievement of the Light Water Reactor Sustainability (LWRS) program milestone “Install and demonstrate a vendor-developed simulator on the Human Systems Simulation Laboratory (HSS) for dispatch of LWR electrical power to a close-coupled electrolysis plant” with a due date of Dec. 22, 2022. Several factors provide motivation for this effort. Coupling the power generation deck of a nuclear power plant to a hydrogen production facility introduces new possibilities for operational transients that must be addressed. In particular, the performance of the integrated system during startup and shutdown of the hydrogen production facility, as well as offnormal conditions, need to be evaluated to ensure there are no adverse effects on the operation of the existing NPP. The concept of operations involving the NPP, the hydrogen plant, and the electric power grid must be tested using NPP simulators and operating procedures that have been modified for TPD operations. These tests must also include dynamic simulations of the coupled tertiary thermal and electric loads as well as coordinated activities with NPP operators, tertiary load operators and grid power coordinators. The report summarizes progress in developing and testing full-scope NPP simulators at the HSSL, including a generic BWR simulator from GSE Systems, Inc. and generic PWR simulator from Westinghouse. In the case of the TPD-GBWR Simulator from GSE Systems, Inc., a BWR is thermally coupled to a high temperature electrolysis (HTE) plant that produces hydrogen and oxygen from de-ionized water. The hydrogen plant is not explicitly simulated but only included as a transient heat sink. A thermal power dispatch (TPD) system transfers heat between the steam systems at the BWR and the hydrogen plant. Operational results from two versions of the modified simulator are presented. The first version uses synthetic oil as a heat transfer fluid in a closed delivery heat loop (DHL) that generates steam at the hydrogen plant. The second version uses steam as the heat transfer fluid in a delivery steam line (DSL) to provide steam to the hydrogen plant. For both versions, the estimated thermal power delivery distance is approximately one kilometer. The amount of thermal power dispatched in the simulators is 15% of the total reactor thermal power such that the simulators provide a tool to study the feasibility of coupling a BWR to industrial processes that benefit from a combination electrical and thermal power dispatch. Ongoing work within a CRADA is also developing a full-scope PWR simulator provided by Westinghouse for both thermal and electric power coupling. This simulator is based on a PWR plant with two three-loop Westinghouse reactors. Westinghouse PWRs are sufficiently similar that a simulator of a three-loop reactor is an appropriate representation for two-loop and four-loop PWR reactors. The three-loop simulator will initially be modified for close-coupling to a 100 MW HTE hydrogen production plant that will require approximately 25 MW of thermal power while operating at its maximum rated capacity. The simulator testing will include full coupling to dynamic simulations of a hydrogen production plant and a representative bulk electric grid. The simulator provided by Westinghouse is similar to the GPWR simulator that INL has already obtained from GSE Systems but has a few important added benefits. First, the Westinghouse simulator is based on digital controls and has additional screens that can be called up to show parameter trends to assist operators in decision-making. The Westinghouse simulator also has upgrades to the controls and hardware representations, such as valve actuators, that make it more realistic and flexible in terms of accurately sim

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Developing a Distributed Trust Model for Distributed Energy Resources

Electric power system operators can manage distribution system reliability by coordinating end customer usage of distributed energy resources. The end customers in this regard are Service Provisioning Customers, who provide their energy resources to a Grid Service Provider, which in turn dispatches large aggregations of distributed energy resources to provide reliable service to the power system.The security of this system relies upon information protection mechanisms, as described in IEEE 2030.5. However, in addition to preventive security measures, a monitoring function is required to ensure trustworthiness. Trust models are a method to detect and respond to both expected and unexpected behavior. Different trust models are required for various types and characteristics of each situation. This paper will describe the topics that must be considered when developing a trust model as it applies to distributed energy resources. The major contribution of this paper is the creation and application of a Distributed Trust Model applied to distributed energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

DETECTING FIRE WITH MACHINE LEARNING-ENABLED VISUAL MONITORING FOR NUCLEAR POWER PLANT ENVIRONMENTS

Nuclear power plants are experiencing significant cost challenges to remain competitive with other energy-generation utilities. Unlike other industries, the cost of operation and maintenance activities is mostly attributed to workforce costs. To mitigate this, nuclear power plant stakeholders are increasingly interested in the development and deployment of machine learning methods to potentially automate or augment manually intensive tasks to reduce costs, especially for monitoring activities. One monitoring function that is visually demanding and that can occur frequently to meet the requirements of a fire protection program is visually monitoring an area for fire occurrence. Currently, fire watch activities consist of a worker physically stationed at a given location with the sole responsibility of observing a given area to ensure a fire is detected and mitigated promptly. This effort focused on the development and evaluation of a suitable deep convolutional neural network to classify individual video frames at a sub-second frequency for the occurrence of “fire” and “no fire” in varying industrial environments similar to nuclear power plants. It is believed that a trained neural network model could be integrated with existing facility video surveillance camera feeds to generate alerts when fire inferences occur in individual frames captured at sub-second temporal resolutions. Extensive effort was dedicated to identifying and curating suitable imagery training data representing varying environments and scene settings with and without flame features to maximize generalization in nuclear power plant environments. The data collection effort resulted in the aggregation of a large, labeled image library exceeding 12,000 images to support model training for diverse industrial environments. A deep neural network model incorporating parallel multi-scale capabilities was developed and trained to support accurate image-based detection of flame incidents of varying sizes and spectral feature properties within heterogeneous scenes. Analysis results show that the trained model can achieve high inference accuracy despite heterogeneous scene environments and components. Testing accuracy exceeded 95.0 percent with very low false positive and false negative inferences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗

DOE OSTI2026

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Machine Governor

This paper introduces the development of a high-fidelity gas turbine governor model using a programmable logic controller for power-hardware-in-the-loop (PHIL) validation. The governor model is integrated with the National Renewable Energy Laboratory's (NREL) PHIL test bed, featuring a 2-MVA synchronous machine and a 2.5-MW variable-speed drive, to emulate NG-driven HRSGs and CTs under various operational scenarios. The primary objective of this research is to study the grid-connected and islanding operations of conventional generation sources, with representative startup sequences including turbine purge, ignition, speed ramp-up, synchronization, and breaker closure. Preliminary results of the generator governor model on NREL PHIL platform, particularly using the 2.5-MW dynamometer system, offered significant insights into the modeling techniques, hardware integration, scaling, and real-world simulation dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Design Power Control Strategies of Grid-Forming Inverters for Microgrid Application

This paper develops and compares two control schemes in the application control layer of a non-phase-locked loop (non-PLL) grid-forming (GFM) inverter to gain insight and understanding into how the two schemes affect the dynamic responses of GFM inverters and the transition operation of microgrids. The first scheme adopts power tracking based on an outer current loop in grid-connected mode and droop control in islanded mode, and the second uses droop control in both grid-connected and islanded modes. Analytical study is developed to compare the performance of these two strategies from various aspects, including fundamental differences, transition operation, power tracking, and P-Q capability with low point-of-common-coupling (PCC) voltages. Extensive simulation testing is carried out to validate the control performance of these two control strategies, and the simulation testing confirms the findings of the analytic study. Finally, the second strategy is recommended because of its superior control performance and ease of implementation. The analysis and results are useful in developing reliable control schemes for non-PLL GFM inverters because increasing numbers of inverters will work as non-PLL grid-forming sources in future grids because of their improved stability and reliability.

grid-forming↗

DOE OSTI2020

Geothermal Deep Direct Use for Turbine Inlet Cooling in East Texas

The National Renewable Energy Laboratory (NREL), the Southern Methodist University Geothermal Laboratory (SMU), Eastman Chemical (Longview, TX), and TAS (Houston, TX) evaluated the feasibility of using geothermal heat to improve the performance of a natural-gas power plant in East Texas. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of a geologic region known as the Sabine Uplift. The feasibility study focused on determining the potential for accessing a subsurface hot-water geothermal resource within a 10-km radius of the site to provide thermal energy for absorption chillers. Wells within a 20-km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, field porosity and permeability. The lithologies of most interest are the Lower Cretaceous Trinity Group and Upper Jurassic Cotton Valley Group. The deeper Cotton Valley formations are hotter (averaging 117 to 130°C), yet permeability and porosity are low. The shallower Trinity Group contains more variability in permeability and porosity and lower temperatures averaging about 98 to 117°C. The shallower formations are considered despite the lower temperature because of increased ability to produce larger volumes of water and extract enough heat before reinjection. The complete SMU analysis is available in the National Geothermal Data System (NGDS). Tapping such deep geothermal sources for direct heating (as opposed to power generation) is known as geothermal deep direct use (DDU). Geothermal DDU has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for what are typically small-scale, variable-demand projects. This project examines the feasibility of geothermal energy integration in a natural-gas combined cycle power station in East Texas. The DDU resource is tapped to drive absorption chillers (24/7) for production of chilled water at 5-10°C (41-50°F). This chilled water is stored until needed, which allows for continuous operation with a relatively small-capacity geothermal/absorption chiller system. When conditions are favorable, the chilled water is dispatched to cool the air entering the compressor stage of a gas combustion turbine. This process, known as turbine inlet cooling (TIC), boosts power production during periods of high temperature and high-power demand. Such systems can enhance grid reliability and reduce the cost for peak-demand power. A simulation model of the power plant was developed in IPSEpro software and validated against operational data from the plant. This model allowed the team to estimate the additional power that could be produced by applying TIC under different operating and ambient conditions. Absorption chiller performance was estimated from vendor sources to determine the production rate of chilled water from the geothermal resource. Geothermal drilling and development costs were estimated using NREL's GEOPHIRES 2.0. The expected lower drilling costs in this region led to an estimated cost of geothermal heat of about $4/MMBtu (1.4 cents/kWh t ). The estimated cost for the absorption chillers and TIC hardware were obtained from literature sources and project partners. Hourly data were obtained for weather, natural gas and electricity prices, and plant operating state for 2017, which served as a representative year. NREL estimated the capital cost, operating cost, and additional electricity production and revenue for different combinations of geothermal capacity, chiller capacity, and water storage-tank size. The analysis drove toward smaller geothermal and chiller systems to reduce equipment cost. A relatively low-cost water storage tank accumulated the near-continuous chilled water output for later use when TIC was most valued.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

XFEM Development for Modeling Crack Growth in Prototypical Welded Components

Nuclear power plant components are subjected to harsh operating environments that can lead to multiple degradation mechanisms in which fracture can play a prominent role. Predicting crack growth is important for assessing the integrity of welded components. The extended finite element method (XFEM) is an important tool for modeling such crack growth, and XFEM capabilities have been developed within the MOOSE framework. This report documents work in the MOOSE XFEM module to model fractures in three-dimensional representations of components using a topologically two-dimensional mesh to define cutting planes. Crack growth algorithms have been implemented to evolve the cutting mesh based on equations for stress corrosion cracking. Additionally, several usability and robustness improvements have been developed to enable three-dimensional fracture simulations. The cutting algorithms were demonstrated on a three-dimensional model of a prototypical reactor component undergoing stress corrosion cracking driven by idealized weld residual stresses. This is an incremental step toward using this capability to model more complex components with residual stresses computed through welding process simulations.

42 - ENGINEERING↗

DOE OSTI2021

Optical Spectrometer With a Pulse-to-Pulse Resolution for Terahertz and mm-Wave Signals

The development of ultra-compact particle accelerators and accelerator-based high-power THz generators are some of the top priorities for research and development programs around the world. These tools require the development of accelerating structures, operating in the mm-Wave and THz range, where diagnostics are not available or are insufficient. This article presents the design of a pulse-to-pulse THz spectrometer, primarily developed for diagnostics of accelerating structures and THz radiation sources. In particular, this spectrometer can be used to detect RF pulse shortening caused by vacuum breakdown and beam misalignment in THz accelerators, as well as for bunch length monitoring and radiation source diagnostics. The spectrometer is based on a diffraction grating and is capable of covering a frequency range where RF-based breakdown measurements are not possible. We have built and tested the first prototype with different sources in a frequency range of 0.1-1.0 THz. In this article, we present the physical design, supported numerical simulations, electronics development, and test results.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Leveraging Existing Bioenergy Data: Workshop Summary Report

The U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) invests in a diverse portfolio of technologies to ensure domestic energy security, continued economic competitiveness, environmental sustainability, and the availability of cleaner fuels and power. The mission of EERE’s Bioenergy Technologies Office (BETO) is to develop transformative and revolutionary sustainable bioenergy technologies for a prosperous nation. BETO develops technologies that convert domestic biomass and waste resources into fuels, products, and power to enable affordable energy, economic growth, and innovation in renewable energy and chemicals production. This report summarizes the input received from attendees of the public workshop sponsored by BETO on July 21–23, 2020, as well as input received from a Request for Information (RFI) run in August and September 2019.

09 BIOMASS FUELS↗

DOE OSTI2023

Interface synergism and engineering of Pd/Co@N-C for direct ethanol fuel cells

Direct ethanol fuel cells have been widely investigated as nontoxic and low-corrosive energy conversion devices with high energy and power densities. It is still challenging to develop high-activity and durable catalysts for a complete ethanol oxidation reaction on the anode and accelerated oxygen reduction reaction on the cathode. The materials’ physics and chemistry at the catalytic interface play a vital role in determining the overall performance of the catalysts. Herein, we propose a Pd/Co@N-C catalyst that can be used as a model system to study the synergism and engineering at the solid-solid interface. Particularly, the transformation of amorphous carbon to highly graphitic carbon promoted by cobalt nanoparticles helps achieve the spatial confinement effect, which prevents structural degradation of the catalysts. The strong catalyst-support and electronic effects at the interface between palladium and Co@N-C endow the electron-deficient state of palladium, which enhances the electron transfer and improved activity/durability. The Pd/Co@N-C delivers a maximum power density of 438 mW cm -2 in direct ethanol fuel cells and can be operated stably for more than 1000 hours. This work presents a strategy for the ingenious catalyst structural design that will promote the development of fuel cells and other sustainable energy-related technologies.

25 ENERGY STORAGE↗

DOE OSTI2025

Physics-informed Deep Reinforcement Learning-based Control in Power systems

Incorporating physics information into the deep reinforcement learning (DRL) process is a promising approach for addressing the challenges faced in learning-based control design problems for physical systems. Power grid dynamics, being a physical system, adheres to specific physical laws, constraints, as well as operational and control rules. Therefore, consideration of such physics-based law improves the learning process drastically. In general, traditional grid control schemes rely on rule-based mechanisms that cannot adapt to changing operating conditions. To improve the adaptability and computation time, recent research has seen a surge of DRL-based applications in power grid control. A generic DRL-based control design imposes the system performance requirements through the design of reward functions. In some cases, some of the important physics information is injected through this reward function. However, due to the complex dynamics and large state-action space, learning an optimal DRL policy often becomes challenging. Inspired by the latest developments in general machine learning (ML) research, power system researchers have been investigating more direct ways of incorporating physics knowledge into DRL training. This chapter specifically focuses on these aspects of physics-informed DRL designs in grid control. It discusses the significance, applications, research gaps, and open problems that need to be addressed in future research.

artificial intelligence, machine learning↗

DOE OSTI2024

Dark Matter and other BSM searches with SRF cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Dark Matter and other BSM searches with SRF cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Zero-Power Wireless Infrared Digitizing Sensors for Large Scale Energy-Smart Farm

This project, funded by ARPA-E and led by Northeastern University, developed zeropower infrared digitizing sensors to optimize irrigation and enhance crop yields. Traditional water stress detection methods are costly and require frequent maintenance, limiting their effectiveness. Our research identified shortwave infrared (SWIR) transmittance as the most reliable indicator of plant water stress and developed plasmonically enhanced micromechanical photoswitches (PMPs) that operate with minimal power. The sensors offer low-cost, large-scale deployment, auto-calibration across different crops, and a 10-year battery life, significantly reducing maintenance costs. The system achieved 4x greater accuracy than conventional soil moisture sensors while ensuring economic feasibility. By enabling precision irrigation, this technology conserves water, enhances crop productivity, and lowers operational costs, making it a scalable solution for sustainable agriculture and global food security.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Dark Matter and other BSM searches with SRF cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

An Advanced Cooling Device for Concentrated Photovoltaic Systems

Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.

14 SOLAR ENERGY↗

DOE OSTI2024

An Advanced Cooling Device for Concentrated Photovoltaic Systems

Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.

Gou, Yimeng↗