Environment-Monitoring IoT Devices Powered by a TEG Which Converts Thermal Flux between Air and Near-Surface Soil into Electrical Energy

Paterova, Tereza; Prauzek, Michal; Konecny, Jaromír; Ožana, Štěpán; Zmij, Petr; Stankuš, Martin; Weise, Dieter; Pierer, Alexander

doi:10.3390/s21238098

Cited by 19 publications

(7 citation statements)

References 35 publications

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“…Devices which harvest energy from temperature differences arising in the environment are ideal for deployment in remote areas [64].…”

Section: Deriving Power From the Environmentmentioning

confidence: 99%

“…To produce energy from small temperature differences, a suitable soil depth is 30 cm [44]. In deeper soil layers, the daily temperature fluctuations are minuscule, and at a depth of 1 m, temperature does not fluctuate over the course of a day [64]. The power output of environment-monitoring devices which harvest thermal energy from temperature differences between air and soil is approximately in the range 2-370 μW.…”

Section: Deriving Power From the Environmentmentioning

confidence: 99%

“…The stochastic nature of harvesting energy sources threatens power system stability and may result in the inability to balance power consumption and power production [92]. The daily total energy predicted for the next day could be used as a supporting parameter to duty-cycle operation control, data collection, or communications with energy harvesting devices [64]. To predict the power supplied by energy harvesters and to ensure a balance between the produced energy and system requirements, analytical equations can be applied to model the system [93] or implement statistical or ML algorithms [94].…”

Section: Energy Predictionmentioning

confidence: 99%

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Thermoelectric energy harvesting for internet of things devices using machine learning: A review

Kucova,

Prauzek,

Konecny

et al. 2023

CAAI Trans on Intel Tech

Self Cite

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Initiatives to minimise battery use, address sustainability, and reduce regular maintenance have driven the challenge to use alternative power sources to supply energy to devices deployed in Internet of Things (IoT) networks. As a key pillar of fifth generation (5G) and beyond 5G networks,IoT is estimated to reach 42 billion devices by the year 2025. Thermoelectric generators (TEGs) are solid state energy harvesters which reliably and renewably convert thermal energy into electrical energy. These devices are able to recover lost thermal energy, produce energy in extreme environments, generate electric power in remote areas, and power micro‐sensors. Applying the state of the art, the authorspresent a comprehensive review of machine learning (ML) approaches applied in combination with TEG‐powered IoT devices to manage and predict available energy. The application areas of TEG‐driven IoT devices that exploit as a heat source the temperature differences found in the environment, biological structures, machines, and other technologies are summarised. Based on detailed research of the state of the art in TEG‐powered devices, the authors investigated the research challenges, applied algorithms and application areas of this technology. The aims of the research were to devise new energy prediction and energy management systems based on ML methods, create supervised algorithms which better estimate incoming energy, and develop unsupervised and semi‐supervised approaches which provide adaptive and dynamic operation. The review results indicate that TEGs are a suitable energy harvesting technology for low‐power applications through their scalability, usability in ubiquitous temperature difference scenarios, and long operating lifetime. However, TEGs also have low energy efficiency (around 10%) and require a relatively constant heat source.

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“…Devices which harvest energy from temperature differences arising in the environment are ideal for deployment in remote areas [64].…”

Section: Deriving Power From the Environmentmentioning

confidence: 99%

Section: Deriving Power From the Environmentmentioning

confidence: 99%

Section: Energy Predictionmentioning

confidence: 99%

See 1 more Smart Citation

Thermoelectric energy harvesting for internet of things devices using machine learning: A review

Kucova,

Prauzek,

Konecny

et al. 2023

CAAI Trans on Intel Tech

Self Cite

View full text Add to dashboard Cite

show abstract

“…For underground structures, thermoelectric generators (TEGs) have significant potential as an energy harvesting technology. TEGs exploit the Seebeck effect to generate energy through temperature differentials [ 73 ]. The main challenge with this technology is finding suitable temperature differences or gradients directly in a borehole for exposure to the TEG.…”

Section: Iot Devices and Cloud Processingmentioning

confidence: 99%

IoT Sensor Challenges for Geothermal Energy Installations Monitoring: A Survey

Prauzek,

Kucova,

Konecny

et al. 2023

Sensors

Self Cite

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Geothermal energy installations are becoming increasingly common in new city developments and renovations. With a broad range of technological applications and improvements in this field, the demand for suitable monitoring technologies and control processes for geothermal energy installations is also growing. This article identifies opportunities for the future development and deployment of IoT sensors applied to geothermal energy installations. The first part of the survey describes the technologies and applications of various sensor types. Sensors that monitor temperature, flow rate and other mechanical parameters are presented with a technological background and their potential applications. The second part of the article surveys Internet-of-Things (IoT), communication technology and cloud solutions applicable to geothermal energy monitoring, with a focus on IoT node designs, data transmission technologies and cloud services. Energy harvesting technologies and edge computing methods are also reviewed. The survey concludes with a discussion of research challenges and an outline of new areas of application for monitoring geothermal installations and innovating technologies to produce IoT sensor solutions.

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“…and can be used only for powering ultra-low-power applications [20]. The temperature gradient between near-surface soil and ambient air can also be used (simulation paper), but here again the recoverable power is less than 1mW in the best configuration [21]. Some interesting publications use a volume of a phase change material (PCM) placed on one side of the TEG, with the other side of the TEG connected to the ambient temperature.…”

Section: Literature Reviewmentioning

confidence: 99%

Powering a Low Power Wireless Sensor in a Harsh Industrial Environment: Energy Recovery with a Thermoelectric Generator and Storage on Supercapacitors

Boitier,

Estibals,

Seguier

2023

EPE

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Wireless sensor networks are widely used for monitoring in remote areas. They mainly consist of wireless sensor nodes, which are usually powered by batteries with limited capacity, but are expected to last for long periods of time. To overcome these limitations and achieve perpetual autonomy, an energy harvesting technique using a thermoelectric generator (TEG) coupled with storage on supercapacitors is proposed. The originality of the work lies in the presentation of a maintenance-free, robust, and tested solution, well adapted to a harsh industrial context with a permanent temperature gradient. The harvesting part, which is attached to the hot spot in a few seconds using magnets, can withstand temperatures of 200˚C. The storage unit, which contains the electronics and supercapacitors, operates at temperatures of up to 80˚C. More specifically, this article describes the final design of a 3.3 V 60 mA battery-free power supply. An analysis of the thermal potential and the electrical power that can be recovered is presented, followed by the design of the main electronic stages: energy recovery using a BQ25504, storage on supercapacitors and finally shaping the output voltage with a boost (TPS610995) followed by an LDO (TPS71533).

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Environment-Monitoring IoT Devices Powered by a TEG Which Converts Thermal Flux between Air and Near-Surface Soil into Electrical Energy

Cited by 19 publications

References 35 publications

Thermoelectric energy harvesting for internet of things devices using machine learning: A review

Thermoelectric energy harvesting for internet of things devices using machine learning: A review

IoT Sensor Challenges for Geothermal Energy Installations Monitoring: A Survey

Powering a Low Power Wireless Sensor in a Harsh Industrial Environment: Energy Recovery with a Thermoelectric Generator and Storage on Supercapacitors

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