Energy harvesting methods for transmission lines: a comprehensive review

Humanity faces important challenges concerning the optimal use, security, and availability of energy systems, particularly electrical power systems and transmission lines. In this context, data-driven predictive maintenance plans make it possible to increase the safety, stability, reliability, and availability of electrical power systems. In contrast, strategies such as dynamic line rating (DLR) make it possible to optimize the use of power lines. However, these approaches require developing monitoring plans based on acquiring electrical data in real-time using different types of wireless sensors placed in strategic locations. Due to the specific conditions of the transmission lines, e.g., high electric and magnetic fields, this a challenging problem, aggravated by the harsh outdoor environments where power lines are built. Such sensors must also incorporate an energy harvesting (EH) unit that supplies the necessary electronics. Therefore, the EH unit plays a key role, so when designing such electronic systems, care must be taken to select the most suitable EH technology, which is currently evolving rapidly. This work reviews and analyzes the state-of-the-art technology for EH focused on transmission lines, as it is an area with enormous potential for expansion. In addition to recent advances, it also discusses the research needs and challenges that need to be addressed. Despite the importance of this topic, there is still much to investigate, as this area is still in its infancy. Although EH systems for transmission lines are reviewed, many other applications could potentially benefit from introducing wireless sensors with EH capabilities, such as power transformers, distribution switches, or low- and medium-voltage power lines, among others.This research was funded by Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

SkinnySensor: Enabling Battery-Less Wearable Sensors Via Intrabody Power Transfer

Tremendousadvancement inultra-low powerelectronics and radiocommunica tionshas significantly contributed towards the fabrication of miniaturized biomedical sensors capable of capturing physiological data and transmitting them wirelessly. However, most of the wearable sensors require a battery for their operation. The battery serves as one of the critical bottlenecks to the development of novel wearable applications, as the limitations offered by batteries are affecting the development of new form-factors and longevity of wearable devices. In this work, we introduce a novel concept, namely Intra-Body Power Transfer (IBPT), to alleviate the limitations and problems associated with batteries, and enable wireless, batteryless wearable devices. The innovation of IBPT is to utilize the human body as the medium to transfer power to passive wearable devices, as opposed to employingon-boardbatteries for each individual device. The proposed platform eliminates the on-board rigid battery for ultra-low power and ultra-miniaturized sensors such that their form-factor can be flexible, ergonomically designed to be placed on small body parts. The platform also eliminates the need for battery maintenance (e.g., recharging or replacement) for multiple wearable devices other than the central power source. The performance of the developed system is tested and evaluated in comparison to traditional Radio Frequency based solutions that can be harmful to human interaction. The system developed is capable of harvesting on average 217µW at 0.43V and provides an average sleep/high impedance mode voltage of 4.5V

A 30mV input battery-less power management system

This paper presents a fully-integrated on chip battery-less power management system through energy harvesting circuit developed in a 130nm CMOS process. A 30mV input voltage from a TEG is able to be boosted by the proposed Complementary Metal-Oxide-Semiconductor (CMOS) voltage booster and a dynamic closed loop power management to a regulated 1.2V. Waste body heat is harvested through Thermoelectric energy harvesting to power up low power devices such as Wireless Body Area Network. A significant finding where 1 Degree Celsius thermal difference produces a minimum 30mV is able to be boosted to 1.2V. Discontinuous Conduction Mode (DCM) digital control oscillator is the key component for the gate control of the proposed voltage booster. Radio Frequency (RF) rectifier is utilized to act as a start-up mechanism for voltage booster and power up the low voltage closed loop power management circuit. The digitally control oscillator and comparator are able to operate at low voltage 600mV which are powered up by a RF rectifier, and thus to kick-start the voltage booster

Power Approaches for Implantable Medical Devices.

Implantable medical devices have been implemented to provide treatment and to assess in vivo physiological information in humans as well as animal models for medical diagnosis and prognosis, therapeutic applications and biological science studies. The advances of micro/nanotechnology dovetailed with novel biomaterials have further enhanced biocompatibility, sensitivity, longevity and reliability in newly-emerged low-cost and compact devices. Close-loop systems with both sensing and treatment functions have also been developed to provide point-of-care and personalized medicine. Nevertheless, one of the remaining challenges is whether power can be supplied sufficiently and continuously for the operation of the entire system. This issue is becoming more and more critical to the increasing need of power for wireless communication in implanted devices towards the future healthcare infrastructure, namely mobile health (m-Health). In this review paper, methodologies to transfer and harvest energy in implantable medical devices are introduced and discussed to highlight the uses and significances of various potential power sources

OBNOVLJIVI IZVORI ENERGIJE U BEŽIČNIM SENZORSKIM MREŽAMA

The advances in the technology of cheap and low power consumption microelectronic components have lead to the expansion of wireless technologies in the past two decades. One of the most important shortcomings of all wireless devices, including sensor ones, are limited energy resources. This paper reviews common mechanism of energy harvesting and energy scavenging, which draw power from the environment to feed the energy reserves in wireless sensor networks. They include conversion of the energy of electromagnetic waves, vibrations and heat.Razvoj jeftinih mikroelektronskih komponenti niske potrošnje uslovio je ekspanziju bežičnih tehnologija u zadnje dve dekade. Jedna od glavnih mana svih bežičnih uređaja, uključujući senzorske, jesu ograničeni energetski resursi. U ovom radu opisani su uobičajeni mehanizmi koji se koriste u „energy harvesting“ i „energy scavenging“ procedurama, kojima se snaga iz okoline koristi za dopunjavanje energetskih rezervi u bežičnim senzorskim mrežama. Oni uključuju konverziju energije elektromagnetskih talasa, vibracija i toplote

Design of Rectenna using RF Harvesting for Batteryless IoT Sensors

In this paper, we propose a compact and highly efficient Rectenna design (rectifying antenna), operating on ISM band with the centre frequency of 2.4 GHz. A RF to DC conversion through Schottky diode (HSMS2860) is used to generate the dc voltage to operate a battery-less IoT Sensor for RF power harvesting using the designed Rectenna. We have achieved more than 80% efficiency through Advanced Design System (ADS-2016) simulation software at different power densities. Further a rectenna circuit is designed using RF to DC Schottky detector diode and a microstrip patch antenna. The rectenna circuit design is simulated through ADS 2016 simulation software. The Battery less sensor requires 2V- 2.5V dc voltage to perform an optimum performance. As per simulation and theoretical/practical modeling we have achieved more than 80% efficiency at single Schottky diode and its operating from 915 MHz to 5.8 GHz. Rectenna operates at lower power densities start from 0.4uW/cm. The proposed rectenna design is a possible candidate to be used as sensors/devices at frequency of 2.4GHz with current technologies e.g. ZigBee, Wi-Fi, BLE etc and future probable application could be long range radio sensor using the latest new generation LoRa technology its line of sight range between 10km-20km

Energy Harvesting Techniques for Internet of Things (IoT)

The rapid growth of the Internet of Things (IoT) has accelerated strong interests in the development of low-power wireless sensors. Today, wireless sensors are integrated within IoT systems to gather information in a reliable and practical manner to monitor processes and control activities in areas such as transportation, energy, civil infrastructure, smart buildings, environment monitoring, healthcare, defense, manufacturing, and production. The long-term and self-sustainable operation of these IoT devices must be considered early on when they are designed and implemented. Traditionally, wireless sensors have often been powered by batteries, which, despite allowing low overall system costs, can negatively impact the lifespan and the performance of the entire network they are used in. Energy Harvesting (EH) technology is a promising environment-friendly solution that extends the lifetime of these sensors, and, in some cases completely replaces the use of battery power. In addition, energy harvesting offers economic and practical advantages through the optimal use of energy, and the provisioning of lower network maintenance costs. We review recent advances in energy harvesting techniques for IoT. We demonstrate two energy harvesting techniques using case studies. Finally, we discuss some future research challenges that must be addressed to enable the large-scale deployment of energy harvesting solutions for IoT environments

Architecture of Micro Energy Harvesting Using Hybrid Input of RF, Thermal and Vibration for Semi-Active RFID Tag

This research work presents a novel architecture of Hybrid Input Energy Harvester (HIEH) system for semi-active Radio Frequency Identification (RFID) tags. The proposed architecture consists of three input sources of energy which are radio frequency signal, thermal and vibration. The main purpose is to solve the semi-active RFID tags limited lifespan issues due to the need for batteries to power their circuitries. The focus will be on the rectifiers and DC-DC converter circuits with an ultra-low power design to ensure low power consumption in the system. The design architecture will be modelled and simulated using PSpice software, Verilog coding using Mentor Graphics and real-time verification using field-programmable gate array board before being implemented in a 0.13 µm CMOS technology. Our expectations of the results from this architecture are it can deliver 3.3 V of output voltage, 6.5 mW of output power and 90% of efficiency when all input sources are simultaneously harvested. The contribution of this work is it able to extend the lifetime of semi-active tag by supplying electrical energy continuously to the device. Thus, this will indirectly  reduce the energy limitation problem, eliminate the dependency on batteries and make it possible to achieve a batteryless device.This research work presents a novel architecture of Hybrid Input Energy Harvester (HIEH) system for semi-active Radio Frequency Identification (RFID) tags. The proposed architecture consists of three input sources of energy which are radio frequency signal, thermal and vibration. The main purpose is to solve the semi-active RFID tags limited lifespan issues due to the need for batteries to power their circuitries. The focus will be on the rectifiers and DC-DC converter circuits with an ultra-low power design to ensure low power consumption in the system. The design architecture will be modelled and simulated using PSpice software, Verilog coding using Mentor Graphics and real-time verification using field-programmable gate array board before being implemented in a 0.13 µm CMOS technology. Our expectations of the results from this architecture are it can deliver 3.3 V of output voltage, 6.5 mW of output power and 90% of efficiency when all input sources are simultaneously harvested. The contribution of this work is it able to extend the lifetime of semi-active tag by supplying electrical energy continuously to the device. Thus, this will indirectly  reduce the energy limitation problem, eliminate the dependency on batteries and make it possible to achieve a batteryless device

A 30mV Input Battery-Less Power Management System

This paper presents a fully-integrated on chip battery-less power management system through energy harvesting circuit developed in a 130nm CMOS process. A 30mV input voltage from a TEG is able to be boosted by the proposed Complementary Metal-Oxide-Semiconductor (CMOS) voltage booster and a dynamic closed loop power management to a regulated 1.2V. Waste body heat is harvested through Thermoelectric energy harvesting to power up low power devices such as Wireless Body Area Network. A significant finding where 1 Degree Celsius thermal difference produces a minimum 30mV is able to be boosted to 1.2V. Discontinuous Conduction Mode (DCM) digital control oscillator is the key component for the gate control of the proposed voltage booster. Radio Frequency (RF) rectifier is utilized to act as a start-up mechanism for voltage booster and power up the low voltage closed loop power management circuit. The digitally control oscillator and comparator are able to operate at low voltage 600mV which are powered up by a RF rectifier, and thus to kick-start the voltage booste

Scheduling Tasks on Intermittently-Powered Real-Time Systems

Batteryless systems go through sporadic power on and off phases due to intermittently available energy; thus, they are called intermittent systems. Unfortunately, this intermittence in power supply hinders the timely execution of tasks and limits such devices’ potential in certain application domains, e.g., healthcare, live-stock tracking. Unlike prior work on time-aware intermittent systems that focuses on timekeeping [1, 2, 3] and discarding expired data [4], this dissertation concentrates on finishing task execution on time. I leverage the data processing and control layer of batteryless systems by developing frameworks that (1) integrate energy harvesting and real-time systems, (2) rethink machine learning algorithms for an energy-aware imprecise task scheduling framework, (3) develop scheduling algorithms that, along with deciding what to compute, answers when to compute and when to harvest, and (4) utilize distributed systems that collaboratively emulate a persistently powered system. Scheduling Framework for Intermittently Powered Computing Systems. Batteryless systems rely on sporadically available harvestable energy. For example, kinetic-powered motion detector sensors on the impalas can only harvest energy when the impalas are moving, which cannot be ascertained in advance. This uncertainty poses a unique real-time scheduling problem where existing real-time algorithms fail due to the interruption in execution time. This dissertation proposes a unified scheduling framework that includes both harvesting and computing. Imprecise Deep Neural Network Inference in Deadline-Aware Intermittent Systems. This dissertation proposes Zygarde- an energy-aware and outcome-aware soft-real-time imprecise deep neural network (DNN) task scheduling framework for intermittent systems. Zygarde leverages the semantic diversity of input data and layer-dependent expressiveness of deep features and infers only the necessary DNN layers based on available time and energy. Zygarde proposes a novel technique to determine the imprecise boundary at the runtime by exploiting the clustering classifiers and specialized offline training of the DNNs to minimize the loss of accuracy due to partial execution. It also proposes a single metric, η to represent a system’s predictability that measures how close a harvesterâs harvesting pattern is to a constant energy source. Besides, Zygarde consists of a scheduling algorithm that takes available time, available energy, impreciseness, and the classifier's performance into account. Scheduling Mutually Exclusive Computing and Harvesting Tasks in Deadline-Aware Intermittent Systems. The lack of sufficient ambient energy to directly power the intermittent systems introduces mutually exclusive computing and charging cycles of intermittently powered systems. This introduces a challenging real-time scheduling problem where the existing real-time algorithms fail due to the lack of interruption in execution time. To address this, this dissertation proposes Celebi, which considers the dynamics of the available energy and schedules when to harvest and when to compute in batteryless systems. Using data-driven simulation and real-world experiments, this dissertation shows that Celebi significantly increases the number of tasks that complete execution before their deadline when power was only available intermittently. Persistent System Emulation with Distributed Intermittent System. Intermittently-powered sensing and computing systems go through sporadic power-on and off periods due to the uncertain availability of energy sources. Despite the recent efforts to advance time-sensitive intermittent systems, such systems fail to capture important target events when the energy is absent for a prolonged time. This event miss limits the potential usage of intermittent systems in fault- intolerant and safety-critical applications. To address this problem, this dissertation proposes Falinks, a framework that allows a swarm of distributed intermittently powered nodes to collaboratively imitate the sensing and computing capabilities of a persistently powered system. This framework provides power-on and off schedules for the swamp of intermittent nodes which has no communication capability with each other.Doctor of Philosoph