Good Research Paper About Energy Scavenging In Wireless Sensor Networks

Type of paper: Research Paper

Topic: Energy, Solar Energy, Sensor, Internet, Radio, Alternative Energy, Wireless, Power

Pages: 6

Words: 1650

Published: 2021/01/02

Abstract

As the world is moving further into the core of digital technology, the requirements of computational devices are growing rapidly that are small in size and consume bare minimum energy. Wireless Sensor Networks (WSNs) belong to this category that form a pervasive set of computational devices, deployed in environment for sensing and monitoring physical phenomenon. Sensor nodes find plenty of applications in industries where we need to continuously monitor parameters such as humidity, temperature etc. They are deployed for lengthy periods in environment, mostly at inaccessible places. As WSNs are deployed in a form of a huge network, it is practically impossible to replace their batteries once they are depleted of charge. They should sustain their communication and sensing functions over their whole lifetime. Therefore, we need to have some kind of energy scavenging or harvesting mechanism for sensor nodes. The dependency on the battery power must be reduced so that sensor nodes could be powered in case of depleted battery. You don’t need to install any kind of power conduits or cables if some kind of energy scavenging method is introduced.
This research study will analyze various methods for energy harvesting in Wireless Sensor Networks. Brief analysis of each method will be provided. We will cover the mechanical energy harvesting that involve converting mechanical energy of any form into electrical energy, piezoelectric energy harvesting based on piezoelectric effect, electrostatic energy harvesting based on capacitance of variable capacitors, photovoltaic energy harvesting by converting solar energy into electricity, electromagnetic energy harvesting based on Faraday’s law of electromagnetic induction, thermal energy harvesting, wireless energy harvesting, wind energy harvesting, and biochemical energy harvesting. The particular emphasis will be on energy harvesting methods based on solar energy that serves as a reliable source of energy in outdoor environments. We will compare different techniques adopted in the literature for using solar energy efficiently for powering wireless sensors. We will explore the requirements of energy for various operations taking place in the WSNs and how to optimally scavenge solar energy.

Introduction

There was a time when presence of a computer was a rarity in industries and offices. In order to improve the productivity at work, computational devices and computers were deployed for several purposes. These smart devices consume energy and need a source of power for their operation. As the demand to conserve energy is increasing, the computational devices must use them in efficient manner. Wireless Sensor Networks provide tiny, low-powered computers that contain sensors for monitoring physical phenomenon and communicate with other devices for relaying information from environment to their control centers.
Wireless Sensor Networks carry huge range of applications in real life for monitoring physical and industrial processes. They are composed of tiny sensor nodes that cover a specified area. Sensor nodes are programmed to configure a network with some kind of communication protocols.
Sensor nodes are powered by energy sources of many kinds covered in this research survey. The Wireless Sensor Network should ideally be functional for many years in an industrial setup. As a result, they need to use energy in an intelligent manner. In order to improve the overall lifetime of the WSN, we can adopt three strategies:

Design sensor nodes with high energy density to accumulate large energy in a small area.

Develop smart methods to conserve available energy in a network.
Design methods to enable sensor nodes to harvest or “Scavenge” power for themselves.
It is obvious that the last method serves as a most reliable source of energy for improving the lifetime of the WSNs. Extensive research has been carried out in the past to explore innovative methods to harvest power for WSNs. We will briefly survey the methods for scavenging energy for WSNs.
Piezoelectric energy harvesting is based on the piezoelectric effect in which the mechanical energy from force or vibrations is transformed into electrical power. Mostly, piezoelectric energy scavenging involves cantilever structure containing a seismic mass attached into a piezoelectric beam.

Mechanical energy harvesting involves converting the displacements of a spring-mounted mass contained inside a harvester into electrical energy.

Vibration dependent variable capacitors generate electricity based as a function of capacitance. When plates are separated by vibrations, the capacitance changes and electricity is produced.
Faraday’s law of electromagnetic Induction derives another method for energy scavenging in WSNs. The inductive mass-spring system converts mechanical energy into electrical energy. An example is the coil containing magnet attached to the spring. The vibrations of the magnet change the flux and induce the voltage in the coil.
Photons from Sun or some other artificial light also carry sufficient energy. This energy can be used to produce electricity using photovoltaic cells. Many prototypes are proposed for photovoltaic cells in the past. The researchers are working hard to optimize the solar energy for powering sensor nodes.
Thermoelectric power generators produce electricity from temperature difference and can be used for energy harvesting. This method can be used by joining two difference metals at two junctions at different temperatures.
RF energy can be harvested by using rectifying antenna or Rectenna. RF power can be obtained from various sources such as TV and radio broadcasting.

Miniature wind turbines are used for converting air flow into electricity for powering sensor nodes.

Biochemical energy harvesting is used for converting oxygen and other chemical materials into electricity using electrochemical processes.
It is clear that we can power pervasive WSNs by a variety of ways. However, solar energy provides plenty of advantages over other methods in this regard. The most obvious one is the availability of the cheap source of solar energy during day times. Due to this reason, this research study will analyze photovoltaic energy scavenging methods used in the literature.

Body and Analysis

This section will survey the methods proposed by researchers in the past for solar energy scavenging for Wireless Sensor Networks. The power density of solar radiation is quite high during day times, roughly around 100mW/cm3. Silicon solar cells, thin film polycrystalline cells, and amorphous silicon solar cells are easily available. The power efficiency is not good on overcast days though. If WSNs have to operate in outdoor environments, solar energy presents the mature and viable solutions for powering sensor nodes. It must also be noted that the power density falls off inversely as square of the distance from the light source.
Optimal solar energy scavenging is proposed by conveying energy into rechargeable batteries even in overcast or foggy days. An ad-hoc adaptive algorithm is proposed for maximizing energy transfer from solar cells to the batteries. This method provides a plug-in solution for various solar panels and battery configurations.
proposes Maximum Power Point Tracking (MPPT) technique for charging circuit of sensor nodes utilizing solar energy. Lithium-ion batteries are used to store the charge obtained from charging circuits. Solar panel charging characteristics were observed carefully to optimize the energy harvesting for sensor motes.
Another basic charging and recharging scheme is proposed using photovoltaic effect. The batteries are recharged when their energy falls below a certain threshold value. Low power design and compatibility are important features of the design. Authors tested the scheme on MICAz hardware.
The practical implementation of solar energy harvesting is provided by many researchers. Fleck platform has been designed as a real world sensor network for observing the charging energy and the consumed power. Fleck1 and Fleck2 have been employed is plenty of WSNs as long-term projects. Fleck3 has emerged as the latest member of the series. You can use Fleck platform for a large number of sensor nodes. Enviromote is another great solar energy harvesting platform for environmental sensor networks. The platform can be upgraded from the energy point of view. present Trio Testbed as a sensor network deployment platform comprising 557 solar powered motes, a root server, and seven gateway motes. The testbed can easily cover an area of 50,000 square meters. This is one of the largest platforms for sensor networks deployed successfully. The platform is based on Trio that offers sustainable operation and fail-safe programming.
The theoretical and practical proposed results discussed above, are just a few examples of the research efforts carried out in the field of solar energy harvesting for Wireless Sensor Networks. Still there is a lot of scope in this field to utilize solar energy for designing efficient charging platforms for sensor nodes.

Conclusions

Owing to stringent requirements of monitoring and sensing, sensor nodes are deployed as low-powered and small-scale computational devices in the form of Wireless Sensor Networks. Such networks should stay alive for a long time once they are deployed. The energy of sensor nodes gets depleted with time. There must be some mechanism to continuously power them without having to manually replacing batteries of thousands of motes. Energy harvesting is a commercially viable solution to these problems. This research thesis presents a useful survey of the energy harvesting techniques used in the literature.
Energy scavenging methods utilize some form of mechanical, electromagnetic, etc to transform into electrical energy. The transformation is carried out by charging circuits that power sensor nodes.
The main part of the thesis revolves around the energy scavenging methods based on outdoor solar energy. Many research efforts are quoted in this regard that lay a firm foundation for theoretical and practical research in this regard. In order to utilize solar energy optimally, charging platforms have been developed for powering environmental sensor networks. MPPT and other optimizations are highlighted briefly. Practical implementations of solar powered charging modules include Fleck platforms, Enviromotes, and Trio testbeds. These charging platforms have been successfully deployed for sensor nodes and can be used efficiently for a large number of industrial applications.
This research study serves as a corner stone for propelling the research in the field of energy scavenging for WSNs as the researchers look for more renewable energy sources for powering sensor nodes. They should work hard to make the current implementations more viable for industries. Versatile algorithms must be proposed using available and renewable energy resources for improving lifetime of WSNs.

References

Alippi, C. a. (2008). An adaptive system for optimal solar energy harvesting in wireless sensor network nodes. Circuits and Systems I: Regular Papers, IEEE Transactions on, 1742--1750.
Bhuvaneswari, P. a. (2009). Solar energy harvesting for wireless sensor networks. Computational Intelligence, Communication Systems and Networks, 2009. CICSYN'09. First International Conference on (pp. 57--61). IEEE.
Dutta, P. a. (2006). Trio: enabling sustainable and scalable outdoor wireless sensor network deployments. Proceedings of the 5th international conference on Information processing in sensor networks (pp. 407--415). ACM.
Fei, F. a. (2012). A wind-flutter energy converter for powering wireless sensors. Sensors and Actuators A: Physical, 163--171.
Hong, T. N. (2014). Solar Energy Harvesting for Wireless Sensor Network. Universiti Teknologi PETRONAS.
Hudak, N. S. (2008). Small-scale energy harvesting through thermoelectric, vibration, and radiofrequency power conversion. Journal of Applied Physics, 101--301.
Kyriatzis, V. a.-R. (2007). Enviromote: A new solar-harvesting platform prototype for wireless sensor networks/work-in-progress report. Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007. IEEE 18th International Symposium on (pp. 1--5). IEEE.
Mitcheson, P. D. (2008). Energy harvesting from human and machine motion for wireless electronic devices. Proceedings of the IEEE (pp. 457--1486). IEEE.
Roundy, S. J. (2003). Energy scavenging for wireless sensor nodes with a focus on vibration to electricity conversion. University of California, Berkeley.
Sitka, P. a. (2007). Fleck-a platform for real-world outdoor sensor networks. Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on (pp. 709--714). IEEE.
Sue, C.-Y. a.-C. (2012). Human powered MEMS-based energy harvest devices. Applied Energy, 390--403.
Tan, Y. K. (2010). Review of energy harvesting technologies for sustainable wireless sensor network. Sustainable wireless sensor networks, 1--30.
Torres, E. O. (2010). An electrostatic CMOS/BiCMOS Li ion vibration-based harvester-charger IC. Georgia Institute of Technology.
Torres, E. O.-M. (2005). Long-lasting, self-sustaining, and energy-harvesting system-in-package (SiP) wireless micro-sensor solution. International Conference on Energy, Environment, and Disasters (INCEED), Charlotte, NC, USA, (pp. 1--33).

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