Rechargeable Sensor Networks: Technology, Theory, And Application - Introducing Energy Harvesting To Sensor Networks

Introducing Energy Harvesting to Sensor Networks

Jiming Chen, Shibo He, Youxian Sun

• Publisher: WSPC
• Year: 2014
• eBook ISBN: 9789814525473
• Topic: Biological Sciences
• Subtopic: Science General
• Index: Biological Sciences

The harvesting of energy from ambient energy sources to power electronic devices has been recognized as a promising solution to the issue of powering the ever-growing number of mobile devices around us.

Key technologies in the rapidly growing field of energy harvesting focus on developing solutions to capture ambient energy surrounding the mobile devices and convert it into usable electrical energy for the purpose of recharging said devices. Achieving a sustainable network lifetime via battery-aware designs brings forth a new frontier for energy optimization techniques. These techniques had, in their early stages, resulted in the development of low-power hardware designs. Today, they have evolved into power-aware designs and even battery-aware designs.

This book covers recent results in the field of rechargeable sensor networks, including technologies and protocol designs to enable harvesting energy from alternative energy sources such as vibrations, temperature variations, wind, solar, and biochemical energy and passive human power.

Contents:

• Wind Energy Harvesting for Recharging Wireless Sensor Nodes: Brief Review and a Case Study (Yen Kheng Tan, Dibin Zhu and Steve Beeby)
• Rechargeable Sensor Networks with Magnetic Resonant Coupling (Liguang Xie, Yi Shi, Y Thomas Hou, Wenjing Lou, Hanif D Sherali and Huaibei Zhou)
• Cross-Layer Resource Allocation in Energy-Harvesting Sensor Networks (Zhoujia Mao, C Emre Koksal and Ness B Shroff)
• Energy-Harvesting Technique and Management for Wireless Sensor Networks (Jianhui Zhang and Xiangyang Li)
• Information Capacity of an AWGN Channel Powered by an Energy-Harvesting Source (R Rajesh, P K Deekshith and Vinod Sharma)
• Energy Harvesting in Wireless Sensor Networks (Nathalie Mitton and Riaan Wolhuter)
• Topology Control for Wireless Sensor Networks and Ad Hoc Networks (Sunil Jardosh)
• An Evolutionary Game Approach for Rechargeable Sensor Networks (Majed Haddad, Eitan Altman, Dieter Fiems and Julien Gaillard)
• Marine Sediment Energy Harvesting for Sustainable Underwater Sensor Networks (Baikun Li, Lei Wang and Jun-Hong Cui)
• Wireless Rechargeable Sensor Networks in the Smart Grid (Melike Erol-Kantarci and Hussein T Mouftah)
• Energy-Harvesting Methods for Medical Devices (Pedro Dinis Gaspar, Virginie Felizardo and Nuno M Garcia)

Readership: Graduates, researchers, and professionals studying/dealing with networking, computer engineering, parallel computing, and electrical & electronic engineering.

Chapter 1

Wind Energy Harvesting for Recharging Wireless Sensor Nodes: Brief Review and A Case Study

Yen Kheng Tan

Energy Research Institute @ Nanyang Technological
University (ERI@N), Singapore
[email protected],
[email protected]

Dibin Zhu and Steve Beeby

Electronics and Computer Science, University of Southampton,
United Kingdom

1. Introduction

With the recent advances in wireless communication technologies, sensors and actuators, and highly integrated microelectronics technologies, wireless sensor networks (WSNs) have gained worldwide attention by facilitating the monitoring and control of physical environments from remote locations, which can be difficult or dangerous to reach. WSNs represent a significant improvement over wired sensor networks with the elimination of the hardwired communication cables and associated installation and maintenance costs. The possible uses of WSNs for real-time information in all aspects of engineering systems are virtually endless, from intelligent building control to health-care systems, environmental control systems, and more. As electronic hardware circuitries become cheaper and smaller, more and more of these WSN applications are likely to emerge, particularly as these miniaturized wireless sensor nodes offer the opportunity for electronic systems to be embedded unobtrusively into everyday objects to attain a “deploy-and-forget” scenario.¹

The major hindrances of the “deploy-and-forget” nature of WSNs are their limited energy capacity and the unpredictable lifetime performance of the battery. To overcome these problems, energy harvesting (EH)/scavenging, which harvests/scavenges energy from a variety of ambient energy sources and converts it into electrical energy to recharge the batteries, has emerged as a promising technology.¹ With the significant advancement in microelectronics, the energy and therefore the power requirement for sensor nodes continues to decrease from a few milliwatts to a few tens of microwatts. This paves the way for a paradigm shift from the battery-operated conventional WSN, which solely relies on batteries, toward a truly self-autonomous and sustainable energy-harvesting wireless sensor network (EH-WSN). EH for powering wireless sensor nodes from ambient environment has drawn more and more attention over the last decade. Some possible energy sources from ambient environment include photonic energy,² thermal energy,³ vibration energy,⁴ and flow energy.⁵ For EH from the kinetic energy in flow of air (wind), existing methods include using turbines, harvesting energy from flow-induced vibration (FIV), and using Helmholtz resonators would be reviewed and elaborated with a case study.

2. Wind Energy Harvesting from Wind Turbines

2.1. Description of technique

A wind turbine is a device that converts wind energy into rotational mechanical energy. Electrical energy can be generated by employing transduction mechanism to exploit the mechanical energy. The first wind turbines for electricity generation had already been developed at the beginning of the 20th century and the technology improved incrementally since the early 1970s.

Wind turbines are classified into vertical and horizontal axis types. Horizontal axis wind turbines (HAWTs) have a horizontal shaft and blades (or sails) revolving in the vertical plane. The horizontal axis refers to the rotating shaft of the wind turbine, not the plane in which the blades rotate. The horizontal axis machine has its main shaft parallel to the ground. Figure 1 shows an example of the horizontal axis wind power generator.

Wind energy conversion systems can be divided into those which depend on aerodynamic drag and those which depend on aerodynamic lift. The early vertical axis windmills utilized the drag principle. Drag devices, however, have a very low maximum energy conversion efficiency of around 0.16.

The simplest vertical axis machine is a Savonious rotor, which consists of two oil-drum halves facing in opposite directions. They are extremely easy to construct and work by drag which makes them quite inefficient; a Savonious can manage to utilize only 10% of the wind energy. A more efficient vertical axis machine is the Darrieus rotor, which operates by lift forces. Its two blades are aerofoil in shape and so are more efficient than the Savonious, and the rotor can turn quite fast. The only problem with the Darrieus is that it is not self-starting and needs a small drag rotor on top. The advantage of all vertical axis machines is that they can turn on wind coming from any direction. So, unlike the horizontal axis machines, they do not have to face up or downwind in order to rotate. Since the end of the 1980s, however, the research and development of vertical axis wind turbines (VAWTs) has almost stopped worldwide. The horizontal axis approach currently dominates wind turbine applications.

Fig. 1. A miniature wind power generator.

Modern wind turbines are predominantly based on the aerodynamic lift. Lift devices use aerofoils to interact with the incoming wind. The force resulting from the aerofoils’ body intercepting the air does not only consist of a drag force component in direction of the flow but also of a force component that is perpendicular to the drag — the lift forces. The lift force is a multiple of the drag force and therefore the relevant driving power of the rotor. By definition, it is perpendicular to the direction of the airflow that is intercepted by the rotor blade, and via the leverage of the rotor, it causes the necessary driving torque. More details are illustrated in Ref. 1.

2.1.1. Savonius wind turbine

Savonius wind turbines are a type of VAWT, used for converting the power of the wind into torque on a rotating shaft. They were invented by the Finnish engineer Sigurd Johannes Savonius in 1922. Savonius turbines are a relatively simple form of turbine. Aerodynamically, they are drag-type devices, consisting of two or three scoops as shown in Fig. 2.

Looking down on the rotor from above, a two-scoop machine has an “S”-shaped cross section. Because of the curvature, the scoops experience less drag when moving against the wind than when moving with the wind. The differential drag causes the Savonius turbine to spin. Savonius turbines extract much less of the wind’s power than other similarly-sized lift-type turbines. The efficiency of a Savonius turbine is only around 10–20%.

Fig. 2. Savonius turbine.

Fig. 3. Darrieus turbine.

2.1.2. Darrieus wind turbine

This type of turbine is another example of VAWT. The turbine consists of a number of aerofoils vertically mounted on a rotating shaft or framework as shown in Fig. 3. This type of wind turbine was patented by Georges Jean Marie Darrieus in 1931. They are sometimes referred to as “eggbeater” turbines, owing to their shape. The major drawback of a VAWT is the inefficiency of dragging each blade back through the wind on each half rotation. They do not self-start and need a manual push or some other, more elaborate starter mechanism. The efficiency is about the same as the Savonius type (sometimes slightly higher, depending on the exact nature of the design).

2.1.3. Maximum available power

The maximum mechanical power that can be extracted by a wind turbine is given by⁷:

Fig. 4. An example of turbine output power (Source: Ref. 8).

where P_t is the power, ρ is the air density, r is the length of the turbine blade, and υ is the wind speed. c_p is the power coefficient which is a function of tip speed to wind speed ratio, λ, and blade pitch angle, β. The power is proportional to square the length of the turbine blade and cube the wind speed, which means that maximum available power can reduce significantly if the turbine is scaled down or works at lower wind speeds.

In order to achieve maximum power, the tip speed to wind speed ratio should be kept at the optimal value for all wind speeds. Figure 4 shows an example of turbine output power versus the turbine rotational speed for different wind speeds.

2.1.4. Efficiency

The power efficiency of the rotor is the fraction of the total power available which the blades are able to convert. The theoretical maximum is 0.59. This is known as the Betz limit. However, many textbooks do not mention that Betz did not consider the impact of unavoidable swirl losses. For turbines with a high tip speed ratio, X>3, and optimum blade...

Table of contents

• Cover
• HalfTitle Page
• Title Page
• Copyright Page
• Contents
• Preface
• 1. Wind Energy Harvesting for Recharging Wireless Sensor Nodes: Brief Review and A Case Study
• 2. Rechargeable Sensor Networks with Magnetic Resonant Coupling
• 3. Cross-Layer Resource Allocation in Energy-Harvesting Sensor Networks
• 4. Energy-Harvesting Technique and Management for Wireless Sensor Networks
• 5. Information Capacity of an AWGN Channel Powered by an Energy-Harvesting Source
• 6. Energy Harvesting in Wireless Sensor Networks
• 7. Topology Control for Wireless Sensor Networks and Ad Hoc Networks
• 8. An Evolutionary Game Approach for Rechargeable Sensor Networks
• 9. Marine Sediment Energy Harvesting for Sustainable Underwater Sensor Networks
• 10. Wireless Rechargeable Sensor Networks in the Smart Grid
• 11. Energy-Harvesting Methods for Medical Devices
• Index