PhD thesis: SmartSense: Indirect Monitoring in Self-Powered Wireless Sensor Networks for Smart Grid and Building Automation

PhD thesis subject

SmartSense: Indirect Monitoring in Self-Powered Wireless Sensor Networks for Smart Grid and Building Automation

Keywords: wireless sensor networks, smart monitoring, energy harvesting, power management, energy reduction, smart grid, smart building

IRISA/INRIA – équipe-projet CAIRN (Lannion) http://www.irisa.fr/cairn

Contacts: Olivier Sentieys

 

Context

Natural resource preservation has recently become a significant concern and has therefore motivated many research and development efforts for energy consumption management in buildings and homes. Efficiently reducing energy consumption at home, work or in a factory, could be afforded by mixing different technologies to not only reduce the energy consumed by consumers, but also to adapt (manage) the energy consumed to the energy that is produced. SMART 2020 [1] outlined the opportunity to capture savings of both energy and Greenhouse Gas (GHG) emissions in 2020, through a range of actions developed by the Information and Communications Technologies (ICT) sector. Smart Grid, Smart Buildings, and Green ICT have the main impact on energy savings.

At the energy production side, the electrical grid infrastructure is comprised of three elements: power generation, transmission, and distribution. Electrical power generation consists mainly of the power plants but also includes more and more renewable sources such as wind power or solar panels on energy farms or locally on top of buildings. The cost of energy storage is very high, and hence the current practice is to match energy consumption closely with energy generation, which is more and more fluctuating: challenges could be seen as being able to use energy when the wind blows or the sun shines, and also to avoid the strong power consumption peaks due to people’s life. A typical example at home could be to automatically use the dryer when energy is available and therefore cheap, and is now well defined as Smart Grid technologies.

At the energy consumption side, the main objective is of course to reduce energy consumption of the different subsystems. Interior lighting, office equipment, heating, cooling, and ventilation make up of more than 85% of the total electricity use [2][3] and the reduction effort should therefore be concentrated on these systems. For energy management and reduction in homes or building a key enabler is the use of wireless sensor networks to monitor the environment (temperature, activity of people, power consumption of equipment, light, etc.) and to act on subsystems (decrease room temperature, stop or start an equipment, adjust cooling or ventilation, etc.). This is the emerging field of Smart Building Automation.

The recurrent theme in all the applications for monitoring our close environment is that we need many miniaturised and affordable sensing systems that can be self-sustaining over long periods of time (with no battery changing and using energy harvesting from the environment) to allow for proper wireless communication in a self-configuring manner. Ease and cost position of deployment are decisive in order to make such devices usable in our daily lives. Despite some isolated attempts to create these useful functionalities, such systems, or even first steps toward them, are unavailable today. Solutions have appeared in the sensor domain, but the systems never became a reality since the energy and communication issues were not yet solved.

 

Subject

The objectives of the thesis are twofold. A first objective is to propose power management techniques to reduce the energy of a sensor network node relying on energy harvesting (in-door light, heat, vibration). A power manager embedded in energy harvesting WSN nodes adapts the power consumption and computation loads according to the harvested energy to obtain a theoretically infinite lifetime. The main advantage of using energy harvesting (EH) in the context of building and home monitoring is to avoid battery replacement and therefore to reduce installation and maintenance costs of the system. The second objective is strongly linked to the usage of these WSN nodes in the context of smart monitoring of energy consumption and environment (temperature, activity, light). We will propose new Indirect Power Monitoring techniques which enable to estimate energy consumed in a building or in a home without effectively measuring the power consumed. A typical AC smart meter [6] is costly equipment and we therefore want to propose cheap and non-invasive sensor nodes. As an example, to estimate the power consumed by the TV, it is not necessary to measure precisely the current it consumed, but a simple sensor able to recognize that TV is on or off can do the same job with a far less complexity [7]. Another example is the development and deployment of room occupancy and people activity sensors [5] that can lead to significant reduction of the energy by regulating HVAC (Heating, Ventilation and Air-Conditioning) or by switching lights and office equipment [4].

As a summary, the thesis will propose disruptive techniques for autonomous smart meters:

  • new algorithms for indirect power monitoring,
  • a flexible autonomous sensor node including energy harvesting from various energy sources,
  • new power management techniques to adapt dynamically processing to available energy and potential future energy scavenging from environment.

These techniques and algorithms will be implemented in a real prototype relying on our current activities in wireless sensor networks [8] [9] and deployed in a real building.

References

[1] http://www.smart2020.org/

[2] Y. Agarwal et al., Understanding the Role of Buildings in a Smart Microgrid, IEEE/ACM Conference on Design Automation and Test in Europe (DATE), March 2011.

[3] Itron Inc. California Commerical End-Use Survey. http://capabilities.itron.com/ceusweb

[4] Y. Agarwal et al., Somniloquy: Augmenting Network Interfaces to Reduce PC Energy Usage, USENIX Symposium on Networked Systems Design and Implementation (NSDI ), April 2009.

[5] Y. Agarwal et al., Occupancy-Driven Energy Management for Smart Building Automation, ACM BuildSys, November 2010.

[6] X. Jiang, S. Dawson-Haggerty, P. Dutta and D. Culler, “Design and Implementation of a High-Fidelity AC Metering Network, Information Processing in Sensor Networks, 2009.

[7] Y. Kim et al., “ViridiScope: Design and Implementation of a FineGrained Power Monitoring System for Homes”, Proc. 11th Intl. Conf. on Ubiquitous Computing, 2009.

[8] M. A. Pasha, S. Derrien and O. Sentieys, A Complete Design-Flow for the Generation of Ultra Low-Power WSN Node Architectures Based on Micro-Tasking, Proc. of the IEEE/ACM Design Automation Conference (DAC,) Anaheim, CA, USA, June 2010.

[9] M. Alam, O. Berder, D. Menard, T. Anger, O. Sentieys, A Hybrid Model for Accurate Energy Analysis of WSN Nodes, Journal of Embedded Systems, 2011.

[10] Welcome to Bretagne, SMARTGRID Project, Bretagne Développement, January 2012.

This entry was posted in Uncategorized. Bookmark the permalink.