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
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  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  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.
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  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 . Another example is the development and deployment of room occupancy and people activity sensors  that can lead to significant reduction of the energy by regulating HVAC (Heating, Ventilation and Air-Conditioning) or by switching lights and office equipment .
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   and deployed in a real building.
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