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VERSION:2.0
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SUMMARY:Decision making under uncertainty in energy systems 
DTSTART:20150320T101500
DTSTAMP:20260509T161108Z
UID:027cc4948fb4320aa70a04a7c06cd5854fca74767747385304d2aecf
CATEGORIES:Conferences - Seminars
DESCRIPTION:Alessandra Parisio\nRobust and stochastic predictive approache
 s to energy management\nAbstract: The increase in energy use\, dominated b
 y the growth of the human population and the improvement in its lifestyle\
 , is expected to continue in the near future\, if no action is taken. Incr
 easing the energy efficiency and reducing the use of energy from non-renew
 able sources is thus a growing need. Achieving these targets requires effe
 ctive energy management systems that incorporate several sources of uncert
 ainty in the decision process (e.g.\, weather conditions\, user behavior\,
  renewable generation)\, and integrate different technologies and informat
 ion. Huge amounts of information can be integrated by means of ICT solutio
 ns and used to take decisions on different sectors\, such as buildings man
 agement. By doing so\, system operation can be optimized\, making sure tha
 t energy efficiency does not compromise the level of service. In this talk
 \, I will discuss possible robust and stochastic approaches to the design 
 of integrated optimization-based management systems for energy systems\, s
 uch as buildings and microgrids. The optimization model includes as many d
 etails as possible while taking the inherent system uncertainty into accou
 nt and still obtaining an optimization problem solvable by standard algori
 thms. The ultimate goal is a practical implementation of the developed alg
 orithms: experimental results provide insights into the performance of the
  proposed frameworks.\nBio: Alessandra Parisio received the PhD degree in 
 Computer Engineering from the University of Sannio\, Italy. As visiting Ph
 D student\, she was involved in the research project "Use of weather and o
 ccupancy forecasts for optimal building climate control (OptiControl)" at 
 the Swiss Federal Institute of Technology (ETH)\, Switzerland. She is curr
 ently a Post-Doctoral Fellow with the Automatic Control Laboratory\, Royal
  Institute of Technology (KTH)\, Sweden. Her research interests focus on t
 he areas of manufacturing system simulation and scheduling\, optimization 
 of energy systems and stochastic constrained control.
LOCATION:ME C2 405 http://plan.epfl.ch/?zoom=19&recenter_y=5864084.17342&r
 ecenter_x=730960.62257&layerNodes=fonds\,batiments\,labels\,information\,p
 arkings_publics\,arrets_metro\,transports_publics&floor=2&q=Me_c2%20405
STATUS:CONFIRMED
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