Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.

  

Price of privacy in smartgrid

Student(en):

Betreuer:

Christos Dimitrakakis, Maryam Kamgarpour
Beschreibung:

Introduction
    A premise of smartgird is a more secure and efficient power system. An enabling factor is real-time pricing, where the consumers adjust their consumption based on (near) real-time electricity prices. Since electricity prices reflect the balance of supply and demand, real-time pricing is hoped to help in stabilizing grid, while saving francs on consumers’ bills. In this project, we aim to design pricing and consumption mechanisms that ensure consumers' data remain private while achieving benefits of real-time pricing.

Project Description
    We consider a scenario in which an aggregation of consumers communicates with a central utility. Each individual consumer shares its real-time consumption patterns with the central utility. The central utility broadcasts the price of electricity in a given planning horizon, according to a price model. Within this setup we address the following questions. First, by observing the public variable, the price, what can an intruder learn about an individual consumer’s private data such as occupancy and sleep pattern, given partial information on patterns of consumption. Second, how can the central utility modify the pricing scheme to ensure the private data such as occupancy is preserved, while ensuring the benefits of real-time pricing. Depending on the progress, we address the question of how could individual consumers use thermal storage or batteries to hide their private data, such as occupancy patterns.

Required background
    courses in probability theory, linear dynamical systems, stochastic control, dynamic programming.

Acquired Skills
    application of probability theory, Markov chains, information theory and dynamical system theory to a relevant problem in smart grid.


Weitere Informationen
Professor:

Maryam Kamgarpour
Projektcharakteristik:

Typ:
Art der Arbeit: Masters/Semester
Voraussetzungen:
Anzahl StudentInnen:
Status: open
Projektstart:
Semester: