Multi-stage stochastic programming for demand response optimization
Author(s)
Advisor
Date
2018-08Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
The increase in the energy consumption puts pressure on natural resources and
environment and results in a rise in the price of energy. This motivates residents
to schedule their energy consumption through demand response mechanism. We
propose a multi-stage stochastic programming model to schedule di erent kinds
of electrical appliances under uncertain weather conditions and availability of
renewable energy. We incorporate appliances with internal batteries to better
utilize the renewable energy sources. Our aim is to minimize the electricity cost
and the residents' dissatisfaction. We use a scenario groupwise decomposition
approach to compute lower and upper bounds for instances with a large number of
scenarios. The results of our computational experiments show that the approach
is very e ective in nding high quality solutions in small computation times. We
provide insights about how optimization and renewable energy combined with
batteries for storage result in peak demand reduction, savings in electricity cost
and more pleasant schedules for residents with di erent levels of price sensitivity.
Keywords
Smart GridDemand Response
Multi-Stage Stochastic Programming
Scenario Groupwise Decomposition