The Stockholm Royal Seaport (SRS) project, ongoing until 2030, aims to rebuild a part of Stockholm in Sweden into an urban smart grid testbed with 10,000 new homes and 30,000 new work spaces among other improvements. The SRS project is part of the Clinton Climate Initiative program, with ambitious goals for energy efficiency and environment conservation. In the SRS project different smart grid technologies and concepts, including renewable energy, battery, flexible demand response, smart home appliances, will be experimented and evaluated. In order to help household users to effectively take advantage of the new smart grid opportunities, automatic decision aiding systems are expected to play an important role in the SRS testbed.
In this undergraduate project the participants are invited to investigate and implement one of the decision aiding systems. In particular, the focus is to design an optimization based scheduling algorithm for the operation of smart home appliances. The schedules seek to operate the appliances in the most efficient manner, subject to requirements such as operational and user comfort constraints. The participants will need to study the scheduling scenarios and derive their own optimization models for the scheduling problem. Mixed integer linear programming will be the main tool for modelling the optimization problem. The optimization model obtained should be solvable by standard solvers such as CPLEX. The participants are expected to visualize the schedules and analyse their effect as part of the outcome of the project.
The participants are expected to be familiar with MATLAB and the basic concepts for optimization. More advanced optimization topics such as mixed integer linear program modelling are not necessary, as the participants will acquire them while working on the project.
Gruppstorlek 3-4 (inte mer än två grupper i projekt MVEX01-14-05 och MVE01-14-06 tillsammans)
Speciella förkunskapskrav Grundkurserna i matematik
Handledare Kin Cheong Sou, email@example.com
Examinator Maria Roginskaya
Institution Matematiska vetenskaper