Smart Energy Grid

Residential setting: CIVIS

Most of the research in this field we conducted for smart grid in residential setting as part of CIVIS project. The main aim of CIVIS was to develop a social energy app to change energy practices in homes towards more sustainable.

Learning from others

First, we have performed a large literature review, in order to understand what has worked and what did not in the energy interventions conducted so far:

Lean, iterative and innovative approach

Alongside, we created mock-ups and conducted user studies in several of the partner universities, in the process of iterative, user-centered app design.

Originally, the name for the app was EnergyUp. At a later stage, we selected YouPower as a more appropriate name.

What we did at Aalto as part of CIVIS

The user study and the startup/innovation project we did at Aalto are described under YouPower on this website.

How we designed the CIVIS app in the end

There is also an external, CIVIS project link for the YouPower app.

The publication about the design:

Yilin Huang, Hanna Hasselqvist, Giacomo Poderi, Sanja Scepanovic, Filip Kis, Cristian Bogdan, Martijn Warnier and Frances M. T. Brazier, YouPower: An Open Source Platform for Community-Oriented Smart Grid User Engagement, in: Proceedings of the 14th IEEE International Conference on Networking, Sensing and Control, pages -, IEEEE, 2017.

 


Industrial setting: Green Big Data

During my visit at CERN, we also worked towards improving energy efficiency, but this time of a data centre. We received a dataset with energy consumption and computing statistics of a large computing centre: CSC — IT Center for Science. CSC provides computing services to the Finnish scientific community, but also to physicists from other countries, as it belongs to the Tier-2 of Worldwide LHC computing grid from CERN.

During this visit, I collaborated with:

We looked at the correlations between the application and system level logs and the energy consumption of the data centre. We clustered the computing nodes based on the vmstat and RAPL variables. Then we also showed that energy consumption on a node can be estimated from these variables.

Our results are accepted for Workshop on Energy-Aware High Performance Computing, EnA-HPC 2017.

Kashif Nizam Khan, Sanja Scepanovic, Tapio Niemi, Jukka K. Nurminen, Sebastian Von Alfthan, Olli-Pekka Lehto. “Analyzing the Power Consumption Behavior of a Large Scale Data Center“, Workshop on Energy-Aware High Performance Computing, EnA-HPC, June 2017.