Analyzing Flexible Demand In Smart Grids

Thesis event information

Date and time of the thesis defence

Topic of the dissertation

Analyzing Flexible Demand In Smart Grids

Doctoral candidate

Master of Science Florian Kühnlenz

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Centre for Wireless Communications

Subject of study

Communications Engineering


Professor Peter D. Lund, Aalto University


Professor Ari Pouttu, Information Technology and Electrical Engineering

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Analyzing Flexible Demand In Smart Grids

The global energy system is undergoing a slow but massive change, initiated by environmental concerns but it is increasingly driven also by the zero-marginal cost of renewable energy. This change includes an increase in the effort to make the electric power system the main transport path for energy in the future. A massive research and development effort has henceforth been put into modernizing the electricity grid towards a so-called Smart Grid, by combining the power grid with communication networks and automation, as well as modernized market systems and structures. This work contributes to this process by introducing two unique models.

The first provides a tool for better understanding the impact of combined infrastructure networks with a simple yet complex model of a combined energy, communication and decision model. The second model provides a detailed agent-based environment of an electricity market, supporting various independent entities inside the market, as well as a high time resolution and the often-neglected aspect of coupled market stages. That is, all mis-predictions of the first market stage (day-ahead) have to be settled at the second (balancing) stage. Both models are then used to assess the problem of demand side management, in which the traditional practice of power production being adjusted to the demand is at least partially dropped and flexibility in the demand is used to match the supply – as such technologies are deemed crucial to integrate the unsteady supply from renewable resources, like wind and solar power.

We find that complicated scaling effects can be found even in the simplified model, hinting at insufficient consideration of the complexities involved in the real world. We then go to show such unfavorable scaling effects also exist in the current market environment as modeled in our second model. Finally, we show how to circumvent these problems within the current environment as well as introduce a framework to analyze cyber-physical systems and better handle their complexity.
Last updated: 1.3.2023