Currently, I am involved in the NSON-DK project, in the workpackage responsible for developing the market and regulatory framework for a North Sea grid 100% wind power grid. Fulfilling my tasks involves:

• Game-theoretic analysis of transmission expansion in the North Sea and the Baltic region.
• Data-driven modelling and simulation of energy systems based on equilibrium programming, stochastic optimisation and mechanism design.


    The NSON-DK project is the Danish part of a North Sea Offshore Network (NSON) project. Its main objective is to study how the future massive offshore wind power and the associated offshore grid development will affect the Danish power system on short term, medium term and long term towards a future sustainable energy system. Specifically, the project addresses:

    • How will the offshore wind power development affect the variability and uncertainty of variable renewable generation in the Danish power system and neighboring systems?
    • How will this increased variability and uncertainty from the offshore wind power development together with onshore renewable generation development influence the balancing and need for reserves in the Danish power system?
    • How will the offshore wind power and offshore grid development influence the electricity markets in future systems with large scale energy storage and coordination of the electricity system with other energy systems (mainly heat and transport)?
    • How will the scale and architecture of the offshore grid development influence the adequacy and security of supply in the Danish power system?
    • Which policy instruments should be applied to support an effective and cost-efficient transition of the Danish power system combining the offshore development with energy storage and coordination between energy systems?


    • Technical University of Denmark, Dept. of Wind Energy
    • Technical University of Denmark, Dept. of Management Engineering
    • Ea Energy Analyses

In my post-doc in Department of Electrical Engineering in DTU (5s – Future Electricity Markets) I focused on the design of Electricity Markets embedding the uncertain nature of renewable energy supply and consumption into the core of the market mechanism. My tasks in connection to the project included:

• Research in efficient market designs for power systems with high shares of renewable sources of energy based on generation forecasts. Forecasting and verification.
• Development of trading strategies combining financial instruments and the wholesale market using stochastic optimisation and historic data.

  • Future Electricity Markets

    5s (FEMs) is a project funded by the Danish Strategic Research Council, focusing on electricity markets dominated by renewable sources of energy (above 50% stake). The proposed markets are expected to optimally deal with the dynamics and uncertainties of renewable energy generation, as well as with dynamic and flexible offers on the demand side. It is the core objective of the ‘5s’ project to forge the scientific and technical core for such future electricity markets to become a reality. In that objective, the ‘5s’ project will propose new market mechanisms in an advanced optimization framework, from the base methodological developments to the practicalities of their implementation requiring a parallel computing environment.


    • Technical University of Denmark
    • University of Copenhagen
    • Copenhagen Business School
    • Norwegian University of Science and Technology
    • Dansk Energi

    Keywords: Electricity Markers, Renewable Energy Sources, Stochastic Optimisation, Market Coupling, Uncertainty Modelling


In my post-doc in CBS and KU (CFEM project) I focused in  merging information elicitation mechanisms with supply allocation auctions. This led to the development of allocation auctions where the supplied quality was uncertain and the agents had to estimate it, and report it to an auctioneer which in turn had to make a decision based on these estimates. Specifically, my tasks in connection to the project included:

• Design of multi-attribute auctions focusing on buyers with limited access to own preferences.
• Research in optimal auction design and efficient procurement under uncertainty.
• AI based assessment and evaluation in project procurement designing auctions incorporating benchmarking methods e.g. Data Envelopment Analysis (DEA).
• Development of a simulation framework for the evaluation of multi-attribute auctions.

  • Center for Research in the Foundations of Electronic Markets

    CFEM is a research center supported by the Danish Council for Strategic Research, committed to combining and advancing state-of-the-art of Computer Science and Economics.  The expected results will be used to design, analyse and implement new efficient and secure solutions for any type of electronic trading. This includes auctions, procurement, market regulation, cost allocation and new emerging types of markets on the Internet. Special focus will be given in emerging applications such as computational advertising, on-line distributed systems, information and prediction markets


    • Aarhus University
    • Copenhagen Business School
    • University of Copenhagen
    • The Alexandra Institute
    • Patricia Market Design
    • Danish Competition and Consumer Authority
    • Trade Extensions
    • Inno:vasion
    • DONG

    Keywords: Cryptography, Algorithmics, Complexity, Game Theory, Mechanism Design, Operations Research.


During my PhD in University of Southampton (MBC project) I focused on networks where intelligent and selfish agents generate costly observations modelled as probabilistic estimates. I developed a series of auction based mechanisms which through strictly proper scoring rules incentivise agents to allocate sufficient resources in generating accurate and precise estimates.

  • Market Based Control of Complex Computational Systems

    This EPSRC funded project (in the Novel Computation call) intends to apply market-based paradigms to the design, control and evolution of complex distributed computational systems in order to attain highly efficient resource allocations in dynamic and uncertain environments. The targeted applications include resource allocation in utility data centres, decentralised control of content delivery and multiple robotic systems. It is a collaboration between several leading UK universities, specialised in economic mechanism design, multi-agent systems and evolutionary computation.

    Duration: 1st January 2005 to 31st December 2009


    • University of Southampton
    • University of Liverpool
    • University of Birmingham
    • Hewlett Packard Research Labs
    • BAE Systems
    • BT Research Labs

    Keywords: Agent Based Computing, E-Business Technologies, Decentralised Information Systems, Artificial Intelligence