Public defence in Electrical Power and Energy Engineering, M.Sc. Ramin Ahmadi Kordkheili

The thesis performed operation-planning studies to maximize the profit of wind farm business considering different energy markets as well as storage and Power-to-X facilities.
Public defence from the Aalto University School of Electrical Engineering, Department of Electrical Engineering and Automation
Doctoral hat floating above a speaker's podium with a microphone

The title of the thesis: Multi-Alternative Operation-Planning Study to Maximize the Profit of Wind Farm Business: Multi-Sector Market Assessment of a Nordic Case

Doctoral student: Ramin Ahmadi Kordkheili
Opponent: Prof. Behnam Mohammadi-Ivatloo, LUT University, Finland
Custos: Prof. Edris Pouresmaeil, Aalto University School of Electrical Engineering, Department of Electrical Engineering and Automation

The concerns over harmful impact of fossil fuels on the environment has led to increasing the share of renewable energies in the electricity generation. Wind farms as renewable sources of energy are replacing such fuels. These producers are considered more environmentally friendly; however, their generation levels are uncertain. This is because wind power production depends on the weather, particularly wind speed, which increases the challenges of integrating wind power into the electricity grid. In the past, wind farms were largely supported by subsidies, through which wind power production was purchased under fixed-price contracts. However, with the growth in wind farms’ share of total electricity generation, these subsidies are decreasing. Therefore, wind farm operators must compete with other conventional producers in the market. Nonetheless, considering the stochastic nature of wind power production, such a situation represents a major challenge for wind farm operators. This is due to the dispatchable nature of conventional producers, which constitutes a considerable advantage. The day-ahead electricity market usually closes hours before the actual delivery of electricity. Consequently, wind farm producers participate in the electricity market with only predictions of their wind power production and thus are likely to face deviations between the amount they are required to deliver to the market and their actual wind power production at time of delivery. To help wind power operators manage the stochasticity in wind power production, this thesis pursues two main aims. The first is to study different markets—the day-ahead electricity market, balancing electricity market, gas market, heat market, and green hydrogen market—as possible platforms for wind farm operators to trade energy. The second aim is to investigate the potential of different facilities to increase the profit of wind farm owners. These facilities include electrical energy storage, gas storage, and different Power-to-X facilities. Such facilities provide wind farm operators with the flexibility to turn wind power into gas, heat, and green hydrogen. The results of the thesis provide a roadmap/look-up table for wind farm owners in their investment and operation decisions.

Keywords: Balancing electricity market, bi-level programming, conditional value at risk, Day-ahead electricity market, electrical energy storage, electrolyzer, gas storage, green hydrogen market, gas market, heat market, Power-to-X, stochastic optimization, wind farm.

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