Evaluation of hedging strategies for electricity procurement risks of a power-to-methanol plant with stochastic modeling: A case study of Denmark
Year: 2025
Type: article
Abstract: Power-to-X (PtX) technology is a key pillar of decarbonization of hard-to-abate sectors. However, producing sustainable fuels through PtX technologies is accompanied by complex challenges. For instance, fueling chemical processes with intermittent renewable energy presents new challenges. Relying on a single renewable energy plant to supply the energy demand of a PtX process, such as e-methanol or e-ammonia production, is hardly feasible. Utilizing the power grid as a backup in countries with a high share of renewables in the power mix, such as Denmark, is a cost-effective option, particularly compared to battery energy storage. However, the price volatility of the power market can add more risks and complexity to the operation of PtX systems. This paper evaluates different risk hedging strategies for the power procurement of the world's first large-scale commercial power-to-methanol plant in southern Denmark. The importance of using the stochastic model to determine the volume and price of methanol for a long-term purchase agreement is also investigated. Results show that a stochastic model can reduce estimation errors with historical data and lead to a more reliable decision. This study also highlights the effectiveness of using hedging tools in risk mitigation and enhancing price competitiveness, as results show a remarkable reduction in Conditional Value at Risk (88 %) and cost of methanol production (13 %) by incorporating diverse power derivatives in an optimal portfolio for power procurement.
Authors: Nafiseh Mirzakhani, Ali Khosravi, Bernd Möller
Institutions: University of Southern Denmark, Europa-Universität Flensburg
Language: English
Subfield: Energy Engineering and Power Technology
Field: Energy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,730
Funder: Villum Fonden
Award: G6979644980
OpenAlex ID: W4410724574
