Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
Wind energy is one of the most promising sources of renewable energy and has gained increasing attention. Nevertheless, as wind turbines age and approach the end of government subsidies, investors face growing exposure to the volatility of the electricity market, underscoring the need for strategic decisions on whether to continue operating, repower, or decommission these assets. Following Design Science Research, we propose a decision support system (DSS) that integrates various modeling and simulation processes to capture market uncertainties, including electricity price, remaining useful life of turbines, and associated costs. These uncertainties are addressed through real options valuation using Least-Squares Monte Carlo simulation to deliver investment strategies. The DSS is further evaluated in a case study of onshore wind turbine investments in Germany. Our results and findings demonstrate that the proposed DSS helps investors optimize investment timing and achieve higher investment returns.
Recommended Citation
Wang, Yifan; Kraschewski, Tobias; Heumann, Maximilian; and Breitner, Michael H., "Continued Operation or Repowering? A Financial Decision Support System for Onshore Wind Turbine Investments" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 3.
https://aisel.aisnet.org/hicss-58/da/energy/3
Continued Operation or Repowering? A Financial Decision Support System for Onshore Wind Turbine Investments
Hilton Waikoloa Village, Hawaii
Wind energy is one of the most promising sources of renewable energy and has gained increasing attention. Nevertheless, as wind turbines age and approach the end of government subsidies, investors face growing exposure to the volatility of the electricity market, underscoring the need for strategic decisions on whether to continue operating, repower, or decommission these assets. Following Design Science Research, we propose a decision support system (DSS) that integrates various modeling and simulation processes to capture market uncertainties, including electricity price, remaining useful life of turbines, and associated costs. These uncertainties are addressed through real options valuation using Least-Squares Monte Carlo simulation to deliver investment strategies. The DSS is further evaluated in a case study of onshore wind turbine investments in Germany. Our results and findings demonstrate that the proposed DSS helps investors optimize investment timing and achieve higher investment returns.
https://aisel.aisnet.org/hicss-58/da/energy/3