Team: Dr. Selva Nadarajah, Satender Gunwal
Overview
The Solar Deployment Accelerator creates computational tools for optimizing solar panel placement and predicting energy output in urban environments. As cities push toward carbon neutrality, efficient placement of distributed solar resources is critical to maximizing energy generation while minimizing costs and visual impact.
Approach
We integrate GIS data, 3D building models, and satellite imagery with mixed-integer optimization models to determine optimal rooftop and ground-mount solar configurations. Our real options framework values the flexibility embedded in phased deployment strategies, helping municipalities and developers make investment decisions under uncertainty about future energy prices and policy changes.
Impact
The tool has been used to plan solar deployments for three mid-size U.S. cities, identifying configurations that increase expected energy yield by 15-22% over standard heuristic approaches while reducing payback periods by an average of 2.3 years.
Related Publications
Physical vs. virtual corporate power purchase agreements: Meeting renewable targets amid demand and price uncertainty
D. Mohseni Taheri, S. Nadarajah, and A. Trivella
European Journal of Operational Research
Hierarchical planning for hydropower capacity upgrade: Exploiting structure in reoptimization and investment policies
A. Kleiven, S. Nadarajah, and S.E. Fleten
Working Paper
Comparison of least squares Monte Carlo methods with applications to energy real options
S. Nadarajah and N. Secomandi
European Journal of Operational Research
Merchant energy trading in a network
S. Nadarajah, F. Margot, and N. Secomandi
Operations Research