Robust Optimization Methods for Production and Capacity Planning of Solar Energy

Abstract

Industrialization and the rapid increase in population growth are uncontrollably increasing the energy demand. Solar energy is the most abundant and readily available renewable energy source. Efficient solar energy production and capacity planning is necessary to satisfy energy demand, specifically if demand is uncertain or exhibits extreme values unpredictably. Robust optimization deals with uncertainty by developing a model that accounts for all possible demand values, ensuring that storage and production decisions remain effective even when demand deviates from nominal values. This paper aims to minimize the production and storage costs while meeting the energy demand, using robust optimization methods to handle demand uncertainty. The results show that increasing the uncertainty parameter leads to more conservative and robust outcomes, and the model’s conservativeness can be tuned through the robustness multiplier parameter.

Date of Award	2025
Original language	American English
Supervisor	Adriana Gabor (Supervisor)