Table 1 Overview of advantages and disadvantages of common optimization methods under uncertainty for renewable energy systems.
From: Optimizing upside variability and antifragility in renewable energy system design
Method | Advantages | Disadvantages |
|---|---|---|
Considers entire variability of uncertain inputs | Requires a lot of data or assumptions on inputs | |
Considers multiple scenarios which allows for flexibility | Large number of scenarios is computationally expensive | |
Performs well under expected conditions | Complex algorithm | |
Requires minimal data (only worst-case scenario) | Does not capture full range of uncertainties | |
Easier to implement and interpret | Assumes that worst-case scenario can be predicted | |
Solution that performs well under any scenario | Overconservative | |
Considers entire variability of uncertain inputs | Requires a lot of data or assumptions on inputs | |
Robust design is least-sensitive to uncertain environment | Computationally expensive | |
Provides trade-off between robustness and performance | Robust design is often overconservative |
