Research map / Probabilistic and scientific modeling / Bayesian optimization
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use GP-MD to account for movement costs, rather than movement-cost-agnostic CGP-LCB | Contextual Bayesian optimization · Synthetic functions, movement cost at least as important as service cost (ρ = 0.5 or 1.0) | total cost | Helped |
| Account for movement costs with GP-MD instead of using CGP-LCB | AWE altitude optimization · Wind data at European locations; varying ρ | total energy generated | Helped |
| Account for movement costs with GP-MD instead of using CGP-LCB | AWE altitude optimization · AWE altitude optimization, ρ = 4 | total energy generated | Helped |
| Use GP-MD rather than movement-cost-agnostic CGP-LCB | Contextual Bayesian optimization · Synthetic functions, movement cost dominates | movement cost | Helped |
| Use GP-MD rather than CGP-LCB as service cost becomes dominant | Contextual Bayesian optimization · Synthetic functions, ρ = 2.0 | total cost | Mixed |
| Increase the service-cost weight ρ, shifting emphasis away from movement cost | AWE altitude optimization · AWE altitude optimization, increasing ρ | total energy generated | Mixed |
| Use GP-MD rather than the stationary strategy | AWE altitude optimization · AWE altitude optimization, ρ = 4 | total energy generated | Helped |
| Use GP-MD rather than the stationary strategy | AWE altitude optimization · AWE altitude optimization, ρ = 4 | service cost | Helped |
| Update confidence bounds after every timestep instead of less frequently (ablation) | GP-MD · Experiments | performance | Helped |
| Use ρ = 1 rather than ρ = 4, increasing the relative importance of movement-cost reduction | GP-MD · AWE altitude optimization | movement cost | Helped |
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