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질문 1 의 8
Why evaluate an energy model under outages and weather extremes?
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- Why evaluate an energy model under outages and weather extremes?
- Rare conditions can affect whether predictions or actions remain safe and useful
- They always appear equally in training data
- Extreme cases are irrelevant to grid operations
- A model can only use historical averages
- A storage controller lowers simulated cost but violates a reserve requirement. What is the issue?
- The simulation proves the controller is safe
- The optimization objective missed a real operating constraint
- Reserve requirements apply only to forecasting
- Lower cost always means better grid performance
- Which operating decision needs a different horizon than day-ahead forecasting?
- A yearly equipment inventory
- A static document search
- Real-time balancing
- A one-time model card review
- How should AI’s energy effect be reported?
- Count only the energy savings
- Assume model serving uses no energy
- Compare different periods without stating them
- Measure the computation’s electricity use and any downstream savings at a defined boundary
- What should an operator do when a forecast is uncertain or outside trained conditions?
- Use the defined escalation or operating procedure rather than treating the forecast as certain
- Follow it because optimization is automatic
- Disable every safety rule
- Assume the input is typical
- Why version weather data and operating policies with the model?
- They improve numerical precision automatically
- They affect inputs and decision behavior and help reconstruct an operational result
- They replace monitoring
- They have no influence after training
- A demand model performs well on average but misses a rare outage scenario. What does the average conceal?
- A guaranteed reduction in electricity use
- That the model has no input drift
- An important low-frequency failure condition
- The operating boundary is irrelevant
- Which comparison can support a claim that an AI optimization saves energy?
- Compare the model’s training time with a utility bill
- Report only the best day
- Use a simulation without stating assumptions
- Measure computation and operating effects over the same boundary and period