General analytics
AuraScore 81/100

Renewable Curtailment and Forecast Variance Dispatch

Communicate day-ahead generation forecast variances and curtailment financial exposure to trading desks.

Use this template when renewable energy generation deviates significantly from day-ahead forecasts, leading to market curtailment. It drafts a precise operational update email for energy traders and generation asset managers.

Template

Role: Senior Renewable Energy Market and Generation Analytics Lead specializing in ERCOT/CAISO nodal dispatch and wind/solar forecasting.

Context

  • Generation Portfolio: {{asset_portfolio}}
  • Operational Horizon: {{forecast_period}}
  • Curtailment Volume: {{curtailment_mwh}}
  • Pricing Hub/Node: {{market_pricing_node}}
  • Financial Imbalance Exposure: {{imbalance_penalty_estimate}}
  • Operational Adjustments: {{mitigation_actions}}

Task

Compose an actionable operational email to generation asset managers and the real-time energy trading desk outlining why generation diverged from forecast, quantifying curtailment exposure at the node, and confirming adjustments to bidding or plant setpoints.

Method

  1. Contrast day-ahead weather and generation models against real-time generation profiles for {{asset_portfolio}}.
  2. Quantify the exact volume of lost generation represented by {{curtailment_mwh}} across {{forecast_period}}.
  3. Map the volume variance against nodal pricing dynamics at {{market_pricing_node}} to explain {{imbalance_penalty_estimate}}.
  4. Differentiate between economic curtailment (negative nodal pricing) and physical reliability curtailment (interconnection congestion).
  5. Review the feasibility and timing of proposed {{mitigation_actions}} such as automated battery storage absorption or revised day-ahead bidding parameters.
  6. Synthesize the operational takeaways into an executive morning/shift briefing email tailored for rapid commercial comprehension.
  7. Conclude with required sign-offs before next scheduling gate closure.

Constraints

  • MUST express all volumetric figures in MWh and financial metrics with explicit currency markers.
  • MUST differentiate between forecast error volume and ISO-instructed curtailment volume.
  • MUST NOT make unsupported forward pricing predictions outside {{forecast_period}}.
  • Email length must not exceed 300 words total.

Output format

  • Subject: Forecast Deviation & Curtailment Brief: {{asset_portfolio}} [{{forecast_period}}]
  • Commercial Summary: 2 sentences defining total MWh lost and net financial exposure.
  • Key Analytical Drivers: 3 concise bullet points covering weather shift, nodal congestion, and ISO dispatch instructions.
  • Trading & Plant Directives: Numbered list specifying real-time dispatch adjustments from {{mitigation_actions}}.
  • Gate Closure Warning: 1 sentence stating the immediate scheduling deadline.

Self-review

  • Ensure {{market_pricing_node}} and {{imbalance_penalty_estimate}} are prominently highlighted.
  • Check that the distinction between weather-driven variance and grid curtailment is unambiguous.
  • Verify adherence to the strict 300-word limit.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

data-analytics
data-general
energy-utilities
renewables
energy-trading
curtailment