Queue density brief
Nearby queue depth, project mix, and interconnection risk memo.
Claude + ChatGPT prompt
Gridleaf dataset: Interconnection Queue Context Tool: gridleaf_queue_context Sources: ISO/RTO queue data, Gridleaf interconnection model Source readiness: On-demand queue context / Feasibility screening Query contract: - Title: Queue context query contract - Primary entity: Interconnection area - Time grain: Latest queue snapshot - Visualization mode: Queue depth + congestion signal - Inputs: location (geo, required) e.g. near Lubbock, TX; market (enum, optional) e.g. ERCOT; radius_miles (number, optional) e.g. 25 miles; technology (list, optional) e.g. solar, storage - Example queries: Show queue MW mix near Lubbock for solar and storage.; How crowded is the interconnection queue within 25 miles of this site? Analysis plan contract: - Version: gridleaf-analysis-plan.v2 - Dataset: Interconnection Queue Context (queue-context) - Tool: gridleaf_queue_context - Workflow: Queue density brief - Output: Queue depth + congestion signal - Result preview: Queue context result (Queue MW) - Query contract: Queue context query contract (Latest queue snapshot) - Metrics: Queue MW, Project count, Congestion signal, Technology mix - Sources: ISO/RTO queue data, Gridleaf interconnection model - Source readiness: On-demand queue context (Feasibility screening) - Source caveats: ISO/RTO queues can lag withdrawal and milestone changes.; Nearby queue density is not an interconnection capacity guarantee. - Source next actions: Refresh queue status before ranking competing projects.; Pair queue density with local substation and congestion evidence. - Steps: Measure queue depth -> Classify competing projects -> Draft interconnection risk memo Result preview contract: - Title: Queue context result - Chart: Queue MW mix - Primary metric: Queue MW - Fields: technology, queue_mw, project_count, congestion_signal - Example rows: Solar: 640 MW (Crowded); Storage: 520 MW (Watch); Hybrid: 310 MW (Moderate) Dataset insight packet: - Version: gridleaf-dataset-insight.v1 - Contract key: dataset_insight - Dataset: Interconnection Queue Context (queue-context) - Tool: gridleaf_queue_context - Workflow: Queue density brief - Visualization: Queue depth + congestion signal - Fields: technology, queue_mw, project_count, congestion_signal - Rows: Solar: 640 MW (Crowded); Storage: 520 MW (Watch); Hybrid: 310 MW (Moderate) - Source readiness: On-demand queue context (Feasibility screening) - Next queries: Show queue MW mix near Lubbock for solar and storage.; How crowded is the interconnection queue within 25 miles of this site?; How crowded is the queue near this site?; What project mix is competing for interconnection? For a solar or storage site near Lubbock, TX, summarize interconnection queue context, congestion signal, and the follow-up diligence questions for Claude. Return a concise analytical memo, call out source freshness and caveats, and suggest the next Gridleaf portal query. Analysis playbook: Queue density brief Outcome: Nearby queue depth, project mix, and interconnection risk memo. Workflow steps: 1. Measure queue depth 2. Classify competing projects 3. Draft interconnection risk memo Playbook prompt: Build an interconnection queue density brief. Summarize nearby queue MW, project mix, congestion signal, and the diligence questions to continue in Claude.