What This Category's Data Looks Like
Ledger data for new energy development comes from multiple channels: project management systems, on-site construction logs, equipment monitoring platforms, government grid connection approval receipts, and other sources. Data update frequency changes with the project phase: updated monthly during project preparation, weekly during construction and installation, and daily after grid connection and operation. Document structure includes two types: structured ledger tables and unstructured acceptance reports. Core fields include project ID, installed capacity (unit: MW), grid connection time, monthly power generation (unit: MWh), and equipment operation and maintenance duration (unit: hours). Some ledgers also include specialized fields such as equipment model and supplier information.
What Constraints Do These Characteristics Impose on Workflow Orchestration?
Multi-source heterogeneous data sources require workflows to support pulling data in different formats. This avoids data format compatibility issues. Differentiated update frequencies require workflows to use pull cycles configured by project phase. A uniform fixed interval cannot be used. Core fields have specific unit requirements. Workflows must include built-in unit verification logic. This prevents errors such as mixing MW and kW, or inconsistent power generation units. Cross-ledger association needs require workflows to include links that match equipment, construction, and power generation data using project ID. This ensures the accuracy of aggregated data associations.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Data source pull cycle | Set by project phase: 7 days per pull during preparation, 3 days per pull during construction, 1 day per pull during operation | Matches the phased update rhythm of new energy development ledgers |
| Field verification rules | Verify installed capacity unit is MW and power generation unit is MWh; filter entries with missing project ID | Matches standard field and unit requirements for new energy industry ledgers |
| Abnormal data interception threshold | Filter records with power generation below 0; filter entries with operation and maintenance duration exceeding equipment rated lifespan | Prevents invalid data from entering subsequent summary links |
| Association matching node | Associate equipment ledger, construction log, and power generation data using project ID | Addresses association constraints of multi-source ledger data |
| Variable configuration | Use variables to store project-specific ID rules and statistical cycle parameters | Adapts to personalized configuration needs of different new energy projects |
| Node timeout setting | 600 seconds | Handles scenarios with network delays during multi-source data pulling and large data volumes |
Three Common Mistakes
- Symptom: The workflow-generated report misses core fields, such as grid connection time or installed capacity. Cause: Core field mapping rules are not configured in
variables, leading to missing required ledger items during data pulling. - Symptom: Workflow run results for different new energy projects have inconsistent formats, with missing fields or unit confusion. Cause: Project-specific statistical rules are not configured using
variables. Generic configurations cannot adapt to differences in ledger structures across projects. - Symptom: Workflow runs timeout, and the interface shows node execution failure. Cause: No reasonable node timeout period is set, or the pull cycle does not match the actual update rhythm of the data source, leading to incomplete data pulling.
How to Confirm the Configuration Is Correct
- Manually trigger the workflow once. Check if pulled raw data includes core fields such as project ID and installed capacity, and if units meet new energy industry standard requirements.
- Simulate input of an abnormal data record, such as a record with -100 MWh of power generation. Confirm if the workflow automatically intercepts the entry and generates a corresponding prompt.
- Check project-specific parameters stored in
variables, such as statistical cycle and project ID prefix. Confirm they match the current project's actual rules. - Check if each node's timeout setting matches the data source's response duration. Avoid runtime timeout errors.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.