What this category's data looks like
Data sources for energy storage due diligence reports include energy storage power station SCADA systems, project approval documents, performance test reports from third-party testing institutions, and grid-connected operation logs from power grid dispatch. SCADA data updates every minute, project documents are archived once after project delivery, and grid-connected logs update monthly. Documents are mostly structured tables paired with paragraph descriptions, including fields such as power station ID, battery cell type, rated charge-discharge power, number of charge-discharge cycles, and grid-connected voltage level. The units of these fields are kW, times, kV, and hours respectively.
What constraints do these characteristics impose on the model access and configuration link
Configure a recall window adapted to short-period data during model access, to avoid recalling redundant information beyond the analysis period, to accommodate minute-level high-frequency updated data from SCADA systems. Configure parsing and mapping rules for structured data, to distinguish fields such as power station ID and power parameters from text descriptions, to handle multi-source documents that include structured tables and paragraph descriptions. Configure trigger strategies for incremental synchronization and full synchronization, to distinguish one-time archived project documents from real-time updated operation logs, to account for differences in update rhythms across different data sources. Configure unit verification rules in the data preprocessing link, to avoid model processing deviations caused by unit mismatches across data sources, to handle field units including standardized units such as kW, kV, and hours.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
embedding_model | text-embedding-3-large | Energy storage due diligence data includes structured parameters and long text descriptions. This model has stronger adaptability to semantic encoding of multi-type fields |
maxContext | 8000–12000 characters | Single energy storage power station due diligence documents have a relatively long average length. This range can cover complete context information for a single document |
UPLOAD_FILE_MAX_SIZE | 500 MB | Energy storage due diligence documents include multiple test reports and operation logs. The total upper limit for single-batch uploaded files needs to adapt to multi-document packaging scenarios |
PARSE_TABLE_ENABLE | Enabled | Energy storage due diligence documents contain a large number of structured table parameters. Enabling this setting can accurately extract field information such as battery cell power and grid-connected voltage |
recall_topk | Top 6–8 entries | Energy storage due diligence needs to balance recall coverage of multi-dimensional parameters. This range balances recall accuracy and context length |
data_sync_interval | 5 minutes | The minute-level update frequency of SCADA systems needs to adapt to the synchronization requirements of real-time operation data |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: When uploading infrared thermal imaging images of energy storage power stations, a token limit exceeded error is triggered, and some low-resolution images can be uploaded normally. Cause: The
IMAGE_TOKEN_LIMITparameter is not configured, or the parameter value does not adapt to the token consumption requirements of high-resolution images, causing the token usage of a single image to exceed the preset upper limit. - Phenomenon: When using a general embedding model to process energy storage due diligence documents, the matching accuracy of professional fields such as recalled battery cell power and grid-connected voltage is low. Cause: An embedding model adapted to structured professional data is not selected, and general models have insufficient semantic encoding effects for exclusive fields in the energy storage domain.
- Phenomenon: Real-time operation data of energy storage power stations updated by the SCADA system does not appear in the recall results of due diligence reports in a timely manner. Cause: The
data_sync_intervalparameter value is too large, which does not adapt to the minute-level real-time data update rhythm, causing synchronization delay to exceed analysis requirements.
How to confirm the configuration is complete
- Upload a copy of the energy storage due diligence document containing structured tables, and check whether the power station parameters in the parsing results are fully extracted, to confirm that the table parsing configuration meets requirements.
- Manually trigger a data synchronization, compare the updated document list after synchronization with the update records of the source system, to confirm that the synchronization interval configuration adapts to the data update rhythm.
- Initiate a knowledge base recall test, check whether the returned context content covers the core parameters of the target document, to confirm that the context window configuration meets analysis requirements.
- Upload a high-resolution energy storage detection image, check whether the upload and parsing processes proceed normally, to confirm that the image token limit configuration adapts to the image size.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.