What the data for this category looks like
Energy storage investment research data comes from public grid dispatch APIs, technical documents from energy storage equipment manufacturers, industry reports, and real-time data from regional power trading platforms. Update frequencies vary significantly: real-time operational data such as grid-connected power and SOC is updated every minute. Project feasibility study documents and policy files are updated quarterly or annually. Manufacturer technical white papers are updated irregularly alongside product iterations. Document structures fall into three categories: standardized equipment parameter tables, project investment calculation documents, and policy interpretation texts. Fields include quantifiable metrics with clear units, such as cell capacity, cycle life, installed capacity, and on-grid electricity prices.
What constraints do these characteristics impose on deployment and upgrade
The multi-source heterogeneous nature and varying update frequencies of energy storage investment research data create multiple constraints for deployment and upgrade workflows. Configure high-frequency synchronization tasks for minute-level real-time operational data to ensure data timeliness. Set scheduled pull rules for quarterly or annual report files. Quantifiable fields with clear units must retain their unit associations during parsing. This prevents loss of unit information after parsing, which would cause deviations in investment research conclusions. Set different parsing priorities for different document types. Prioritize completeness for operational data documents. Preserve original formatting for policy text files. When upgrading, retain existing real-time synchronization configurations. This prevents version updates from interrupting minute-level tasks and disrupting data continuity.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Feasibility study reports and equipment parameter tables in the energy storage industry are often lengthy. Some PDF documents exceed 100 pages, requiring a sufficient timeout to complete parsing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Multi-source data from energy storage projects includes batch operational log files. Individual files may exceed standard thresholds, requiring support for large-document uploads |
maxContext | 8000–12000 characters | Investment research scenarios require linking multiple sets of equipment parameters and project data. A longer context ensures coherence across cross-document associations |
Recall Count | Top 8–10 results | Energy storage investment research covers multidimensional data (equipment, policy, market). Too many recalled results increase latency, while too few fail to cover all relevant information |
Similarity Threshold | 0.75–0.85 | Quantifiable metrics in the energy storage industry have high similarity. A reasonable threshold is needed to filter low-correlation non-target data |
PARSE_SEGMENT_LENGTH | 1500–2000 characters | Energy storage equipment parameter tables contain long sequences of quantifiable fields. Segments that are too long reduce recall accuracy, while segments that are too short increase parsing overhead |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: After upgrading from version 4.8.4 to 4.9.6, real-time data synchronization tasks fail to start. Logs return
504 Gateway Timeout. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted before the upgrade to support parsing of large energy storage documents. The default parameter after upgrade cannot support parsing of long documents, causing synchronization tasks to time out and fail. - Issue: The knowledge base only supports single questions, and cannot handle contextual continuous follow-up questions. The result of the second question is unrelated to the previous conversation. Cause: The
maxContextparameter configuration was not updated during the version upgrade, or the parameter was reset to a low default value after the upgrade. This fails to support the contextual association requirements of multi-round investment research conversations. - Issue: Locally modified front-end page code fails to sync to the online deployment instance. The page does not change. Cause: No code mount mapping was configured for containerized deployment, or the deployment service was not restarted to load updated code files. The online instance still runs the initial image code.
How to Verify Successful Configuration
- Upload a typical energy storage industry document. Check that quantifiable fields in the parsing results retain their preset units to confirm parsing configuration is active.
- Trigger a scheduled synchronization task. Review task execution logs to confirm the synchronization frequency matches the preset rules. Verify that synchronization configurations were not reset during the upgrade.
- Launch two linked investment research questions. Confirm the system can reference previously mentioned equipment parameters or project data to verify contextual configuration is active.
- Check the code mount path of the deployment instance. Confirm locally modified files have been synced to the running directory to verify code update configuration is active.
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.