Model Access and Configuration for Photovoltaic Yield Rate Daily Reports

Photovoltaic yield rate daily report data comes primarily from local power station monitoring systems, regional grid dispatching platforms, and public

What this category’s data looks like

Photovoltaic yield rate daily report data comes primarily from local power station monitoring systems, regional grid dispatching platforms, and public meteorological data sources. Data is updated daily, with complete datasets for the prior calendar day generated on a T+1 basis. Each data entry uses a single power station as its sole dimension, in structured table format. Fields include power station unique ID, statistical date, total power generation, self-generated and self-consumed electricity, grid-connected exported power, grid-connected electricity price, subsidy standard, and operation and maintenance cost. All numerical fields use units of kilowatt-hour, yuan per kilowatt-hour, or yuan per kilowatt.

Constraints for model access and configuration

The daily batch data nature of photovoltaic yield rate daily reports requires the model access link to support structured batch data import, to avoid the inefficiency of single-item processing. The presence of multiple fields with clear units requires configuring a data preprocessing link to perform unit validation and format alignment for numerical fields, preventing semantic confusion. The T+1 update cycle requires binding a daily scheduled trigger task that matches the business data production timeline. The requirement for complete fields in single power station data requires configuring missing value detection logic, to avoid yield rate calculation deviations caused by missing partial fields. Additionally, the broadcast and document distribution scenario requires preconfiguring format parameters for the corresponding processing links.

Configuration Settings

Configuration ItemRecommended ValueRationale
PARSE_STRUCTURED_FIELD_MAPPINGMap to 电站ID,统计日期,总发电量,自发自用电量,上网电量,上网电价,补贴标准,运维成本Match the standard business fields of photovoltaic yield rate daily reports, to ensure the model can accurately recognize business semantics
DATA_IMPORT_SCHEDULE0 1 2 * * ? (triggered at 2 AM daily)Match the T+1 production cycle of photovoltaic daily reports, to avoid triggering tasks before data is ready
MODEL_INPUT_MAX_LENGTH800–1200 charactersThe character volume of single power station data in photovoltaic daily reports falls within this range, to avoid field loss caused by truncation
LOCAL_MODEL_PATH/data/fastgpt/models/qwq-32b (private deployment scenario)Match the storage path of the locally deployed QWQ-32B model, to ensure the model call link works properly
TTS_AUDIO_FORMATmp3Adapt to the universal audio format of most broadcast scenarios, to reduce cross-platform compatibility costs
DOC_EXPORT_TYPEmarkdownSupport quick generation of distributable yield rate daily report documents, to adapt to subsequent broadcast or archiving needs

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Configuration Errors

  • The locally deployed QWQ-32B model does not respond after uploading attachments in the chat window, with no effect on simple applications or workflow applications. The cause is incorrect configuration of the LOCAL_MODEL_PATH parameter, or file permission settings that prevent FastGPT from reading model weights.
  • The yield rate broadcast content output by the model does not include correct unit information, leading to ambiguity in the broadcast content. The cause is failure to configure the PARSE_STRUCTURED_FIELD_MAPPING parameter, meaning fields and units are not mapped and bound, so the model cannot recognize the business meaning corresponding to numerical values.
  • The scheduled photovoltaic yield rate daily report generation task returns a 504 Gateway Timeout error. The cause is that the trigger time set in DATA_IMPORT_SCHEDULE is earlier than the actual production time of photovoltaic data, resulting in unavailable data during model calls.

How to Verify Proper Configuration

  • Upload a single standard structured file of a photovoltaic yield rate daily report, and confirm that the field mapping configuration fully matches the business fields, with no omissions or mismatches.
  • Manually trigger a scheduled import task, and review the task execution log to confirm there are no records of field format errors, missing data, or call timeouts.
  • Call the configured local model, upload test photovoltaic data attachments, and confirm that the model can parse data normally and output yield rate analysis content that conforms to business logic.
  • Configure the TTS model and generate a test broadcast segment, and confirm that the output audio format and parameters meet the preset requirements.

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.