What the data for this category looks like
Wind power yield-related data primarily comes from wind farm SCADA collection systems, regional power trading platforms, and meteorological monitoring platforms. There are two update schedules:
- Daily market data updates full previous-day data every early morning.
- Real-time intraday operating data is pushed every 15 minutes.
Documents use structured table format. Each row corresponds to a single wind turbine or a single wind farm project. Included fields are project code, wind turbine serial number, daily grid-connected power, grid-connected settlement electricity price, daily operation and maintenance expenditure, daily subsidy income, daily total revenue, and cumulative revenue.
Units follow these rules: power is measured in kilowatt-hours, electricity price in yuan per kilowatt-hour, and all types of revenue, expenditure and income in yuan.
Constraints on Multi-turn Dialogue and Prompt Engineering
The multi-source and dispersed nature of wind power data requires multi-turn dialogue to gradually guide users to clarify query scope, to avoid confusing data from single wind turbines and entire wind farms.
The update schedules for different time dimensions require prompts to fix time parameters, to prevent time range shifts across multi-turn conversations.
The structured format with multiple fields requires prompts to explicitly specify returned fields and their corresponding units, to avoid returning redundant content or content that does not meet industry specifications.
At the same time, multi-turn dialogue must retain key context such as project codes and dates specified by users. This ensures subsequent queries can proceed based on confirmed information without repeated inquiries about basic parameters.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 2000–3000 characters | Wind power data has many fields. This interval retains key information such as project IDs and time ranges from multi-turn dialogue, balancing context completeness and model input limits. |
CHAT_FILE_EXPIRE_TIME | 7 days (default), adjustable to 30 days as needed | Daily data for wind power projects is suitable for weekly analysis scenarios. The 7-day default value meets conventional needs. The 30-day configuration supports multi-turn dialogue for monthly review. |
recall count | Top 6–8 entries | Wind power yield queries need to cover core fields such as power, electricity price, and expenditure. This value covers core information without increasing context burden. |
similarity threshold | 0.75–0.85 | Wind power data field names follow unified industry specifications. This threshold filters irrelevant power data from other categories while retaining matching detailed project information. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Wind power historical data files usually contain long-term operating data for multiple wind turbines, with long parsing time. This duration meets the needs of large file parsing. |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: After consecutive multi-turn queries for wind power yields of different dates, returned results confuse project IDs and time ranges. Cause: Context-bound project code parameters are not fixed in prompts, leading to loss of confirmed basic information across cross-turn queries.
- Phenomenon: When multiple AI dialogue tasks with different functions are inserted into a batch execution node, task results have data crossover. Cause: Independent context storage identifiers are not configured for each dialogue node, leading to multiple tasks sharing context and data interfering with each other.
- Phenomenon: Dialogue logs cannot distinguish wind power query requests from different users. Cause: User identifier transparent transmission configuration is not enabled, and unique user identifier fields are not carried in requests, leading to logs being unable to associate corresponding query subjects.
How to Verify Configurations Are Correct
- A single-turn dialogue is initiated to inquire about the daily yield of a specified wind farm. Confirm whether the returned result includes the specified project ID, date and corresponding fields. Adjust configurations if units or fields are missing.
- A file containing 7 days of wind power historical data is uploaded, and 3 consecutive yield queries for different dates are initiated. Confirm that each round of results is based on the specified parameters of the current context, with no information confusion.
- A batch execution task is configured, and 2 AI dialogue nodes with different functions are inserted. After execution, confirm that the returned results of each group of tasks are independent, with no data crossover or parameter confusion.
- The dialogue log list is reviewed. Confirm that each log carries a unique user identifier, which can be used to distinguish query requests from different users.
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.