PV TOU Configuration Using NLP Input and Preset Modes
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Solution Overview
Problem
Users and technical personnel face challenges in accurately configuring the Time-of-Use (TOU) mode for PV power stations due to complex settings and varying parameters across countries and power companies, leading to a cumbersome process with high error rates and poor user experience.
Innovation Solution
An autonomous management method for PV TOU mode that includes setting up an interaction terminal with preset configuration modes, allowing users to input instructions through voice, text, or images, and utilizing natural language processing tools like ChatGPT to simplify the configuration process, including fully automatic, semi-automatic, and autonomous modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration of each time period is performed, then precise TOU mode settings can be achieved, but the configuration process becomes complex and time-consuming
Solution Approach 1:
The patent segments the configuration process into different modes (fully automatic, semi-automatic, and autonomous configuration modes) that can be selected based on user needs. This segmentation allows users to choose the appropriate level of manual intervention, balancing precision and time efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-setting configuration modes and parameters. The interaction terminal is pre-configured with multiple configuration modes and templates, allowing users to quickly select and apply pre-defined settings rather than manually configuring each parameter from scratch.
2Measurement precision
If detailed manual configuration is performed, then accurate TOU mode settings can be achieved, but the error rate increases due to complexity
Solution Approach 1:
The autonomous configuration mode enables the system to automatically analyze user input, extract key parameters, and generate configuration settings without manual intervention. This self-service approach eliminates human errors associated with manual configuration while maintaining high accuracy through automated parameter extraction and validation.
Solution Approach 2:
The system incorporates feedback mechanisms where user input is analyzed and processed to generate configuration settings, which can then be reviewed and adjusted. This feedback loop ensures accuracy by allowing users to verify automated settings before final implementation, reducing error rates.
3Ease of operation
If traditional configuration methods are used, then comprehensive control can be achieved, but user experience deteriorates due to cumbersome processes
Solution Approach 1:
The interaction terminal is designed with multi-functionality, supporting multiple configuration modes (fully automatic, semi-automatic, and autonomous) and accepting various input formats. This universal design allows different users with different skill levels and needs to use the system effectively, improving ease of operation while managing complexity through standardized interfaces.
Solution Approach 2:
The system changes parameters by offering different configuration modes that adjust the level of automation and user involvement. Users can select the appropriate configuration mode based on their needs, and the system automatically adjusts the complexity of the configuration process accordingly, simplifying the user experience while maintaining comprehensive control capabilities.
Data Source
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AI summary
Provided are an autonomous management method for a photovoltaic (PV) Time-of-Use (TOU) mode, a computing device, and a readable storage medium. The method includes the following processing steps: presetting a TOU data template and a plurality of configuration modes in an interaction terminal; inputting a mode selection instruction at the interaction terminal, and selecting a specific configuration mode according to the mode selection instruction; inputting a parameter configuration instruction that meets requirements of the selected configuration mode at the interaction terminal, analyzing and processing the parameter configuration instruction, and performing feature extraction on keywords in the parameter configuration instruction to form valid feature data; filling or modifying the TOU data template according to the valid feature data to form TOU configuration information data; and completing TOU configuration by issuing: sending the TOU configuration information data to a PV power station for TOU control. This application can reduce the technical threshold for operators in PV energy management, which not only improves user experience but also enables better management of PV power stations.