Photovoltaic Power Prediction Using Extraterrestrial Solar Radiation
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Solution Overview
Problem
Existing photovoltaic power generation prediction methods require detailed information about panel efficiency and installation site, which is often unavailable, leading to inaccurate predictions due to singular relationships between weather phenomena and power generation amounts, especially when local weather changes occur.
Innovation Solution
A photovoltaic power generation amount prediction device that calculates predicted power generation amounts using extraterrestrial solar radiation and actual weather records, deriving a prediction formula without requiring detailed panel or installation site information, by classifying similar weather days and using past actual weather records and power generation amounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional power generation amount prediction methods are used (multiplying solar radiation by panel efficiency coefficients), then prediction can be performed with available weather data, but prediction accuracy deteriorates when detailed panel information (efficiency, azimuth, inclination) is unavailable or when local weather changes occur
Solution Approach 1:
The patent creates a virtual model (power generation amount prediction formula) that replicates the relationship between weather conditions and power generation output based on historical data. This virtual copy allows accurate prediction without requiring physical access to or detailed knowledge of the actual panel specifications, effectively copying the system's behavior patterns rather than its physical characteristics.
Solution Approach 2:
The patent transforms the prediction approach by changing from using fixed panel parameters (efficiency, azimuth, inclination) to using dynamic weather parameters and historical power generation data. The prediction formula uses variables such as solar radiation amount, weather conditions, and temporal patterns rather than static panel specifications, allowing the system to adapt to varying conditions without requiring detailed panel information.
2Measurement precision
If prediction methods using detailed panel information are employed, then theoretical prediction accuracy can be maximized, but device complexity and data acquisition difficulty increase
Solution Approach 1:
The system performs self-characterization by automatically learning its own power generation characteristics through historical data analysis. Rather than requiring external input of panel specifications, the system observes its own past performance under various weather conditions and derives its unique prediction formula, effectively serving itself in terms of parameter acquisition and model development.
Solution Approach 2:
The patent implements a preliminary data collection and model derivation phase where historical power generation data and weather data are gathered and analyzed before actual prediction operations begin. This preliminary action creates a customized prediction formula specific to each system's location and characteristics, so that subsequent predictions can be performed quickly and accurately without complex real-time calculations or detailed panel information.
3Ease of operation
If conventional prediction formulas based on meteorologic phenomena are used, then prediction can be performed without detailed panel data, but responsiveness to local weather changes and seasonal variations deteriorates
Solution Approach 1:
The patent applies local quality by creating a customized prediction formula for each specific installation location and system configuration. Rather than using a generic meteorological model, the system learns the local relationship between weather patterns and power generation output at that specific site, capturing local characteristics such as microclimate effects, surrounding terrain, and system-specific performance patterns that generic models cannot account for.
Data Source
AI summary
An actual power generation amount receiver acquires an actual power generation amount of a photovoltaic power generation system of each time slot of each day. An extraterrestrial solar radiation calculator calculates an extraterrestrial solar radiation of each time slot of each day at a disposition position. A weather information receiver acquires an actual weather record of each time slot of each day and a weather forecast of a prediction target time slot. A similar date extractor classifies a time slot, which is the same as a prediction target time slot of each day in a search range in which an actual power generation amount is acquired, as a similar time slot for each actual weather record type. A prediction formula deriver derives a power generation amount prediction formula for calculating a predicted power generation amount based on an actual power generation amount.