Photovoltaic Degradation Forecasting via Satellite Irradiance Simulation
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Solution Overview
Problem
Current methods for forecasting photovoltaic power generation system degradation are costly, inexact, and challenging due to year-to-year weather variability and data collection issues, making it difficult to accurately predict long-term degradation and requiring expensive on-site tests.
Innovation Solution
A digital computer-based system that infers photovoltaic system configuration specifications through historical production data and solar resource data, simulates power production, and adjusts for errors to forecast long-term degradation, using a normalized solar power simulation model and statistical methods to derive degradation over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct power measurements are collected from individual photovoltaic systems at fine-grained time intervals, then high resolution power output time series data can be generated, but transmission bandwidth and storage space requirements become insurmountable as fleet size grows
Solution Approach 1:
The patent extracts only the essential information needed for degradation forecasting rather than collecting complete high-resolution power output data from all systems. By using satellite-derived solar irradiance data and system configuration specifications, the method obtains sufficient input data without the burden of collecting, transmitting, and storing large volumes of actual power measurements from each photovoltaic system.
Solution Approach 2:
The patent creates a virtual model of photovoltaic system performance by simulating power output based on satellite irradiance data and system specifications, rather than relying on physical measurements from each system. This digital copy allows degradation analysis without requiring actual high-resolution power data collection infrastructure.
2Measurement precision
If photovoltaic system degradation is assessed through on-site tests and direct measurement comparison, then degradation can be detected, but the process becomes costly and challenging due to weather variability and data collection issues
Solution Approach 1:
The patent uses satellite-derived solar irradiance data that serves multiple purposes: it provides the solar resource input for simulating expected power output, enables degradation analysis across the entire photovoltaic fleet uniformly, and eliminates the need for location-specific measurement infrastructure. This universal data source simplifies the degradation assessment process while maintaining consistency across diverse geographic locations and weather conditions.
Solution Approach 2:
The patent introduces a simulation model as an intermediary between satellite irradiance data and degradation assessment. Rather than directly comparing measured power outputs affected by weather variability, the model translates irradiance data into expected power production, which then serves as the baseline for detecting degradation. This intermediary layer isolates the degradation signal from weather-related fluctuations.
3Productivity
If high speed data collection and analysis is implemented for large photovoltaic fleets, then real-time power output monitoring is achieved, but processing resources and computational costs become prohibitive
Solution Approach 1:
The patent performs preliminary calculations by using pre-acquired satellite irradiance data and system configuration specifications to simulate expected power output before actual power measurements are needed. This advance preparation creates a baseline for degradation analysis without requiring real-time processing of actual power data, significantly reducing computational resource requirements while maintaining forecasting capability.
Data Source
AI summary
Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data to determine the degree of error between simulated and measured production. The simulated production is adjusted to account for the error and to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.