Photovoltaic Module Shadowing Detection from Power Curve Deviations
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Solution Overview
Problem
Existing methods fail to reliably recognize and assess shadowing events affecting photovoltaic modules, which impact their electric power output, as they cannot differentiate between shadowing and other environmental disturbances.
Innovation Solution
A method that records and analyzes electric power data to define an ideal power course based on peak values from cloudless days, calculates an expected power value for each sun position, and determines shadowing probability by comparing actual power to the ideal course, without requiring additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing methods are used to monitor photovoltaic module power output, then power production data can be recorded, but shadowing events cannot be reliably recognized or differentiated from other environmental disturbances
Solution Approach 1:
The system performs preliminary actions by collecting power production data over multiple previous days and fitting an ideal power course curve before comparing it with actual present day data. This preliminary curve fitting enables the system to establish a baseline for detecting shadowing events, resolving the contradiction by preparing the reference framework in advance rather than attempting real-time differentiation without context
Solution Approach 2:
The system implements feedback by continuously comparing actual power output against the fitted ideal power course and calculating shadowing probabilities. The comparison results feed back into the assessment process, allowing the system to reliably identify shadowing events by measuring deviations from the expected power curve, thus improving both reliability and precision simultaneously
2Measurement precision
If additional sensors are installed to detect shadowing events, then detection precision improves, but device complexity and cost increase
Solution Approach 1:
The system applies self-service by using its own existing power production measurements to detect shadowing events. Instead of requiring external sensors, the method processes the electrical power data already being collected for energy production monitoring, thereby improving detection precision without adding device complexity or additional hardware components
Solution Approach 2:
The system achieves multi-functionality by enabling the power measurement device to serve dual purposes: monitoring energy production for billing purposes and detecting shadowing events for system optimization. This universal approach allows one device to perform multiple functions, eliminating the need for separate shadowing detection sensors and reducing overall system complexity
3Loss of energy
If shadowing events are not assessed, then system operation continues unchanged, but energy losses from shadowing obstacles are not quantified or addressed
Solution Approach 1:
The system uses feedback by calculating shadowing probabilities based on deviations from the ideal power course and providing this information back to operators. This feedback loop quantifies energy losses by comparing actual versus expected power output and communicates the shadowing event information, enabling informed decisions about removing obstacles without losing critical performance data
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate recognition and assessment of shadowing events, enabling quantification of energy losses and informing decisions on removing obstacles, thereby optimizing photovoltaic module performance.
Implementation Method 1
a photovoltaic module (1) whose electric power is recorded
Data Source
AI summary
For recognizing shadowing events affecting a photovoltaic module, electric power produced by the module is recorded. For each position of the sun on a present day an expected value of the electric power is defined. Further, an ideal power course of the electric power over the present day is determined by fitting a curve that corresponds to cloudless sun without shadow casting obstacles to peak values of the electric power recorded for same positions of the sun during a plurality of previous days. For all positions of the sun at which the electric power produced on the present day falls short of the ideal power course a shadowing probability of not less than zero is defined whose magnitude depends on the level of accord of the electric power produced on the present day with the expected value at the position of the sun.