Photovoltaic MPP Tracking via Constrained Search Area
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Solution Overview
Problem
Photovoltaic generators face energy losses due to existing MPP tracking methods' inability to distinguish between local and global maxima, especially under partial shading conditions, leading to suboptimal operation and reduced energy yield.
Innovation Solution
A method that intelligently restricts the search area for the maximum power point by varying voltage or current within a defined search area, using multiple limiting conditions and search directions to efficiently locate the global maximum power point, thereby minimizing search duration and losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the search area is restricted to reduce energy losses, then energy efficiency improves, but the risk of missing the global maximum power point increases
Solution Approach 1:
The search area is segmented into multiple candidate regions based on historical MPP data and environmental conditions. Instead of searching the entire operating range, the algorithm divides the search space into plausible segments where the global MPP is most likely to be located, reducing the search area while maintaining reliability through targeted exploration of high-probability regions.
Solution Approach 2:
The system performs preliminary actions by pre-defining search boundaries and candidate regions before the actual MPP search begins. Historical operating data and environmental parameters are analyzed in advance to establish likely search zones, so that when the search executes, it is already constrained to the most relevant areas, reducing energy losses while ensuring the global MPP is not missed.
2Loss of energy
If the search duration is reduced to minimize energy losses, then energy efficiency improves, but the precision of locating the global maximum power point deteriorates
Solution Approach 1:
The algorithm performs partial action by conducting a focused search only in the most promising regions of the operating space rather than exhaustively searching all possible points. By concentrating search efforts on high-probability areas identified through historical data and environmental conditions, the system achieves sufficient precision for locating the global MPP while significantly reducing search duration and energy losses.
Solution Approach 2:
The system dynamically changes search parameters such as step size, search range, and evaluation criteria based on environmental conditions and historical performance data. Under favorable conditions with stable environmental parameters, the search can be more aggressive with larger steps and shorter duration. When conditions are variable or uncertain, the algorithm adjusts to finer resolution searches, optimizing the balance between search speed and precision adaptively.
3Reliability
If multiple search directions are implemented to ensure finding the global maximum, then reliability improves, but device complexity and search duration increase
Solution Approach 1:
The search algorithm dynamically adapts its behavior based on real-time feedback from the photovoltaic system performance and environmental conditions. Rather than rigidly executing multiple fixed search directions, the system adjusts search parameters, step sizes, and exploration strategies on-the-fly, allowing it to achieve reliable MPP location with adaptive complexity that responds to actual system conditions rather than predetermined complexity.
Solution Approach 2:
The system implements continuous feedback mechanisms where the results of initial search phases inform subsequent search directions and parameters. Power measurements, environmental sensor data, and historical performance information are fed back into the algorithm to refine the search strategy, allowing the system to achieve high reliability by concentrating efforts on the most promising search directions identified through feedback rather than uniformly exploring all directions.
Data Source
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Figure 3a~3b
AI summary
The method involves defining a starting point (4) with starting power with starting voltage and starting current. A maximum power point (MPP) is searched in a search direction (5) by repeatedly varying search voltage or search current in a search area under consideration of two limiting conditions for limiting the search area. The search is completed when one of the limiting conditions is fulfilled, and is taken place as left- and right-side searches. A maximum search voltage (20) and maximum search current (30) are provided during defining the search area at the starting point.