Wind Farm Wake Loss Quantification via Turbine Data
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Solution Overview
Problem
Wind farms experience sub-optimal performance due to wake effects from upwind turbines, leading to significant energy capture losses that are difficult to quantify accurately, affecting the overall power output and longevity of downwind turbines.
Innovation Solution
A method and system for determining wind farm wake losses by collecting turbine-level data, estimating freestream power output, and measuring actual farm-level power output, allowing for the calculation of wake losses without additional remote sensors, and enabling verification of energy production increases from upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If independent optimization of wind turbines is implemented to maximize local energy output, then individual turbine efficiency is improved, but overall wind farm performance deteriorates due to wake effects
Solution Approach 1:
The patent changes the operational parameters of wind turbines by adjusting rotor speed, pitch angle, and torque based on wake conditions detected by LIDAR. This allows turbines to adapt their operating points to minimize wake impacts and optimize overall farm productivity while maintaining individual turbine efficiency.
Solution Approach 2:
The system implements feedback control by using LIDAR to continuously measure wind conditions and wake effects, then feeding this information back to the turbine control systems. This enables real-time adjustments to turbine operation to balance individual efficiency with farm-level performance optimization.
2Measurement precision
If wake loss quantification is performed using traditional methods with remote sensors, then measurement capability is improved, but system complexity and cost increase
Solution Approach 1:
The patent enables wind turbines to perform their own wake loss measurement and characterization using their existing LIDAR systems and operational data. Each turbine serves itself by collecting and analyzing data about its own performance and the wakes it experiences, eliminating the need for separate remote sensing infrastructure.
Solution Approach 2:
The system makes the LIDAR and control systems already present on wind turbines multi-functional by using them not only for standard operational control but also for wake loss quantification and characterization. This universal use of existing components avoids additional hardware complexity.
3Measurement precision
If more sensors and measurement equipment are deployed to accurately quantify wake losses, then measurement precision is improved, but installation cost and maintenance complexity increase
Solution Approach 1:
The patent leverages the self-diagnostic and measurement capabilities already built into modern wind turbines through their LIDAR and SCADA systems. The turbines automatically collect and process the data needed for wake loss quantification without requiring external measurement equipment, thereby avoiding additional installation and maintenance costs.
Solution Approach 2:
The system replaces physical remote sensing equipment with computational methods that use existing turbine operational data and LIDAR measurements. By substituting mechanical/sensor-based measurement systems with data-processing-based approaches, the patent eliminates the need for additional hardware installation and maintenance.
Data Source
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AI summary
The present disclosure is directed to a system and method 100 for determining wake losses of a wind farm 200. The wind farm 200 includes a plurality of wind turbines 202. The method 100 includes operating the wind farm 200 in a first operational mode 102. Another step includes collecting 104 turbine-level data from at least one upstream wind turbines 202 in the wind farm 200 during the first operational mode. The method 100 also includes estimating 106 a freestream farm-level power output for the wind farm 200 during first operational mode based, at least in part, on the collected turbine-level data. A further step 108 includes measuring an actual farm-level power output for the wind farm 200 for the first operational mode. Thus, the method 100 also includes determining 110 the wake losses of the wind farm 200 for the first operational mode as a function of the measured actual farm-level power output and the estimated freestream farm-level power output.