Wind Turbine Layout Optimization with Multi-Objective Constraints
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Solution Overview
Problem
Current methods for optimizing wind turbine placement in wind power plants lack multi-disciplinary optimization capabilities that incorporate mechanical loads analysis, leading to inefficiencies in energy capture and operational costs.
Innovation Solution
A method that determines wind turbine locations within a wind power plant by evaluating site conditions, applying constraints, and adjusting layouts to meet multiple criteria including mechanical loads, noise, and financial metrics, using a computationally efficient platform for multi-disciplinary optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional single-objective optimization methods are used to maximize energy production, then energy capture is improved, but multi-disciplinary constraints such as mechanical loads, noise, and cost cannot be simultaneously optimized
Solution Approach 1:
The patent implements a multi-objective optimization framework that simultaneously evaluates multiple design criteria including energy production, mechanical loads, noise constraints, and cost metrics. The system integrates wind resource assessment, mechanical load analysis, noise modeling, and cost modeling into a unified optimization process that can handle multiple competing objectives and constraints, making the optimization system versatile across different design goals rather than limited to single-objective optimization.
2Adaptability or versatility
If manual trial and error methods are used to adjust turbine layout, then design flexibility is maintained, but optimization time and computational efficiency deteriorate
Solution Approach 1:
The patent employs an iterative optimization algorithm that automatically adjusts turbine layout based on feedback from multiple design criteria evaluations. The system evaluates plant design metrics including energy production, mechanical loads, noise, and cost, then uses this feedback to automatically refine the turbine placement. This automated feedback loop maintains design flexibility while dramatically reducing optimization time compared to manual trial and error methods.
3Manufacturing precision
If comprehensive multi-disciplinary analysis is performed including mechanical loads, noise, and cost, then design quality is improved, but computational complexity and resource requirements worsen
Solution Approach 1:
The patent divides the comprehensive multi-disciplinary analysis into separate modular analysis components: wind resource assessment, mechanical load analysis, noise modeling, and cost modeling. Each module independently evaluates its specific criteria and feeds results to the optimization framework. This segmentation maintains high design quality through comprehensive analysis while managing computational complexity through modular, organized processing of multiple design criteria.
Data Source
AI summary
A method for determining wind turbine location within a wind power plant based on at least one design criteria. A wind turbine layout including at least one wind turbine location is prepared and site conditions at each wind turbine location are determined. One or more plant design metrics are evaluated in response to the site conditions. The plant design metrics are analyzed in response to the site conditions. The method further includes applying constraints to the wind turbine layout and comparing the plant design metrics to the design criteria and constraints. Thereafter, the wind turbine locations are selectively adjusted within the layout in response to the comparing step until a stop criteria is reached.