Wind Turbine Layout Optimization with Axial Induction Dispatching

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Solution Overview

Problem

Existing wind turbine layout optimization methods for wind farms primarily focus on individual turbine maximum power generation without considering farm-level dispatching strategies, leading to suboptimal efficiency and increased wake effects, which affect overall wind farm power production and cost.

Innovation Solution

A wind turbine layout optimization method that integrates a dispatching strategy during the design stage, using a two-step optimization process involving a greedy algorithm and particle swarm optimization to optimize the number and placement of wind turbines, considering farm-level capacity maximization and safe distances, to reduce wake effects and energy costs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Power

If traditional individual turbine maximum power generation strategy is used in layout optimization, then each turbine can achieve maximum power generation, but the overall wind farm power production is suboptimal due to wake effects

Engineering Contradiction:

Improveindividual turbine power generationVSAvoidoverall wind farm power production

Core Design Contradiction:

PowerVSProductivity

Solution Approach 1:

The patent applies dynamic dispatching strategy where the axial induction factor of each turbine is adjusted in real-time based on wind conditions and turbine positions. This dynamic adjustment allows the system to optimize the balance between individual turbine performance and overall farm productivity, resolving the contradiction by making the control parameters adaptive rather than static

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes the control parameter from fixed maximum power point tracking to variable axial induction factor control. By optimizing the axial induction factor as a adjustable parameter in the layout optimization process, the system can reduce wake effects while maintaining acceptable individual turbine performance, thereby improving overall wind farm power production

Inventive Principle:

Principle #35Parameter changes

2Productivity

If farm-level dispatching strategy is integrated into layout optimization, then overall wind farm power production is improved, but the optimization problem becomes more complex

Engineering Contradiction:

Improvewind farm power productionVSAvoidoptimization problem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the optimization problem into two parts: layout configuration optimization and dispatching strategy optimization. The layout optimization determines turbine positions and numbers, while the dispatching strategy optimizes axial induction factors. This segmentation allows each sub-problem to be solved independently, reducing the overall complexity while achieving integrated optimization results

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary layout optimization to determine optimal turbine positions and numbers before implementing the dispatching strategy. This preliminary action establishes a good foundation for the subsequent dispatching optimization, reducing the search space and computational complexity of the overall problem

Inventive Principle:

Principle #10Preliminary action

3Quantity of substance

If more wind turbines are installed to increase capacity, then energy production increases, but wake effects between turbines increase and reduce efficiency

Engineering Contradiction:

Improvenumber of wind turbinesVSAvoidwake effect

Core Design Contradiction:

Quantity of substanceVSObject-affected harmful factors

Solution Approach 1:

The patent applies local quality optimization by adjusting the axial induction factor of each individual turbine based on its specific position and local wake conditions. Instead of uniform control, each turbine operates with optimized local parameters that account for its unique environment, allowing higher turbine density while minimizing local wake effects

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent converts the harmful wake effect into a beneficial control parameter by using axial induction factor adjustment. By intentionally controlling the wake characteristics through axial induction factor optimization, the system can manage wake effects constructively, allowing higher turbine installation density while maintaining overall efficiency

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Data Source

PatentUS11669663B2Wind turbine layout optimization method combining with dispatching strategy for wind farm

Publication Date: 2023.06.06 ZHEJIANG UNIV

AI summary

Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.