Adaptive Wind Capture Surface with Mechanical Inertia Storage

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Solution Overview

Problem

Current windmill-based electricity generators are static and unable to dynamically adjust their surface area to optimize wind capture, leading to inefficient electricity generation due to fixed dimensions based on expected wind flow, resulting in suboptimal energy production when wind conditions vary.

Innovation Solution

A self-adaptive wind generator system utilizing AI/ML to collect data from local sensors and online sources to dynamically expand or retract the wind capture surface and accumulate mechanical energy as inertia, which is then released when needed to optimize electricity generation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If windmills are designed with fixed dimensions based on expected wind flow, then the structure is simple and manufacturing is easier, but electricity generation becomes inefficient when wind conditions vary

Engineering Contradiction:
Improveease of manufactureVSAvoidelectricity generation efficiency
Core Design Contradiction:
Ease of manufactureVSProductivity

Solution Approach 1:

The patent applies the dynamics principle by making the wind capture surface movable and adjustable rather than fixed. The surface can expand or retract based on real-time wind conditions detected by sensors, allowing the windmill to optimize its capture area dynamically. This resolves the contradiction by enabling the system to adapt to varying wind flows, thereby maintaining high electricity generation efficiency without requiring overly complex manufacturing for multiple fixed-size configurations.

Inventive Principle:
Principle #15Dynamics

2Productivity

If the wind capture surface is made larger to capture more wind, then energy capture improves, but the device complexity and manufacturing difficulty increase

Engineering Contradiction:
Improvewind energy captureVSAvoiddevice complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent applies segmentation by dividing the wind capture surface into multiple independent segments or panels that can be individually adjusted. This allows the surface to be expanded or contracted in a modular fashion, reducing the overall device complexity compared to a single large movable surface. The segmented approach enables incremental adjustment and simplifies the mechanical structures required for each segment.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The dynamic adjustment capability allows the wind capture surface to be optimized for current wind conditions without permanently requiring the maximum possible size. The surface can be retracted when wind flow is low, effectively reducing the active capture area and associated structural complexity only when necessary, rather than always requiring the full complex structure.

Inventive Principle:
Principle #15Dynamics

3Productivity

If the windmill surface is made adjustable to adapt to wind flow, then electricity generation optimization improves, but the control system complexity increases

Engineering Contradiction:
Improveelectricity generation optimizationVSAvoidcontrol system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent implements feedback by using sensors to continuously monitor wind flow conditions and automatically adjusting the surface area accordingly. The control system receives feedback from the sensors about current wind conditions and makes real-time adjustments to the capture surface, creating a closed-loop system that optimizes electricity generation without requiring complex predictive modeling or manual intervention.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The windmill system performs self-adjustment based on sensor feedback, making the control process relatively simple. The system serves itself by automatically detecting wind conditions and adjusting its own surface area without requiring external control or complex decision-making algorithms, thereby reducing control system complexity while maintaining optimization capability.

Inventive Principle:
Principle #25Self-service

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

The system enhances wind energy capture and generation efficiency by adapting to varying wind conditions, ensuring consistent electricity production even in areas with limited wind flow by converting windmill rotation into mechanical inertia for later energy release.

Implementation Method 1

the dimensions of the surfaces capturing wind flow extend or retract dynamically and automatically depending on the flow of wind available

Methodology Applied
Scientific EffectAerodynamic force: Aerofoil

Implementation Method 2

accumulate the generated energy as mechanical inertia to be released at later stage

Methodology Applied
Scientific EffectMechanical inertia: Inertia

Implementation Method 3

a pressure valve, a set of springs or metal blades

Methodology Applied
Scientific EffectSpring energy storage: Spring

Implementation Method 4

electric generator based on a windmill

Methodology Applied
Scientific EffectElectromagnetic induction: Electromagnetic Induction

Data Source

PatentEP4343141A1Dynamic ai based self-adapting windmill generator
Publication Date: 2024.03.27 COSTA REQUENA JOSE
  • EP4343141A1 patent drawingFigure 1~4
  • EP4343141A1 patent drawingFigure 5
  • EP4343141A1 patent drawing

AI summary

This invention is related in general to an electric generator based on a windmill, and, in the mobile, dynamic, and self-adaptive surface of the wind generator based on Artificial Intelligence or Machine learning logic to optimize the generation of electricity based on the wind available at all times and accumulate the generated energy as mechanical inertia to be released at later stage. The dimensions of the surfaces capturing wind flow extend or retract dynamically and automatically depending on the flow of wind available at any given moment, which is detected by the same system of the mill to adapt to the wind flow present in each moment. The windmill will include a set of in-built local sensors such wind direction monitoring device, humidity, temperature and other parameters collected from online sources e.g. Public Internet or private data networks that obtain weather forecast information. The AI/ML module in the windmill will collect the parameters from the local sensors together with the information from online sources to predict wind flow and adapt the surface of the windmill for optimal wind capture and energy generation. The windmill rotation force will be used to generate electricity during the run time but the windmill will also translate the rotating force into pressure action over the mechanical module that will comprise a pressure valve, a set of springs or metal blades. This mechanical module will accumulate the rotating energy from the windmill into mechanical energy in form of compressed strings or void valve which will release their accumulated energy as inertia rotation movements into electricity generator when needed.