Wind Power Forecasting Through Supervised Machine Learning Techniques

We will forecast the wind speed in long and short terms time horizons. We will use the supervised and unsupervised learning techniques through which we can forecast the wind power. For checking the performance of our model we will perform certain benchmark tests that may include;

Project Title

Wind Power Forecasting Through Supervised Machine Learning Techniques

Project Area of Specialization

Artificial Intelligence

Project Summary

We will forecast the wind speed in long and short terms time horizons. We will use the supervised and unsupervised learning techniques through which we can forecast the wind power. For checking the performance of our model we will perform certain benchmark tests that may include;

. Real time/historical data (a platform or site). 

. Collection of Algorithms and models

Project Objectives

The objectives of our project are,

• Analyzing current advancement in prediction techniques.
• Current advancement in the field of wind power and speed forecasting based on prediction models.
• To forecast the long term and short term time horizon wind speed by supervised and unsupervised Machine Learning Techniques (MLT).
• Applications of prediction models in renewable energy.

Project Implementation Method

We will arrange a proper computer setup for this project if needed. A personal computer or laptop can be helpful in this regard. We can also use Matlab software for simulation if required.

• Data collection from sites
• Different Spreadsheets used for the collection of data
• Hardware based forecasting for non-linear calculations
• Gpu based fast training models
• Gpu is used for batch processing array
• Short term , longterm forecasting

Benefits of the Project

Our Final Year Project will help in utilization of the following industrial/economical issues;

1:  Power production by renewable energy.

2: Shortage of power generation for short/long term by forecasting the wind speed through short and long terms in different time horizons.

3:  Enhancement in Wind power production.

4:  Estimation of future wind power production.

Technical Details of Final Deliverable

• Survey of forecasters
• Performance of forecasting models in renewable energy
• Plausable data sets for training ANNs
• Small Scale wind power plant for prototype
• Trained ANNs running on fast GPUs for real time forecasting

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Energy

Technologies

Artificial Intelligence(AI), Internet of Things (IoT), Big Data

Sustainable Development Goals

Affordable and Clean Energy, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com