Meteodyn Forecast

Meteodyn Forecast is a wind power production forecasting service coupled with a web application for monitoring and visualizing the generated data. Our tool combines meteorological forecasts with machine learning to provide accurate and reliable power production forecasts.

Wind Power Production Forecast Service

The application automatically provides you with power production forecasts for your wind farms from very short-term (10 minutes) to medium-term (several months), with a delivery frequency ranging from once per day to four times per hour.

Accurate wind power forecasts are crucial to maintaining the balance between power consumption and production, thereby reducing penalties and operating costs. Energy price forecasting becomes more accurate, simplifying negotiations and resulting in more affordable costs for the end consumer.

Meteodyn has over 20 years of experience and research in wind engineering and meteorology. 

Accurate and reliable forecasts for operating or start-up wind farms

location

The forecast data provided by Meteodyn Forecast

– Wind power forecast for the entire wind farm:

  • Very short-term: minutes, hours.
  • Short-term: days, weeks.
  • Mid-term: months, seasons.

– Wind speed and direction.

– Production probability distribution (P10, P25, etc.).

location

Accurate wind power forecasts for operating wind farms.

Training with our artificial neural network requires at least:

  • One year of wind power production data,
  • One year of historical weather forecast data.

The system then provides the upcoming production using the meteorological forecasts.

 

location

Wind power forecasts for start-up wind farms

Our wind power forecasts are also available for wind farms in the start-up phase with little or no production history.

For these wind farms, we leverage our expertise by modeling your wind farm and its topography in our Computational Fluid Dynamics (CFD) software, Meteodyn WT.

We integrate wind data from your measurement mast into it to generate the production histories required for learning.
Then, the artificial neural network delivers the upcoming production of your wind farm using weather forecasts.

These results increase visibility during the start-up phase.

To increase accuracy, we periodically conduct a re-learning session using actual production data from your wind farm.

location

Information Required for Forecasting

1. The necessary horizon:

  • Very short-term,
  • Short-term,
  • Mid-term.

2. The expected delivery frequency

3. The desired forecast time step

4. The wind farm characteristics

5. Historical production data of the wind farm (except for start-up wind farms)

6. Delivery format and support

Strengths

Reliable weather forecasts

Our meteorological variables’ forecasts are produced using leading numerical weather prediction models. They are then transposed to the desired location at turbine hub height.

For greater accuracy, we can perform a micro-scale transposition using our Meteodyn WT software.

The power of artificial intelligence (AI) for machine learning

Thanks to our self-learning artificial neural network, the software autonomously adapts its way of considering input data.

The more data analyzed, the more accurate it becomes – a critical strategy for accurate energy production forecasting.

High availability of deliveries

The frequency of power forecast deliveries ranges from once per day to 4 times per hour.

Forecasts are provided with a few minutes time step, allowing you to interact with your customers and partners in real time.

Options

Performance Report

In addition to this wind power forecast service, we can provide you with performance reports on our forecasts using our Meteodyn WPA software.

Testimonials

Since December 2009, Meteodyn provides technical services on the definition of wind farm and the solar power plant, and module of short-term & ultra-short-term forecasting system, with the forecasting data. Zhao Fang Meteorology provides customer services, final power prediction system and the in-situ implementation services, according to IEC standards, the grid interconnected system and the equipments, etc.

As of June 2021, power prediction is realized on 129 wind farms power stations, and customers’ technical need and power grid requirements are completely satisfied.

Wenming GUO, General Manager, Zhao Fang Meteorology, China

Working at Meteodyn

Explore new career opportunities by reviewing our job openings.