WindFor

Wind Power Forecasting

Introduction

WindFor™ (formerly known as WPPT) is a software solution for wind power forecasting. WindFor™ delivers highly accurate predictions of wind power production for the operational horizon (ranging from a few minutes ahead in time, up to a couple of weeks). WindFor™ is very flexible and has a long track record of producing accurate forecasts in almost any condition.

 

Why do you need WindFor™

Intermittent power production from renewables, like wind farms, has transformed the electricity sector in many countries. Wind power forecasting is a necessity in such markets in order to plan accurately and operate the power system efficiently. This applies to both commercial players in liberalized power markets and system operators who need to understand the impact of renewable energy production in their portfolio and on the electricity system as a whole.

Accurate wind power forecasting is needed by asset owners and electricity traders in order to nominate and trade the power production efficiently. By increasing forecast accuracy, asset owners and traders can reduce costs of imbalance fees and penalties.

Transmission system operators need accurate wind power forecasts to maintain system stability. Intermittent power production from wind power can cause system instability and increase the cost of balancing the electricity system (e.g. from standby capacity). In order to increase system stability, reduce cost and minimize curtailment of wind power, it is essential for the system operator to be able to plan and manage the total power production based on accurate wind power forecast.

The highly accurate wind power forecasts delivered by WindFor™ help asset owners, traders and system operators around the world to manage and optimize their portfolio every day.

 

Key benefits

  • Market leading wind power forecast accuracy
  • Long and proven operational track record of more than 15 years
  • Highly flexible and configurable to almost any condition. WindFor™ has been deployed all over the world for both off-shore and on-shore wind farms in every type of climate and terrain: from mountainous, icy and complex terrain to hot, dry and flat terrain
  • Supports asset owners and traders optimize their power production portfolio for accurate nomination and trading of electricity, minimizing imbalance fees and penalties
  • Supports system operators manage overall electricity grid, increase system stability and minimize cost of balancing the system and reserve cost
  • Self-learning algorithms which continuously adapt and re-configure power forecasts
  • Reliable, stable and with high availability with a proven track record from clients requiring availability of 99,9% and above
  • Robust, low maintenance system with minimal interference for the client
  • Long list of special tailored modules which can be deployed to handle complex requirements for specific and challenging wind farms or complex regulatory or commercial requirements in specific markets
  • Efficient error handling, fall-back procedures and issue warning system

Comparisons between a large number of wind power forecasting services have shown that WindFor™ delivers very accurate state-of-the-art predictions, making it the preferred choice for customers all over the world.

 

How does WindFor™ work

WindFor™ is a self-learning and self-calibrating software system based on a combination of physical models and advanced machine learning. This combines the best of artificial intelligence with wind power domain knowledge in order to produce the most accurate wind power forecasts available.

WindFor™ is initialized using either a power curve from the design of the wind farm or by using historical weather and production data to train the models.

After initialization, forecasts are produced every time the system receives new data which can be either updated weather forecasts or new production data. WindFor™ can run in either online mode and continuously receives real-time production data or in off-line mode where historical data are retrieved monthly or any other time interval.  By integrating WindFor™ directly with the SCADA system and thereby providing real-time production data, very accurate short term forecasts can be achieved.

Weather forecasts (incl. ensemble forecasts) are typically supplied as an integrated part of the solution. The system can use one or more weather forecast providers as input and automatically detect the optimal prioritization of the different weather forecasts for each wind farm and for different forecast horizons. Weather data is also made available to the client such that the client can compare power forecasts and weather inputs.

The self-learning and self-calibrating algorithms will continuously learn about the wind farm characteristics and will adapt to changing conditions, seasonal variations and as the wind turbines ages such that forecasts stay accurate at all times.

By delivering schedules of availability and curtailments, the client can make sure that WindFor™ takes these planned events into consideration. Furthermore, if the client provides real time availability and curtailment information from the wind farm, the data will be used to train models and adjust short term forecasts which significantly increase accuracy.

WindFor™ can deliver power forecasts in almost any file format and can be integrated directly into the operational IT-platform of the client, such that data are retrieved and delivered seamlessly to and from relevant systems.

WindFor™ is available as a software package installed locally on the client’s servers or as a service hosted on servers operated and maintained by ENFOR.

WindFor™ is supplied with various support, maintenance and license packages, which can be tailor-made to client specifications to provide a cost/performance ratio which fits the needs of the individual client.​

 

Key features

  • Integrates with weather forecast from all major weather forecast providers
  • Data flow and input validation automatically issue warnings in the event of errors
  • Efficient fall back procedures and estimation of substitute values in case of errors or missing input values
  • Highly configurable browser based graphical user interface for easy access and display of all relevant information
  • On-line mode or off-line mode, using either online production data or historical production data
  • Configurable forecast horizons. Furthermore; different weather forecasts providers can be used for different forecast horizons for optimal accuracy
  • Configurable time resolution in forecasts. Different intervals can be defined for short term intraday forecasts and day-head and week-ahead forecasts
  • Configurable forecast update frequency
  • Spatio-temporal correction taking advantage of the correlation in time and space between forecast errors for farms located in the same region
  • Configurable performance reports to monitor and track system performance
  • Data integration interfaces based on FTP, SFTP or Web Services supporting numerous formats and file types (CSV, XML, SOAP, JSON etc.)

Key features provided from special modules

  • Module for forecasting of uncertainty bands (quantiles) which can be used for trading/bidding strategies and risk assessment
  • Module for forecast scenario generation
  • Cut-out module. Estimates the probability/risk of cut-out at high wind speeds
  • Ramping module. Estimates the probability of a ramp occurrence of a certain size for a given time interval
  • Module for ice detection and forecasting of ice decay
  • Combination module. Combines multiple internal forecasts (based on different weather forecasts) and/or external forecasts. Calculates optimal weighing of individual forecasts, and produce high accuracy combined forecast
  • Downscaling module available for adapting weather forecasts and power predictions to local conditions in complex and mountainous regions
  • Upscaling module for using online measurement from some wind farms improve forecast for other wind farms without on-line measurements
  • Ensemble weather forecast module. Use ensemble forecast as input for improving forecast accuracy on both short term and long term horizons
  • Curtailment module for estimating “lost production” during curtailment
  • High resolution forecasting module. Forecasting of time resolution of 5 minutes or less

 

Example configuration 1: Potential electricity traders setup - off-line mode with changing portfolio of wind farms

  • Large number of wind farms and stand-alone wind turbines grouped into three areas
  • Frequent changes in the number of wind turbines and wind farms (turbines/farms are removed or introduced in the portfolio)
  • Power curve model for each area combined with weather forecast for the three areas
  • Off-line production data available and updated daily
  • Forecasts are provided for each area as well as a total

See Our References

You can find our references on the References page.

Additional information

WINDFOR™ BROCHURE

To see more complete details and specifications of the service, download WindFor™ brochure in PDF format

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