T19IceLossMethod

T19IceLossMethod Free Software Start Up Page


T19IceLossMethod:

p-curve.jpgA standardized method to assess production losses due to icing from wind turbine SCADA data. This site describes a method to assess production losses due to icing based on standard SCADA data available from modern wind turbines. An open source software using Python code is publicly available based on the method. To download the software, Email username and password request to Timo Karlsson.

Registration information includes:

  • First name
  • Last name
  • Valid email address
  • Country
  • Employer (company, institute etc)

Once the request is granted, the Operating Agent of Task 19 will send username and password for access to the FTP site.

The software package includes the source code, theory and user manuals. The subscription information should not be distributed to 3rd parties. Software and T19IceLossMethod related news may be sent to subscribed persons via email.

Motivation


Currently, production losses due to wind turbine rotor icing are calculated with different methods, all resulting in different results. Task 19 has three main reasons why a standardized production loss calculation method is needed:

  1. There is a large need to compare different sites with each other with a systematic analysis method
  2. To validate the IEA Ice Classification
  3. Evaluate effectiveness of various blade heating systems

Current production loss methods usually use a constant -15% or -25% clean power curve drop as an indication of icing. Similarly standard deviation (or multiples of it) has been widely used to define iced turbine production losses (Figure 1). Both of these methods result to different results and are not necessarily representing the actual ice build-up and removal process to wind turbine blades reliably enough.

With the method described here, anyone with access to SCADA data from wind turbines can assess and calculate turbine specific production losses due to icing. The standardized method will use existing standards and will be developed in order to minimize the uncertainties related to production loss estimations from SCADA data. The method does not require icing measurements as input.

Disclaimer


The Software is provided "AS IS" and VTT makes no representations or warranties of any kind with respect to the Software or proprietary rights, whether express or implied, including, but not limited to merchantability, fitness for a particular purpose and non-infringement of third party rights such as copyrights, trade secrets or any patent. VTT shall have no liability whatsoever for the use of the Software or any output obtained through the use of the Software by you.

Method


Task 19 proposes a method that is robust, easily adaptable, filters outliers automatically and does not assume a normal distribution of the SCADA data for individual turbines and wind farms. The proposed method uses percentiles of the reference, non-iced power curve in combination with temperature measurements. Ice build-up on turbine blades gradually deteriorates the power output (or results to overproduction to iced anemometer) so for increased accuracy the method uses three consecutive 10-minute data points for defining start-stop timestamps for icing events. In other words, the turbine rotor is used as an ice detector. Iced turbine power losses are defined by comparing the performance to the calculated power curve using heated anemometers from nacelle and the measured reference, expected power curve. Production losses are separated into 2 categories: operation and standstill losses due to icing.

On a general level, the method can be divided into 3 main steps:

  1. Calculate reference, non-iced power curve
  2. Calculate start-stop timestamps for different icing event classes
  3. Calculate production losses due to icing

Below is the list of required SCADA data signals used as input for the production loss calculation method.


Table 1. List of required SCADA data signals for standardized production loss method due to icing.

Signal

Description

Unit

Value

ws

Heated nacelle
wind speed

m/s

10-minute mean

temp

Ambient temperature
(from nacelle weather mast)

°C

10-minute mean

pwr mean

Turbine output power

kW

10-minute mean

nacdir

Nacelle yaw angle

deg

10-minute mean

mode

Turbine operational mode

-

10-minute mean