A key step towards making most of the data is related to having the complete operation data from the beginning and having a database which makes data mining easy.

A section of the industry believes that the large amount of SCADA data that is being produced is generally difficult for wind farm operators to interpret.

The data routinely acquired and stored by SCADA systems represents a vast amount of valuable information. This information has historically been widely neglected because of the resource necessary to extract it from the data.

It is also pointed out that it has often been considered worthwhile to analyse the data only once something has already gone wrong with a turbine.

According to Peter Clive, technical development officer, SGURR Energy, however, analysis that have hitherto been conducted in a reactive, post hoc manner to diagnose faults or to progress post investment appraisals are now being automated, radically reducing the resource necessary to conduct them, and new tools have been developed which further enable rapid performance assessment and enhance its value. Rapid performance assessment enables routine performance assessment from which all the benefits of a more pro-active approach can be derived.

Sharing his viewpoint, Michael Melsheimer, Managing Director, Windguard North America, who is scheduled to speak during Wind Energy Operations and Maintenance Summit USA, to be held on April 1-2 in Dallas, Texas, feels the value of the collected data and the interpretaion of it is widely underestimated.

“The key is to have the complete operation data from the beginning and to have a database which enables you to make data mining easy. Also, to have an understanding of the uncertainties and the problems in data comparison is a major aspect,” Melsheimer told windenergupdate.com.

The development of improved scientific predictions is the refinement and validation of models against measured data. It is considered that the SCADA data from wind farms contains information that allows further validation of models and assumptions used in energy assessment. Compromising a SCADA system can lead to a number of undesirable consequences, such as disruption of operations, asset availability, asset misconfiguration, loss of data and confidentiality and unsafe conditions.

New trends

One current trend is the move towards data aggregation among owners, operators and network management of multiple wind farms: the data from multiple disparate SCADA systems installed at multiple wind farms is put into a common format for centralised asset control in a “SCADA on top of SCADA” setup.

Acknowledging the same, Melsheimer says to get an overview of a portfolio, it is necessary to normalise the data which are provided by the vendors SCADA systems. Descision makers will be enabled to find the weak points in portfolios and to eliminate them.

On realisation of data acquisition over large portfolios that will allow one to make the most out of the SCADA system, Melsheimer firstly referred to automating the data collection in order to avoid gaps in the database. Secondly, the data has to be filtered and normalised to avoid inaccurate values and make the data stucture comparable. The third step is dependent on the customer needs, but usually a wide spread of data viewing and fault analysis tools help the operater to be always on top of the information.

“Not every message is high prioity, and sometimes a validity check will bring up problems. Also the `missing’ data is an item of investigation,” he said.

For its part, SGURR Energy has also highlighted that another interesting trend is the ongoing investigation of exactly how much information can be extracted from routine SCADA data. For example, an active topic of research related to performance assessment is the extent to which the stresses the machine is subject to, arising from, for example, turbulence, wind shear and veer, and flow inclination, can be discerned using standard performance assessment tools. This field is one of the most rapidly progressing fields in a rapidly developing industry and SgurrEnergy engages in continuous innovation to remain at the cutting edge delivering the maximum achievable benefit to its clients.

Resolving issues

Providing a rundown on typical analysis to identify highly specialised issues and then evaluate and resolve them, Melsheimer referred to three topics.

Availability - this can be tracked with the alarm logs. Custom specified availability routines can sort out if a lower availability is a turbine problem or if it is another problem.

Power curve assessment. Losses in power can be tracked by constantly reviewing the power curves. An automised approach helps to keep track on a high number of turbines.

Troubleshooting: A good database tool is sorting out where your touible-turbines are and what the reasons are. Useful planning of resources and maximise the revenue are the positive results of that.

Melsheimer also agreed with the fact that in general the most valuable analysis of turbine performance are not implemented by the SCADA system per se but by the tools with which the system may be augmented for the purposes of performance monitoring and assessment and which utilise for that purpose the data routinely acquired by the SCADA system.

For example, some limited turbine inter-comparison and performance trending is sometimes performed by reporting modules of SCADA systems but the most sophisticated analyses delivering the greatest benefit are beyond the scope of essential supervisory control and data acquisition implemented by SCADA.