GL Garrad Hassan at European Wind Energy Association 2011

GL Garrad Hassan has developed a new software tool to help facilitate this. WindHelm provides a single platform for the monitoring, optimisation and control of any combination of operational wind turbines, wind farms and wind power portfolios. It gives owners and operators uniform access to, and analysis of, their SCADA data.
 
This facilitates intelligent operational decisions, therefore maximising availability, efficiency, production and financial return. WindHelm was officially launched today at the European Wind Energy Association conference currently taking place in Brussels.

WindHelm was developed out of GL Garrad Hassan’s leading independent SCADA product and so clients benefit from the related international consulting experience and can be confident of a robust and intelligent product, and world-class support.

With a rich reporting environment and an advanced analysis engine, WindHelm enables clients to get real value out of their wind farm data. Experts from GL Garrad Hassan’s SCADA and asset management and optimisation teams have worked together to offer a broad range of reports, based on their significant experience helping clients around the world to effectively manage and optimise their assets. WindHelm also offers the flexibility of user-defined reports for clients that would prefer to conduct their own advanced analyses.

Key features:

. Instant access to "near real time" data via a single user interface accessible from any web browser
. No software dongles required or equipment required at project sites
. Capable of managing any volume and combination of turbines
. Fully compatible with any SCADA system with an ODBC interface, including all existing GH SCADA systems
. Ability to send event alerts and status messages via email, mobile phone or pager to facilitate rapid remediation of problems
. A full range of summary and detailed operational reports to facilitate optimisation including power curves, availability, meteorological data, faults/events, efficiency, actual v expected production
. Access to KPIs via a portfolio dashboard
. An advanced analysis engine for forensic analysis and trending of available data at the turbine, project and portfolio level
. Accommodates component taxonomies for standardisation and benchmarking of fault analysis
. Taxonomy from the RELIAWIND project included as standard
. Supports regulatory performance metric reporting
. Multiple output formats – HTML, CSV and compatible with Crystal Reports
. Ability to import Excel templates

Wind industry could earn €0.5 billion more per year through joined up thinking in operational wind farm portfolios

There are 165,000MW of wind turbines currently operating globally and many of them do not meet their full production potential because they are not operating at optimum production levels. While this is obviously an issue for both manufacturers and owners, it is also a significant problem for the wind power industry as a whole: wind energy has arrived in the mainstream of electricity generation and therefore direct comparisons are made between it and other older sources of electricity.

For wind energy to consolidate and extend its position and quash the detractors, it needs to perform at its full potential. Imagine that every problem on each one of the world’s wind turbines was resolved and they were all performing at optimal level. What might the impact be?

For the purposes of this article, GL Garrad Hassan has used average figures, drawn from its international consultancy experience with owners and operators, to demonstrate what is at stake and provide food for thought for the industry as a whole.

Drowning in data

Data is routinely recorded by many sensors on each individual turbine on a ten minute basis and can be incredibly valuable in helping to monitor and optimise the performance of a wind turbine, a wind farm, or an entire portfolio. Realising the full value of those data, however, requires a significant understanding of realworld performance monitoring and some sophisticated data management and analytical tools.

Original equipment manufacturers need data to facilitate their O&M and help them meet their availability and performance warranties. Owners also need data to enforce those warranties but, while they provide a good safety net in the early years of operation, they should not form the entire basis for any owner’s asset management and optimisation decisions.

Even where there’s some upside-sharing, it’s pretty clear that it’s the owners who have the strongest motivation to maximise performance. In a multi-supplier or even multi-technology portfolio, they find themselves being the only party really able to squeeze maximum value from the whole – and there’s a lot more value to be extracted from the data by taking that approach. Corrective action in the field costs owners money and a comprehensive data management and performance monitoring programme will reduce those costs by allowing the related activity to be targeted in an accurate and timely manner.

Availability still the primary focus

Although it is realistic to assume that a modern turbine can achieve an average availability of up to 98%, this is not the average availability across the world’s operating wind turbines. Published analyses by GL Garrad Hassan and others suggest that the European average is in the 97-98% range, whereas the US fleet is a couple of percent lower.

Offshore wind power projects are a different story altogether, with access problems multiplying up any downtime so that many projects are struggling to achieve over 90% availability – a level which all but the most remote projects should be able to exceed comfortably. So, there is still some scope to improve operational practice and, in the context of offshore projects, a pressing imperative to do so.

Do those assets perform properly when they are available?

While availability has improved over the recent years, it remains the main focus of operators. GL Garrad Hassan’s experience indicates that by also monitoring operational efficiency, to make sure that wind turbines perform at optimum levels during the time that they are available, the yield can improve by another 1%.

Common causes of degradation of performance such as de-rating, non-optimal controller settings, dirt, component misalignment and sensor error can all be rapidly identified and corrected with a comprehensive approach to collection, and systematic scrutiny, of data.

Predictive maintenance

GL Garrad Hassan is actively involved in the EC RELIAWIND R&D project – classifying every permutation of a physical part of a turbine, situation or failure mode. Structuring this methodology into an operational monitoring programme allows data to be collected in relation to each classification, which, in turn, provides information on the seriousness and probability of each failure mode and operational deficiency. This approach enables predictive and targeted intervention – moving beyond capturing what has already gone wrong with a wind turbine.

If short-term forecasting data is also at hand, then timing of any required intervention can be set to minimize its impact on revenue, or for larger projects and portfolios, on the transmission system operation.

In summary, GL Garrad Hassan’s experience shows that availability figures of 97 – 98% are achievable and can be sustained, and the downtime risk can be mitigated with a suitably informed O&M strategy that is influenced by reliability profiling. Where performance is concerned, experience has proven that well monitored sites can achieve 100% power curve efficiency.

Achieving the above levels requires a joined up approach with a single robust data management solution and the right analyses, whether these be performed by person or technology. This approach allows desk-based staff to provide those in the field with the guidance needed to make use of their resources with maximum benefit and minimum cost.

Imagine if the global fleet of 165 GW of operating wind turbines were managed that way. Taking into account the current levels of availability and operational efficiency, it is not outlandish to think that there could be scope for a global improvement of 2% in output or €500m1 more per annum – definitely worth the effort!

1 165 GW at a capacity facory of 25% earning €70 / MWh.

With significant understanding of both the asset and the resource, GL Garrad Hassan has been bridging the gap for owner/operators for years, providing a range of services to help them get the most out of their portfolios and improve the bottom line. Its forecasting team provides short-term forecasting for over 33 GW of wind projects and portfolios worldwide, from 1 hour to 10 days in advance, and its asset management and optimisation team has analysed over 30 GW of operational assets globally.

GL Garrad Hassan’s new WindHelm Portfolio Manager software complements the existing service range by offering a core facility for owner/operators to access and exploit the data related to their wind turbines, regardless of manufacturer, in a uniform way across their portfolio.

WindHelm combines the strength of GL Garrad Hassan’s asset management and optimisation experience with the underlying technology from its independent SCADA system which is presently used to monitor over 6 GW of operational wind farms around the world. It has a flexible analysis and reporting system for those that really want to drill in to their data, a built in Operational Analysis reporting pack, written by GL Garrad Hassan’s asset management and optimisation experts, and facilitates the analysis and profiling of turbine and component reliability.

www.gl-garradhassan.com/