COPA-DATA Blog

Combining distributed systems

Written by Martyn Williams | June 2018

Consider offshore wind farms as an example. The world’s soon-to-be-largest offshore wind farm is currently under construction 74.5 miles off the Yorkshire coastline. To accurately manage these vast generation sites, the data from each asset needs to be combined into a singular entity.

This software should be able to combine many items of distributed equipment, whether that’s an entire wind park or several different forms of renewable energy sources, into one system to provide a complete visualisation of the grid.

Operators could go one step further, by overlaying geographical information systems (GIS) data into the software. This could provide a map-style view of renewable energy parks or even the entire generation asset base, allowing operators to zoom on the map to reveal greater levels of detail. This provides a full, functional map enabling organisations to make better informed decisions.

 

Reporting on renewables

Controlling and monitoring renewable energy is the first step to better grid management. However, it is what energy companies do with the data generated from this equipment that will truly provide value. This is where reporting is necessary.

Software for renewable energy should be able to visualise data in an understandable manner so that operators can see the types of data they truly care about. For example, wind farm owners tend to be investors and therefore generating profit is a key consideration. In this instance, the report should compare the output of a turbine and its associated profit to better inform the operator of its financial performance.

Using intelligent software, like zenon Analyzer, operators can generate a range of reports about any of the information they would like to assess — and the criteria can differ massively depending on the application and the objectives of the operator. Reporting can range from a basic table of outputs, to a much more sophisticated report that includes the site’s performance against certain key performance indicators (KPIs) and predictive analytics, which can be generated from archived operational data.

As investments in renewable energy generation continue to increase, the need for big data technologies to manage these sites will also continue to grow. Managing these volatile energy sources is still a relatively new challenge. However, with the correct software to combine the data from these sites and report on their operation, energy companies will reap the rewards of these increasingly popular energy sources.