Data analytics has always played a major role in the renewable energy industry. Even before a project is commissioned, multiple studies are undertaken to understand historical wind patterns, sun-hours, historical solar radiation data sets and other important parameters. The data is analyzed to understand future weather patterns to decide on the energy potential of the site. The data is also used by analysts to determine tariff and bid for government tenders.
With an increase in solar and wind assets, the renewable energy industry is witnessing a shift in focus from building new assets to optimizing operations of existing assets. With tons of data being generated by renewable assets, data analytics is being leveraged to generate actionable intelligence.
Renewables offer a unique proposition vis-à-vis conventional energy resources by having zero fuel costs, so the major costs in any generating solar plant lie in O&M. The unique proposition also poses a challenge in energy generation as unpredictable weather leads to unpredictable energy generation. Solar asset owners are therefore leveraging data analytics to bring in reductions in OPEX cost and improve reliability.
A comprehensive data analytics platform offers the following benefits to asset owners
Asset management software automates report generation, notification and dashboard development. While basic reporting on parameters like generation can emanate from site SCADA a range of enhancements and improvements to make the report accurate and actionable. For e.g. in plants where a number of pyrometers provide data, the most common solution is use an average value, however, erroneous value from one pyrometer is often enough to change the performance ratio (PR) by 1% to 2%. The ability of the system to flag such deviations and help increase the accuracy of the data is critical.
Asset owners usually have multiple OEMs across assets. Data analytics provides insights into performance of the different OEMs as well as failure patterns which helps asset owners in formulating their future buying decisions. Apart from benchmarking, data analytics allows control over key metrics to increase yield. One such example lies in component level performance analysis. Most software offer performance view for solar assets at inverter level while few allow drill down to string level performance. String level analysis provides plant O&M team a dashboard to single out underperforming strings and take corrective action.
Inventory and Personnel management
Another key benefit of data analytics lie in helping asset owners in streamlining a major operating cost. Inventory management is critical and cost intensive for asset owners. Usually, most asset owners play safe by keeping excess inventory at site to reduce downtime in case of failures. Data analytics proactively identifies impending failures and also provides insights into MTTF (Mean Time to Failure) for vital components in a farm. Thus, allowing asset owners to streamline their inventory management and optimize inventory levels. Another benefit accrued lies in improved personnel management. Failure prediction coupled with weather data allows asset owners to identify key time windows to undertake maintenance activities and lower lost production.
The benefit of seamless management of farm data for actionable insights has led asset owners to take on a proactive approach to solar farm management. Data analytics has made a significant impact on wind farm management and with increased uptake of solar farm under analytics, it looks poised to accrue benefits for solar farm management as well.