9 Wind Asset Management KPIs You Can Optimize with Digital Wind Turbine Technology

9 Wind Asset Management KPIs You Can Optimize with Digital Wind Turbine Technology

16 Apr 2024 Written by Naomi Stol Zamir

The International Energy Agency (IEA) states that wind and solar energy are the two predominant power generation methods to help achieve net zero emissions by 2050. However, the IEA notes that wind capacity needs to significantly increase to reach global emission goals.

Wind capacity typically means adding more turbines and creating entirely new farms, which is certainly crucial for achieving net zero goals. However, enhanced wind turbine efficiency also contributes to these goals by maximizing the output of existing turbines.

How do you increase the efficiency of every turbine on your farm? It’s certainly a complex goal, but consistently measuring and enhancing specific KPIs will go far in enhancing wind farm management.

Keep reading to learn more about wind asset management KPIs that can contribute to greater wind turbine optimization.

Top Wind Asset Management KPIs

Accurately understanding, measuring, and monitoring KPIs is necessary to strategically optimize wind farm management. Wind turbine maintenance, cost-effective inspections, and data-driven repairs all enhance the profitability of wind farms.

So let’s go over three cornerstone categories of KPIs that are crucial for operating an efficient wind farm. While not an all-inclusive list, we’ve chosen nine KPIs across three categories to explore.

Reliability KPIs

Having reliable turbines is vital to a successful operation, so these KPIs strive to measure how reliable components are throughout the wind farm:

  1. Mean Time Between Failures (MTBF): How frequently are components or entire turbines failing? Tracking each incident and measuring the time between incidents produces MTBF. Increasing MTBF is achieved with effective inspections and maintenance routines.
  2. Mean Time to Failure (MTTF): This metric measures the reliability of a non-repairable turbine component. These parts will stop functioning and need to be replaced at some point, and tracking MTTF allows managers to learn when they need replacement. Predicting the failures of these parts is the overall goal of MTTF.
  3. Mean Time to Repair (MTTR): Similar to MTTF, MTTR describes components that can be repaired and strives to predict when repairs should be made. Ideally, repairs are made when they will have the highest impact on reliability.

Performance KPIs

The heart of any wind farm is its performance. These KPIs strive to measure performance and can pinpoint key ways to improve:

  1. Time-Based Availability (TBA): This simple yet essential KPI describes the amount of time a specific turbine is operational or available as compared to the overall time being measured. If TBA suffers, technicians need to be dispatched to conduct a wind turbine inspection and possible repairs.
  2. Wind/Energy Index: This index describes how effectively turbines operate in relation to available wind. A new wind farm will need to establish a baseline over a longer period of time, which can then be used to gauge if performance is improving or degrading over time.
  3. Energy-Based Availability (EBA): EBA is a ratio of the actual energy produced by wind turbines as compared to the actual energy available. The result is a percentage of the energy a wind farm captures from available wind. 

Maintenance KPIs

Maintenance represents a major expense to wind farm management, so the following KPIs strive to monitor maintenance effectiveness and costs:

  1. Response Time: How long does it take for technicians to begin maintenance following the detection of any type of failure? Response time is a reflection of how effectively technicians are able to be dispatched to a turbine and begin correcting the issue, which can have effects throughout the wind farm.
  2. Scheduled Compliance: This KPI describes how many maintenance tasks are completed as compared to the total number of tasks scheduled to be completed for the same period. Lacking schedule compliance means that technicians are running behind, which warrants investigation. 
  3. Total Annual Maintenance Costs (TAM): The cost of maintenance is crucial to understand and perhaps the most important for reporting to stakeholders. TAM conveys a high-level overview of the real costs of maintaining a wind farm. This KPI is often compared to the Annual Maintenance Budget (AMB) to understand if a wind farm is spending more or less than expected.

Challenges in Monitoring Wind Farm KPIs

Monitoring the KPIs we discussed above is no simple task. Some of them, like response times, are relatively straightforward; other KPIs require robust data tracking and possibly additional sensors to track effectively.

Acquiring data is a massive challenge for many wind farms, but without it, monitoring and improving these KPIs aren’t possible. Other industries can benefit from easy data collection, but new and established wind farms alike might need to invest in new technologies to properly monitor KPIs and increase operation efficiency.

Fortunately, new technologies like autonomous drone inspections, Digital Twins, and the Industrial Internet of Things (IIoT) have made it possible for operations to gain access to real-time data or better acquire data from the field. 

How vHive’s Digital Twin Technology for Wind Farm Helps Measure & Optimize Your KPIs

Why should you prioritize monitoring the above KPIs? The overarching goal of monitoring these metrics is to improve them, reassess them, and repeat them. 

Capturing the data necessary to properly measure these KPIs can be challenging, however. Fortunately, vHive provides autonomous data acquisition through multi-drone technology to conduct inspections much faster than previous approaches.

vHive provides digitization starting with autonomous drone inspection that can help with many of the KPIs we discussed. Our solution equips OEMs, wind turbine operations departments, and wind farm owners with the tools to carry out rapid inspections and analysis, which can affect KPIs in all three categories:

  1. We can reduce total annual maintenance (TAM) costs by making the inspection process significantly more time and workforce efficient. Wind turbines can be inspected more frequently to reduce downtime and enhance overall operational efficiency.
  2. Our inspection software focuses on detailed data capture that can improve reliability KPIs to enhance the mean time between failures (MTBF) and the mean time to repair (MTTR). Autonomous inspections and digital twin software make it easier for technicians and engineers to identify defaults that may degrade output prematurely, allowing them to conduct pre-emptive repairs to maximize output.
  3. Digital Twins allow you to better understand performance KPIs, such as the wind/energy index and time-based availability (TBA). vHive’s platform enables a deeper understanding of the condition of every turbine, enabling you to better identify and correct any deficiencies.
  4. vHive can enhance profitability by reducing inspection and maintenance costs, which becomes increasingly crucial as energy costs can vary significantly. Keeping your overhead under control allows you to remain profitable or reduce losses if prices become negative.

The vHive platform can significantly contribute to optimizing many of the KPIs indicated above. Are you ready to discover how vHive can help you achieve your KPIs? Schedule a demo today to see vHive’s solution in action.

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