The five common causes why wind plants underperform and how to address them

The five common causes why wind plants underperform and how to address them

The five common causes why wind plants underperform and how to address them WITH gpm hORIZON.

In a world where the transition to cleaner and more sustainable energy sources is no longer a choice but a necessity, wind power stands as a powerful symbol of hope. Wind plants contribute significantly to the reduction of greenhouse gas emissions and the quest for a greener future. However, while the potential of wind energy is immense, the efficiency and reliability of wind plants can be hindered by underperformance.

Wind plant underperformance is an issue that impacts not only energy production, but also the broader goals of sustainability and environmental responsibility. The causes of underperformance are diverse and often subtle, requiring careful analysis and strategic solutions.

In this article, we embark on a journey to unveil the five common issues behind wind plant underperformance and provide actionable strategies for addressing them.

Electrical and mechanical failures

Causes

Electrical and mechanical failures are a major cause of downtime and lost revenue for wind plant operators. These failures can be caused by a variety of factors, including:

  • Wear and tear: wind turbines are complex machines with multiple moving parts. Over time, these parts can wear and tear, leading to failures.
  • Manufacturing defects: can lead to electrical and mechanical failures. For example, a defect in a bearing or gear can cause a premature failure.
  • Improper installation:  can lead to electrical and mechanical failures. For example, a turbine that is not properly aligned can experience excessive wear and tear.
  • Environmental factors: extreme temperatures, high humidity, corrosive airborne particles, and other factors can also contribute to electrical and mechanical failures.

Most common failures

Electrical and mechanical failures are a major cause of downtime and lost revenue for wind plant operators. These failures can be caused by a variety of factors, including:

  • Generator: the component that converts mechanical energy from the wind turbine blades into electrical energy. Generator failures can be caused by various factors, including insulation, bearing, and winding failure.
  • Gearbox: transfers mechanical energy from the wind turbine blades to the generator. Gearbox failures can be caused by a variety of factors, including bearing failure, gear tooth failure, and lubrication failure.
  • Rotor: the assembly of blades that converts the kinetic energy of the wind into mechanical energy. Rotor failures can be caused by numerous factors, including blade failure, hub failure, and bearing failure.

Solutions

Identify root causes and predict failures before they happen

Condition-based monitoring systems that use sensors and data analytics are the key to early detection of irregularities in electrical and mechanical components. Implementation of predictive algorithms with machine learning to analyze data from wind turbines help predict failures before they happen.

The Predictive module of GPM Horizon is here to help our clients to do exactly that. Discover more information in this article.

Improve communication between wind plant operators and maintenance teams

A centralized dashboard can improve communication between wind plant operators and maintenance teams. The dashboard can provide real-time data on the status of wind turbines, as well as alerts about potential problems. This allows maintenance teams to access information about wind turbine failures quickly and easily so that they can take corrective action as quickly as possible.

In GPM Horizon, we offer comprehensive dashboards to monitor the current situation of your assets, making it easy to detect issues and address them right on the spot. Check the alarms in real time, set up automatic notifications, acknowledge, create tickets, and follow up on the progress.

Suboptimal wind turbine maintenance

Outlook

As mentioned above, wind turbines are intricate machines with various mechanical and electrical components. Like any machinery, they require optimized maintenance activities to operate at peak efficiency:

  • Insufficient or infrequent maintenance can lead to equipment breakdowns, mechanical failures, or malfunctioning sensors. These issues can result in underperformance and costly downtime.
  • Suboptimal scheduling of regular maintenances and inspections during peak wind production periods can significantly disrupt energy production, resulting in missed opportunities to generate electricity and earn revenue.

Solutions

Proactive predictive maintenance

A robust maintenance strategy that encompasses regular inspections, predictive maintenance using data analytics and condition-based monitoring, is essential.

Implementing predictive maintenance techniques can help anticipate potential component failures, allowing proactive maintenance scheduling before issues occur. By identifying wind turbines that are at risk of failure, wind plant operators can focus their maintenance efforts on those turbines.

In GPM Horizon, our Predictive module gives you a noticeably clear picture of the detected anomalies sorted by levels of severity.

For each anomaly, you get a list of failure modes indicating where the problem most likely is. And it gets even better when machine learning comes into place: the more you work with the system and provide feedback from the field, the more accurately it will determine the potential causes in the future!

Optimizing maintenance schedules

Accurate wind production forecasts can help identify periods of low wind activity, allowing maintenance to be scheduled during these times to minimize disruptions to peak production hours.

In GPM Horizon, you can plan your maintenance activities in advance, using a user-friendly calendar view to visualize them by categories.

It is easy to set up recurring events and receive timely notifications about them.

You can use production forecasts to assist schedule your maintenance at the most optimal time. Based on the duration of your event, GPM Horizon will present the best options and clearly highlight them for you. It’s quite simple!

Environmental factors

Outlook

Wind plants are subjected to the whims of Mother Nature:

  • Ice accumulation: during frigid winter months, ice accumulation on wind turbine blades can significantly hinder performance. Ice deposits add weight and alter the aerodynamic profile of the blades, reducing their ability to capture wind energy. In severe cases, ice buildup can cause structural damage to the blades.
  • Extreme temperatures: when temperatures soar too high or plummet too low turbine efficiency can suffer. Excessive heat can lead to overheating of components, while extreme cold can cause lubricants to thicken, increasing friction and wear on moving parts.
  • Turbulence: characterized by erratic wind patterns and rapid changes in wind direction, this can disrupt the smooth operation of wind turbines. Turbulent winds can cause sudden changes in blade loading, leading to fatigue and potential damage. Moreover, turbulence can reduce the overall energy capture efficiency of the turbines.

Solution

Icing

  • Blade heaters: Blade heaters can be used to melt ice that accumulates on the blades of wind turbines. This can help to improve blade efficiency and reduce wear and tear.
  • De-icing systems: De-icing systems use a variety of methods to remove ice from the blades of wind turbines, such as compressed air, vibration, and ultrasonic waves.

GPM Horizon offers a De-Ice module aimed at displaying the relevant info about the icing situation in your affected assets, such as current ice mass, blade heating impact, simulated power with/without ice.

Turbulence

  • Turbine placement: wind turbines can be placed in areas with less turbulence such as flat terrains, without any obstacles like trees or houses. By far the best conditions are found in offshore environments.
  • Turbine control: wind turbine control systems can be used to adjust the turbine blades to reduce fatigue and damage caused by turbulence.

Extreme weather events

  • Turbine design: wind turbines can be designed to withstand extreme weather events, such as hurricanes and tornadoes.
  • Early warning systems and advanced weather forecasting: can detect approaching extreme weather events, so that wind turbines can be taken offline before they are damaged.

Grid constraints and curtailments

Outlook

Wind plants must be connected to the electrical grid to deliver the power they generate. If there is insufficient transmission capacity, the amount of power that can be delivered from a wind plant may be limited. This can lead to lost production and revenues:

  • Grid congestion: even if a wind plant is generating electricity efficiently, it may not be able to deliver all that electricity to the grid if there is congestion on the transmission lines. It occurs when there is flow of increased electricity through a particular part of the grid, which can cause power outages and equipment damage.
  • Curtailment: wind plants are sometimes curtailed, or turned off, for a variety of reasons, such as to avoid overloading the grid or to reduce noise levels. Curtailment can reduce the amount of electricity that a wind plant generates.

Solutions

There are several potential solutions to grid congestion and curtailments.

Expanding and upgrading the transmission grid

This is the most expensive and time-consuming solution, but it is also the most effective in the long term. Expanding the transmission grid will create new pathways for electricity to flow, reducing the risk of congestion. Upgrading the transmission grid will make it more efficient and resilient, strengthening its ability to manage significant volumes of power from renewable energy sources.

Deploying distributed energy resources (DERs)

DERs are small-scale energy generation and storage devices that can be located close to where the electricity is consumed. This can help to reduce the need for long-distance transmission, which can assist in reducing congestion. DERs can also provide flexibility to the grid and help to balance supply and demand, and reduce the need for curtailment.

Market reforms

Market reforms can help to create incentives for wind plant operators to reduce their output during times of grid congestion. For example, wind plant operators could be paid to reduce their output during times of low demand. This would help to reduce the risk of congestion and blackouts.

GPM Horizon offers a clear financial view of all the energy and revenues your plant generates, including compensated energy. Check your performance against the budget and theoretical production, follow-up on a daily and monthly basis, compare with previous years, upload your personalized invoices, and view the production figures instantly updated on the platform.

Using energy storage

Energy storage systems can store electricity when it is generated and release it when it is needed. This can help to smooth out the flow of electricity on the grid and reduce the risk of congestion. Energy storage can also help reduce curtailment by storing excess electricity from wind plants when the grid is congested and releasing it when it can handle more power.

Inadequate wind resource assessment

Outlook

The location of a wind plant is not by accident. There are large variations in the reliability of wind resources based on geography, terrain and local weather patterns. An inadequate assessment of these factors can result in underperformance, as turbines may not receive the necessary wind flow to generate optimal energy.

Solutions

Better data collection methods

Traditional wind resource assessments rely on data from a limited number of meteorological stations. Newer technologies, such as lidar and satellite remote sensing, can provide more comprehensive and accurate data about wind resources.

Sophisticated modeling tools

Wind resource modeling tools have become increasingly sophisticated in recent years. These tools can consider a variety of factors, such as topography, land use, and vegetation, to provide more accurate predictions of wind resources at a particular site.

It is worth mentioning that DNV offers Computational Fluid dynamics (CFD) services for extremely accurate wind flow simulations. Based on the terrain and meteorology data, the wind flows are modeled with minimal error. The accurate prediction of the energy output can be crucial to determine the correct placement of the site and optimize its design.

Long-term assessments with experienced professionals

Wind resource assessments should be conducted over at least one year to capture seasonal variations in wind patterns. Additionally, it is crucial that they be carried out by experienced professionals who are conversant with the latest modeling tools and technological advances.

A brighter and a cleaner energy future

As we conclude our exploration of wind plant underperformance and its solutions, we envision a brighter and cleaner energy future. Wind energy, with its boundless potential, stands as a cornerstone of sustainability, offering a beacon of hope in the global quest for more efficient energy sources.

By understanding and addressing the common causes of underperformance, wind plant operators can ensure that their facilities operate at peak efficiency, making the most of this extraordinary and renewable resource.

The challenges of underperformance are not isolated issues: they represent opportunities for collaboration and innovation. As the wind energy sector continues to grow and evolve, industry leaders, researchers, and technology developers have collaborated to address them.

Numerous issues need to be addressed, as we have seen, but we enjoy a challenge.

The team of GPM believe in constant innovation and in the future we plan to expand GPM Horizon´s capabilities in the energy storage area. Follow us on LinkedIn to never miss an update about our product releases and new improvements.


Article by :
Sucharita Banerjee, Alexey Bakulin and Francisco Laucirica.


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