IN Southern Africa, wind energy is still a relatively young industry, and so is the experience of operation and maintenance (O&M) of these assets optimally and cost-effectively. Wind farms are strategically situated in windy regions – locations usually prone to harsh weather conditions, exposing equipment to mechanical stress and corrosion. Accessibility can also be problematic, as wind farms are frequently located in remote areas, resulting in limited control over assets and delayed responses to breakdowns.
Experts in Enterprise Asset Management Systems, Pragma, shares its suggested solutions to the challenge of maintenance of wind farm assets so that reliable energy production can be ensured.
The challenge qualified
The engineering process of electrical energy generation on South Africa’s onshore wind farms, with an operating capacity of close to 3 GW, is identical to all others on the planet with a total capacity of more than 900 GW. However, local asset owners are subjected to additional challenges. Once the not-insignificant regulatory hurdles are overcome, they have to deal for decades with spare parts supply chain logistics, scarcity of skilled technical resources, including special tools and handling equipment, and limited access to the original equipment manufacturer’s (OEM) historical data, to name just the high-level elements.
Reliability enhancement tactics and technologies
Key to addressing the risks posed by challenges in local wind farm operations and maintenance, is the ability of independent power producer (IPP) asset owners and operators to obtain timeous information on the potential reduction of performance and critical failures of the key assets, i.e. the wind turbine generators (WTGs), electrical MV components and the sub-station. To this end, well-established asset care strategies should be employed and enhanced with emerging modern technology-based solutions.
WTGs are highly mechanical in nature and physically massive in size. With blades reaching 60 m in length, nacelles weighing over 200 tons, and tower height exceeding 100 m, highly specialised construction and maintenance techniques are not negotiable. Unexpected failures can lead to significant downtime, reduced energy production, and increased maintenance costs. Whilst less critical, the effect of failing or degraded performance of the electrical balance of plant, such as the wide-spread MV network and substation equipment, can also have severe consequences if not countered in time.
Preventive maintenance
The aim of quality preventive maintenance, as a primary risk-reduction strategy, is to minimise unplanned downtime and extend the lifespan of critical assets. Preventive maintenance strategies, including the optimisation of maintenance schedules, are the cornerstone of reliable wind farm operations. These strategies involve regular inspections and maintenance to identify and address issues proactively before they become larger failures. However, the downside of possibly pre-mature interventions cannot be ignored and drives the need for more advanced strategies.
Predictive maintenance
In addition to preventive maintenance, wind farms are increasingly adopting predictive maintenance techniques, which require monitoring and analysing data from sensors to detect early signs of degradation or malfunction in components. With data-driven insights and real-time equipment data, predictive maintenance aims to forecast the optimal time for maintenance activities. This approach minimises downtime, lowers maintenance costs, and prevents catastrophic failures that can lead to significant disruptions.
Both preventive and predictive maintenance have benefits and challenges. While preventive maintenance mitigates the risk of unexpected breakdowns, it can sometimes result in excessive maintenance costs because of routine inspection and servicing. On the other hand, predictive maintenance is cost-effective, but its successful implementation requires additional investments for accurate sensor data and advanced data analysis.
Advanced condition monitoring, IoT and AI
Advanced condition monitoring technologies further enhance the reliability of wind farm assets. Techniques such as Very Low Frequency (VLF), Tan Delta (TD), Partial Discharge (PD) and Dissolved Gas (DGA) analysis provide real-time insights into the health of the MV network components and transformers. Application of Internet of Things (IoT)-enabled sensors takes this a step further by continuously monitoring not just WTG engineering parameters such as vibration, temperature, pressure and electrical variables, but also pin-points weather parameters that will affect the WTG operation. Artificial Intelligence (AI) will then play a crucial role, with machine learning algorithms processing and analysing vast amounts of data collected from sensors in real-time. By detecting patterns in this data, AI can predict potential failures before they occur, reducing unscheduled downtime. This means that deviations from normal operational behaviour can be spotted quickly to enable wind farm operators to make informed decisions, thereby reducing the likelihood of critical failures and improving overall asset performance.
Lifecycle considerations and cost impacts
The lifespan of a WTG typically ranges from 20 to 30 years, although some turbines can operate beyond this range with quality maintenance and refurbishment. The final lifespan is influenced by various factors, including the quality of components, maintenance practices, environmental conditions, technological advancements, and the specific design and construction of the turbine. Regular maintenance, upgrades, and replacement of components can extend the operational life of wind turbines well beyond their initial design expectations.
The ramifications of equipment breakdowns reverberate through financial and operational aspects. Such failures usher in elevated repair expenses, curtailed energy production, and escalated maintenance outlays. The latent economic repercussions intensify with time, underscoring the urgency of timely interventions to mitigate these effects.
Outsourcing maintenance and contractor management
Engaging specialised contractors has many benefits such as access to expert knowledge, less strain on internal teams, and financial savings. Other advantages are lowered labour and training expenses. However, it’s crucial to recognise potential drawbacks of outsourcing to contractors, which include quality control challenges and a loss of in-house control.
Mitigating these drawbacks requires efficient contractor management, starting with a stringent selection process. From there, scopes of work must be clearly defined and contracts must prioritise performance and accountability. Vigilant performance tracking is essential, and further important measures include transparent communication and regular audits.
Asset data and historical information
It should be clear that most of the elements described above will result in a flood of data. The value of the data increases with time and spatial diversity resulting from recording it over extended periods of the WTG lifespan, and from multiple units installed across multiple landscapes.
Ownership, or at least unlimited access to such asset data, is highly important to windfarm asset owners. Whilst the data is most often handled by OEMs, the right of access should be determined proactively during design and procurement stages to ensure that the benefits can be reaped by the asset owner.
