Asset management encompasses a broad set of activities related to operating, monitoring, upgrading, and maintaining solar PV projects to optimize power production and returns on investment. Effective asset management is not a one-time effort, but rather an ongoing process that must adapt over decades to improve performance and mitigate risks.
Core responsibilities include continuous monitoring, reporting and analysis, preventive and corrective maintenance, troubleshooting, optimizing budgets, and planning for end-of-life equipment replacement or decommissioning. For large utility-scale plants, experienced third-party operators are often contracted to handle specialized asset management services. But owners of commercial, industrial, and rural solar installations also need robust plans to manage assets in the long-term.
Implementing monitoring and reporting
The foundation for asset management is comprehensive monitoring of solar plant equipment, production data, weather, and other parameters. A Supervisory Control and Data Acquisition (SCADA) system or dedicated software platform collects real-time telemetry from inverters, meters, sensors and other datapoints across the site. Monitoring Key Performance Indicators (KPIs) at both the system and component level provides transparency into overall plant health. Relevant parameters include AC/DC power output, converter efficiency ratios, soiling losses, array voltages, energy yield, availability, and equipment faults.
Data should be consolidated into user-friendly dashboards with timely alerts for any issues. Most systems allow setting performance thresholds, so anomalies are automatically flagged for investigation. Generating customized daily, weekly, and monthly monitoring reports is essential for tracking trends over time and identifying problems early. Reports should outline not just technical KPIs, but also financial factors like energy sales and O&M costs.
Implementing comprehensive maintenance programs
Informed by monitoring data, solar companies can cost-effectively maintain assets by implementing customized maintenance programs. Planned preventive maintenance involves proactive upkeep at scheduled intervals to minimize equipment degradation and weather-related damage. This includes activities such as PV panel cleaning, vegetation trimming, component replacement based on age (wear/tear) and software updates.
Corrective maintenance is unplanned repair or replacement of faulty components that have failed or are severely underperforming (informed by monitoring). Optimized maintenance plans align with equipment warranties and service level agreements. For example, supplier warranties may require biannual inverter inspections or filter changes. Technicians follow standardized procedures and document all maintenance via digital platforms. Failure to follow rigorous maintenance protocols will result in subpar asset performance.
Leveraging performance data analytics
Beyond day-to-day monitoring, regular analysis of historical plant data helps identify opportunities to improve operations and maximize electricity generation. Data analytics reveals insights around underperforming equipment, degradation trends across system components, correlations between weather patterns and output, and more.
Key performance metrics to analyze include performance ratio, temperature-corrected yield, inverter efficiency ratios, uptime percentage and component-level degradation rates.
Any arrays or inverters degrading quicker than expected may require replacement under warranty. Data-driven root cause analysis also helps diagnose why losses are occurring – for example, consistently low output in certain array zones could signify shading, soiling, or wiring issues. Statistical analysis can forecast future equipment maintenance needs and expenses based on observed degradation patterns.
Implementing advanced software and diagnostics
Powerful software and diagnostic tools are indispensable for effective asset management at scale across large portfolios. Cloud-based monitoring platforms provide centralized control rooms to seamlessly collect, process, analyze and act on equipment data enterprise-wide. Many systems integrate digital twins of assets, geographical information systems and advanced analytics like machine learning algorithms. These tools help automate functions like:
- Generating KPI reports, work orders and documentation
- Monitoring asset health and performance in real-time
- Forecasting production and flagging any underperformance
- Building predictive models to estimate future maintenance needs
- Optimizing O&M decision-making and budget allocation
Diagnostic tools like infrared (IR) / electroluminescence (EL) imaging, I-V curve tracing and drone thermography surveys help identify equipment defects and issues needing maintenance.
Proactive lifecycle management
To maximize uptime and availability, asset owners must follow proactive lifecycle management practices to keep assets operating at peak capacity over decades. This requires forecasting equipment replacement needs and proactively swapping out components nearing end-of-life based on age, warranty expirations, wear, and tear metrics, etc.
For example, inverters may need replacement every 7-10 years. Being proactive avoids emergency replacements and makes budgeting easier. Critical spare parts like inverters and transformers should be kept in inventory to minimize downtime.
Decommissioned modules and broken components must be disposed of properly within the laid-out rules and following the best ESG practices. Lifecycle management also requires monitoring the market to know when upgraded, more efficient technology becomes available for retrofits. Software tools can automate inventory and lifecycle tracking across
entire portfolios.
Expert personnel and standardization
Underpinning all asset management activities is having qualified personnel with the right skillsets. Engineers must possess expertise across PV systems, electrical standards, data science, analytics and more. Companies should invest in comprehensive training programs, certification, and educational partnerships to develop talent. Standardization of processes, documentation and KPI-tracking across assets is equally important for efficiency. This allows staff to apply lessons across
the portfolio.
Some best practices for asset management can be adopted from ISO 55000 standards. As solar proliferates globally, adequate investments in personnel and standardization will pay dividends.
Financial planning for asset management success
While rigorous asset management requires investments, the long-term cost savings and revenue benefits are substantial. Ongoing costs include expenses related to monitoring platforms, software tools, diagnostics, inventory, maintenance, personnel and more. However, this is dwarfed by the value of increased energy production, avoided downtime and emergency maintenance, and enhanced system lifetime.
Budget forecasting should account for the full range of asset management expenses over the plant’s lifespan. Cost-benefit analyses can quantify the financial upsides of specific practices. Financing instruments like operational expenses reserves ensure capital for O&M is available when needed. Bankability assessments may consider the strength of asset management plans and teams when structuring investments in solar projects as well.
Emerging trends and technologies
Several emerging trends and technologies show promise for further optimizing solar PV asset management:
- Robotics and drones such as automated panel cleaning robots can improve cleaning operations at large utility-scale plants.
- Artificial intelligence and machine learning for advanced monitoring, diagnostics, and analytics. Systems can continuously improve by learning
from data. - Digital twin technology uses virtual models of assets to optimize decision-making around maintenance and upgrades.
- Blockchain solutions enable seamless and secure data sharing across PV ecosystem participants to optimize collaboration.
- Extended reality tools like augmented reality provide technicians immersive access to asset information in the field to improve maintenance.
- Improved weather forecasting and climate modeling informs asset management by predicting risk, such as when de-soiling should occur.
India has now graduated from megawatts to gigawatts in terms of renewable energy production.” – Narendra Modi, Prime Minister of India
Harnessing AI and ML
Looking ahead, Artificial Intelligence (AI) and machine learning (ML) technologies are poised to transform solar PV asset management by enabling intelligent automation at scale. By analyzing vast troves of solar plant data, AI-based models can forecast degradation rates, predict faults and maintenance needs, optimize production, minimize risks, and generate insights unattainable via manual analysis.
Machine learning algorithms will enhance monitoring capabilities by learning continuously from operational data. AI will also augment human personnel by automating complex tasks like root cause analysis allowing staff to focus on higher value work.
Integrating augmented reality devices can provide technicians with AI-assisted maintenance and repair instructions in the field. On the software side, digital twin technology can simulate the effects of different O&M strategies on asset performance to optimize decision-making.
For solar companies managing portfolios of distributed assets, AI services on the cloud can provide economies of scale. Ultimately AI-powered tools will help drive down costs while maximizing solar energy production over decades of operation.
As India moves firmly towards its ambitious 2030 renewable energy vision, advanced asset management will be crucial for optimizing performance and profits for solar power producers and asset owners alike.
Mrigendra Rai holds an MBA in Power Management from the National Power Training Institute, Faridabad, and Bachelor’s in Electrical Engineering from College of Technology and Engineering, Udaipur. He is a seasoned professional with over 10 years of experience in the renewable energy industry. As Client Manager at WiseEnergy, he oversees a large global solar portfolio across Europe, US and India. He leads efforts to optimize technical, commercial and financial performance of the assets, ensuring operational excellence to maximize output, reduce costs and deliver strong returns.
