Energy performance certificates and smart readiness frameworks increasingly emphasise operational performance, supporting automated rooftop solar inspection and maintenance as part of long-term building asset management.
Andrej Lazarkov, Mechanical Engineer & Co-Founder at SunSweep
Jovan Redzic, Power & Automation Engineer & Co-Founder at SunSweep
Marko Chavdar, Software & Flight Systems Engineer & Co-Founder at SunSweep
(Note: Opinions in the articles are of the authors only and do not necessarily reflect the opinion of the European Union)
As building certification frameworks evolve beyond design-stage considerations towards operational performance and life-cycle assessment, they increasingly draw attention to the long-term performance of renewable energy assets. Modern building assessment frameworks, such as energy performance certificates (EPCs) and the Smart Readiness Indicator (SRI), are shifting focus from static design parameters towards continuous monitoring and long-term operational efficiency. This article examines how these developments can support a shift from reactive, labour-intensive maintenance towards more proactive approaches for rooftop solar installations.
For solar assets, maintaining performance requires more than the initial installation. Soiling, thermal anomalies and other faults can reduce energy yield and increase operational risk. Autonomous aerial systems combining thermal inspection and automated cleaning offer one potential response, allowing inspection and maintenance activities to be performed more frequently and with less direct exposure of workers to rooftop hazards. In this context, certification frameworks, smart readiness approaches and life-cycle costing can provide a basis for evaluating the operational value of such technologies.
For over a decade, the Energy Performance of Buildings Directive (EPBD) has provided a policy framework for improving the energy performance of buildings and supporting the integration of renewable energy. Building assessment schemes and certification systems such as EPCs, BREEAM and LEED have traditionally placed substantial emphasis on design characteristics and installed systems. However, as the European Union advances towards zero-emission buildings, attention is increasingly shifting towards how buildings perform in operation.
The recast EPBD and the development of the SRI illustrate this broader shift. Building performance is increasingly considered in relation to operational efficiency, monitoring, responsiveness and the ability of technical systems to adapt to changing conditions. For rooftop solar installations, this reinforces the importance of maintaining the performance of an asset after installation rather than treating commissioning as the end of the process.
Neither framework prescribes a specific maintenance technology; rather, both provide a context in which monitoring, maintenance and operational performance can be evaluated. While the SRI currently serves as a voluntary framework at the EU level under the EPBD, its methodology provides a valuable benchmark for the digital and operational readiness of building systems, particularly for commercial facilities.
A reduction in photovoltaic (PV) output caused by soiling, faults or degradation can affect the energy performance of a building and the economic return from its renewable assets. This makes maintenance strategy an important part of long-term asset management. Facility managers and engineering, procurement and construction contractors therefore need to consider not only installation costs but also inspection, maintenance, safety and performance over the asset's operational life.
Despite the engineering advances behind modern monocrystalline PV panels, real-world performance remains sensitive to environmental conditions. Two persistent factors affecting energy generation are soiling and thermal anomalies, both of which can reduce the effective performance of a rooftop array.
The magnitude of the resulting energy loss varies substantially with climate, local particulate matter, rainfall, panel inclination and other site-specific conditions. Reviews of the literature show that soiling can cause substantial yield losses and that the appropriate mitigation strategy is site-dependent (Ilse et al., 2019).
For building owners, the operational consequence is straightforward: persistent soiling can reduce renewable energy output and weaken the expected performance of the installation. The appropriate cleaning interval therefore depends on local conditions rather than a fixed annual schedule.
Rooftop arrays can also develop electrical and structural faults, including micro-cracks, diode failures and hotspots. Infrared thermography can help identify thermal abnormalities associated with certain faults and supports preventive inspection of PV modules and plants (IEC TS 62446-3:2017). Research on unmanned aerial vehicle (UAV)-based infrared inspection also shows that thermal imaging can be used to detect and localise abnormal PV modules, although inspection quality depends on sensor configuration, viewing geometry and environmental conditions (Bellezza Quater et al., 2022).
Traditionally, identifying and addressing these issues have relied heavily on manual inspection and maintenance. Cleaning commercial rooftop arrays can require access equipment, safety measures and considerable labour. As a result, cleaning may be scheduled infrequently, even where environmental conditions would justify more regular inspection or cleaning. More frequent, condition-based maintenance can provide a way of responding to this gap.
Autonomous aerial systems provide one potential link between the need for more consistent asset monitoring and the practical constraints of rooftop maintenance. Heavy-duty drones equipped with appropriate flight-control, imaging and cleaning systems can support a maintenance model in which inspection and cleaning are performed as recurring operational activities.
Drones equipped with radiometric thermal cameras and real-time kinematic positioning can survey commercial rooftop arrays and associate thermal observations with specific locations. Published studies have demonstrated UAV-based infrared thermography for detecting and localising thermal anomalies in PV modules, while also highlighting the importance of flight geometry, environmental conditions and image quality (Bellezza Quater et al., 2022; Tanda & Migliazzi, 2024). The resulting data can be used to support diagnostic reporting and, where appropriate, integration with digital asset records or digital-twin workflows.
The main value is not the drone itself, but the monitoring and operational data generated during inspection. Repeated surveys can help establish performance trends, identify anomalies earlier and support maintenance decisions based on observed asset condition.
Following inspection, specialised cleaning drones can be used to remove accumulated material from solar modules. Compared with conventional manual methods, automated systems can use controlled movement, calibrated brush systems and either targeted fluid application or dry-cleaning methods to perform cleaning while reducing the need for personnel to work directly on the rooftop. Automated and robotic approaches are increasingly recognised for their ability to maintain optimal glass transmittance while significantly reducing the occupational hazards of manual rooftop access (Hussain et al., 2017).
Where site conditions justify more frequent cleaning, automation can make shorter maintenance intervals more practical. The appropriate frequency should, however, be determined by factors such as season, local pollution, rainfall, soiling rates and the measured effect on energy yield. The objective is not simply to maximise cleaning frequency, but to maintain the array at an economically and technically appropriate level of performance.
Figure 1: The SunSweep autonomous aerial platform, illustrating the structural frame used for commercial rooftop deployment.
The transition from reactive manual maintenance to proactive maintenance can also be assessed through life-cycle costing. Building owners may initially view maintenance primarily as an operating expenditure, but a life-cycle approach considers how maintenance decisions affect energy generation, equipment longevity, safety, labour requirements and overall asset value.
For renewable assets, the economic case for automated maintenance depends on inspection and cleaning costs relative to the value of the energy yield that can be preserved. It may also include avoided access costs, reduced worker exposure to rooftop hazards and earlier identification of faults that could otherwise develop into more costly failures.
Building performance and sustainability frameworks can provide an additional context for this assessment. Where maintaining renewable generation contributes to a building's overall energy performance objectives, reliable inspection and maintenance can form part of a broader asset-management strategy. The precise effect on certification, financing or property value will depend on the applicable scheme, building and market conditions and should therefore be assessed on a case-by-case basis.
Autonomous systems may also reduce water consumption where targeted or water-free cleaning methods replace conventional water-based approaches. Deb and Brahmbhatt (2018), for example, describe an automated water-free cleaning system and report increased energy capture on regularly cleaned modules. Any quantified saving should be based on measured operational data for the specific equipment and cleaning methodology rather than treated as a universal performance figure.
| Operational metric | Traditional manual maintenance | Autonomous drone maintenance |
| Cleaning frequency | Typically scheduled at regular intervals | Potentially more frequent and condition-based |
| Water consumption | May involve hoses or pressure-washing equipment | Can use targeted fluid application, depending on system design |
| Safety risk | Personnel may require rooftop access, fall protection or other access measures | Inspection and cleaning can be remotely controlled, reducing direct rooftop exposure |
| Intervention time | Access and setup can extend intervention time | Automated deployment may reduce setup and intervention time, depending on site conditions |
| Energy-yield recovery | Outcome depends on cleaning quality and site conditions | Performance depends on the effectiveness and frequency of the automated cleaning process |
Table 1: Operational metric comparison. (Note: This table provides an indicative comparison. Actual operational metrics and economic viability will vary depending on site-specific environmental conditions, system scale and local labour costs.)
As the European building sector moves towards decarbonisation, building performance assessment increasingly emphasises on operational performance alongside design and installation. Renewable assets therefore need to be considered as long-term components of building energy systems, with inspection and maintenance forming part of their operational management.
Autonomous drone technology, combining thermal diagnostics with automated cleaning, offers one approach to addressing the practical challenges of maintaining rooftop solar installations. By enabling more frequent inspection and potentially reducing the need for direct rooftop access, these systems can support condition-based maintenance while generating operational data that can inform asset-management decisions.
Building certification does not, by itself, require autonomous maintenance. Rather, certification and smart readiness frameworks provide assessment criteria and performance-related objectives, while maintenance technologies can help manage the assets that contribute to those objectives. Life-cycle costing can then be used to evaluate whether the resulting operational benefits justify investment in autonomous maintenance.
For commercial buildings, this integrated approach – combining performance assessment, data-driven diagnostics, maintenance and life-cycle economics – can support more resilient and efficient management of rooftop renewable energy assets.
Ilse, K. et al. (2019). 'Techno-Economic Assessment of Soiling Losses and Mitigation Strategies for Solar Power Generation'. Joule, 3(10), 2303–2321. https://doi.org/10.1016/j.joule.2019.08.019
Hussain, A. et al. (2017). 'Implications of dust accumulation on photovoltaic panels and cleaning methods: A review". Renewable and Sustainable Energy Reviews, 69, 473-485. https://doi.org/10.1016/j.rser.2016.11.135
Deb, D. & Brahmbhatt, N. L. (2018). 'Review of yield increase of solar panels through soiling prevention, and a proposed water-free automated cleaning solution'. Renewable and Sustainable Energy Reviews, 82, 3306–3313. https://doi.org/10.1016/j.rser.2017.10.014
IEC TS 62446-3:2017. Photovoltaic (PV) systems – Requirements for testing, documentation and maintenance – Part 3: Photovoltaic modules and plants – Outdoor infrared thermography.
Bellezza Quater, P. et al. (2022). 'Automatic Inspection of Photovoltaic Power Plants Using Aerial Infrared Thermography: A Review.' Energies, 15(6), 2055. https://doi.org/10.3390/en15062055
Bellezza Quater, P. et al. (2022). 'Criticalities of the Outdoor Infrared Inspection of Photovoltaic Modules by Means of Drones.' Energies, 15(14), 5086. https://doi.org/10.3390/en15145086
Tanda, G. & Migliazzi, M. (2024). 'Infrared thermography monitoring of solar photovoltaic systems: A comparison between UAV and aircraft remote sensing platforms.' Thermal Science and Engineering Progress, 48, 102379. https://doi.org/10.1016/j.tsep.2023.102379
