Amid the current disruption caused by Covid-19 and the oil price war, solar power is demonstrating its resilience. At the height of the epidemic in China during January and February this year, solar was the only form of energy generation that saw an increase in production from the previous year – rising by 12%.
In this context – and in this new world of remote working and social distancing – maintaining solar electricity generation through remote monitoring has become increasingly vital, with asset managers making every effort to keep solar assets running and optimise performance.
In Europe, ambitious clean energy targets have driven renewables development in the region, attracting new manufacturers, developers and investors into the space. Though competition is good for the industry, multiple data formats are not, and data managers need to be able to collect and organize different data sets into a comparable format, or face the risk of increased asset downtime, lower life expectancy and reduced rate of return.
With industry portfolios getting bigger and containing multiple technologies, often across wind and solar assets, the inability to efficiently gather data is becoming a challenge for portfolio owners. Without the ability to fully understand data, identifying where issues lie becomes harder, which matters when you don’t know whether the problem is affecting a single panel or an entire array. The potential lost energy is therefore incalculable.
The question of how, why, where and when assets are losing productivity can therefore only be answered by creating data which is understandable, comparable and high enough quality to identify when these issues will occur. Despite data management proving a significant headache to everyone from local data managers to international portfolio owners, little has been done to rectify the situation. The question is why?
Up until relatively recently, common consensus had concluded that solar was less complex to manage than wind due to its fewer moving parts. Though this has since been proved a myth, the pace of digitalization in the European solar industry has failed to keep up with wind and many solar data management platforms continue to lack the sophistication of wind data management systems.
Whilst the wind industry has come a long way in terms of quality standards and data collection – from the hardware installed on-site, to the communication protocols needed to access the data, and finally the resolution of the data – the subsequent lack of high-end operations and maintenance (O&M) equipment and service platforms in the solar industry has had a direct impact on asset performance. Research indicates that losses due to inefficiencies can account for up to 27% of the energy export at grid meter level (Lilo-Bravo et al., 2018).
High levels of complexity
Greenbyte’s research suggests that causes of energy loss in the solar PV sector usually fall within two categories, (1) failures and (2) inefficiencies. This may sound simple, but the greater number of internal electrical components – and therefore parts that can fail – in solar panels compared to wind turbines adds a higher level of complexity when identifying and preventing or mitigating internal issues leading to energy loss.
Component failures and inefficiencies can be caused by a multitude of factors, both internal and environmental, including: (1) the electrical grid, wiring and inverter/transformation stations and (2) module degradation, shading and soiling effects, tracker misalignment, inverter overheating and wiring.
On top of this, each solar site needs to be managed individually in order to fully optimise assets, with all of its unique characteristics taken into consideration, including its geographical location, brand of modules and the quality of the underground installation, amongst others.
The generation of quality data is key to accurately breaking down losses in solar PV plants, but despite the sector being active for over 15 years many players are still unsure whether their data is of high enough quality to add value to company decision making – though a certain level of matureness has been achieved in Europe.
Individual data collection methods – and even industry standards – abound, but the sector has not successfully evolved to the point where data has become easily comparable across different formats. With over 900 inverter component manufacturers alone, this presents a challenge when it comes to gathering, harmonizing, and cleaning data to enable more complex analysis methods – such as machine learning.
Data reliability issues also commonly stem from installed onsite hardware – such as weather sensors and power generation equipment. As the installation of such hardware is determined by their capex and estimated cost/benefit ratio however, the number and quality can significantly vary across solar sites, potentially leading to insufficient data coverage and collection from solar assets.
Preventing solar PV energy losses
Whilst some of these challenges are inherent to the industry, data management software which can create comparable, high quality data formats are already available on the market. For example, technology-agnostic ‘datahubs’ such as Greenbyte can pull together and map multiple data formats onto a global signal list to create a unified data set on hundreds of data points and alert types.
To enable this, cloud-based software platforms support a host of data intake techniques including – but not limited to – SCADA, FTP uploads and API. In this way, owners and asset managers are able to view data from different types of solar sites and technologies under the same data type, scaling, and units – removing the need to standardize equipment or post-process data.
In addition, specialised software platforms can fully configure and map new assets to drive the existing workflow of monitoring and analysis. Data, KPIs, and alerts then match the client's existing data set to drive quick and seamless adoption of new assets into a client's existing monitoring and asset management workflow.
Multiple solar industry standards on data management, non-compatible software and misunderstandings surrounding the complexity of solar technology have left the solar operations and maintenance industry unable to fully prevent or mitigate the challenges resulting in energy losses.
With data managers now handling larger and more technologically diverse solar portfolios – where rapid identification of issues plays a crucial part in order for projects to meet their desired return on investment – in an increasingly volatile market, it is particularly important now more than ever for the industry to mitigate these issues through sophisticated software platforms.