The renewable energy sector is today on the verge of an unprecedented expansion phase. Solar energy plays the lion’s role in the new era of zero carbon emissions because of its abundance and because its exploitation becomes every year more and more convenient thanks to technology. However, owing to the nature and the number of factors that influence the performance of photovoltaic systems (availability of solar radiation, wear/reliability of the system components, maintenance etc.) many aspects related to their exploitation are still widely perfectible today and they present great earning opportunities for those who invest in renewables. The keywords in this sense are: optimization and forecasting. In particular, thanks to Big Data and technological evolution, predictive analysis is the one that promises the greatest results today thanks to AI and Deep learning.
Automate the photovoltaic ecosystem and improve ROI
Perhaps it may seem futuristic but the use of artificial intelligence is not exactly new. An interesting study by McKinsey shows how AI finds space across many industrial sectors, how it generates greater profits for the companies that use it and how it can increase the competitive advantage. The key applications of Artificial Intelligence in the photovoltaic sector concern three main categories: forecasting, efficiency and energy accessibility.
Artificial Intelligence takes advantage of the enormous flow of data from the sensor present in photovoltaic systems and allows you to create specific analysis algorithms which are capable of examining the production of the plant field and comparing it with reference models useful for improving its performance; an example are the monitoring platforms that allow prescriptive diagnostics optimization.
These technological systems, made up of specialized software and hardware, allow not only to identify the underperforming parts of photovoltaic systems, but also to direct the maintenance choices on the best cost-benefit ratio. Unlike a normal monitoring system, solutions equipped with Artificial Intelligence are able to identify the problem, analyze the causes through an RCA (Root Cause Analysis) and suggest the maintenance actions that will lead to the ROI objective required by the property. Thus it will maximize profits. Furthermore, thanks to Deep Learning, these systems are able to learn from the choices made in the past by technicians, predict cost trends and propose corrective actions by providing O&M staff with the tools necessary for targeted and above all efficient interventions. If then the KPI on which the asset manager focuses on is not the ROI but, for example, it is the PR (Performance Ratio), the system equipped with Artificial Intelligence can provide analytical answers using the same database, automating the processes and guaranteeing enormous potential efficiency and especially gain.
Big data are revolutionizing the world of asset management in the photovoltaic industry likewise in other sectors. The growing availability of digital information, especially in an unconventional format, is changing the way managers make investment decisions and monitor their portfolios. From this endless mass of bytes, useful indications can be obtained to anticipate market trends, to predict the place and the time of maintenance and to invest in plants with the greatest growth potential in the secondary market. All this is possible thanks to the use of Artificial Intelligence with which the most modern monitoring and remote control systems are equipped. It is an epochal change just at the beginning, but it is capable of making a difference for those who seize its potential.