Solar energy in the era of AI encompasses more than just solar panels; it also involves leveraging intelligence and digital services. Clean energy isn’t solely about generation; it’s about smart utilization. Given the current limitations in storage and surplus energy distribution, accurate prediction of energy fluctuations and dynamic arrangement of its usage are essential.
To effectively control production and energy consumption, digitizing processes requires extensive utilization of both historical and real-time data, including factors like weather conditions. This, coupled with the support of Artificial Intelligence, is essential for turning theoretical goals into practical solutions.
The path (or leap) from classic solar installations to energy-related digital services is exactly what our client a Sicilian company with hundreds of installations at companies nationwide – has bravely undertaken in recent months.
To do so, it has equipped itself with several new functional partners for the project: from an IoT provider for field data collection to data and AI consulting from Neodata.
The digital architecture designed by Neodata is based on 3 pillars and an additional new direction is to be developed in the coming months.
Digitization of every aspect of the business
The basis of the whole project is the availability of data. Every aspect of the company, from production to customers to suppliers, has been digitized.
A new generation of CRM and ERP has been introduced, and every process has become automatic and traceable. The side effect is also to have made a highly scalable company in which an increase in the number of projects does not generate an equivalent increase in workforce and personnel.
Monitoring of energy production
Every plant and every panel is monitored, and production data is collected and made available to customers. In addition, the production forecast is not only based on predefined forecasts, but the AI is capable of providing very precise indications over the next 72 hours based on historical data and weather forecasts.
Energy Consumption Monitoring
Through IoT installation on client systems (e.g., a factory), consumption data is collected for each area or various production processes.
AI uses this data to identify the areas of greatest impact and any energy waste, to suggest corrective measures and energy efficiency interventions, and to propose re-planning of activities based on the energy production forecast:
“Paradoxically, in this technological transformation we have undertaken, the technological aspect is the least relevant – says the Technical Designer Manager and project manager. Aspects such as the definition of a new strategy for the evolution of our company in terms of business but also in terms of internal organization, changes in every aspect of the daily work of our people and the relationship with our customers, are those that require more effort but fascinate us at the same time.“
Fundamental then was Neodata’s role above all in supporting the company in creating this new vision and putting it into the field, as the CEO of the company explains well:
“We sat down at the first meeting with Neodata with our idea of the future. Instead, we realized after a few minutes that there was a world of opportunities and business models that we had not considered, we understood that AI is not something about the future or other realities, but that it is here, immediately usable, even for our company and our business. We started a period of joint study, a consulting project that we can now call a full-fledged partnership. To have guided us through this cultural leap is what we are most grateful to the Neodata team.”
It is therefore difficult to see this as a project with a beginning and an end, but rather a constant evolution in which the various teams work together and periodically certain tools are introduced into the various processes and available to our clients.
Neodata AI Team
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