One of the rapidly growing fields of electricity generation is photovoltaics, a method that allows the conversion of solar radiation into electricity through the use of photovoltaic panels.

“Energy from the sun”, as this term is commonly used, is the simplest method of obtaining electricity from renewable sources, which is currently undergoing dynamic development. Investors are eagerly interested in this way of investing their funds, because with small operating costs, virtually maintenance-free operation, provide stable income for a long time.

Photovoltaic power plants are subject to different types of damage, and their aging processes are heterogeneous and often unpredictable. Some plants degrade much faster than other plants built at the same time. The photovoltaic power plant, as a complex technical installation, is subject to failures and damages during its operation, which causes irreversible and often significant financial losses.

The efficiency of the control process of an operating PV power plant, in order to ensure the best results in the form of stable energy production, requires from the monitoring tools the highest accuracy and high stability of operation. For this purpose, our OpenEye SCADA platform, together with the integrated IoT PV controller, has been built using modern technologies applied in the growing IoT (Internet of Things) market sector.

The OpenEye SCADA solution, together with the proprietary IoT PV Monitor industrial controller, is the answer to the market’s need to ensure the technical performance and energy efficiency of PV power plants. As a result, we are able to retrieve, process and store, in real time, information acquired with maximum frequency, from all key components of the power plant.

• Detection of permanent and temporary inverter faults
• Detection of inverter instability
• DC / AC conversion efficiency of inverters
• Auto inventory of inverters, including their software versions
• Location of damage to PV panel wiring
• Location of PV panel string fuse blown
• Locate damaged panels to an accuracy of approximately 20 pieces
• Monitoring the efficiency / performance of PV panel groups
• Long-term monitoring of the aging process of PV panels