Solar power plant forecast with AI and managing software - from 2018 to 2020

Solar power plant forecast with AI and managing software - from 2018-2020

Software solution for implementing the planned production of solar power plants - 2018-2020

The solution supports the operation of solar power plants in the following areas:  

• Calculation module
• Neural network - AI - calculation for expected production based on weather data.
• Monitoring module - approx. Status check of 8,000 devices with a 5-minute check cycle. 
• Access management - Create your own user groups by assigning a function.
• Task / maintenance management - Management and follow-up of tasks related to power plant equipment.

The scheduling obligation of the power plants means that the expected energy production during the given time unit must be predicted for MAVIR.The system performs route planning and related administrative tasks automatically, with the help of a neural network. Currently, the input parameters are the weather data. The output parameter is the % value of expected radiation.The system provides an effective background for carrying out servicing tasks, possibly faulty elements can be traced, and the physical condition of the systems can be checked.

Its monitoring system operates on a schedule, every 15 minutes. Its tasks are reading out and storing data; recognition of detectable errors; detection of inverter faults; FTP, VPN connection scheduled check; Scheduled control of access to data providers.

Main strengths

• Distributed system with distributed computing modules: 4 application server instance, 1 data server instance 
• Robust, redundant design at the level of operational logic and equipment (Multiple negative branch management, 4-fold redundancy, fail-safe operation, approx. 120 server units in total)
• A large number of cooperating systems and devices: 219 plant connected at the end of project.
• Deployment pipeline:
  
  

MAVIR interface module

The system for estimating the production of solar power plants and providing data to MAVIR.

Main strengths:

• Realization of calculation (expected energy production) based on the various parametersVisual display of production data
• Cloud-based technologies