Project description:

Investigation of the possibilities for improving the quality and electrical compatibility of the electricity generated by hydropower plants

The proposed project is split in the tasks:

Hydropower has the primary task of providing a reliable sustainable supply of electricity, creating flexibility and stability by absorbing the peak load of the EES. It produces cheap, flexible and environmentally friendly energy and its development is based on the principle of multifunctional water and electricity regulation combined with comprehensive management, monitoring and optimisation of construction and operation processes. In this regard, it is highly relevant for the hydropower industry to establish a global national communication system for the administration of the electricity market and the balancing market, as well as subsystems for electricity quality control and electromagnetic compatibility, cybersecurity, sustainability and reliability, and a database of the energy characteristics and operational modes of hydropower facilities, etc.

Project aim and hypothesis:

The statistical models /SM/, extended statistical models /RMST/ and machine learning models /ML/
require a significant initial accumulation of experimental data to build adequate models suitable for analysis.
Subsequently, these experimental data, their processed statistical assessments, and the statistical and ML models
will be used for comparative evaluation of software models and simulation results.