Optimisation of hybrid power system with on site meteo station with integrated prediction methods

Acceleration of dynamics in all areas of the economy and especially in the energy sector create challenges to focus on upgrade, acceleration and increasing precision of optimisation processes in energy sector as well. For example, climate changes introduce heightened fluctuations in weather patterns, posing significant challenges to the operational efficiency of renewable energy systems. In this context, the optimal operation of hybrid systems, designed to work complementarily with various renewable sources, becomes critical. The paper discusses about middle-term and real-time optimisation in three parts: (a) prediction of meteorological profiles together with prediction of consumer’s behaviour based on specialised artificial neural networks, (b) real-time techno-economic optimisation and planning models based on genetic algorithms, (c) optimisation with energy accumulators. The world unique approach of optimisation described in this paper relays on the fact, that all algorithms including artificial intelligence methods are implemented and realised in PLC environment (OT) not in database systems (IT). Nowadays, programmable logic controllers PLC (or programmable automation controllers PAC) as basic element of overall control system represents most reliable, safety and real-time environment for control of energetic systems. It is not negligible fact, that these three parts of this paper are designed according to the primary principles of cybernetics and whole system presented here, we will name as ECOGI. The ECOGI was upgraded and extended by research and development project from EU funds (1) and implemented into practise in the countries of Central and Eastern Europe. The paper also presents case study of ECOGI implementation in one of the Slovakian enterprise. From many years of experiences some conclusions are mentioned here.