MODELLING, SIMULATION AND OPTIMIZATION OF HYDROPOWER PLANTS CASCADE BY GENETIC ALGORITHMS

摘要

Hydroelectric power plants (HPP) are playing a major role in any modern (competitive) electrical energy system. The hydropower systems have certain advantages compared to other energy production systems: they have the ability to accumulate hydraulic energy in reservoirs for different periods of times; they have the fastest response time in case of energy demand; they provide reliable and quality grid services (frequency regulation, voltage regulation an reactive energy balancing); the produced energy is competitive on any energy market based on financial targets. This paper presents a new method to improve the contribution of a cascade of power plants on a spot market. The above result was obtained by the aid of an optimization algorithm having as main objective to maximize the generated income by planning the energy production in high demand hours. To prove the ability of this original algorithm, a comparison for two operation scenarios is presented, showing the influence of the market prices. The comparison is based on the same hydrological regime, the same availability of the power plant cascade, and offers two results for different optimization objectives: maximizing the energy production or maximizing the generated income. The two objectives are significantly different: maximizing the energy produced requires keeping the level in the lakes at the highest availability in order to have maximum head and therefore working as much as possible at rated power of turbines, where maximizing the generated income requires to accumulate water during trading intervals where the energy is cheaper based on market data and generate maximum energy during trading intervals with high prices.