Title :
A genetic algorithm modelling framework and solution technique for short term optimal hydrothermal scheduling
Author :
Orero, S.O. ; Irving, M.R.
Author_Institution :
Brunel Inst. of Power Syst., Brunel Univ., Uxbridge, UK
fDate :
5/1/1998 12:00:00 AM
Abstract :
A genetic algorithm is applied to the problem of determining the optimal hourly schedule of power generation in a hydrothermal power system. A multi-reservoir cascaded hydroelectric system with a nonlinear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is also taken into account. The main control parameters that affect the genetic algorithm performance are discussed and a summary of the theoretical basis of the genetic algorithm method is presented. It is shown that a multiple step genetic algorithm search sequence can provide the optimal hourly loading of the system generators
Keywords :
genetic algorithms; hydroelectric power stations; hydrothermal power systems; power system planning; scheduling; thermal power stations; control parameters; genetic algorithm; hydrothermal power system; multi-reservoir cascaded hydroelectric system; multiple step GA search sequence; net head; optimal hourly loading; planning optimisation; short-term power generation sheduling; water discharge rate; water transport delay; Genetic algorithms; Optimal scheduling; Power generation; Power generation economics; Power system control; Power system modeling; Power systems; Reservoirs; Water resources; Water storage;
Journal_Title :
Power Systems, IEEE Transactions on