Open AccessOptimal short-term hydro-thermal scheduling using multi-function global particle swarm optimization
Author(s) -
Surender Reddy Salkuti
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v20.i1.pp537-544
Subject(s) - particle swarm optimization , mathematical optimization , thermal , thermal power station , scheduling (production processes) , electricity generation , power balance , computer science , power (physics) , automotive engineering , environmental science , engineering , mathematics , electrical engineering , meteorology , physics , quantum mechanics
An optimal short-term hydro-thermal scheduling (ST-HTS) problem is solved in this paper using the multi-function global particle swarm optimization (MF-GPSO). A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, power generation and net head is considered in this paper. The ST-HTS problem determines the optimal power generation of hydro and thermal generators which is aimed to minimize total fuel cost of thermal power plants during a determined time period. Effects of valve point loading and prohibited operating zones in the fuel cost function of the thermal power plants is examined. Power balance, reservoir volume, water balance and operation constraints of hydro and thermal plants are considered. The effectiveness and feasibility of MF-GPSO algorithm is examined on a standard test system, and the simulation results are compared with other algorithms presented in the literature. The results show that the MF-GPSO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques reported in the literature.