Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm

• Published in: Water resources management Vol. 30; no. 11; pp. 3995 - 4009
• Main Authors: Azizipour, Mohammad, Ghalenoei, Vahid, Afshar, M. H., Solis, S. S.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2016; Springer Nature B.V
• Subjects: Adaptation; Algorithms; Atmospheric Sciences; Civil Engineering; Earth and Environmental Science; Earth Sciences; Energy shortages; Environment; Evolutionary algorithms; Freshwater; Genetic algorithms; Geotechnical Engineering & Applied Earth Sciences; Hydroelectric plants; Hydroelectric power; Hydrogeology; Hydrology/Water Resources; Linear programming; Methods; Nonlinearity; Optimization; Optimization algorithms; Optimization techniques; Reservoirs; Seeds; Standard deviation; Studies; Water supply; Weeds; United States > US; Hydropower operation; Invasive weed optimization; Genetic algorithm; Particle swarm optimization
• ISSN: 0920-4741; 1573-1650
• DOI: 10.1007/s11269-016-1407-6

The optimal hydropower operation of reservoir systems is known as a complex nonlinear nonconvex optimization problem. This paper presents the application of invasive weed optimization (IWO) algorithm, which is a novel evolutionary algorithm inspired from colonizing weeds, for optimal operation of hydropower reservoir systems. The IWO algorithm is used to optimally solve the hydropower operation problems for both cases of single reservoir and multi reservoir systems, over short, medium and long term operation periods, and the results are compared with the existing results obtained by the two most commonly used evolutionary algorithms, namely, particle swam optimization (PSO) and genetic algorithm (GA). The results show that the IWO is more efficient and effective than PSO and GA for both single reservoir and multi reservoir hydropower operation problems.