Paper Info
Title
Electricity generation cost reduction for hydrothermal systems with the presence of pumped storage hydroelectric plants
Abstract
This paper presents the applications of novel metaheuristic algorithms including equilibrium optimization (EO), coot optimization, and slime mould optimization together with three Particle swarm optimization variants for optimal power generation cooperation of power systems with conventional hydroelectric power plants, thermal power plants and especially pumped-storage hydroelectric plants (PHPs). Three different power systems are applied to run these algorithms to prove that PHPs have a significant contribution to the generation cost reduction. In the first two systems, there are not inflows to the upper reservoirs of the PHPs and these plants only produce electricity by using pumped water. In the third system, inflows to PHPs are considered. The requirement is that the volume of reservoir at the beginning and the end of a day must be the same. However, the generation cost for the cases with the operation of PHPs is much less than other cases without the PHPs or without the pump mode of PHP. About the generation cost of three systems, PHPs support to reach the saving cost of $1,222.1998, $89,091.16, and $94,449.2 corresponding to 0.45%, 3% and 3.4%, respectively. So, the PHPs should be run in power systems. Among the six applied methods, EO is the best since it can reach less cost than others from higher than 2% to under 8%. Hence, it is recommended that EO is a potential method for finding optimal operation parameters of power systems with the PHPs.
Year
DOI
Venue
2022
10.1007/s00521-022-06977-0
Neural Computing and Applications
Keywords
DocType
Volume
Equilibrium optimization, Hydroelectric plants, Thermal power plants, Generation cost
Journal
34
Issue
ISSN
Citations 
12
0941-0643
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
Phu Trieu Ha100.34
Dao Trong Tran200.34
Thang Trung Nguyen301.35