%0 Journal Article
%T Day-Ahead Economic Dispatch of Coupled Desalinated Water and Power Grids with Participation of Compressed Air Energy Storages
%J Journal of Operation and Automation in Power Engineering
%I University of Mohaghegh Ardabili
%Z 2322-4576
%A Jabari, F.
%A Mohammadi ivatloo, B.
%A Bannae Sharifian, M. B.
%A Ghaebi, H.
%D 2019
%\ 05/01/2019
%V 7
%N 1
%P 40-48
%! Day-Ahead Economic Dispatch of Coupled Desalinated Water and Power Grids with Participation of Compressed Air Energy Storages
%K Day-ahead economic dispatch
%K mixed integer nonlinear programming (MINLP)
%K combined desalinated water and power (CDWP) generation systems
%K compressed air energy storage (CAES)
%R 10.22098/joape.2019.4533.1356
%X Nowadays, water and electricity are closely interdependent essential sources in human life that affect socio-economic growth and prosperity. In other words, electricity is a fundamental source to supply a seawater desalination process, while fresh water is used for cooling this power plant. Therefore, mutual vulnerability of water treatment and power generation systems is growing because of increased potable water and electricity demands especially during extremely-hot summer days. Hence, this paper presents a novel framework for optimal short-term scheduling of water-power nexus aiming to minimize total seawater desalination and electricity procurement cost while satisfying all operational constraints of conventional thermal power plants, co-producers and desalination units. Moreover, advanced adiabatic compressed air energy storage (CAES) with no need to fossil fuels can participate in energy procurement process by optimal charging during off-peak periods and discharging at peak load hours. A mixed integer non-linear programming (MINLP) problem is solved under general algebraic mathematical modeling system to minimize total water treatment cost of water only units and co-producers, total fuel cost of thermal power plants and co-generators. Ramp up and down rates, water and power generation capacities and balance criteria have been considered as optimization constraints. It is found that without co-optimization of desalination and power production plants, load-generation mismatch occurs in both water and energy networks. By incorporating CAES in water-power grids, total fuel cost of thermal units and co-producers reduce from $1222.3 and $24933.2 to $1174.8 and $24636.8, respectively. In other words, application of CAES results in $343.9 cost saving in benchmark water-power hybrid grid.
%U https://joape.uma.ac.ir/article_739_97e1cee18fc1b66b459261ba689a034a.pdf