DocumentCode :
187792
Title :
Co-optimization of electricity day-ahead market and steady-state natural gas system using Augmented Lagrangian
Author :
Biskas, Pandelis N. ; Kanelakis, N.G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear :
2014
fDate :
28-30 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
A coupled optimization of the electricity and gas systems is presented in this paper. The electricity problem involves a unit commitment with co-optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints. The gas problem involves a large-scale highly non-convex and non-linear problem structure, which is modeled as a Mixed Integer Non-Linear Programming model. The decomposition of the overall problem is based on the Augmented Lagrangian method. An iterative process is implemented, coordinating the two interdependent systems using an alternating minimization method, in which the Lagrange multipliers are updated using a subgradient method. The solution algorithm is evaluated using the Greek power and gas system, employing thirteen gas-fired units and fifty-three gas network nodes. The test results indicate the strong interdependence of the two systems, and demonstrate the efficiency of the presented algorithm in coordinating them.
Keywords :
concave programming; gas turbine power stations; integer programming; linear programming; minimisation; power generation dispatch; power generation scheduling; power markets; Greek power; Lagrange multipliers; augmented Lagrangian; augmented Lagrangian method; co-optimization; electricity day-ahead market; electricity problem; electricity systems; gas network nodes; gas systems; gas-fired units; iterative process; minimization method; mixed integer nonlinear programming model; nonconvex problem structure; nonlinear problem structure; steady-state natural gas system; subgradient method; system operational constraints; unit commitment; unit technical constraints; Electricity; Linear programming; Liquefied natural gas; Manganese; Mathematical model; Production; Augmented Lagrangian method; Mixed Integer Non-Linear Programming; day-ahead electricity market; natural gas network; unit commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
European Energy Market (EEM), 2014 11th International Conference on the
Conference_Location :
Krakow
Type :
conf
DOI :
10.1109/EEM.2014.6861223
Filename :
6861223
Link To Document :
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