TY - JOUR
T1 - A fully distributed asynchronous approach for multi-area coordinated network-constrained unit commitment
AU - Wang, Yamin
AU - Wu, Lei
AU - Li, Jie
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - This paper discusses a consensus-based alternating direction method of multipliers (ADMM) approach to solve the multi-area coordinated network-constrained unit commitment (NCUC) problem in a distributed manner. Due to political and technical difficulties, it is neither practical nor feasible to solve the multi-area coordination problem in a centralized fashion, which requires full access to all the data of individual areas. In comparison, in the proposed fully distributed approach, local NCUC problems of individual areas can be solved independently, and only limited information is exchanged among adjacent areas to facilitate the multi-area coordination. Furthermore, since traditional ADMM can guarantee convergence only for convex problems, this paper discusses several strategies to mitigate oscillations, enhance convergence performance, and derive good-enough feasible solutions, including: (1) a tie-line power-flow-based area coordination strategy is designed to reduce the number of global consensus variables; (2) different penalty parameters ρ are assigned to individual consensus variables and are updated via certain rules during the iterative procedure, which reduces the impact of the initial values of ρ on the convergence performance; (3) heuristic rules are adopted to fix certain unit commitment variables to avoid oscillations during the iterative procedure; and (4) an asynchronous distributed strategy is studied, which solves NCUC subproblems of small areas multiple times and exchanges information with adjacent areas more frequently within one complete run of slower NCUC subproblems of large areas. Numerical cases illustrate the effectiveness of the proposed asynchronous fully distributed NCUC approach, and we investigate key factors that would affect its convergence performance.
AB - This paper discusses a consensus-based alternating direction method of multipliers (ADMM) approach to solve the multi-area coordinated network-constrained unit commitment (NCUC) problem in a distributed manner. Due to political and technical difficulties, it is neither practical nor feasible to solve the multi-area coordination problem in a centralized fashion, which requires full access to all the data of individual areas. In comparison, in the proposed fully distributed approach, local NCUC problems of individual areas can be solved independently, and only limited information is exchanged among adjacent areas to facilitate the multi-area coordination. Furthermore, since traditional ADMM can guarantee convergence only for convex problems, this paper discusses several strategies to mitigate oscillations, enhance convergence performance, and derive good-enough feasible solutions, including: (1) a tie-line power-flow-based area coordination strategy is designed to reduce the number of global consensus variables; (2) different penalty parameters ρ are assigned to individual consensus variables and are updated via certain rules during the iterative procedure, which reduces the impact of the initial values of ρ on the convergence performance; (3) heuristic rules are adopted to fix certain unit commitment variables to avoid oscillations during the iterative procedure; and (4) an asynchronous distributed strategy is studied, which solves NCUC subproblems of small areas multiple times and exchanges information with adjacent areas more frequently within one complete run of slower NCUC subproblems of large areas. Numerical cases illustrate the effectiveness of the proposed asynchronous fully distributed NCUC approach, and we investigate key factors that would affect its convergence performance.
KW - ADMM
KW - Asynchronous
KW - Distributed NCUC
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U2 - 10.1007/s11081-018-9375-8
DO - 10.1007/s11081-018-9375-8
M3 - Article
AN - SCOPUS:85042215565
SN - 1389-4420
VL - 19
SP - 419
EP - 452
JO - Optimization and Engineering
JF - Optimization and Engineering
IS - 2
ER -