TY - JOUR
T1 - Priority-Considered Load Shedding in Economic Dispatch
T2 - Distributed Optimization Approach
AU - Fitri, Ismi Rosyiana
AU - Kim, Jung Su
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - This article studies two fundamental problems in power systems: 1) the economic dispatch problem (EDP) and 2) load shedding. In particular, convex optimization problems are formulated for both the EDP and the load shedding problem. For the EDP, an extension of the problem considering the transmission losses is presented. Furthermore, emphasis is placed on scheduling the load shedding when there exist some priorities on the loads. To solve the EDP and the load shedding problem in a distributed setting, we develop a method that combines the dual decomposition approach and the extragradient-based strategy. Notably, this work provides a fixed step size-based scheme for a strongly convex resource allocation problem considering general nonaffine coupled constraints. We show that the proposed algorithm converges to the optimal solution under the assumption that the underlying graph is undirected. In addition, the method has an ergodic convergence rate of O(1/k) in terms of the optimality residuals and the constraint violations. Simulation results are presented to demonstrate the effectiveness of the proposed optimization problems and distributed algorithm.
AB - This article studies two fundamental problems in power systems: 1) the economic dispatch problem (EDP) and 2) load shedding. In particular, convex optimization problems are formulated for both the EDP and the load shedding problem. For the EDP, an extension of the problem considering the transmission losses is presented. Furthermore, emphasis is placed on scheduling the load shedding when there exist some priorities on the loads. To solve the EDP and the load shedding problem in a distributed setting, we develop a method that combines the dual decomposition approach and the extragradient-based strategy. Notably, this work provides a fixed step size-based scheme for a strongly convex resource allocation problem considering general nonaffine coupled constraints. We show that the proposed algorithm converges to the optimal solution under the assumption that the underlying graph is undirected. In addition, the method has an ergodic convergence rate of O(1/k) in terms of the optimality residuals and the constraint violations. Simulation results are presented to demonstrate the effectiveness of the proposed optimization problems and distributed algorithm.
KW - Coupled constraints
KW - distributed optimization
KW - dual decomposition
KW - economic dispatch
KW - extragradient
KW - load shedding
KW - strongly convex program
UR - http://www.scopus.com/inward/record.url?scp=85146236200&partnerID=8YFLogxK
U2 - 10.1109/TCNS.2022.3231185
DO - 10.1109/TCNS.2022.3231185
M3 - Article
AN - SCOPUS:85146236200
SN - 2325-5870
VL - 10
SP - 1400
EP - 1411
JO - IEEE Transactions on Control of Network Systems
JF - IEEE Transactions on Control of Network Systems
IS - 3
ER -