TY - JOUR
T1 - Preventing Outages under Coordinated Cyber-Physical Attack with Secured PMUs
AU - Huang, Yudi
AU - He, Ting
AU - Chaudhuri, Nilanjan Ray
AU - Porta, Thomas F.La
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - Due to the potentially severe consequences of coordinated cyber-physical attacks (CCPA), the design of defenses has gained significant attention. A popular approach is to eliminate the existence of attacks by either securing existing sensors or deploying secured PMUs. In this work, we improve this approach by lowering the defense target from eliminating attacks to preventing outages and reducing the required number of PMUs. To this end, we formulate the problem of PMU Placement for Outage Prevention (PPOP) under DC power flow model as a tri-level non-linear optimization problem and transform it into a bi-level mixed-integer linear programming (MILP) problem. Then, we propose an alternating optimization framework to solve PPOP by iteratively adding constraints, for which we develop two constraint generation algorithms. In addition, for large-scale grids, we propose a polynomial-time heuristic algorithm to obtain suboptimal solutions. Next, we extend our solution to achieve the defense goal under AC power flow model. Finally, we evaluate our algorithm on IEEE 30-bus, 57-bus, 118-bus, and 300-bus systems, which demonstrates the potential of the proposed approach in greatly reducing the required number of PMUs.
AB - Due to the potentially severe consequences of coordinated cyber-physical attacks (CCPA), the design of defenses has gained significant attention. A popular approach is to eliminate the existence of attacks by either securing existing sensors or deploying secured PMUs. In this work, we improve this approach by lowering the defense target from eliminating attacks to preventing outages and reducing the required number of PMUs. To this end, we formulate the problem of PMU Placement for Outage Prevention (PPOP) under DC power flow model as a tri-level non-linear optimization problem and transform it into a bi-level mixed-integer linear programming (MILP) problem. Then, we propose an alternating optimization framework to solve PPOP by iteratively adding constraints, for which we develop two constraint generation algorithms. In addition, for large-scale grids, we propose a polynomial-time heuristic algorithm to obtain suboptimal solutions. Next, we extend our solution to achieve the defense goal under AC power flow model. Finally, we evaluate our algorithm on IEEE 30-bus, 57-bus, 118-bus, and 300-bus systems, which demonstrates the potential of the proposed approach in greatly reducing the required number of PMUs.
UR - http://www.scopus.com/inward/record.url?scp=85128280876&partnerID=8YFLogxK
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U2 - 10.1109/TSG.2022.3165768
DO - 10.1109/TSG.2022.3165768
M3 - Article
AN - SCOPUS:85128280876
SN - 1949-3053
VL - 13
SP - 3160
EP - 3173
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 4
ER -