A Robust Energy Storage System Siting Strategy Considering Physical Attacks to Transmission Lines

Protecting Power Transmission Systems against Intelligent Physical Attacks: A Critical Systematic Review

“…Methods for Minimzing Load Interruptions [2] Lower level of a bi-level optimization model after the attack [6] First objective of a bi-objective model of a transmission expansion planning problem [7] Lower level of a bi-level optimization model by reconfiguration after the attack [13,[19][20][21] The objective function was to minimize the amount of total interrupted loads. [15] Lower level of a tri-level optimization model during the restoration process [22] First objective of a tri-objective model of a transmission expansion planning problem [23,24] Upper level of a tri-level model of a transmission expansion planning problem [25] First objective of a bi-objective model of a transmission expansion planning problem [26] Lower level of a tri-level optimization model during the restoration process [27] Upper and lower levels of a tri-level optimization model for before and after the attack [28] The first objective of a bi-objective optimization model for a resiliency problem [29] The system defender minimizes the load interruption after the attack at the lower level of a tri-level optimization model [30] The system defender minimizes the load interruption after the attack at the lower level of a tri-level optimization model [31] Lower level of a tri-level optimization model after the attack [32] Lower level of a tri-level optimization model after the attack…”

“…Furthermore, in [36], the unserved load costs for both the power and gas loads have been considered as $1000/MWh and $200/Sm 3 (standard cubic metric), respectively. Although, some other research studies [12,14,15,23,24,26,31,37,38] have considered unserved load cost, its value has not been mentioned.…”

“…In [13], fourteen time stages have been considered to study the impact of attacking lines on cascading failure phenomenon. In some other research studies, a 24-h horizon has been considered to analyze the impact of attacking TLs [15,26]. Additionally, in [6], 4 × 24 h (four sample seasonal days) have been considered.…”

“…[2] 3 time periods [6] 96 time periods (for four seasonal days of the year) [13] 14 stages [15] 24 time periods (for hourly periods of the day) [26] 24 time periods (for hourly periods of the day) [28] 3 time periods (for base load, peak load, and mean load in a typical day of year) [30] 3 time periods [33] 12 time periods (for 12 months of the year) [36] 4 time periods (each time period was 6 h in a 24-h horizon) [43] 6, 8, and 5 time period respectively for case studies I, II, and III…”

“…Some studies have dealt with four types of uncertainties, namely uncertainty in the maximum number of TLs that are defended, success probabilities of attacks, defense budget, and load demand [2] and the uncertainty in attack resources, defense resources, cyber-attack resources, and the proportion of post-allocated DG units [29]. In [26], five uncertainty sources, i.e., attack budget, attack time, and maximum number of concurrent attacks (maximum number of TLs to be simultaneously attacked), the total capacity of energy storage to be installed, the maximum number of buses for energy storage installation have been taken into account.…”