Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources

Abstract

Power system security against attacks is drawing increasing attention in recent years. Battery energy storage systems (BESSs) are effective in providing emergency support. Although the benefits of BESSs have been extensively studied earlier to improve the system economics, their role in enhancing the system robustness in overcoming attacks has not been adequately investigated. This paper addresses the gap by proposing a new battery storage sizing algorithm for microgrids to limit load shedding when the energy sources are attacked. Four participants are considered in a framework involving interactions between a robustness-oriented economic dispatch model and a bilevel attacker-defender model. The proposed method is tested with the data from a microgrid system in Kasabonika Lake of Canada. Comprehensive case studies are carried out to demonstrate the effectiveness and merits of the proposed approach.

Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

“…According to (5), C + VaRt and C -VaRt need to be calculated to solve (5). However, it is often difficult to solve C +…”

“…In order to tackle the significant increase of uncertainties caused by high penetration of RESs, exploiting the flexible resources from generation-load-storage side is the key to maintaining power balance in real time [3]. The microgrids (MGs), which are composed of distributed generation (DG), energy storage (ES) and flexible load, provide an effective technical means for the comprehensive utilization of RESs [4], [5]. According to whether connected to the main grid, MGs can be classified into grid-connected MGs and islanded MGs (IMGs) [6].…”

Root event‐based dynamic space pruning algorithm for contingency screening of transmission system

“…When Loss(X) is not larger than Loss X root i , z 2 is forced to be 0 in constraint (20). z 1 is forced to be 1 in constraint (18). On the other hand, if Loss(X) is larger than Loss( X root i ), z 1 is forced to be 0 in constraint (19) and z 2 is forced to be 1 in constraint (18).…”

“…z 1 is forced to be 1 in constraint (18). On the other hand, if Loss(X) is larger than Loss( X root i ), z 1 is forced to be 0 in constraint (19) and z 2 is forced to be 1 in constraint (18). Thus, z 1 can act as the indicator function I(Loss(X)).…”

“…When the lower-level problem is linear and convex, the bilevel programming can be converted into a mixed integer linear programming (MILP) with the Karush-Kuhn-Tucher conditions or the duality theory [17]. Bilevel programming has been widely adopted in power system for quantifying the operational cost in the most severe scenarios such as generation planning [18], transmission expansion planning [19] and cyber-attack modelling [20]. With the 'leaderfollower' structure, two formulations of contingency screening were constructed to identify the critical N − k events [17].…”