Collaborative stochastic expansion planning of cyber-physical system considering extreme scenarios

In this paper, a collaborative stochastic expansion planning model of cyber-physical system (CPS) with resilience constraints is proposed. The model can reduce the coupling risk and enhance the resilience under extreme scenarios, from the perspective of the structural/functional coupling between the physical and cyber systems. The model is to collaboratively optimize expansion transmission line siting, expansion communication fibre siting, and service routing distribution to minimize total investment cost. Constraints are divided into conventional constraints and resilience constraints. In the resilience constraints, the impact of cyber failures on the dispatch strategy is analyzed, and the load shedding in stochastic scenarios is limited to guarantee the resilience of the planning scheme. Particularly, to reach a stable solution for the stochastic planning, a mixed scenario set is proposed based on the probabilistic typhoon model and the complex network theory. Finally, the model is solved by the progressive hedging (PH) algorithm. The case studies of the IEEE RTS-79 test system demonstrate that, compared with the traditional independent planning model, the model proposed in this paper performs better in limiting load loss and enhancing resilience under extreme scenarios.

Automated summary

In this paper, a collaborative stochastic expansion planning model of cyber-physical system (CPS) with resilience constraints is proposed, which can reduce coupling risk and enhance resilience under extreme scenarios. The model optimizes the siting of transmission lines, communication fibres, and service routing to minimize investment cost. Resilience constraints analyze the impact of cyber failures on dispatch strategy and limit load shedding in stochastic scenarios. The model is solved using the progressive hedging algorithm and case studies show its superiority over traditional independent planning models in limiting load loss and enhancing resilience under extreme scenarios.