Cyber‐attack has become one of the main threats to the safe operation of the load control system in the distribution network. Currently, a large number of methods are developed to detect cyber‐attacks. However, most of these methods make decisions based on information from a single cyber layer or physical layer. If the decision is wrong, there is no way to verify it. Therefore, if the separate decisions can be made in the cyber layer and physical layer at the same time, and a final judgment is received throughout the two decisions, then the accuracy and credibility of cyber‐attack detection can be improved. First, the particle swarm optimization‐based backpropagation neural network is adopted to detect attacks in the cyber layer, at the same time, the criteria importance though intercrieria correlation‐based grey relational analysis is adopted for the assessment of node risk level in the physical layer. Then, based on the incidence matrix model between the cyber layer and the physical layer, a crosscheck mechanism is proposed to detect the cyber‐attack through the verification of the two decisions. Finally, taking the IEEE 33‐node system as an example, the validity of the proposed method to detect the denial of service attack is verified.
Leveraging distributed resources to enhance distribution network (DN) resilience is an effective measure in response to natural disasters. However, the willingness and economy of distributed resources are typically ignored. To address this issue, this paper proposes an emergent trading framework that uses parking lots (PLs) as resources to provide power support to critical loads (CLs) in a blackout due to typhoons. In this trading framework, an evolutionary Stackelberg game‐based trading model is established to consider maximizing all stakeholders’ economic benefits, considering possible resources isolation under typical fault scenarios caused by typhoons, and a benefit allocation mechanism is proposed for all stakeholders to motivate all stakeholders to participate in the trading. This framework allows that critical loads could reduce their load loss, parking lots could receive adequate compensation to stimulate them to participate in the trading, and distribution utility could ensure its economic benefits. Furthermore, an iterative evolutionary‐Stackelberg solution set‐up is applied to obtain the equilibria of the proposed framework. Simulation results on the modified IEEE 69‐bus test system and IEEE 123‐bus test system reveal the validity of the proposed method.
Natural disasters have posed great challenges to the power system in
recent years. This paper proposes an emergent trading framework that
uses parking lots as resources to provide power support to critical
loads in a blackout due to typhoon. Firstly, a distribution line fault
model under typhoon is established to create possible fault scenarios
with the typhoon trajectory data. Subsequently, an evolutionary
Stackelberg game-based trading model is proposed to maximize all
stakeholders’ economic benefits while reducing the critical load loss
for all chosen scenarios, leading to enhanced system resilience. At the
same time, a benefit allocation mechanism and free-riding penalty are
incorporated in the framework to motivate players’ participation while
limiting the negative effect of free-riders. Further, an iterative
evolutionary-Stackelberg solution set-up is applied to obtain the
equilibria of the proposed framework. Finally, a modified IEEE 69-bus
system is used to illustrate and validate the proposed framework.
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