Jinrui Guo

With increasing integration of intermittent renewable energy into power systems, effective frequency regulation is more urgent. Virtual power plants (VPPs), aggregating demand-side distributed resources, have great potential for frequency regulation. Nevertheless, deep cyber-physical interactions render VPPs susceptible to diversified cyber attacks, such as denial of service (DoS), false data injection (FDI), and deception attacks, which degrade frequency performance. Notably, existing research on VPPs’ frequency regulation largely ignores comprehensive impacts of such attacks. To address this gap, this paper presents a multi-agent system based cooperative power control method for distributed VPPs to ensure frequency regulation under diversified cyber attacks. First, we introduce a novel VPPs cooperative power control strategy to obtain optimal power references for VPPs and mitigate the combined effects of DoS and FDI hybrid attacks. It combines acknowledgment technique, event-triggered mechanism, and trust agents-based state screening and compensation method, enhancing reliability and economic efficiency of VPPs’ frequency regulation. Moreover, we propose a unique inverters dynamic power control scheme for accurate reference tracking of each internal unit within VPPs under deception attack. Based on a new event-triggered dynamic power control model with deception attack, it employs a specially designed dynamic event-triggered communication-based control strategy, ensuring robust tracking control and reducing communication burdens. Finally, simulation results demonstrate the validity and superiority of our presented method.

The virtual power plants (VPPs) formed by aggregating distributed energy resources on the demand side have high potential in frequency regulation of power systems. However, due to the complexity of real communication network, diverse communication issues, such as random packets loss and malicious cyber-attacks, may cause undesirable power dispatch and inaccurate dynamic control. This brings great challenges to the participation of VPPs in frequency regulation. To bypass these hurdles, we propose a cyber-physical integration design to facilitate VPPs frequency regulation in a real-time and reliable manner. First, we suggest a joint design scheme of VPPs power dispatch and communication resources allocation for packets loss under cloud-edge collaboration. That is, in the physical-layer, we propose the VPPs power dispatch under packets loss and in the cyber-layer, we develop the communication resources allocation strategy. This scheme aims to eliminate the packets loss impacts and thus determine accurate power dispatch. Second, we present a high reliable information transmission approach for preventing cyber-attacks under edge-end collaboration. Specifically, in the physical-layer, we implement dynamic control for responding to received regulation power and in the cyber-layer, we execute digital signcryption algorithm. Its objective is to improve system information transmission against cyber-attacks and thus ensure the accurate dynamic control. Finally, simulation results validate the feasibility and superiority of our proposed integration design.

Virtual power plants (VPPs) possess significant potential to support power systems’ frequency regulation through the aggregation of demand-side distributed energy resources. However, due to their heavy reliance on information technology, VPPs inevitably face diverse communication issues, such as cyber-attacks, privacy disclosure, and packet losses, which poses a serious challenge to ensure efficient power control for frequency regulation. To this end, this paper proposes a multiagent system-based VPPs cooperative power control strategy to achieve frequency regulation in a resilient, optimal, and scalable manner. First, a joint design scheme of VPPs cooperative power control and information interaction mechanism is presented to determine the optimal regulation power of VPPs for frequency regulation, where a consensus-based collaborative strategy is designed for cyber-attacks and a homomorphic encryption technology is introduced for privacy protection. Also, an event-triggered mechanism is adopted for communication burden. Second, a dynamic power control scheme for inverter is presented to enable the internal units of VPPs to track the power reference from the joint design scheme, in which an improved model predictive control method is suggested for packet losses to enhance control performance. Finally, simulation results reveal that, when confronting diverse communication issues, the proposed strategy exhibits significant effects in defending against cyber-attacks, ensuring privacy security, alleviating the communication burden, and achieving fast response, thus effectively facilitating VPPs frequency regulation.

Exploiting the potential for aggregation regulation of virtual power plants (VPPs) on the distribution network side to support the frequency regulation (FR) of the main grid is an essential research topic. However, in the process of implementing FR through communication networks, the imperfect communication may affect the rapid power support performance of the VPP. As such, we propose a cyber-physical collaboration based control method. In the physical layer, in order to effectively respond to power regulation instructions, a dispatch-based control strategy is presented according to the adjustment capacity of the VPP. In the cyber layer, a joint spectrum scheduling and relay power allocation method is developed to mitigate the impact of network uncertainty and meet communication demands. Finally, extensive simulation results verify the effectiveness of the proposed method.

In this paper, a cloud-edge-end collaboration-based control architecture is established for frequency regulation in interconnected power systems (IPS). A model predictive control (MPC)-based load frequency control strategy for the IPS with photovoltaic aggregation and energy storage systems under model uncertainty and communication delay is proposed. This can effectively overcome the issues of model uncertainty, random load perturbation and communication delay. First, a state space model for the IPS is constructed. To coordinate the frequency and contact line power fluctuation of the IPS, a robust controller based on the theory of MPC is then designed. Then, considering the communication delay of frequency response commands during transmission, a predictive compensation mechanism is introduced to eliminate the effect of delay while considering model uncertainty. Finally, simulation results verify the effectiveness and robustness of the proposed control strategy.