This study proposes a cooperative secondary voltage and frequency control strategy to reduce the number of controller updates by using an event-triggered approach. The proposed approach is applied to the secondary control that will offset primary control deviations in islanded microgrids with limited computation resources. The controller updating mechanism considered here is event-triggered which judges whether a certain measurement error has reached the event-triggered condition (ETC) associated with the norm of a function with a standard state. We consider two secondary control options to form an ETC, which include a centralized strategy in which an auxiliary controller would collect all agents’ states, and a distributed control strategy which only require the neighboring agents information. The corresponding stability and convergence analyses are presented and simulation results for an islanded microgrid test system consisting of four distributed generators (DGs) are provided. The simulation results validate the effectiveness of the proposed control strategies and show that the proposed strategies based on an event-triggered approach can dramatically reduce controller updates.

This paper presents a perturbation estimation based robust load frequency control (LFC) scheme for power system subject to random time-delay attack. Perturbation term is defined to describe the measurement deviation caused by random time-delay attack. Besides, perturbation observer is designed to estimate the system perturbation. The load frequency controller is compensated based on the perturbation estimation to mitigate the random time-delay attack and ensure the stable operation of power system. Case studies are undertaken on a two-area LFC model to demonstrate the control performance of the scheme.

This article presents an observer-based decentralized detection and mitigation (ODDM) scheme for the interconnected power system subject to multiarea multichannel false data injection attacks (FDIAs). In the ODDM scheme, the FDIAs on the measurement channel and control channel of power system are modeled as unknown input and unknown output, respectively, which are described by extended states of the system. A state and attack observer (SAO) is developed using local measurements for each control area of power system, so as to simultaneously estimate the system states and attack signals in the presence of model uncertainties. During the occurrence of malicious attacks, the attack estimations provided by observer can automatically detect the FDIA on each control area. Besides, the load frequency control system is reconfigured by attack compensation based on the attack estimations of observer, thus achieving the mitigation of multiarea multichannel FDIAs. Case studies are undertaken on a three-area interconnected power system model under the conditions of single attack, multiple attack, and parameter variations to validate the performance of the proposed ODDM scheme.

This paper compares the performance of unified power flow controllers (UPFCs), static var compensators (SVCs), and static compensators (STATCOMs) in commutation failure immunity (CFI) improvement of line-commutated converter-based high-voltage direct-current transmission (LCC-HVDC) systems. Theoretical analysis is presented to investigate the capacity requirements of SVCs, STATCOMs, and UPFCs to maintain the inverter-side ac voltage in the cases where three-phase faults occur on the receiving-end ac grids with different short-circuit ratio (SCR). Simulation studies were undertaken to validate the CFI improving performance achieved by UPFCs in comparison to SVCs and STATCOMs. Results of three-phase and single-phase fault tests manifest the superior CFI of LCC-HVDC systems having UPFCs installed.

This paper presents a security assessment method for cascading failures of cyber-physical power system (CPPS) with high penetration of wind power. First of all, a mathematical model considering the cyber-physical coupling and cyber attack risks of power systems is established, and a stochastic model for wind power is developed based on Markov chain Monte Carlo (MCMC) method. On this basis, a cascading failure model of CPPS with wind power penetration is presented. To improve the accuracy of cascading failure simulation, a phase-estimated based linear power flow (PELPF) method is proposed, which not only maintains computational accuracy fairly close to that of Newton Raphson method but also significantly enhances computational efficiency and avoids convergence issues. Moreover, a restoration control model is built based on PELPF against cyber attacks in cascading failures. Finally, two security assessment indices based on power flow entropy are introduced, which can quantitatively evaluate the short-term and potential cascading failures propagation risks. Simulation studies are conducted on the IEEE 118-bus system under the conditions of cyber attacks and different wind power penetration rates to demonstrate the effectiveness of the proposed method.