The conventional model predictive torque control (MPTC) used for dual three-phase permanent magnet synchronous motors (DTP-PMSMs) faces several challenges, such as significant computational burden, large current harmonics, and large torque and flux ripples due to the application of imprecise voltage vectors. To address these issues, a novel three-vector-based MPTC strategy was introduced in this study for DTP-PMSMs. First, virtual vectors were adopted to reduce the current harmonic components. Second, four candidate vector groups were determined based on torque deviation and flux position. Each candidate vector group comprised two virtual vectors and one zero vector, which enabled the precise control of torque and flux through the duty-ratio modulation strategy. Third, the switching sequence was optimized to facilitate implementation in digital controllers. Then, a cost function was defined to evaluate the average torque and flux ripples of each candidate vector group in a sampling period, and the one with the minimum cost function was applied in the next sampling period. This approach effectively reduced the current harmonics, torque ripple, and flux ripple while avoiding large computational burden. Finally, experiments were conducted to demonstrate the effectiveness of the proposed method.

This paper proposes a hierarchical event-triggered model predictive control (HEMPC)-based voltage control strategy to coordinate the reactive power (Var) outputs among all WTs for improving the high-voltage ride-through (HVRT) and post-fault voltage restoration capability of the large-scale wind farms (WFs), while reducing the heavy computational task of the WF controller. The event-triggering condition and optimal controller are designed to activate the proposed HEMPC strategy based on the system state deviation and input-to-state stability (ISS) mechanism, which can substantially decrease data communication in a non-periodic sampling fashion. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed, aiming to further improve the computing efficiency of the voltage optimization problem of the large-scale WF. Two time-domain WF simulation cases in Matlab/Simulink corroborate that the proposed HEMPC strategy is more efficient in minimizing the WT terminal voltage deviations and reducing the computational burdens of the WF controller compared with traditional control strategies.

Introduction: In recent years, there have been numerous online privacy violation incidents caused by the leakage of personal information of social media users, yet there seems to be a tendency for users to burn out when it comes to privacy protection, which leads to more privacy invasions and forms a vicious circle. Few studies have examined the impact of social media users' privacy invasion experiences on their privacy protection intention. Protection motivation theory has often been applied to privacy protection research. However, it has been suggested that the theory could be improved by introducing individual emotional factors, and empirical research in this area is lacking.Methods: To fill these gaps, the current study constructs a moderated chain mediation model based on protection motivation theory and regulatory focus theory, and introduces privacy fatigue as an emotional variable.Results and discussion: An analysis of a sample of 4800 from China finds that: (1) Social media users' previous privacy invasion experiences can increase their privacy protection intention. This process is mediated by response costs and privacy fatigue. (2) Privacy fatigue plays a masking effect, i.e., increased privacy invasion experiences and response costs will raise individuals' privacy fatigue, and the feeling of privacy fatigue significantly reduces individuals' willingness to protect their privacy. (3) Promotion-focus individuals are less likely to experience privacy fatigue than those with prevention-focus. In summary, this trend of “lie flat” on social media users' privacy protection is caused by the key factor of “privacy fatigue”, and the psychological trait of regulatory focus can be used to interfere with the development of privacy fatigue. This study extends the scope of research on privacy protection and regulatory focus theory, refines the theory of protection motivation, and expands the empirical study of privacy fatigue; the findings also inform the practical governance of social network privacy.

This paper proposes a robust emergency preparedness planning (EPP) scheme to optimally pre-position diverse mobile emergency resources (MERs) in staging locations and perform proactive network reconfiguration for resilience enhancement of energy-transportation nexus (ETN) against extreme rainfalls. Based on rainfall-runoff simulation with hydrodynamic partial differential equations, a risk identification approach for flood-prone transportation modeling is developed for vehicle travel time estimation and MER routing optimization. To handle uncertainties in line outages and flooded roads incurred by extreme rainfalls, a tri-level robust EPP model is proposed to determine the optimal emergency preparedness plan immunized against the worst-case realization of uncertainties. Furthermore, a tailored solution method combining nested column-and-constraint generation algorithm with multiple linearization techniques is devised to cope with the proposed nonlinear robust EPP model. Comparative studies have validated the effectiveness of the proposed scheme for resilience enhancement of the ETN confronted with extreme rainfall disasters.

Due to the flexibility and economy, energy storage systems (ESSs) have been widely deployed in wind energy power plants for power regulation. The coordination of generators and ESSs is critical for the wind farm (WF) operation. In this article, a two-stage voltage control is proposed in WFs equipped with distributed ESSs to achieve a near-global optimal performance without any centralized computations and communication links. To achieve it, the WF control is divided into two regions based on the demand-supply relationship of reactive power to consider the different operating conditions and multiple optimization objectives. The distributed battery-supercapacitor hybrid ESSs are deployed in each wind turbine within the WF to regulate the power output while ensuring voltage stability and enhancing the Var support capability. An optimization problem is formulated considering the node voltage deviation, the state of charge, and the cost of the storage units, which can be simply calculated using only local measurements through a decoupling method based on network topology characteristics. Further, an asynchronous response framework is designed for the battery and the supercapacitor to achieve a better economic benefit. Case studies in MATLAB/Simulink verify the effectiveness and reliability of the proposed method.