Longitudinal and Age-Related Implications of Primary and Secondary Control for Happiness

While previous research addressed two distinct types of happiness, including hedonia and eudaimonia, the longitudinal associations of primary and secondary control with these happiness constructs had not been fully studied. The present study aimed to contribute to the literature by examining these associations and their age differences. Using data from the second and third waves of the Midlife in the United States (MIDUS; N = 4,963, aged 28 to 84 at baseline), the present study conducted structural equation modeling analyses to examine whether primary and secondary control predicted residualized changes over around a decade in the latent constructs of hedonia and eudaimonia and whether there were age differences in these associations. The results indicate that while only primary control predicted change in eudaimonia overall, the associations of primary and secondary control with changes in hedonia and eudaimonia differed by age. Particularly, in comparing these effects for younger and older individuals, primary control predicted increases in eudaimonia only for younger individuals, whereas secondary control predicted decreases in hedonia for younger individuals but predicted increases in eudaimonia for older individuals. Considering these findings, the importance of primary and secondary control for happiness may vary between adults of different ages, which is possibly due to their life priorities that may change with age. The present study suggested potential directions of future research further examining the role of primary and secondary control for happiness and exploring potential interventions to promote happiness, for example, by modifying primary and/or secondary control for adults of different ages.

Association Between Future Orientation and Anxiety in University Students During COVID-19 Outbreak: The Chain Mediating Role of Optimization in Primary-Secondary Control and Resilience

The unfamiliar and menacing epidemic has undoubtedly increased the anxiety of students. Therefore, the strategies to reduce anxiety are urgently required. The present study principally investigated a protective mechanism of future orientation in anxiety during the low-risk period of COVID-19 outbreak. The study was conducted in 528 non-infected students (range = 16–24 years) recruited from five universities in China. The participants completed questionnaires between January 22, 2021, and January 24, 2021. Chain intermediary analyses were performed after controlling for gender and age. Results indicated that future orientation lowers anxiety through (a) optimization in primary and secondary control, (b) resilience, and (c) chain mediating path of optimization in primary and secondary control coupled with resilience. We investigated how individuals deal with risk factors after encountering adversity and how their psychological flexibility stimulates and promotes them to achieve a well-adapted developmental state. This study provided reference suggestions on reducing anxiety levels during an emergency.

Optimization-based primary and secondary control of microgrids

This article discusses how to use optimization-based methods to efficiently operate microgrids with a large share of renewables. We discuss how to apply a frequency-based method to tune the droop parameters in order to stabilize the grid and improve oscillation damping after disturbances. Moreover, we propose a centralized real-time feasible nonlinear model predictive control (NMPC) scheme to achieve efficient frequency and voltage control while considering economic dispatch results. Centralized NMPC for secondary control is a computationaly challenging task. We demonstrate how to reduce the computational burden using the Advanced Step Real-Time Iteration with nonuniform discretization grids. This reduces the computational burden up to 60 % compared to a standard uniform approach, while having only a minor performance loss. All methods are validated on the example of a 9-bus microgrid, which is modeled with a complex differential algebraic equation.