Particle Swarm Optimization Based Reactive Power Dispatch for Power Networks with Distributed Generation

Reactive power is critical to the operation of the power networks on both safety aspects and economic aspects. Unreasonable distribution of the reactive power would severely affect the power quality of the power networks and increases the transmission loss. Currently, the most economical and practical approach to minimizing the real power loss remains using reactive power dispatch method. Reactive power dispatch problem is nonlinear and has both equality constraints and inequality constraints. In this thesis, PSO algorithm and MATPOWER 5.1 toolbox are applied to solve the reactive power dispatch problem. PSO is a global optimization technique that is equipped with excellent searching capability. The biggest advantage of PSO is that the efficiency of PSO is less sensitive to the complexity of the objective function. MATPOWER 5.1 is an open source MATLAB toolbox focusing on solving the power flow problems. The benefit of MATPOWER is that its code can be easily used and modified. The proposed method in this thesis minimizes the real power loss in a practical power system and determines the optimal placement of a new installed DG. IEEE 14 bus system is used to evaluate the performance. Test results show the effectiveness of the proposed method.

Mitigating Risk For Anxiety Among Preschool-Age Children Living In Poverty: Evaluating The Impact Of Adult-Provided Social Support On Autonomic Stress Reactivity

Poverty increases children's exposure to stress, elevating their risk for developing patterns of heightened sympathetic and parasympathetic stress reactivity. Repeated patterns of high sympathetic activation and parasympathetic withdrawal place children at risk for anxiety disorders. This study evaluated whether providing social support to preschool-age children during mildly stressful situations helps reduce reactivity, and whether this effect partly depends on children's previously assessed baseline reactivity patterns. The Biological Sensitivity to Context (BSC) theory proposes that highly reactive children may be more sensitive than less reactive children to all environmental influences, including social support. In contrast, conventional physiological reactivity (CPR) theory contends that highly reactive children are more vulnerable to the impact of stress but are less receptive to the potential benefits present within their social environments. In this study, baseline autonomic reactivity patterns were measured. Children were then randomly assigned to a high-support or neutral control condition, and the effect of social support on autonomic response patterns was assessed. Results revealed an interaction between baseline reactivity profiles and experimental condition. Children with patterns of high-reactivity reaped more benefits from the social support in the experimental condition than did their less reactive peers. Highly reactive children experienced relatively less reactivity reduction in the neutral condition while experiencing relatively greater reactivity reduction in the support condition. Despite their demonstrated stability over time, reactivity patterns are also quite susceptible to change at this age; therefore understanding how social support ameliorates reactivity will further efforts to avert stable patterns of high-reactivity among children with high levels of stress, ultimately reducing risk for anxiety disorders.