Establishment and optimization of project investment risk income models on the basis of probability χ distribution

In this paper, two kinds of models are presented and optimized for project investment risk income on the basis of probability χ distribution. One kind of model being proved has only a maximal value and another kind being proved has no extreme values.

The causes of chronic and transient poverty and the implications for poverty reduction policy in rural China

The study focuses on two components of total poverty:chronic and transient poverty,and investigates their relative importance in total observed poverty,as well as the determinants of each component.We find that transient poverty accounts for a large proportion of total poverty observed in the poor rural areas of China.By analyzing the determinants of the two types of poverty,we find that household demographic characteristics,such as age of the head of households,family sizes,labour participation ratio,and educational level of the head of the households,are very important to the poverty status of households.These factors matter more to chronic poverty than transient poverty,and have greater impacts on the poverty measured by consumption than that measured by income.Besides the demographic factors of households,other household factors like physical stocks,the composition of income,and the amount of cultivated lands also have significant effects on both chronic and transient poverty.It is also confirmed that change in cash holding and saving and borrowing grain are used by rural households to cope with income variation and smooth their consumption.Attributes of community where the households reside are also important to poverty.With very few exceptions,we do not find that poverty programs have significant impact on poverty reduction at the households’level.We interpret this as the poverty programs benefiting the wealthy more than the poor in a given poor area.The main reason for this could be that the implementation design of these programs fails to target the poor.

Decision Support System for Adaptive Restoration Control of Transmission System

The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decision support framework for adaptive restoration control of transmission system is proposed, which can support the coordinated restoration of multiple partitions, coordinated restoration of units and loads, and coordination of multi-partition decision-making process and actual restoration process. The proposed framework is divided into two layers, global coordination layer and partition optimization layer. The upper layer partitions the transmission system according to the power outage scenario, constantly and dynamically adjusts the partitions during the restoration process, and optimizes the time-space decision-making of inter-partition connectivity. For each partition, the lower layer pre-selects restoration targets according to the estimated restoration income, optimizes the corresponding restoration paths, and evaluates the restoration plans according to the expected net income per unit of power consumption. During the restoration process, if the restoration operation such as energizing the outage branch fails, the current restoration plan will be adaptively switched to the sub-optimal one or re-optimized if necessary. The framework includes two operation modes, i.e., the on-line operation mode and training simulation mode, and provides an information interaction interface for collaborative restoration with related distribution systems. The effectiveness and adaptability of the proposed framework is demonstrated by simulations using the modified IEEE 118-bus system.