China is developing at relatively high speed, not only the regional development speed should be focused upon, but also the environmental impact of economic growth should be paid attention to, especially the level change of carbon dioxide emission. To some degree, quantity of carbon dioxide emission has become one of the most important indexes for measuring quality of a nations economic growth. Thus, this thesis is trying to analyze the driving relations between economic growth and carbon dioxide. Upon STIRPAT model, ridge regression method and elasticity theory are applied to analyze the influencing factors of carbon dioxide quantity such as the population quantity, Chinas urbanization process, per capita GDP, energy density and the percentage of the secondary industry. Correspondingly, based on the different influencing variables to carbon dioxide emission quantity, needy measures are brought out to control and decrease emissions. Feasible suggestions are trying to improve Chinas economic development quality.

With extensive access to distributed power sources and the rising electricity load, the structure and tide of distribution networks are becoming increasingly large and complex, leading to great challenges for fault location methods. In this paper, the power coupling phenomenon of the T-section in the distribution network is studied, and a hierarchical optimization model for fault location is proposed based on the port equivalence principle, which divides the fault location into two levels—area location and section location—to reduce the fault search dimension. Then, an improved binary particle swarm optimization algorithm (IBPSO) applied to the area location is proposed to improve the convergence accuracy and speed by optimizing the convergence criterion and integrating the chaotic mapping and mutation strategies. Finally, based on the topological characteristics of the sections in the fault area, a fault candidate scenario screening method based on the fault confidence factor is proposed to realize a second dimensionality reduction in the section location link. Simulation tests show that the proposed method demonstrates a good dimensionality reduction effect for large-scale, active distribution networks; additionally, the accuracy rate is improved by 25.7% and the location speed is improved by 300 ms when compared with traditional fault location methods.

In this paper, a fault location method based on divide-and-conquer (DAC) is proposed to solve the inadequacy problem that arises when using the traditional fault section location method based on the optimization model of logic operation. The problem is that it is difficult to balance speed and accuracy after the scale of the distribution network is expanded. First, the causal link between fault information and the faulty device was described using the road vector, the equivalent transformation of the logical operations in the traditional model was implemented with the properties of the road vector, and the numerical computational model of the fault location was constructed. Based on this, the optimization-seeking variable “approximation gain” was introduced to prove that the proposed model conforms to the recursive structure of DAC, and the method of applying DAC to locate faults is proposed. The method applies the “Divide-Conquer-Combine” recursive mode to locate faults, and each level of recursion contains only linear-time “approximation gain” operations and constant-time decomposition and combination operations. The efficiency analysis and simulation results show that the proposed method has linear-time complexity and can accurately locate faults in milliseconds, providing a reference for solving the fault location problem in large distribution networks.

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