| In1998, Watts and Strogatz in the" Nature" published the article, revealed the small world property behind a complex network. Barabasi and Albert in1999, in "Science", published research results and proposed scale-free properties of distribution of node degree. This set out a wave of research in complex network theory and has attracted scholars of physics, mathematics, engineering, sociology, biology and other fields to explore the nature law of the complex world. So it has become a hot research issue in many areas.Prevalence of complex networks in nature, such as Internet, transportation networks, electricity networks, personal relationships, research and cited networks, virus transmission networks, air transportation networks, international trade networks, physiological networks, metabolic networks and so on. In recent years, problems caused by complex networks have become increasingly prominent, like, SARS virus epidemic in a very short time, the global financial crisis spread to many countries, the more severe climate, and electricity accidents have occurred. Hence, there is a great need for understanding complex networks and if we understand the nature law, it is easy to avoid weaknesses in applications. Complex network system from instability to stability is a dynamic process. In this process there is a critical state, which features should be shown in a critical state for the complex network system, how to design a more excellent and stable synchronization controller, while avoiding disadvantages of the treatment of complex network problems. This is a new hot topic of theoretical research in the present time.With the rapid development of society, the energy shortage problem is becoming increasingly prominent, the oil and coal as the core energy resourse will become short soon. At the same time, it also brings serious environmental pollution problems. Development of new energy has become theme of the times, and it also brings new power grid security issues. In2003, the U.S. Electric Power Research Institute (EPRI) defined the future grid as intelligent grid; in2005, the European first proposed "Smart Grid "----smart grid concept, intended to solve the new situation facing human energy, environment and power grid security. How to really solve the power security issues from the grid physical structure has motivated us to the era of this new research field.Therefore, in this thesis, we have considered the current status of complex network theory study and power grid construction characteristics and the use of this theory to study existing issues, including mainly the following aspects:1. Study critical complex synchronization mechanism. Complex network system will be more complicated for the node characteristics and the diversity of coupling characteristics of edges. For such a complex network system has the overall shape of two diametrically opposite (stable and unstable). In order to better control such a system and use it, it is necessary to study the critical state of synchronization. Experimental results demonstrate the existence of this critical. After extensive research find the sufficient and necessary conditions of a class of complex networks to determine the critical state.2. Study the pinning control theory of synchronization of complex networks. Pinning control is the most effective way to realize complex network synchronization, controlled by a small number of nodes to drive the network to the desired state or path. In here, a bridge is proposed by introducing importance index between the complex networks and the actual contribution of power of nodes. Pinning control strategy has beed proposed based on the node importance index. Meanwhile, by introducing the node importance index into the design of controller, a more reasonable and effective way of designing controller is obtained, to resolve to the issue of the lack of theoretical basis during the design of pinning control parameters.3. Study AC and DC transmission system based on complex network theory. Study properties of complex networks of china AC and DC hybrid transmission system, depth analysis the effect of DC transmission to characteristics of the grid. AC-DC hybrid transmission system is proposed using vulnerability assessment methods. Examples demonstrate the introduction of DC transmission will transfer grid characteristics to the scale-free feature. At the same time HVDC converter station location is also studied. Eamples demonstrate the node of converter station selected according to degree can increase the network survivability.4. Study the Grid AGC pinning control based on Complex Network Theory. Under the requirements of the smart grid, it is more flexible and efficient electric power, in order to real-time tracking changes in network load, and can well predict the situation on the power grid. Transform the transmission constraints and capacity into complex network edge weight, then consider node's actual capacity, combined with the physical network connection to get the node point weight. Basen on complex networks pinning control strategy add pinning adaptive control on the part of nodes, achieve synchronization in the each generator speed.5. Established the model of power system load online forecasting model based on fuzzy support vector machine learning theory. Machine learning is an important area of research and the core research of artificial intelligence; its notable feature is the small sample study. It is a trade-off between learning ability and the model complexity based on a limited sample of the information and to get the best generalization ability, and does not exist in the learning process over learning and local minimum, be widely used. In this thesis, use of least squares support vector machine (LS-SVM) which is a learning methods for small sample, combined with thinking of embedding dimension, and the use of particle swarm optimization (PSO) algorithm for model parameter optimization, research online prediction method to arrive to real-time online learning and accurate forecasting, which is the basis of power adjusted correctly.
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