Study On The Additional Electric Power Absorption Management In Esource-based Region Of Inner Mongolia

As a major energy provider of the national economy, the status of the power industry is very important. Because of disequilibrium of energy and uneven levels of economic development in China, it is difficult to sustain a balanced balance of supply and demand, through long-distance transport of coal and generating power locally. Inner Mongolia Autonomous Region is rich in coal resources, it is advisable to develop coal-based electric power industry under the existing grid structure. Inter-regional power transmission can effectively alleviate the transport pressure of primary energy such as coal, and in the same time, we can gain the advantages of inter-regional peak load shifting, hydro power and thermal power transferring, reserve capacity reduceing and other benefits. All these will do good to improve the regional power grid reliability, promote economic, environmental and power industry harmoniously and sustainable development in Inner Mongolia.In this thesis, four questions are mainly studied as the following:Firstly, Inner Mongolia regional energy production status of research.three aspects of regional energy resources, the power supply size, power structures, as well as the carrying capacity of power transmission, are studied to analysis the advantages and problems in Inner Mongolia Autonomous Region electricity production.Secondly, Inner Mongolia Electric Power market supply and demand forecasting and balance analysis. The thesis using regression, least squares support vector machines and other methods to predict demand and supply for electricity on the Inner Mongolia Autonomous Region. By equilibrium analysis, potential outgoing capacity is estimated.Thirdly, additional electric power consumption research. For the actual situation of Inner Mongolia region, operating mode, price mechanism, transaction process, congestion management, ancillary services, and supervision mechanism are studied for additional electric power consumption, which regulated the operating procedures and specificed implementation electric in details.Fourthly, risk assessment and early warning system study in additional electricity consumption. A risk assessment and early warning system construction framework is proposed, in which, interactive artificial intelligence approaches are established to map fuzzy relations between the risk issues and its'values. After a large number of training, this system can automatically calls Knowledge Base reserves to do judgments likes expert. Risk early warning system are realized by the classification algorithm of Support Vector Machine (SVM).