The Design And Development Of Carbon And Energy Management System

As China has stepped into a middle period of industrialization, huge amounts of energy consumption especially from the fossil fuels that demanded by the fast growing economy has consequently make its contribution to a serious array of problems that have posed a minus impact on social and economic growth, e.g. energy shortages, environmental issues such as high carbon emissions. With the network and information techniques progress, carbon or energy related management systems are firmly demanded by current as they could run data processing, offer valuable information and analyzing results to relevant personnel. (e.g. researchers, management officials), and would be a more saving and efficient way in terms of slashing management costs, reducing technological barriers, etc.While it’s still in its early stage of development in which there yet have been many researches or designs and major problems lying ahead summarized by this thesis are:current systems are isolated with one another and offer single respect of information bringing less productive, taking less good to data integration and sharing; Statistical data processing is the major function in current systems, therefore a lack of mathematical models that in turn leads to less analyzing functions built based on a number of carbon and energy models has been considered as another principal problem so far. In this context, this thesis engages in designing and developing a new type of system that would basically make progress in two points below:To meet the demand of data integration recognized as a main feature of the latest generation of information technology, this system provides a suite of integrated web-based services involving 3 respects of information:carbon emissions, energy consumptions, and energy efficiencies that differ from previous independent systems which could save costs from developing independent systems, achieve synchronization, data sharing and offering more convenience. Being supported by a number of built-in functions, this system is able to present specific conditions, differences, trends in 30 provinces and 6 regions of China concerning to those 3 respects. Additionally, a measurement known as data envelopment analysis (DEA) is used to assess total-factor energy efficiencies in areas which is distinct from partial-factor efficiencies used previously. The measurement would be full-scale and objective as it involve extra factors into consideration such as labor, capital, and environmental costs.A lack of mathematical models has been well addressed and progressed on this system by offering analyzing functions through a C# plus Matlab mixed developing mode. In this way, a number of functions based on mathematical models such as prediction, decomposition, and DEA have been implemented. Additionally, a Web GIS application has been established in the form of which a series of functions (e.g. querying and displaying regional differences) has been made.Finally, by using this system, a series of analysis concerning carbon emissions, energy consumptions, and energy efficiencies in China’s 30 provinces and 6 regions in the years of 2006-2012 has been carried out and major results have been summarized as following:(1) Carbon emission keeps a similar situation with energy consumption among 7 years in terms of growth and regional characteristics. There shows a continuous growth for each of them in this period especially both of them bumping up from 2009 to 2011. Provinces in east region consume relatively high in total volume while possessing relatively low increasing rates, however provinces in the west are on the opposite situation which have lower consumptions in total volume while increasing rates are relatively high.(2) TFEE scores rise in all 6 regions of China which suggest continuous improvements have taken effect during this period. Provinces in the middle and the east rank relatively high in contrast with provinces in the west especially provinces in the northwest part which have been assessed obtaining the worst energy efficiencies over the years. Finally a research on factor decomposition for China’s 30 provinces in 2012 has been conducted by choosing three factors:economic size, technology and economic structure, and results suggest all three are positive to lifting TFEE among which technology contributes the most, economic structure the second, economic size for the last.