With the rapid development of science and technology, digital information such as text, pictures, audio, and video has grown exponentially, and the era of big data has come. The total amount of global information doubles every two years. The total amount of data created and copied in 2011 was 1.8ZB (1021 bits). It is expected to reach 35ZB in 2020, which is 50 times the current value. According to IBM's 4V theory, big data is discrete massive data covering the four dimensions of scale, diversity, high rate, and authenticity. Big data has the characteristics of massive scale, multi-source heterogeneity, high noise, strong timeliness, socialization and sudden emergence. It has penetrated into various industries and become an important production factor alongside physical assets and human capital, triggering global Sexual attention. The energy industry, as the foundation of national economic and social development, is being profoundly affected by big data. In the 21st century, big data technology innovation must be adopted to meet the energy challenges of long-term sustainable development. Big data will profoundly affect the energy system Big data will play a huge role in increasing clean energy supply, controlling energy consumption and reducing energy consumption, to green buildings and smart grid construction. Taking smart grids as an example, grid interconnection is an objective law of power system development. It is necessary to strengthen the research and development of large-scale interconnected grid safe and stable operation technology, advanced and reliable distribution network and sharing technology, and distributed power system based on micro grid technology. . Therefore, collecting, analyzing and effectively applying big data is an important factor to solve the key business of energy and utilities. It can realize the transformation to smart grid, improve the asset forecast and dispatch of distributed renewable power generation, improve the efficiency of power generation and change the operation mode of customers. At present, major developed countries are in the process of R & D and deployment. For example, in early July 2011, 13 European industrial groups signed a memorandum of understanding on the implementation of the "green energy transmission" project to carry out a feasibility study on the construction of a high-voltage power grid project across the Mediterranean. In March 2012, the US Department of Energy spent US $ 25 million to establish the Scalable Data Management, Analysis and Visualization (SDAV) Institute to help scientists effectively manage and visualize energy big data to promote more effective scientific research and discovery. Japan ’s Ministry of Economy, Trade and Industry organized Toshiba, Tokyo Electric Power and other 286 companies to establish a “smart community alliance†consortium. They wanted to build a smart grid-based urban layout and social system, which opened the curtain on the development of smart grid by officials and citizens. . China is not far behind, and through the "973" plan, "863" plan and science and technology support plan and major special projects, increase R & D support for the next-generation Internet and energy integration related technologies, and promote the development of intelligent and clean energy. Effective use is the key Currently, there are four main applications of big data in the energy sector. First, promote new product development. By analyzing tens of thousands of data points per second, American General Motors has combined energy storage and advanced prediction algorithms to develop 2.5-120 wind turbines that can flexibly control 120-meter blades, and seamlessly transfer data to neighboring wind turbines, For service technicians and customers, the efficiency and power output have increased by 25% and 15% compared to current wind turbines, respectively. Second, to make energy more "green", the key is to use renewable energy technologies, such as Iceland's Green Earth Data and Green Qloud, relying on Iceland's abundant geothermal and hydropower resources to provide 100% renewable energy for data centers. Third, to achieve intelligent energy management. The energy industry can use big data to analyze the purchase volume of natural gas or other energy, predict energy consumption, manage energy users, improve energy efficiency, and reduce energy costs; the integration of big data and the power grid can form a smart grid that involves the entire energy generation from the user The conversion process and power transmission chain mainly include the basic technology of smart grid, large-scale new energy power generation and grid connection technology, smart transmission grid technology, smart distribution network technology and smart power technology, etc., which are the future development direction of the power grid. Fourth, change society and bring opportunities for urban infrastructure, energy, transportation, and environment. Big data makes cities more and more intelligent. New York, Chicago and Seattle open data to the public and encourage the construction of diverse smart cities. Reshape energy intelligent management At present, IBM has taken data analysis as the core of its big data strategy, invested a total of US $ 16 billion for 30 data analysis related acquisitions, and made a series of innovations in its massive data analysis platform InfoSphere BigInsights and other related products Put forward initiatives such as power grid transformation, improved power generation efficiency and customer operation transformation to better support energy big data processing. Current research shows that intelligent management of solar farm grids requires equipment control of PV panels, converters, etc. to optimize power generation under various conditions throughout the day, and effective equipment management can increase productivity by 10%. The demand for real-time wide-area, monitoring, protection and control systems from power companies around the world is increasing, and synchronous measurement technology will become an effective support for the system. It is not enough for a smart grid to shift from a one-way grid to a two-way power system network. The real need is to establish a complete set of energy and intelligent management systems that serve as carriers for electricity, heat, hydrogen, biological and non-biofuels. This needs to go beyond intelligence Grid and consider a clear transformation of smart energy networks. China's energy development and utilization technology has a certain foundation and has formed a considerable scale of industry, but the arduous understanding of the energy technology innovation value chain is insufficient, and the understanding and research of energy intelligent management are at the initial stage. Energy storage technology and intelligence The power grid is the key to promoting the sustainable development of renewable energy; it is necessary for enterprises to establish an energy intelligent management system, and analyze the characteristics, main functions, and implementation points of the energy intelligent management system. The era of big data has arrived. Big data has an important impact on the effective use of energy, and it has become a consensus of all sectors of society to reshape the energy system. However, what is the mechanism of the emergence, evolution and spread of energy big data? What will happen to energy business intelligence? What are the requirements and challenges for energy intelligent management reengineering? What kind of energy intelligent decision-making system is needed to meet these challenges? Solving this series of scientific problems will not only help to discover the Xinjiang domain and new knowledge of the fusion of information and energy, but also reveal the internal laws of energy intelligent management and decision-making in the era of big data, and it is expected to lay the theoretical and technical foundation for sustainable development of energy. Therefore, it has very important theoretical value and practical significance, and urgently needs to attract the attention of experts and scholars in related fields such as energy, information, science and technology policy.
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