As a state-owned key enterprise that is related to the national energy security and the lifeline of the national economy, the State Grid Corporation has achieved remarkable results in independent innovation, and has overcome core technologies such as UHV, smart grid, new energy, and large grid security.
Big data, big change
Bigger, more, faster
In January 2012, the World Economic Forum in Davos, Switzerland, published a report on Big Data, Big Impact. According to the report, data has become a new class of economic assets, just like money or gold. Since then, data scientist Victor Meyer-Schoenberg has published a book, The Age of Big Data, which describes the thinking, business, and management revolution in the era of big data. The book points out that the information storm brought by big data is transforming people's lives, work and thinking, and big data has opened a major era transformation.
The power system is one of the most complex physical systems. It has a wide geographical distribution, real-time balance of power generation, a large amount of transmission energy, a high speed of light transmission, a highly reliable communication schedule, a never-stop operation in real time, and an instantaneous expansion of major faults. Features. These characteristics determine the amount of data generated during the operation of the power system, rapid growth, and a rich variety. Power data conforms to all the characteristics of big data.
The characteristics of power big data are: large volume, multiple types, fast speed, data is energy, data is interaction, and data is empathy.
Large volume. It is an important feature of power big data. With the informationization of power companies and the comprehensive construction of smart grids, the scope and frequency of data collection have increased significantly, and power data has developed rapidly.
More types. Power big data involves multiple types of data, including structured data, semi-structured data, and unstructured data. With the increasing number of video applications in the power industry, the proportion of unstructured data such as audio and video in power data has further increased. In addition, there are still a large number of correlation analysis requirements for multi-type data such as energy data and weather data inside and outside the industry in the process of power big data application, which directly leads to the increase of power data types.
high speed. Mainly refers to the speed of power data acquisition, processing and analysis. The requirements for processing time limit in the power system are relatively high. Real-time processing is an important feature of power big data. This is the biggest difference between power big data and traditional post-processing business intelligence and data mining.
Data is energy. Power big data has the characteristics of no wear, no consumption, no pollution, easy to transfer, and can be continuously refined and added value in the process of use. It can reduce the energy consumption in all aspects of the power system under the premise of ensuring the interests of power users. A unique and enormous role in sustainable development.
Data is interactive. Power big data has a wide and close relationship with the national economy and society. Its value is not only limited to the power industry, but also to the national economy, social progress and innovation and development of various industries. Through the interaction and integration with the data outside the industry, and on the basis of all-round mining, analysis and display, it will definitely make the power big data play more value.
The data is empathy. The fundamental purpose of the enterprise is to create customers and create demand. Through the full digging and satisfaction of the needs of power users, we will establish emotional connections and provide more high-quality, safe and reliable power services for the majority of power customers.
Big data, new business
When PV services become data
On April 26, the State Grid Distributed Photovoltaic Cloud Network 2.0 was officially released and launched. State Grid Distributed Photovoltaic Cloud Network is a new platform and new format of “platformization + distributed + ecologicalization†based on the innovation of Internet and sharing economic thinking. It is independently developed and constructed by State Grid E-Commerce Co., Ltd.
In April 2017, PV Cloud Network 1.0 was officially launched, which built a full-service, full-process integrated service platform for the development of distributed PV industry. Over the past year, the platform has promoted the development of distributed photovoltaic scale and the development of photovoltaic poverty alleviation, and fostered an open and shared industrial ecosystem. Compared with the 1.0 platform, the PV Cloud 2.0 platform has been fully upgraded from the technical and functional experience.
Photovoltaic Cloud Network 2.0 utilizes spatio-temporal big data to realize multi-scenario and multi-dimensional data intelligent analysis and application, and provides one-stop service for distributed PV whole industry chain with “online platform + offline serviceâ€. Distributed 980 million households with installed capacity of 395.583 million kilowatts, 285 high-quality supply chain enterprises, 754 pieces of photovoltaic equipment components, and a total transaction of 9.687 billion yuan, becoming the largest "technology" in China. +Service + Finance" distributed PV service cloud platform. At the same time, based on the photovoltaic cloud network, the national photovoltaic poverty alleviation management platform will be built to realize the whole life cycle management of poverty alleviation power stations, help the country to accurately help the poor, and serve the national clean energy development strategy.
Class 3 power big data
Cross-unit, cross-professional, cross-business
Power big data can be divided into three categories: First, grid operation or equipment detection (monitoring) data, mainly included in energy management systems, distribution network management systems, wide-area measurement management systems, production management systems, power grid dispatch management systems, and faults. Management system, image monitoring system, etc.; second, power marketing system, such as transaction price, electricity sales, electricity customers, etc., mainly including marketing business system (SG186), 95598 customer service system, electric energy metering system, electricity Information collection system, etc.; third, power enterprise management data, mainly in the collaborative office system, enterprise resource planning system, material e-commerce platform system. Power big data involves all aspects of development, transmission, transformation, distribution, use and adjustment. It is across units, across disciplines and across businesses. The rapid development of smart grids has rapidly integrated information technology, communication technology and production management of power companies, and power companies are facing a big data environment that is emerging.
Big data, closely related to you and me
When the power outage information becomes data
The power outage lean management analysis scenario developed by State Grid Fujian Electric Power Co., Ltd. is based on the big data platform. It mainly uses real-time power outage monitoring and frequent power outage monitoring. It uses decision tree and logistic regression algorithms to construct equipment blackout classification analysis and equipment blackout impact. Models such as analysis and equipment power outage distribution analysis analyze the frequent power outages from the distribution of power outages, the number of power outages, and the length of power outages.
In the aspect of real-time power outage monitoring, real-time display of the network (discontinued) power distribution in each area, timely positioning of the power supply and power failure reasons, to provide support for fault repair work. By analyzing the distribution of real-time power outage units, power outage lines and distribution types, as well as real-time power outages, stop (re) electricity time trends, and power outages affecting customers, you can gain a deeper understanding of the impact of power outages on all aspects, making it faster and more accurate. Coping with the ground. In the aspect of frequent power outage monitoring, through the mining of historical data of power outages, analyze the number and severity of power failures of each distribution transformer and each line, and take measures in a targeted manner. At the same time, analysis of the length of power outages, areas, lines and distribution types, etc., provides a strong support for priority management of severe power outages and rapid improvement of power quality.
Since the application of the Lean Management Lean Management Analysis Scenario, the efficiency of the State Grid's Fujian Power Analysis and location has increased by 30%, and the reliability of distribution network has increased from 99.91% to 99.99%.
Big data, big platform
When the new energy industry chain becomes data
The Qinghai New Energy Big Data Innovation Platform was built by the State Grid Qinghai Electric Power Company. It was completed and put into operation on January 8, 2018. It is the first new energy big data innovation platform in China and builds the first new energy source in China based on the platform carrier. Data Innovation Park. The platform takes innovation as the engine and data as the carrier, and is committed to providing big data services covering the whole industry chain such as new energy planning, design, equipment manufacturing, construction, operation, overhaul and recycling for government, manufacturing enterprises, power generation companies and power grid companies. .
The main business includes: First, to provide centralized monitoring platform and shared innovation park services for new energy power generation enterprises. The centralized monitoring platform realizes centralized monitoring and remote control of power generation equipment and booster stations of power plants owned by each power generation company through accurate collection of operating data of new energy power plants. Second, provide application market services for the entire energy industry chain. Deploy and release third-party application management products such as power plant production management, centralized power forecasting, equipment early warning, equipment grid-connected capability assessment, etc., for the purchase and application of new energy industry chain customers. Third, provide online and offline business integration services to meet the needs of major players in the entire industry chain for supply and demand transactions such as equipment maintenance, centralized maintenance, spare parts storage, and financial services. 30 new energy plant stations have been connected to the line to achieve particle size data collection of fan component and photovoltaic panel grades, and 33GB of industrial grade data is added every day. Fourth, data innovation services. The use of energy technology and information and communication technology to provide raw data and big data technology support for the entire industry chain, based on the value of data to meet the needs of the industry chain.
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