How to build a data application system based on overall value for energy enterprises

The digital economy is booming , Digitalization of the energy industry is also being carried out in an orderly manner , Through digital technology , Build more efficiently 、 cleaner 、 More economical 、 A safer modern energy system .

Take electric power energy enterprises as an example . At present , The ultimate goal of China's smart grid is to cover the entire production process of the power system , And support smart grid security 、 The foundation of reliable operation , It is the panoramic real-time data acquisition of power grid 、 Transmission and storage , And the accumulated massive multi-source data for rapid analysis .

The core demand of data analysis of power energy enterprises

Carry out the main business activities and core resources of the company “ all-weather 、 comprehensive 、 The whole process ” Online monitoring of 、 Operational analysis 、 Coordinated control 、 And panoramic display , To fully understand the company's operating conditions , Business application scenarios such as dynamic monitoring and automatic early warning of changes and problems during the company's operation have become the core demand .

The power industry IT Solid strength , It is generally equipped with multiple sets of relatively independent and hierarchical business systems , However, the data visualization management and application development are slightly insufficient , Lack of unified planning for data analysis and application that fits the future business layout .

Unified construction of data analysis platform , It can meet the overall operation of internal data of power energy enterprises and the law analysis and mining of professional fields , Promote Lean Management , Realize the overall monitoring of internal and external management of power enterprises , Improve insight into the current business situation , Adjust the strategic direction in time , Promote the health of the power industry 、 Scientific development . Make efficient use of historical data and real-time production and operation data accumulated by power enterprises for many years , Form an index system and tap its deeper value , Provide a large number of high value-added services , Meet the power business demand , Generate innovative business , Improve the core competitiveness of the company .

Solution

Data analysis and application solutions for power and energy industry , Based on one-stop big data analysis platform , It can centrally integrate the data of multiple independent systems , Strengthen the management of data assets of power enterprises , Breaking the data silos , Quickly build analysis applications that fit business scenarios , Realize operation and maintenance monitoring 、 operation management 、 Emergency management 、 Equipment overhaul management 、 Data application requirements of different business modules such as operation and maintenance cost analysis .

Based on the enterprise value model , According to the strategic development requirements of electric power enterprises , Combined with the core competence of the enterprise , Establish a key indicator system , Support the integrity of all kinds of business of the company 、 systematicness 、 Multi perspective analysis and management , Aid decision making .

1、 Focus on achieving profitability and development potential . From the current financial return 、 Analyze the company's value realization from two aspects of future business development potential .

2、 Expand the perspective of overall analysis . At the overall level of power enterprises , Expand financial business integration 、 Covering the main business 、 End to end integrity analysis .

3、 Balance benefits and risks . Focus on risk , The early warning mechanism is initially adopted to promote forward-looking risk warning and prevention .

Data preparation for self-service 、 High performance computing 、 Exploratory self-help analysis 、 In-depth analysis of 、 Enterprise level management and control BI platform , Seamless integration of all the core components needed in data operations , Provide the ultimate user experience and extremely low maintenance costs .

for example , Monitor the operation and maintenance of power grid , Real time understanding of equipment availability factor 、 Timely elimination rate of serious defects 、 O & M costs 、 Completion of overhaul and technical transformation and other key indicators , When a key indicator is abnormal , The system will provide message alerts , And you can view more fine-grained data in the corresponding analysis topic , Diagnose business problems .

Yonghong BI Analysis of power grid maintenance and operation Demo

Analyze the maintenance and operation , The maintenance workload can be divided into: 、 Monitor and analyze the proportion of repeated equipment maintenance tasks and the number of pre-test tests , In area 、 Device type 、 Time 、 Multi dimensional linkage analysis of voltage grade , Real time monitoring and management of power grid maintenance and operation .

Carry out data management for power grid equipment overhaul management , It can be used for technical transformation projects 、 Overhaul items 、 The number and amount of funds for the completed projects of technical transformation and overhaul , Conduct linkage analysis and comparative analysis from the dimensions of time and region , Realize the overall management and control of design and overhaul projects .

Yonghong BI Overhaul of power grid equipment Demo

Operation and maintenance cost analysis , The maintenance cost can be calculated from the annual and monthly dimensions 、 actual cost 、 Number of unplanned power outages 、 Conduct comprehensive analysis on outage time of maintenance work , Timely find out that the operation and maintenance cost is too high , Areas and equipment that have been overhauled for too long , Realize accurate reduction of operation and maintenance costs .

Yonghong BI Operation and maintenance cost analysis Demo

In operation management analysis , The completeness of technical management data can be improved 、 Completion rate of overhaul project plan 、 Equipment account coverage 、 Planned completion rate of renovation project 、 Data integrity rate of main distribution network 、 Compliance rate of condition monitoring 、 The timeliness of fault information and the coverage of status detection are the eight core indicators of operation management , From region to region 、 Time 、 Device type 、 Comprehensive analysis of multiple dimensions such as voltage grade , Help power enterprises to monitor the operation performance in real time , Discover the change points in internal operation , Timely optimize resource allocation , Implement the analysis , Effectively support the management improvement of power enterprises .

For equipment safety , Then the transformer availability factor can be calculated 、 Circuit breaker availability factor 、 Transmission line unplanned outage rate and transmission line availability factor are four core safety management indicators for real-time monitoring and management , Give early warning of equipment safety risks in time .

Yonghong BI Safety analysis of power grid equipment Demo

Program value

1、 Platform value

Greatly reduced 了 Data analysis application construction threshold , Let's build data analysis applications 不 Hang high in the air . As business and management value is realized , Form a good snowball cycle , Give full play to the great value that data brings to the enterprise .

2、 Business value

Help enterprises improve the accuracy and timeliness of data , Improve the innovation of operation management , Improve the decision-making level of enterprises , Realize the online monitoring and panoramic display of the company's main business activities and core resources , Fully understand the operation status of the enterprise .

3、 Customer value

Help power enterprises build data analysis application system , Consideration 不 The characteristics and requirements of the same analysis topic , Quickly build analytical models , Real data-driven decision making . Through data operation ,不 At the same level, the data analysis results are transformed into operation management and strategies , So as to really release the value of data , Building the core competitiveness of enterprises .

Typical application cases

Case a ：

The informatization application framework of a nuclear power group is based on ERP At the core , Business processes are centralized IT Application mode , After years of construction and application , Gradually accumulated a large number of valuable data resources . Each member company of the group based on its own business needs , Gradually start the exploration of in-depth analysis and application of data resources . When the existing management visual analysis tools cannot meet the requirements , A lighter weight is needed 、 convenient 、 A development tool platform for self-help innovative data application , To meet the needs of the group's functions or business units at all levels to manage the application of visual means , Support the group's digital transformation , Meet business online monitoring , Support data mining 、 Analysis and other big data services , Improve the data governance level of the group .

1、 Pain points

Use traditional reporting tools to provide data analysis services , It is difficult to develop reports in practical applications 、 The response was not timely 、 Data cannot be supplemented 、 Authority is not easy to control 、 Problems such as scheduling failure to monitor . Facing the complex and changeable data analysis needs of front-end business users ,IT The technical department is unable to respond in time , Become the bottleneck of business process .

2、 programme

Group level big data analysis platform ： Extremely easy to use 、 Self service 、 High performance 、 Stable and safe 、 Open and flexible 、 Report scheduling whole process monitoring .

Solution supporting capacity ： For the nuclear business , Provide data application consulting services and on-site training guidance services , Enable data analysis thinking and data operation methodology , Design and complete nearly 100 operation and management indicators , Successfully transfer the data analysis methodology and experience to the customer's own team .

3、 earnings

Report development cycle is shortened ： The development cycle is shortened from weeks to days , Greatly improved IT Efficiency and responsiveness of the Department , Reduced labor costs .

Improve self-help analysis ability ： Business users should at least 30% The analysis requirements of can be realized through self-service data analysis and application exploration .

1 Eight themes were successfully delivered within a period of years （ Customer / operating / business / Prescription / Quality control / Risk, etc. ）, near 500 An analysis report , And cultivated 20 More than professional data analysts , Self service capability .

Case 2 ：

The project mainly focuses on the operation of equipment and facilities 、 Control and customer service are three core management objects , Data analysis and visualization cover 7 Categories: 67 Indicators 、83 An analytical perspective . The source data covers the basic equipment data 、 Equipment operation data 、 Telemetry data 、 Remote signaling data 、 Alarm data 、 Work order data, etc . Converging in the data center to form 129 Data sheets , contain 3700+ Data fields , The total amount of data involved is about 7.4TB. The system users cover the headquarters 、 province 、 City 、 County and district level Four , There are more than ten thousand registered users , Live more than 2000 people , The daily traffic of the report is nearly 10000 Time .

1、 Pain points

Data is scattered in big data platforms and traditional data warehouses , The daily increasing data volume is nearly 5 Ten million lines , Large amount of data , Data warehouse can only provide data support for nearly three months . The system resource consumption is large and the response speed is slow , It is difficult to provide effective support for the application of data statistical analysis . There is no analysis in the whole report 、 Full results without insight , Business departments at all levels can only extract data from the system based on Excel Make reports , The analysis dimension is single 、 Poor timeliness 、 Long cycle and lack of insight and Thinking on data .

2、 programme

High performance computing cluster ： High performance and fast response 、 Load balancing 、 Highly available backup 、 Unified deployment , Realize rapid analysis of large amount of data .

Mixed use of data ： For statistical indicators, it is calculated on a daily basis 、 Monthly summary and extraction to high-performance computing platform for label storage , Meet the efficiency of daily business applications and realize long-term storage , When drilling down to the detail level, query from the original data platform , Give full play to the comprehensive computing power of each data platform .

Professional consulting and training services ： Design operation and maintenance index system and realize business closed loop , By empowering business personnel to improve their data analysis ability , Achieve full business control 、 Systematic analysis .

3、 earnings

After high performance calculation ,80%+ Analysis report response time is less than 3 second 、90% The response time of the above analysis report is less than 5 second , Performance improvement 30 More than times , Improve the efficiency of data analysis 41%, Monthly data analysis saves more manpower than 2100 Man hour , The new demand response cycle has increased from a few weeks to 2 Within days , Statistical indicators from the original can only be analyzed recently 3 Months up to permanent storage and Analysis .