Application and research of global grid database design based on geographic information

1 Introduction

Chinese President Xi Jinping delivered a keynote speech at the UN Sustainable Development Summit in the United Nations Headquarters in New York on Sept. 26, 2015,proposing a discussion on establishing a Global Energy Interconnection to facilitate efforts to meet the global power demand with clean and green alternatives. This global initiative has received widespread praise and positive response from the international community.

GEI is an infrastructure platform on which clean energy can be developed, transmitted and used massively worldwide[1]. By definition, it is “Smart Grid + UHV Grid + Clean Energy”. With the explosive growth of the data to be processed, the research on GEI is facing unprecedented opportunities and challenges [2]. However, the existing data management and analysis methods can hardly support the storage, management and analysis of such a large amount of complex and rapidly growing data [3-7]. Gathering and building a global grid database is one of the prerequisites for conducting research on GEI. Therefore, it is urgent to build a global grid database based on geographic information to realize the visual management of power lines, substation facilities, electrical parameters and other information of different voltage levels in different countries. Strengthen the ability on data collection, storage, processing and analysis of the entire value chain, to provide technical support for GEI research.

In this paper, a global grid database based on geographic information is designed and implemented. The paper is organized as follows. Section 2 presents the global grid data acquisition and management mechanism according to big data and geographic information technology. Section 3 sorts out and designs the global grid database structure. A grid data hierarchical simplification algorithm is proposed in Section 4. In Section 5, the applications of the global grid database are presented. Finally, section 6 concludes the paper.

2 Acquisition and processing mechanism of global grid data

2.1 Data content

Global grid data includes grid geodata and electrical parameters data. The specific data content and related indicators are shown in Table 1.

Table 1 Data categories of global grid database

1st level index 2nd level index 3rd level index Substation Name, Type, Voltage level, Stage, Country...Transmission Line Start point, Terminal point, Length, Voltage level, Stage, Country...Generation Name, Type, Status, Voltage level, Stage, Country...Grid geodata Bus Name, Reference voltage, Zone, Active power output, Reactive power output...Transmission Line Start bus, Terminal bus, Number of circuits, Impedance, Admittance, Rated current, Length...Transformer Start bus, Terminal bus, Number of circuits, Rated capacity...Parameter Project name, Result file, Result map file, Iterations numbers...Electrical parameter

2.2 Data sources

The data sources of the global grid database are complex and mainly obtained from the following aspects：

1) National grid companies of each country;

2) The electrical and energy associations or organizations of each country;

3) Regional cooperation organizations;

4) Reports and relevant materials publicly released by various countries;

5) Public internet resources;

6) Historical and available information.

Since the data sources are complex and the data quality is different, a reasonable data acquisition and analysis process is required. According to the characteristics of various types of data, how to integrate the data closely and construct a unified global grid database is studied to provide a complete, accurate, consistent, timely and reliable basic information for the development of GEI research.

2.3 Data acquisition and analysis process

Global grid data acquisition and analysis process includes data collection and integration, data storage and management,data analysis and mining, etc. The three steps are closely linked and progressive. The relationship between the three steps is shown in Fig. 1.

Fig. 1 Process of global grid data acquisition and analysis

1) Data acquisition and integration

According to the data types, the original global grid data is divided into raster data, vector data, grid parameter data, etc.

Raster data： It is mainly the grid geodata of each country. It contains the geographic coordinate information.The process of data translation, registration, vectorization and properties appendant is required to convert raster data to vector data.

Vector geographic data： The data sources include shp format data, ESRI Geodatabase data, CAD data,online map service, etc. The spatial references of various vector data are different. In order to ensure the accuracy and efficiency of subsequent processes, WGS84 spatial reference is adopted as the uniform spatial reference for global grid database.

Vector tile data： The vector tile data has a lot of advantages, such as small storage requirement, high display efficiency, etc. However, it lacks projection information, therefore, data capture, format analysis, data preprocessing, data registration and other processes are required to complete the data acquisition.

Electrical parameter data： The data sources include BPA(Bonneville Power Administration) data, PSS/E (Power System Simulator / Engineering) data, Excel, etc. The data models of different sources are nonuniform. Moreover,there is a problem that grid parameter data cannot match vector geographic data. In this paper, a common data model based on InterPSS ODM (Open Data Model) is constructed to uniformly manage the data required for electrical calculations.

2) Data storage and management

MySQL data warehouse is used to store and manage energy big data [8]. MySQL has good usability, and it makes the system and database management more intuitive and simple through graphical user interface. In addition,MySQL is scalable, which can fully meet the deployment requirements of distributed database [9]. To update and manage data within MySQL through index database, it can greatly improve the efficiency and accuracy of operation[10-11].

The management of geographic data is realized by using Geodatabase data. Geodatabase is a data model provided by ESRI. It organizes geographic information with hierarchical data objects. These data objects are stored in object classes, feature classes and feature datasets. Object class is a table that stores nonspatial data in Geodatabase.Feature class is a collection of feature with the same geometric type and attribute structure.

3) Data analysis and mining

Power grid planning includes power supply-demand balance analysis, load flow calculation, short circuit analysis, etc. [12-14]. In this paper, different types of data,applications and processes of various simulation software are integrated into one unified framework by constructing application integration functional unit. In this way, the requirement of simulation analysis and research is met.Details are as follows：

a) Construct a well-calculated parameter model based on InterPSS ODM. Unified management of parameter data required by electrical calculation and conversion of formats required by different software are realized. The specific data model construction method is shown in Fig. 2.

Fig. 2 Conversion of electrical software data format based on ODM

b) Design a unified data access interface based on the architecture of SOA. Web services are provided to access various types of component model library and parameter library. The data query, browse, extraction and other operations are supported. According to different simulation software, the corresponding data conversion model is constructed to realize automatic data extraction, and the conversion of different data formats.

c) The remote asynchronous calling service is constructed to realize the integration of simulation module. Based on the extracted input data, the specific simulation model is invoked to realize the scheduling control of the calculation process. Moreover, the calculation results are flexibly and intuitively displayed in a graphical way by combining with the visualization technologies such as HTML5, GIS, and BI, etc.

3 Global grid database structure design

3.1 Logical architecture design

In order to centrally manage geographic data and grid parameter data, Geodatabase spatial data model is used to organize the spatial data. The feature dataset of basic geographic data is created to store basic geographic data such as roads, rivers, administrative divisions. The feature dataset of distribution data of grid data is created to store line and substation distribution data. The feature dataset of electrical parameter data is created to store bus and branch parameters of grid. The logical structure of the database is shown in Fig. 3.

3.2 Program management structure design

In this research, a program management mechanism is used to manage the global grid database. The data organization is divided into three levels which are layers,programs and projects. A project includes multiple programs,such as Asia program, Europe and Africa program, North America program, South America program, etc. A program contains three vector layers, which are transmission line layer, substation layer and gereration layer respectively, as shown in Fig.4. Parameter data of electrical components are stored in the project database in the form of attribute tables and associated with layers.

Fig. 3 Logical architecture of global grid database

Fig. 4 Program data management architecture

3.3 Electrical parameters data structure design

At present, most of the existing power system simulation software stores data in the form of text, and uses data in the form of arrays within the program. XML (Extensible Markup Language) is a source language that allows users to define their own markup language. XML is structured,self-describing and scalable. It is widely used to mark data,define the data type. It has also become the factual standard of information description.

The CIM (Common Information Model) standard proposed by IEC (International Electrotechnical Commission)is described by XML and it is usually used to describe the physical grid. However, the model is massive and complex for simulation calculation. It is difficult to use it directly by power system simulation software. Based on the concept of CIM and XML Schema, InterPSS built an optimized model named ODM. In this research, ODM is used as the model of electrical parameters data.

Network, Bus and Branch are the three most basic concepts in ODM. The overall structure of ODM is shown in Fig. 5. The root element is Study Case. The sub elements of Study Case are Base Case and Study Scenario. Base Case contains complete information about the grid data, including bus records and branch records. The bus record contains the base voltage, load flow data, dynamic data, etc. The branch record contains start bus reference, terminal bus ID reference, circuit ID, load flow branch data, etc. The element Study scenario is used to describe the simulation scenario, such as the type of the fault that occurs during dynamically simulation. The element Modification describes the modification of the system parameters of the Base Case, such as area load, output adjustment, etc.

Fig. 5 ODM structure

4 Grid data hierarchical simplification algorithm

Grid data is mainly composed of point and line features.The Global Grid Map gathers massive amounts of grid data and its display range is all over the world. At a small measure scale, a large number of power sources,substations (point features) and power lines (line features)need to be displayed. Especially the line feature, rendering it often requires a large amount of computing resources because it contains a lot of coordinate information. This has led to long response time and poor user experience of map refreshing, zooming, panning and other operations.However, with a small measure scale, observers can only get the approximate outline of the power line usually [15].The details of the specific power line can only be seen by zooming in.

The existing map service technology of image data usually displays in a hierarchical way. The image data is hierarchically tiled to form a pyramid structure storage, as shown in Fig. 6.

Although this increases the space requirement for storing data to a certain extent, it greatly improves the display efficiency of the map and optimizes the user experience. In this paper, a hierarchical simplification algorithm of grid vector data is proposed based on the idea of map hierarchy.Details are as follows：

Fig. 6 Hierarchical tile of image

Assuming the line feature L consists of n points. The horizontal range of the map’s spatial extent is [xleft,xright],the vertical range is [ybottom,ytop]. The map is divided into m levels and indexed by Quadtree. The first level contains one quadrant, the second level contains four quadrants, and so on.

1) Calculate the spatial range of each quadrant of the i-th level. There are 2i-1 rows, 2i-1 columns and 2(i-1)*2 subquadrants totally in i-th level. The sorting rule is from top to bottom and left to right, and the starting index number is 0. The spatial range of the j-th quadrant of the i-th level is defined as

where the width and height of each sub-quadrant is

2) Calculate quadrants that each point of the line feature locates. For the i’-th point pointi’ of line feature L, set

The location of pointi’ is

3) Divide coordinate points of the line feature according to the quadrant range. Starting from the first point point0,traverse all the coordinate points of current line feature, and calculate which quadrant each point locates in according to step 2). Record the coordinate points in the same quadrant to one set List〈point〉i (i≥0).

4) Simplify line feature. After traversing the n coordinate points of the line feature L according to step 3), n’ point sets are obtained. Simplify each point set：

a) Set the number of coordinate points contained in List〈point〉i (0≤i〈n’) as k. If k≤ 4, there is no need to simplify. If k〉 4, the first and the last coordinate points of current set are reserved, and then the MBR (Minimum Bounding Rectangle) is established for the 2nd to the k-1th coordinate points. The points from the 2nd to the k-1th which fall on the border of the MBR are taken as the key points. Store the first point, key points and the last point into key points set ListKeyPoint〈point〉.

b) Filter the key points obtained in step a). Traverse the key points set, for i’th point keypointi’, if , remove keypointi’ from the key points set.

5) Unify all the key point sets obtained by the above steps and get the key points set of L under the current level.The simplification of line feature L under the current level is complete.

6) Traverse all the levels of the map according to the steps from 1) to 5). The simplified line of the line feature L under all levels can be obtained.

The simplification of line feature is shown as Fig.7.Fig.7 (a) shows the initial condition of a line feature. The blue line represents the initial line feature L and the current map is divided into four quadrants; Fig. 7 (b) shows the simplification of the line feature in the first quadrant.Yellow points indicate the starting and ending points within the current quadrant. The red rectangle represents the MBR that is generated. The red points represent the key points obtained by the MBR. The dashed red line represents the resulting simplified line. Fig. 7 (c) shows the simplification of the entire line feature at current level. The dashed red line represents the simplified line feature. It can be seen that the simplified line preserves most geometric information of the original line feature while the coordinate points have been greatly simplified.

Fig. 7 Line Simplification

5 Global grid database application

The application of global grid database includes：

1) Management of “one map” data of the global grid is realized. GEIDCO has collected data of various sources and drawn the world’s first “Global Grid Map”, as shown in Fig. 8. It covers the main framework grids of more than 140 countries in six continents (Asia, Europe, Africa,South America, North America and Oceania). Although the years of data are uneven and there is a lot of room for optimization and improvement, it still provides a rich data foundation for the research on the GEI.

2) A visual data maintenance update process is achieved.During the process of grid database construction, visual planning and design software was developed synchronously to support the updating and maintenance of grid data, such as project data management, graphic browsing inquiry,graphic data editing, graphic symbolization setting, parameter data management, layer management, graphic element editing and cartography output, etc. The functions of browsing, querying, editing and outputting graphics are realized, as shown in Fig. 9.

3) Online release and statistical analysis of global grid data are realized, as shown in Fig. 10. A global grid database publishing and visualization system is established based on B/S. The system provides fast browsing function of grid project distribution, project attribute and electrical parameter data in different voltage levels in the browser.It is easy to retrieve and count data of different voltage levels as well.

4) The connection with professional simulation analysis software is realized. Through the interface integration, the system realized the integration call based on the global grid database and professional simulation analysis software,including project management, data import and export,data conversion, online computing, results analysis, power flow graph display, etc., as shown in Fig. 11.

6 Conclusion

In this paper, aiming at the grid database construction in the context of GEI, taking global grid data as the research object, a set of reasonable data acquisition and processing mechanism are designed by analyzing the global grid data content and data sources. At the same time, a global grid database structure is proposed and the database is constructed. The functions of visual management, data maintenance and statistical analysis based on geographic information are realized. In addition, the integration of database and simulation software is realized, including the management and maintenance of the data required by simulation calculation, data conversion among different software, calling the analysis and calculation function,and the storage and visualization of the calculation results.It is a great support for the GEI research. The proposed global grid database structure, data acquisition and analysis mechanism based on geographic information are universal and have good promotion value.

Fig. 8 Global Grid Map

Fig. 9 Graphical maintenance interface of global grid database

Fig. 10 Statistical analysis of global grid diagram

Fig. 11 Integrated presentation of power flow calculation