Renewable Energy on Data Collection and Visualized Hosting Capacity
Hosting Capacity Visualization System for Transmission Power Supply System and Power Distribution System
1. Background Information
In recent years, with the government expanding its efforts to promote the green energy development policy, related renewable energies such as photovoltaics, wind power, hydroelectricity and geothermal power, all of which are Distributed Energy Resources (DER), will be massively grid-connected to the distribution system, and it will significantly change the entire distribution network structure. The electric power will no longer be generated by the generator units in large power plants, but rather be generated by small and decentralized devices. In order to fully understand the grid-connection status of the renewable energies, Taipower began to develop the Distribution Planning Information System (DPIS) since years ago, attempting to regulate the possible impact to the system when those energies are grid-connected by adopting the application review mechanism for Distributed Energy Resources.
According to records, there are nearly 10,000 feeders in the power distribution lines in Taiwan. The amount of data is huge and its number in the hosting capacity sections is as high as 3.26 million. When presented on a traditional web-based graphics platform, it would consume a considerable amount of software and hardware resources and may result in performance problems caused by a large amount of map data loading. Therefore, the Map Tile display technology will be used to generate the map tile files after the incorporation of timed calculations of each hosting capacity section, and then combined with the TGOS Address Geocoding Service and the generic version of the electronic maps to construct the visualized distribution feeder hosting capacity system. The system provides the public or the industry to conduct a location query by means of an address to achieve the purpose of visualizing the distribution feeder hosting capacity.
2. System Architecture Description
The system is divided into two parts: the internal system and the external system. In order to allow external users to have a more intuitive understanding on the possible hosting capacity of feeder line, this project will regularly extract the topology information of existing distribution equipment from each business branch of Taipower by using the Extract-Transform-Load (ETL) technology. This project then simplifies it to become the information structure required to calculate the possible hosting capacity and subsequently summarize and send it to the information center as the basic information for computation. We tested several computing cores and compared their benefits. Analyze its accuracy and calculation speed, and choose the best one.
Calculation results will integrate to the Geographic Information System (GIS) technology and displaying the possible hosting capacity of each feed line section on the map with colors.
Furthermore, to solve the performance issue that may be caused by external users downloading a large number of map data, this project constructs a feeder hosting capacity visualization system by using Map Tile display technology. It was thereby achieving the establishing hosting capacity visualization of the feeder.
3. Power System Impact Analysis
This system integrates data from several systems automatically, such as Distribution Mapping Management System, Renewable Energy Management Systems, Distribution Planning Information Systems, etc. Input data mainly include wire parameters, transformer parameters, electrical connectivity, power distribution equipment data, transformer data, load data, renewable energy data, user data, coordinate points, etc. Comprehensively organize all the materials and build a complete feeder input file. The schematic diagram of power system impact analysis is shown in the right picture.
Taipower has about 10,000 total feeders, and the number of calculations for each joint is very large. Considering the overall load of the mainframe and the accuracy of the data, the core of the most cost-saving calculation is adopted. Each joint will be inversely calculated one by one, and get the maximum hosting capacity finally. It will be the basis of updating the externally displayable hosting capacity.
4. System introduction
In order to allow the user to clearly view the hosting capacity of each section of feeder, we indicate the hosting capacity of each section by means of color display. This referred to the webpages which are built by the foreign electricity utility.
The hosting capacity is divided into six levels and six colors from small to large, and display on the geographic map.
(1) Feeder hosting capacity visualization system for power distribution system:
(2) Line hosting capacity visualization system for Transmission power supply system (Due to national security issues, only opened for internal use):
5. Future Development
The system is designed to collect data, calculate hosting capacity and release map tiles automatically. Through the artificial elimination of abnormalities, it is expected to improve the system's capabilities.
Compared with the relevant open systems of advanced countries, this system is more advanced, integrated and flexible in development. It can provide consistency comprehensive information for the government, the electricity industry, the industry, and users about renewable energy build land and hosting capacity. It may help to achieve 20% renewable energy government policy before 2025.
In the future, more information will be collected to strengthen the system impact analysis and reduce the need for human intervention. We will continue to study and modify the logic of constructing feeder and make the feeder closer to the actual situation.
Renewable Energy Monitoring
TaiPower company had 169 wind turbines in 17 sites in Taiwan, including 5 brands and 8 models. Each brand of manufacturer has developed and designed its monitoring system. To facilitate the unified and centralized management of real-time operation information of wind power stations scattered across Taiwan and outlying island, a complete integrated monitoring platform system has been established since 2011. After the compiled program interface determines the status of various types of wind turbines, it will organize the operation status in real-time and display on the website.
2. Architecture of the Monitoring platform system
Due to the difference in the communication system of wind turbines, we need to integrate different wind turbine operation information. We set up a system provided with an interface computer beside the original monitoring computer of each wind power plant, connect with the OPC communication protocol to retrieve the real-time operation information. The data is transmitting from the regeneration office via of Taipower company through the communications network to monitoring center server room in office (PISRV1，main server)and Onshore Wind Power Plant computer server room (PISRV2，backup). Then the original data of PISRV1 will transmit to another server (PISRV3) on the company intranet through an isolator, finally established the data structure through a logical layer computer (PIAF01). The web host (PIWEB) then retrieves the data and builds a website for users to connect with the browser to improve network.
Each wind power station system is roughly similar. Taking the〝Datan wind power station〞as an example, it was established in three-phase with a total of 8 wind turbines, 3 different brands of the manufacturer, including 3 GE’s、2 Enercon’s and 3 Vestas’s wind turbines. Therefore, it is more complicated to retrieve data in the interface. The data transmission structure is as shown below.
The wind turbine operation data of Datan wind power station was retrieved from the original computer SCADA data and directly transmit to the main engineering room in Taichung control center office through the interface of Datan power plant microwave computer room.
3. Security and Convenience
In response to the intermittent renewable energy power generation, TPC currently collects information on renewable energy power generation systems and developed a 48-hour renewable energy power generation forecasting system through algorithms. It can help to optimize the dispatch and be used to arrange the unit's scheduled maintenance as a massive amount of renewable energy feed-in the grid in the future.