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| Research on Transient Real-Time Simulation of New Energy Low-Voltage DC Distribution System Based on Field Programmable Gate Array |
| Wang Shouxiang1,2, Zhang Chunyu1,2, Zhao Qianyu1,2 |
1. Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin 300072 China;
2. Tianjin Key Laboratory of Power System Simulation and Control Tianjin 300072 China |
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Abstract New energy low-voltage direct current (DC) distribution system is closely connected with the power consumers and has advantages of low construction cost, high operation efficiency and high compatibility of power electronic devices. However, the new energy generation systems that have fluctuating and intermittent characteristics directly affect the stability and reliability of the low-voltage DC distribution system operation. A real-time simulation device of the low-voltage DC distribution system can reproduce its dynamic characteristics in real time to help each device in the system complete hardware-in-loop test so as to improve the stability and reliability of the entire system. As an application-specific integrated circuit, field programmable gate array (FPGA), which integrates various functional circuits, has the advantages of small size, low cost and outstanding parallel computing capabilities. But one factor that must be considered is that FPGA only has limited hardware resources, which determines the operation of the simulator. As a result, in the development of FPGA-based simulator, both the real-time performance of simulation calculation and the operating efficiency of internal hardware resources should be taken into account. After considering these issues, this paper develops an FPGA-based real-time simulator of low-voltage DC distribution system containing a variety of distributed new energy sources.
Firstly, the characteristics of different types of distributed power supply are analyzed and the corresponding simulation method based on FPGA is designed. The simulation method of the switching components of power electronics is obtained by using the associated discrete circuit method. Secondly, an FPGA-based simulation architecture of the new energy low-voltage DC distribution system is presented. In this architecture, the electrical system and the control system operate in parallel to improve the computational efficiency and are further decomposed into smaller functional blocks. The internal floating-point operations are factorized by introducing the methodology of "algorithm architecture adequation (AAA)" to reduce the occupancy of hardware resources inside FPGA. Then, under the framework of nodal analysis method, a parallel solution method for the electrical system nodal conductance matrix combining matrix LDU decomposition and directed acyclic graph (DAG) is established. In this method, after obtaining the triangular matrices L and U, the data dependencies in solving the corresponding equations are expressed in the form of DAG. The DAG is further decomposed and reorganized to multiple new computational areas with relatively balanced computational load so as to improve the computational efficiency of the hardware processing elements (PEs), which are operated in parallel online. Finally, an FPGA-based real-time simulator of new energy low-voltage DC distribution system is developed. The experiment results under different transient scenarios are obtained and compared with the calculation results of PSCAD/EMTDC to verify the effectiveness and accuracy of the developed real-time simulator.
The experiments lead to these conclusions: (1) The comparative experimental results show that the relative error of the real-time simulator constructed in this paper is within the allowable range. (2) The proposed series-parallel hybrid computing architecture established by introducing AAA methodology effectively reduces the occupancy of FPGA internal hardware resources. (3) The proposed real-time solution method of electrical system node conductance matrix combining matrix LDU decomposition and DAG improves the dynamic calculation efficiency of FPGA and the ability to solve high-dimensional linear equations.
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Received: 03 July 2023
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2024, Vol. 39 
