Research on Simulation Training System of Immersive Substation Based on Virtual Reality

Abstract

Virtual reality technology has been widely used by constructing a virtual space to simulate and restore the real world. The system uses 3ds MAX and Unity3D software to establish a 500kV substation virtual simulation system. The system completely establishes the 3D models of primary and secondary equipment of 500kV substations, and truly restores the overall layout of the substations. At the same time, the Unity3D engine, VR technology and interactive equipment are used at the same time to make this system able to provide trainees with an immersive training experience, which is more realistic than the application over the same period. The system completes the realization of substation training, station roaming and fault simulation functions, including substation equipment technical parameter display and synchronous voice introduction, interface design, basic operation, and fault phenomenon simulation; the infrastructure of the system is developed well and has strong expandability, which lays a foundation for subsequent function development. This system satisfies the substation training needs and can be used for related staff training of substations and to help students in electrical major to gain cognitive learning.

A comparative analysis of the application of Fourth Industrial Revolution technologies in the energy sector: A case study of South Africa, Germany and China

“…Voyant et al (2017) speak of machine learning (or AI) techniques that may be used to better forecast solar radiation, which allows solar plants to optimise productivity. Yunfeng and Mingming (2019) and Liao et al (2019) explain how AI (or virtual reality) is being used to reproduce various operational environments in the power system for power grid simulation teaching and training, safety and rescue training, and virtual maintenance testing of power system equipment, as well as addressing training-related challenges such as lack of personnel and the need for expensive testing equipment. Machines are being developed to carry out what Makala and Bakovic (2020, 2) refer to as 'deep learning' to 'help discern patterns and anomalies across very large datasets -both on the power demand and power supply sides -that otherwise would be nearly impossible to achieve.…”