@article{(Open Science Index):https://publications.waset.org/pdf/10012455,
	  title     = {Elegant: An Intuitive Software Tool for Interactive Learning of Power System Analysis},
	  author    = {Eduardo N. Velloso and  Fernando M. N. Dantas and  Luciano S. Barros},
	  country	= {},
	  institution	= {},
	  abstract     = {A common complaint from power system analysis students lies in the overly complex tools they need to learn and use just to simulate very basic systems or just to check the answers to power system calculations. The most basic power system studies are power-flow solutions and short-circuit calculations. This paper presents a simple tool with an intuitive interface to perform both these studies and assess its performance in comparison with existent commercial solutions. With this in mind, Elegant is a pure Python software tool for learning power system analysis developed for undergraduate and graduate students. It solves the power-flow problem by iterative numerical methods and calculates bolted short-circuit fault currents by modeling the network in the domain of symmetrical components. Elegant can be used with a user-friendly Graphical User Interface (GUI) and automatically generates human-readable reports of the simulation results. The tool is exemplified using a typical Brazilian regional system with 18 buses. This study performs a comparative experiment with 1 undergraduate and 4 graduate students who attempted the same problem using both Elegant and a commercial tool. It was found that Elegant significantly reduces the time and labor involved in basic power system simulations while still providing some insights into real power system designs.},
	    journal   = {International Journal of Educational and Pedagogical Sciences},
	  volume    = {16},
	  number    = {3},
	  year      = {2022},
	  pages     = {120 - 125},
	  ee        = {https://publications.waset.org/pdf/10012455},
	  url   	= {https://publications.waset.org/vol/183},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 183, 2022},
	}