Educational Strategy Combining Technological Capacity and Ant Colony Algorithm to Improve the Ideal Dispatch Using Wind Energy Neider Duan Barbosa Castro , Jhon Alexander Hernández Martin , Fabiola Sáenz Blanco , and Evy Fernanda Tapias Forero Abstract In this article, the reader will find an educational strategy, combining technological capacity and ant colonies to improve the ideal dispatch with plants of solid generation (hydraulic and thermal) and plants with variable generation (wind), as a case study for a Colombian electricity network. In order to achieve this process, we intend to use problem-based learning strategy as follows: posing the problem, listing the known data, dividing the main problem in analog form, looking for and implementing solutions, and consequently looking at the technological assets of all plants. This information is registered into the McKinsey matrix and finally, the solutions are analyzed. 1 Introduction The projections of the world energy panorama for the next 20 years contemplate an energy scenario based on an intensive exploitation of resources due to the increase in energy demand throughout the world. This could have worrying consequences and impacts at the energy level, due to the reduction of reserves and at the economic level, due to the increase in fuel prices, among other aspects. Under these conditions, non- conventional renewable energies emerge as a mechanism within the energy landscape that favors environmental sustainability [1] N. D. Barbosa Castro (B ) Compensar University Foundation, Bogota, Colombia e-mail: ndbarbosac@ucompensar.edu.co J. A. Hernández Martin National Learning Service, Medellín, Colombia e-mail: jhonmartin56@gmail.com F. Sáenz Blanco University Distrital Francisco José de Caldas, Bogota, Colombia e-mail: fsaenz@udistrital.edu.co E. F. Tapias Forero Colombian Technology Corporation, Bogota, Colombia e-mail: eftapiasf@correo.udistrital.edu.co © Springer Nature Singapore Pte Ltd. 2022 S. Bennani et al. (eds.), WITS 2020, Lecture Notes in Electrical Engineering 745, https://doi.org/10.1007/978-981-33-6893-4_51 553