Optimal scheduling with opposition based differential evolution optimized fixed head hydro-thermal power system

This research incorporates an optimization techniques Opposition-based Differential Evolution (ODE) for estimating optimum hourly energy generation scheduling of a hydro-thermal system. In order to increase the efficacy and quality of the solution the ODE is used. The suggested ODE uses opposition-based learning(OBL) to initialize population as well as for enhancing generation. Two fixed head hydrothermal tests have been taken to verify the efficacy of the suggested technique. These results are contrasted with the results of other techniques of evolution. It has been concluded that the proposed technique is capable of providing a better solution.Copyright (c) 2022 Elsevier Ltd. All rights reserved.Selection and peer-review under responsibility of the scientific committee of the International Conference on Artificial Intelligence & Energy Systems.

Automated summary

This research uses optimization techniques based on Opposition-based Differential Evolution (ODE) to estimate the optimum hourly energy generation scheduling of a hydro-thermal system, aiming to improve the efficacy and quality of the solution.