Optimization of gas-fired units using teaching-learning meta-heuristic algorithm

The service companies that provide the task of operating the power grids of industrial cities obtain the electricity they need from the electricity markets or gas power plants. To minimize the company's cost, an objective function is introduced considering the energy supply constraints of consumers, gas unit constraints, and recycling system constraints. The algorithm used for optimization is the heuristic learning-learning algorithm, and finally, the simulation results of the introduced algorithm have been compared with the genetic algorithm. The codes related to the simulation are presented in the software of the article and the relevant results show that the teaching-learning algorithm can find the optimal solution to the problem faster than the genetic algorithm.