Optimal scheduling of multi-energy medium in steel enterprises based on improved genetic simulated annealing algorithm

The scheduling of energy medium in steel enterprises is a complex problem of multi-media coupling and multi-period coordination. Considering the time-of-use electricity price, a mathematical programming model for the optimization of byproduct gas is established. Aiming at the above model with more variables and constraints, an improved genetic simulated annealing algorithm is proposed based on matrix real-coded. The initial population is generated by using the chaos theory which is characterized by randomness and ergodicity. The simulated annealing process and constraint handling strategies are carried out for new individuals to maintain population diversity. The comparison experiment simulation verifies that the proposed method can solve the problems of optimal allocation of energy medium and reduce the production cost.