Unified operation optimization model of integrated coal mine energy systems and its solutions based on autonomous intelligence

An integrated coal mine energy system involves the production, transmission, conversion, storage, and consumption of multiple types of energy with complicated coupling relationships. The operation optimization problem of this system is characterized by multi-scenario, multi-variable, multi-objective, and strong constraints, making it difficult to be solved. Based on the structure of this system, a unified system operation optimization model suitable for various scenarios is established to minimize the economic and carbon transaction costs. To effectively solve optimization problems in various scenarios, we propose an autonomous intelligent optimization strategy based on a support vector machine to make full use of their characteristics in various scenarios to generate the most target intelligent optimization algorithms. To improve the performance of a population in convergence under strong constraints, we develop three strategies for repairing infeasible solutions according to specific preferences. Taking a mine in Shanxi Province as the object under test, a series of experiments are conducted under four typical scenarios, and the experimental results show the effectiveness of the proposed algorithm. • A unified model for the operation optimization with various scenarios is established. • SVM-AIO is developed to generate algorithms according to problem characteristics. • Three repair strategies are designed to guide the evolution towards feasible regions.