A hybrid metaheuristic optimization approach for the synthesis of operating procedures for optimal drum-boiler startups

A steam generator serves as a power generation equipment that uses the expansive power of the steam to generate electricity. The startup process of a steam generator plays an important role in the ability of a power plant to adjust its electricity generation to changes in demand. As renewable generation plants increase, the levels of variability in electricity production increase. Fast startups become instrumental as they enable traditional power generation plants to provide the quantity of electricity missing when variable renewable energies cannot satisfy demand. A main equipment involved in the startup process of the steam generator is the drum boiler. However, if the startup process is carried out too fast, excessive thermal stresses can occur and provoke damage to the components of the drum boiler. This thesis proposes a dynamic optimization methodology to synthesize operating valve profiles that minimize the startup time of the drum boiler while avoiding the excessive formation of thermal stresses. Since valve operations influence the time-varying behavior of the steam, dynamic simulation is needed in order to evaluate the operating procedure. This thesis proposes a dynamic optimization approach with a hybrid-metaheuristic algorithm that generates the optimal startup procedure of a drum boiler. The proposed algorithm is based on two important elements of two metaheuristic algorithms. Namely, the search zone in the cooling element from the simulated annealing algorithm and the efficient computational performance provided from the tabu search algorithm memory structures. A case study evaluates the proposed approach by comparing it against results previously published in the literature.