Abstract
A steam generator serves as a power generation equipment that uses the expansive power of steam to generate electricity. The startup process of a steam generator plays an important process in a power plant to adjust its electricity generation in response to changes in load 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 the load demand. The drum boiler is one of the main pieces of equipment involved in the startup process of a steam generator. However, if the startup process is carried out too fast, excessive thermal stresses may occur, thus provoking damage to the components of the drum boiler. This paper proposes a dynamic optimization methodology to synthesize operating procedures 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. The proposed algorithm is based on two important elements of two metaheuristic algorithms: the acceptance probability of the simulated annealing algorithm and the tabu search memory structures. A case study evaluates the proposed approach by comparing it against results previously published in the literature.
Highlights
Conventional thermal power plants (CTPP) play a key role to deal with one of the biggest challenges of the energy sector: the reliable and efficient supply of electricity
To overcome the limitations of previous works, this paper proposes a scalable approach for the synthesis of operating procedures that minimize the startup time of the drum boiler while avoiding the excessive formation of thermal stresses
The results were compared against a benchmark solution [17] and a solution obtained with the micro genetic algorithm described in [10]
Summary
Conventional thermal power plants (CTPP) play a key role to deal with one of the biggest challenges of the energy sector: the reliable and efficient supply of electricity. When coping with normal demand variations or when variable renewable energies cannot meet the demand, CTTP generation has to be adjusted employing lower or greater production of electricity (reduction or increase of load) respectively. This adjustment is applied by doing start-ups and shutdowns of equipment in the power plants. The drum boiler has the potential to improve the competitiveness of a thermal power plant by reducing its startup time. Despite the focus on startup-time reduction, current approaches [9,13,14] fail shortly because they can only obtain startup curves of the drum boiler state variables but cannot identify the corresponding control actions (operations) and their sequence.
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