A machine-learning approach to speed-up simulation towards the design of optimum operating profiles of power plants

Rosado-Tamariz, Erik; Zuniga-Garcia, Miguel A.; Santamaría-Bonfil, Guillermo; Batres, Rafael

doi:10.1145/3323716.3323735

Cited by 1 publication

(2 citation statements)

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“…The proposed strategy is based on an integrated approach that encompasses the synthesis of optimum operating procedures of high efficiency conventional thermal power plants and the sector coupling to supply useful thermal energy. The development of this approach involves metaheuristic optimization algorithms, 22 dynamic simulations models, response surface models, and machine learning models 23 …”

Section: Background Contextmentioning

confidence: 99%

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Enhanced dynamic simulation approach towards the efficient mining thermal energy supply with improved operational flexibility

et al. 2020

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Summary This paper presents a thermal power plant retrofitting approach focused on improvements in the operational flexibility of existing combined cycle power plants dedicated to providing thermal energy for medium and low‐temperature processes in copper mining facilities. The main motivation for this research was aimed at evaluating the operational flexibility of the electrical industry through sector coupling and its effect on solving the energy sector decarbonization issues. The research evaluates the advantages of hybridization systems for supporting the electrical and mining industries to better predict operations. The proposed approach is based on a dynamic simulation scheme that finds the optimal operating parameters of the combined heat and power (CHP) system, such as location, type, and arrangement of each component of the CHP system. The power plant dynamic simulation model was validated against data available in the literature; it was also characterized by real operational data of the San Isidro II power plant installed in Chile. Several alternatives for the cogeneration plant location, as well as the splitter system design, were investigated and then compared. A cogeneration plant design with two heating modules was selected based on the comparative study performed in this work and its CHP system was evaluated for a load reduction case study. The results were compared against a reference model. The proposed CHP system exhibited improved performance: a minimum of 15% of the exhaust gases are required to supply the thermal energy demand of the electrowinning process when a full load is considered. It was also found that an average decrease of 5% of the mechanical power at each steam turbine stage noted. Finally, the proposed CHP system's average thermodynamic efficiency is found to be 19% greater than the power plant average efficiency. Consequently, an average decrease of 32 500 tons of carbon dioxide emissions per year is predicted.

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Section: Background Contextmentioning

confidence: 99%

“…The development of this approach involves metaheuristic optimization algorithms, 22 dynamic simulations models, response surface models, and machine learning models. 23 3 | PROPOSED METHODOLOGY…”

Section: Background Contextmentioning

confidence: 99%