Soft Actor-Critic Reinforcement Learning Improves Distillation Column Internals Design Optimization
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A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
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Designing terrestrial multijunction (MJ) cells with 5+ junctions is challenging, in part because the presence of atmospheric absorption bands creates a design space with numerous local maxima. Here we introduce a new taxonomical structure which facilitates both numerical convergence and the visualization of the resulting designs.
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Abstract not provided.
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Abstract not provided.
Abstract not provided.