2022
Autores
Klyagina, OS; Zatsepa, SN; Pokazeev, KV; Solbakov, VV;
Publicação
Springer Proceedings in Earth and Environmental Sciences - Physical and Mathematical Modeling of Earth and Environment Processes
Abstract
2022
Autores
Garcia, S; Elhawash, M; Cabral, J; Hormigo, T; da Encarnação, T; Alves, S; Dias, A;
Publicação
2022 Solid-State Sensors, Actuators and Microsystems Workshop, Hilton Head 2022
Abstract
Satellite gravimetry requires sub-ng acceleration measurement at frequencies below 100mHz. To bring the performance of a MEMS accelerometer closer to this level, one must decrease noise sources and maximize sensitivity (to decrease input-referred electronic noise). Electrostatic pull-in based operation has great potential for high sensitivity since it relies on time transduction. Devices were fabricated with maximized proof mass (170mg over a 13x14mm2 footprint) and tuned damping coefficient (trade-off between noise and sensitivity – pull-in operation requires low Q-factors). Novel stopper designs and caps limit both in-plane and out-of-plane displacements. Devices tested using pull-in voltage-based transduction showed sensitivity of 218 V/g. © 2022 TRF.
2022
Autores
Carrillo-Galvez A.; Flores-Bazán F.; Parra E.L.;
Publicação
Applied Energy
Abstract
Although electricity is a clean and relatively safe form of energy when it is used, the generation and transmission of electricity have severe effects on the environment. An alternative to diminish the polluting emissions released by the generating units is the Emission Constrained Economic Dispatch (ECED). This is an optimization problem where the total fuel cost is minimized while treating emissions as a constraint with a pre-specified limit. Usually, the fuel cost and emission functions of the generating units must be experimentally derived, introducing then uncertainties in the obtained models. However, these uncertainties are often neglected and the ECED problem is solved considering the coefficients of the functions involved as exact (totally known) values. In this investigation we analyzed the effect of the uncertainties associated to the experimental derivation of the input–output curves of thermal power plants. Particularly, when polynomial models are fitted through multiple linear regression, we proposed an approach that, based on the respectively prediction intervals, can provide solutions immunized, in some sense, against variability in the coefficients estimates. We tested the proposed approach in a real system from the Chilean electrical power network. For the analyzed system we noted that, when uncertainties are not considered, the deterministic optimal solutions can be environmentally infeasible in some scenarios; whereas solutions obtained through the proposed approach, can significantly diminish the risk of environmental violations. The robustness of the prediction interval-based solutions was obtained with a negligible increase of the total fuel cost in all the cases studied.
2022
Autores
Pedro Gelati Pascoal; Leonardo A. Brum Viera; Cassiano Rech; Rafael Concatto Beltrame; Vitor Cristiano Bender;
Publicação
Procedings do XXII Congresso Brasileiro de Automática - Procedings do XXIV Congresso Brasileiro de Automática
Abstract
2022
Autores
Vera, EG; Canizares, CA; Pirnia, M; Guedes, TP; Melo, JD;
Publicação
IEEE Transactions on Smart Grid
Abstract
2022
Autores
Bot, K; Aelenei, L; da Glória Gomes, M; Silva, CS;
Publicação
Renewable Energy and Environmental Sustainability
Abstract
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