A comprehensive thermo-economic model combining a geothermal heat mining system and a direct supercritical CO_(2) turbine expansion electric power generation system was proposed in this *** by this integrated model,th...
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A comprehensive thermo-economic model combining a geothermal heat mining system and a direct supercritical CO_(2) turbine expansion electric power generation system was proposed in this *** by this integrated model,thermo-economic and optimization analyses for the key design parameters of the whole system including the geothermal well pattern and operational conditions were performed to obtain a minimal levelized cost of electricity(LCOE).Specifically,in geothermal heat extraction simulation,an integrated wellbore-reservoir system model(T2Well/ECO_(2)N)was used to generate a database for creating a fast,predictive,and compatible geothermal heat mining model by employing a response surface methodology.A parametric study was conducted to demonstrate the impact of turbine discharge pressure,injection and production well distance,CO_(2) injection flowrate,CO_(2) injection temperature,and monitored production well bottom pressure on LCOE,system thermal efficiency,and capital *** was found that for a 100 MWe power plant,a minimal LCOE of$0.177/kWh was achieved for a 20-year steady operation without considering CO_(2) sequestration *** addition,when CO_(2) sequestration credit is$1.00/t,an LCOE breakeven point compared to a conventional geothermal power plant is achieved and a breakpoint for generating electric power generation at no cost was achieved for a sequestration credit of $2.05/t.
In this paper, a new hierarchical robust control approach based on decentralized and distributed schemes is proposed for voltage regulation and power sharing in islanded DC microgrids. In this method, using a decentra...
In this paper, a new hierarchical robust control approach based on decentralized and distributed schemes is proposed for voltage regulation and power sharing in islanded DC microgrids. In this method, using a decentralized robust PI control structure, the primary voltage control loop is designed based on Kharitonov’s theorem to be robust against uncertainties and disturbances. Then, using a distributed PI robust control, the voltage deviation caused by the droop control is compensated. The simulation results show the effectiveness of the proposed controller under different disturbances by using the MATLAB/SimPowerSystems toolbox. In addition, the proposed controller can increase microgrid reliability due to exchanging low data volume in communication channels.
In this article, we provide a novel and broadly-applicable contraction-theoretic approach to continuous-time time-varying convex optimization. For any parameter-dependent contracting dynamics, we show that the trackin...
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This paper summarizes the talks of a special session on the IPF 2.0 project, a collaborative German-US research project that leverages self-awareness principles for the self-management of distributed systems of autono...
This paper summarizes the talks of a special session on the IPF 2.0 project, a collaborative German-US research project that leverages self-awareness principles for the self-management of distributed systems of autonomous multiprocessor systems-on-chip (MPSoCs).
Polyatomic molecules equipped with optical cycling centers (OCCs), enabling continuous photon scattering during optical excitation, are exciting candidates for advancing quantum information science. However, as these ...
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In this note we study contractivity of monotone systems and exponential convergence of positive systems using non-Euclidean norms. We first introduce the notion of conic matrix measure as a framework to study stabilit...
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The design of fixed point algorithms is at the heart of monotone operator theory, convex analysis, and of many modern optimization problems arising in machine learning and control. This tutorial reviews recent advance...
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This paper introduces a spectral parameterization of ambiguity sets to hedge against distributional uncertainty in stochastic optimization problems. We build an ambiguity set of probability densities around a histogra...
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ISBN:
(数字)9781665467612
ISBN:
(纸本)9781665467629
This paper introduces a spectral parameterization of ambiguity sets to hedge against distributional uncertainty in stochastic optimization problems. We build an ambiguity set of probability densities around a histogram estimator, which is constructed by independent samples from the unknown distribution. The densities in the ambiguity set are determined by bounding the distance between the coefficients of their Haar wavelet expansion and the expansion of the histogram estimator. This representation facilitates the computation of expectations, leading to tractable minimax problems that are linear in the parameters of the ambiguity set, and enables the inclusion of additional constraints that can capture valuable prior information about the unknown distribution.
It has been extensively studied in the literature that solving Maxwell equations is very sensitive to the mesh structure, space conformity and solution regularity. Roughly speaking, for almost all the methods in the l...
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