Optimal algorithms for testing monotonicity and Lipschitz over hypergrids
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This report proposes a reformulation of U.S. ISO/RTO-managed wholesale electric power mar- kets for improved reliability and e ciency of system operations. Current markets do not specify or compensate primary frequency response. They also unnecessarily limit the participation of new technologies in reserve markets and o er insu cient economic inducements for new capacity invest- ment. In the proposed market reformulation, energy products are represented as physically-covered rm contracts and reserve products as physically-covered call option contracts. Trading of these products is supported by a backbone of linked ISO/RTO-managed forward markets with planning horizons ranging from multiple years to minutes ahead. A principal advantage of this reformulation is that reserve needs can be speci ed in detail, and resources can o er the services for which they are best suited, without being forced to conform to rigid reserve product de nitions. This should improve the business case for electric energy storage and other emerging technologies to provide reserve. In addition, the facilitation of price discovery should help to ensure e cient energy/reserve procurement and adequate levels of new capacity investment.
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With an increasing number of Distributed Generation (DG) being connected on the distribution system, a method for simplifying the complexity of the distribution system to an equivalent representation of the feeder is advantageous for streamlining the interconnection study process. The general characteristics of the system can be retained while reducing the modeling effort required. This report presents a method of simplifying feeders to only specified buses-of-interest. These buses-of-interest can be potential PV interconnection locations or buses where engineers want to verify a certain power quality. The equations and methodology are presented with mathematical proofs of the equivalence of the circuit reduction method. An example 15-bus feeder is shown with the parameters and intermediate example reduction steps to simplify the circuit to 4 buses. The reduced feeder is simulated using PowerWorld Simulator to validate that those buses operate with the same characteristics as the original circuit. Validation of the method is also performed for snapshot and time-series simulations with variable load and solar energy output data to validate the equivalent performance of the reduced circuit with the interconnection of PV.
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Proposed for publication in Journal of Solar Energy Engineering.
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Proposed for publication in SIAM Journal on Uncertainty Quantification.
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Review of Scientific Instruments
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Proposed for publication in Elsevier Journal Coordination Chemistry Reviews. .
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Proposed for publication in Chemistry of Materials.
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Journal of Physical Chemistry C
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ACM Transactions on Parallel Computing
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The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.
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Review of Scientific Instruments
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Journal of Non-Crystalline Solids
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Nature Nanotechnology
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Environmental Science&Technology
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Environmental Science and Technology
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Earthquake Engineering and Structural Dynamics (Online)
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Journal of Chemical Physics
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Biotechnology and Bioengineering (Online)
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Scripta Materialia
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IEEE Selected Topics in Quantum Electronics
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