133 resultados para Anaconda Reduction Works


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Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

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Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

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A phosphoramidite modified [FeFe]H2ase mimic is studied as a model for photodriven production of H2. On cathodic activation, the pyridyl–phosphoramidite complex exhibits a strongly enhanced rate of proton reduction over the previously reported pyridylphosphine model at the same overpotential. Analysis of the cyclic voltammograms shows an apparent H2 evolution rate strongly influenced by the presence of both side-bound pyridyl and phosphorous-bound dimethylamino moieties at the phosphoramidite ligands. This difference is ascribed to the basic amines acting as proton relays.

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Blends of PEEK with macrocyclic thioether-ketones show initial melt-viscosities reduced by more than an order of magnitude relative to the polymer itself, enabling more facile processing and fabrication. On raising the temperature of the melt, however, the macrocycle undergoes spontaneous, entropically-driven ring-opening polymerization (ED-ROP), so that the properties of the final polymer should not, in principle, be compromised by the presence of low-MW macrocyclic material.

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The 2e reduced anion [Mn(CO)3(iPr-DAB)]− (DAB = 1,4- diazabuta-1,3-diene, iPr = isopropyl) was shown to convert in the presence of CO2 and a small amount of water to the unstable complex [Mn(CO)3(iPr-DAB)(η1-OCO2H)] (OCO2H− = unidentate bicarbonate) that was further reductively transformed to give a stable catalytic intermediate denoted as X2, showing νs(OCO) 1672 and 1646 (sh) cm−1. The subsequent cathodic shift by ca. 650 mV in comparison to the single 2e cathodic wave of the parent [Mn(CO)3(iPr-DAB)Br] triggers the reduction of intermediate X2 and catalytic activity converting CO2 to CO. Infrared spectroelectrochemistry has revealed that the high excess of CO generated at the cathode leads to the conversion of [Mn(CO)3(iPr-DAB)]− to inactive [Mn(CO)5]−. In contrast, the five-coordinate anion [Mn(CO)3(pTol-DAB)]−(pTol = 4-tolyl) is completely inert toward both CO2 and H2O (solvolysis). This detailed spectroelectrochemical study is a further contribution to the development of sustainable electro- and photoelectrocatalysts of CO2 reduction based on abundant first-row transition metals, in particular manganese.

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In The Global Model of Constitutional Rights Kai Möller claims that the proportionality test is underlain by an expansive moral right to autonomy. This putative right protects everything that advances one’s self-conception. It may of course be limited when balanced against other considerations such as the rights of others. But it always creates a duty on the state to justify the limitation. Möller further contends that the practice of proportionality can best be understood as protecting the right to autonomy. This review article summarizes the main tenets of Möller’s theory and criticizes them on two counts. First, it disputes the existence of a general right to autonomy; such a right places an unacceptably heavy burden on others. Second, it argues that we do not need to invoke a right to autonomy to explain and justify the main features of the practice of proportionality. Like other constitutional doctrines, proportionality is defensible, if it is grounded in pragmatic –mainly epistemic and institutional- considerations about how to increase overall rights compliance. These considerations are independent of any substantive theory of rights.

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Gum arabic is widely used in the food industry as an additive, both as a thickener and an emulsifier. This study has compared the emulsification properties of two types of gums, KLTA (Acacia senegal) and GCA (Acacia seyal), both in their native/untreated forms and after exposure to high pressure (800 MPa). Further studies were undertaken to chemically modify the disulphide linkages present and to investigate the effects of their reduction on the diffusion of the carbohydrate materials. The emulsification properties of the gum samples were examined by determining the droplet size distribution in a ‘‘model’’ oil-in-water system. Results showed that high pressure treatment and chemical reduction of gums changed the emulsification properties of both gums. The high molecular weight component in arabinogalactanproteins (AGP/GP), and more ‘‘branched’’ carbohydrates present in gum arabic, may be responsible for the emulsification properties of GCA gum, indicating that the emulsification mechanisms for KLTA and GCA were different.

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A journal article published in the Blue Notebook: Journal for artists' books. Vol 8 No 2, April 2014 exploring the work of video and book artist John Woodman and his relationship with John Ruskin's life and landscapes.

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The transition parameter is based on the electron characteristics close to the Earth's dayside magnetopause, but reveals systematic ordering of other, independent, data such as the ion flow, density and temperature and the rientation and strength of the magnetic field. Potentially, therefore, it is a very useful tool for resolving ambiguities in a sequence of satellite data caused by the effects of structure and motion of the boundary; however, its application has been limited because there has been no clear understanding of how it works. We present an analysis of data from the AMPTE-UKS satellite which shows that the transition parameter orders magnetopause data because magnetic reconnection generates newly-opened field lines which coat the boundary: a direct relationship is found with the time elapsed since the boundary-layer field line was opened. A simple model is used to reproduce this behaviour.

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Group 6 complexes of the type [M(CO)4(bpy)] (M=Cr, Mo, W) are capable of behaving as electrochemical catalysts for the reduction of CO2 at potentials less negative than those for the reduction of the radical anions [M(CO)4(bpy)].−. Cyclic voltammetric, chronoamperometric and UV/Vis/IR spectro-electrochemical data reveal that five-coordinate [M(CO)3(bpy)]2− are the active catalysts. The catalytic conversion is significantly more efficient in N-methyl-2-pyrrolidone (NMP) compared to tetrahydrofuran, which may reflect easier CO dissociation from 1e−-reduced [M(CO)4(bpy)].− in the former solvent, followed by second electron transfer. The catalytic cycle may also involve [M(CO)4(H-bpy)]− formed by protonation of [M(CO)3(bpy)]2−, especially in NMP. The strongly enhanced catalysis using an Au working electrode is remarkable, suggesting that surface interactions may play an important role, too.

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This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization.