Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

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.

A peak reduction scheduling algorithm for storage devices on the low voltage network

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.

A phosphoramidite-based [FeFe]H2ase functional mimic displaying fast electrocatalytic proton reduction

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.

Long-term cultivation-independent microbial diversity analysis demonstrates that bacterial communities infecting the adult cystic fibrosis lung show stability and resilience.

Whilst not true in all cases, the microbial communities that chronically infect the airways of patients with CF can vary little over a year despite antibiotic perturbation. The species present tended to vary more between than within subjects, suggesting that each CF airway infection is unique, with relatively stable and resilient bacterial communities. The inverse relationship between community richness and disease severity is similar to findings reported in other mucosal infections.

Ring-opening polymerization in molten PEEK: transient reduction of melt-viscosity by macrocyclic aromatic thioetherketones

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.

Electrocatalytic reduction of carbon dioxide with a manganese(I)tricarbonyl complex containing a nonaromatic α‑diimine ligand

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.

Effects of high hydrostatic pressure and chemical reduction on the emulsification properties of gum arabic

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.

Mammalian-microbial cometabolism of L-Carnitine in the context of atherosclerosis

g-butyrobetaine has long been known as the precursor of endogenous L-carnitine synthesis. In this issue, Koeth et al. (2014) demonstrate that it is also a major metabolite of L-carnitine degradation by gut bacteria that precedes the enteric production of trimethylamine and trimethylamine-N-oxide.

Intra-tumor heterogeneity: lessons from microbial evolution and clinical implications

Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome.

[M(CO)4(2,2′-bipyridine)] (M = Cr, Mo, W) as efficient catalysts for electrochemical reduction of CO2 to CO at a gold electrode

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.

Microbial community dynamics in the forefield of glaciers

Retreating ice fronts (as a result of a warming climate) expose large expanses of deglaciated forefield, which become colonized by microbes and plants. There has been increasing interest in characterizing the biogeochemical development of these ecosystems using a chronosequence approach. Prior to the establishment of plants, microbes use autochthonously produced and allochthonously delivered nutrients for growth. The microbial community composition is largely made up of heterotrophic microbes (both bacteria and fungi), autotrophic microbes and nitrogen-fixing diazotrophs. Microbial activity is thought to be responsible for the initial build-up of labile nutrient pools, facilitating the growth of higher order plant life in developed soils. However, it is unclear to what extent these ecosystems rely on external sources of nutrients such as ancient carbon pools and periodic nitrogen deposition. Furthermore, the seasonal variation of chronosequence dynamics and the effect of winter are largely unexplored. Modelling this ecosystem will provide a quantitative evaluation of the key processes and could guide the focus of future research. Year-round datasets combined with novel metagenomic techniques will help answer some of the pressing questions in this relatively new but rapidly expanding field, which is of growing interest in the context of future large-scale ice retreat.

Dimensionality reduction assisted tensor clustering

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.

Gaussian processes autoencoder for dimensionality reduction

Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing. The autoencoder is a powerful dimensionality reduction technique based on minimizing reconstruction error, and it has regained popularity because it has been efficiently used for greedy pretraining of deep neural networks. Compared to Neural Network (NN), the superiority of Gaussian Process (GP) has been shown in model inference, optimization and performance. GP has been successfully applied in nonlinear Dimensionality Reduction (DR) algorithms, such as Gaussian Process Latent Variable Model (GPLVM). In this paper we propose the Gaussian Processes Autoencoder Model (GPAM) for dimensionality reduction by extending the classic NN based autoencoder to GP based autoencoder. More interestingly, the novel model can also be viewed as back constrained GPLVM (BC-GPLVM) where the back constraint smooth function is represented by a GP. Experiments verify the performance of the newly proposed model.

Impact of variation in structure of condensed tannins from sainfoin (Onobrychis viciifolia) on in vitro ruminal methan production and fermentation characteristics

Our study investigated the effects of condensed tannins (CT) on rumen in vitro methane (CH4) production and fermentation characteristics by incubating lucerne in buffered rumen fluid in combination with different CT extracts at 0 (control), 40, 80 and 120 g CT/kg of substrate DM. Condensed tannins were extracted from four sainfoin accessions: Rees ‘A’, CPI63763, Cotswold Common and CPI63767. Gas production (GP) was measured using a fully automated GP apparatus with CH4 measured at distinct time points. Condensed tannins differed substantially in terms of polymer size and varied from 13 (Rees ‘A’) to 73 (CPI63767) mean degree of polymerization, but had relatively similar characteristics in terms of CT content, procyanidin: prodelphinidin (PC: PD) and cis:trans ratios. Compared to control, addition of CT from CPI63767 and CPI63763 at 80 and 120 g CT/kg of substrate DM reduced CH4 by 43% and 65%, and by 23% and 57%, respectively, after 24-h incubation. Similarly, CT from Rees ‘A’ and Cotswold Common reduced CH4 by 26% and 46%, and by 28% and 46% respectively. Addition of increasing level of CT linearly reduced the maximum rates of GP and CH4 production, and the estimated in vitro organic matter digestibility. There was a negative linear and quadratic (p < 0.01) relation between CT concentration and total volatile fatty acid (VFA) production. Inclusion of 80 and 120 g CT/kg of substrate DM reduced (p < 0.001) branched-chain VFA production and acetate: propionate ratio and was lowest for CPI63767. A decrease in proteolytic activity as indirectly shown by a change in VFA composition favouring a shift towards propionate and reduction in branched-chain VFA production varied with type of CT and was highest for CPI63767. In conclusion, these results suggest that tannin polymer size is an important factor affecting in vitro CH4 production which may be linked to the CT interaction with dietary substrate or microbial cells.