A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

A refined parametric model for short term load forecasting

Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.

Evaluating and optimizing oral formulations of live bacterial vaccines using a gastro-small intestine model

Gastrointestinal (GI) models that mimic physiological conditions in vitro are important tools for developing and optimizing biopharmaceutical formulations. Oral administration of live attenuated bacterial vaccines (LBV) can safely and effectively promote mucosal immunity but new formulations are required that provide controlled release of optimal numbers of viable bacterial cells, which must survive gastrointestinal transit overcoming various antimicrobial barriers. Here, we use a gastro-small intestine gut model of human GI conditions to study the survival and release kinetics of two oral LBV formulations: the licensed typhoid fever vaccine Vivotif comprising enteric coated capsules; and an experimental formulation of the model vaccine Salmonella Typhimurium SL3261 dried directly onto cast enteric polymer films and laminated to form a polymer film laminate (PFL). Neither formulation released significant numbers of viable cells when tested in the complete gastro-small intestine model. The poor performance in delivering viable cells could be attributed to a combination of acid and bile toxicity plus incomplete release of cells for Vivotif capsules, and to bile toxicity alone for PFL. To achieve effective protection from intestinal bile in addition to effective acid resistance, bile adsorbent resins were incorporated into the PFL to produce a new formulation, termed BR-PFL. Efficient and complete release of 4.4x107 live cells per dose was achieved from BR-PFL at distal intestinal pH, with release kinetics controlled by the composition of the enteric polymer film, and no loss in viability observed in any stage of the GI model. Use of this in vitro GI model thereby allowed rational design of an oral LBV formulation to maximize viable cell release.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

An evaluation of different growth functions for describing the profile of live weight with time (age) in meat and egg strains of chicken

A total of 86 profiles from meat and egg strains of chickens (male and female) were used in this study. Different flexible growth functions were evaluated with regard to their ability to describe the relationship between live weight and age and were compared with the Gompertz and logistic equations, which have a fixed point of inflection. Six growth functions were used: Gompertz, logistic, Lopez, Richards, France, and von Bertalanffy. A comparative analysis was carried out based on model behavior and statistical performance. The results of this study confirmed the initial concern about the limitation of a fixed point of inflection, such as in the Gompertz equation. Therefore, consideration of flexible growth functions as an alternatives to the simpler equations (with a fixed point of inflection) for describing the relationship between live weight and age are recommended for the following reasons: they are easy to fit, they very often give a closer fit to data points because of their flexibility and therefore a smaller RSS value, than the simpler models, and they encompasses simpler models for the addition of an extra parameter, which is especially important when the behavior of a particular data set is not defined previously.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

Part load operation coefficient of air-conditioning system of public building

IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary.

A method of formulating energy load profile for domestic buildings in the UK

There are varieties of physical and behavioral factors to determine energy demand load profile. The attainment of the optimum mix of measures and renewable energy system deployment requires a simple method suitable for using at the early design stage. A simple method of formulating load profile (SMLP) for UK domestic buildings has been presented in this paper. Domestic space heating load profile for different types of houses have been produced using thermal dynamic model which has been developed using thermal resistant network method. The daily breakdown energy demand load profile of appliance, domestic hot water and space heating can be predicted using this method. The method can produce daily load profile from individual house to urban community. It is suitable to be used at Renewable energy system strategic design stage.

A model of UK domestic appliance-use using Artificial Neural Networks

The development of an Artificial Neural Network model of UK domestic appliance energy consumption is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 households during the summer of 2010. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with backpropagation training and has a12:10:24architecture.Model outputs include appliance load profiles which can be applied to the fields of energy planning (micro renewables and smart grids), building simulation tools and energy policy.

Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modelling approach

A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley

An enhanced model for small-signal analysis of the phase-shifted full-bridge converter

This paper presents an in-depth critical discussion and derivation of a detailed small-signal analysis of the Phase-Shifted Full-Bridge (PSFB) converter. Circuit parasitics, resonant inductance and transformer turns ratio have all been taken into account in the evaluation of this topology’s open-loop control-to-output, line-to-output and load-to-output transfer functions. Accordingly, the significant impact of losses and resonant inductance on the converter’s transfer functions is highlighted. The enhanced dynamic model proposed in this paper enables the correct design of the converter compensator, including the effect of parasitics on the dynamic behavior of the PSFB converter. Detailed experimental results for a real-life 36V-to-14V/10A PSFB industrial application show excellent agreement with the predictions from the model proposed herein.1

A laminated polymer film formulation for enteric delivery of live vaccine and probiotic bacteria

Live bacterial cells (LBC) are administered orally as attenuated vaccines, to deliver biopharmaceutical agents, and as probiotics to improve gastrointestinal health. However, LBC present unique formulation challenges and must survive gastrointestinal antimicrobial defenses including gastric acid after administration. We present a simple new formulation concept, termed Polymer Film Laminate (PFL). LBC are ambient dried onto cast acid-resistant enteric polymer films that are then laminated together to produce a solid oral dosage form. LBC of a model live bacterial vaccine and a probiotic were dried directly onto a cast film of enteric polymer. The effectiveness at protecting dried cells in a simulated gastric fluid (pH 2.0) depended on the composition of enteric polymer film used, with a blend of ethylcellulose plus Eudragit L100 55 providing greater protection from acid than Eudragit alone. However, although PFL made from blended polymers films completely released low molecular weight dye into intestinal conditions (pH 7.0), they failed to release LBC. In contrast, PFL made from Eudragit alone successfully protected dried probiotic or vaccine LBC from simulated gastric fluid for 2h, and subsequently released all viable cells within 60min of transfer into simulated intestinal fluid. Release kinetics could be controlled by modifying the lamination method.

Quantifying sources of inter-model diversity in the cloud albedo effect

There is large diversity in simulated aerosol forcing among models that participated in the fifth Coupled Model Intercomparison Project (CMIP5), particularly related to aerosol interactions with clouds. Here we use the reported model data and fitted aerosol-cloud relations to separate the main sources of inter-model diversity in the magnitude of the cloud albedo effect. There is large diversity in the global load and spatial distribution of sulfate aerosol, as well as in global-mean cloud-top effective radius. The use of different parameterizations of aerosol-cloud interactions makes the largest contribution to diversity in modeled radiative forcing (up to -39%, +48% about the mean estimate). Uncertainty in pre-industrial sulfate load also makes a substantial contribution (-15%, +61% about the mean estimate), with smaller contributions from inter-model differences in the historical change in sulfate load and in mean cloud fraction.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.