Discrete demand side control performance under dynamic building simulation: a heat pump application

This study presents the findings of applying a Discrete Demand Side Control (DDSC) approach to the space heating of two case study buildings. High and low tolerance scenarios are implemented on the space heating controller to assess the impact of DDSC upon buildings with different thermal capacitances, light-weight and heavy-weight construction. Space heating is provided by an electric heat pump powered from a wind turbine, with a back-up electrical network connection in the event of insufficient wind being available when a demand occurs. Findings highlight that thermal comfort is maintained within an acceptable range while the DDSC controller maintains the demand/supply balance. Whilst it is noted that energy demand increases slightly, as this is mostly supplied from the wind turbine, this is of little significance and hence a reduction in operating costs and carbon emissions is still attained.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

Random orthogonal matrix simulation

This paper introduces a method for simulating multivariate samples that have exact means, covariances, skewness and kurtosis. We introduce a new class of rectangular orthogonal matrix which is fundamental to the methodology and we call these matrices L matrices. They may be deterministic, parametric or data specific in nature. The target moments determine the L matrix then infinitely many random samples with the same exact moments may be generated by multiplying the L matrix by arbitrary random orthogonal matrices. This methodology is thus termed “ROM simulation”. Considering certain elementary types of random orthogonal matrices we demonstrate that they generate samples with different characteristics. ROM simulation has applications to many problems that are resolved using standard Monte Carlo methods. But no parametric assumptions are required (unless parametric L matrices are used) so there is no sampling error caused by the discrete approximation of a continuous distribution, which is a major source of error in standard Monte Carlo simulations. For illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio.

Comparing a discrete and continuum model of the intestinal crypt

The integration of processes at different scales is a key problem in the modelling of cell populations. Owing to increased computational resources and the accumulation of data at the cellular and subcellular scales, the use of discrete, cell-level models, which are typically solved using numerical simulations, has become prominent. One of the merits of this approach is that important biological factors, such as cell heterogeneity and noise, can be easily incorporated. However, it can be difficult to efficiently draw generalizations from the simulation results, as, often, many simulation runs are required to investigate model behaviour in typically large parameter spaces. In some cases, discrete cell-level models can be coarse-grained, yielding continuum models whose analysis can lead to the development of insight into the underlying simulations. In this paper we apply such an approach to the case of a discrete model of cell dynamics in the intestinal crypt. An analysis of the resulting continuum model demonstrates that there is a limited region of parameter space within which steady-state (and hence biologically realistic) solutions exist. Continuum model predictions show good agreement with corresponding results from the underlying simulations and experimental data taken from murine intestinal crypts.

Making the least active pay: a simulation of rewards and penalties under Demand Side Participation programs

The orthodox approach for incentivising Demand Side Participation (DSP) programs is that utility losses from capital, installation and planning costs should be recovered under financial incentive mechanisms which aim to ensure that utilities have the right incentives to implement DSP activities. The recent national smart metering roll-out in the UK implies that this approach needs to be reassessed since utilities will recover the capital costs associated with DSP technology through bills. This paper introduces a reward and penalty mechanism focusing on residential users. DSP planning costs are recovered through payments from those consumers who do not react to peak signals. Those consumers who do react are rewarded by paying lower bills. Because real-time incentives to residential consumers tend to fail due to the negligible amounts associated with net gains (and losses) or individual users, in the proposed mechanism the regulator determines benchmarks which are matched against responses to signals and caps the level of rewards/penalties to avoid market distortions. The paper presents an overview of existing financial incentive mechanisms for DSP; introduces the reward/penalty mechanism aimed at fostering DSP under the hypothesis of smart metering roll-out; considers the costs faced by utilities for DSP programs; assesses linear rate effects and value changes; introduces compensatory weights for those consumers who have physical or financial impediments; and shows findings based on simulation runs on three discrete levels of elasticity.

Simulation of monsoon disturbances in the LMD GCM

The monsoon depressions that form over India during the summer are analyzed using simulations from the Laboratoire de Meteorologie Dynamique general circulation model. This type of synoptic system often occurs with a frequency of one to two per month and can produce a strong Indian rainfall. Two kinds of analyses are conducted in this study. The first one is a subjective analysis based on the evolution of the precipitation rate and the pattern of the sea level pressure. The second one is an objective analysis performed using the TRACK program, which identifies and tracks the minima in the sea level pressure anomaly held and computes the statistics for the distribution of systems. The analysis of a 9-yr control run, which simulates strong precipitation rates over the foothills of the Himalayas and over southern India but weak rates over central India, shows that the number of disturbances is coo low and that they almost never occur during August, when break conditions prevail. The generated disturbances more often move north, toward the foothills of the Himalayas. Another analysis is performed to study the effect of the Tibetan Plateau elevation on these disturbances with a 9-yr run carried out with a Tibetan Plateau at 50% of its current height. It is shown that this later integration simulates more frequent monsoon disturbances, which move rather northwestward, in agreement with the current observations. The comparison between the two runs shows that the June-July-August rainfall difference is in large part due to changes in the occurrence of the monsoon disturbances.

Simulation of the diurnal cycle in a climate model and its evaluation using data from Meteosat 7

The representation of the diurnal cycle in the Hadley Centre climate model is evaluated using simulations of the infrared radiances observed by Meteosat 7. In both the window and water vapour channels, the standard version of the model with 19 levels produces a good simulation of the geographical distributions of the mean radiances and of the amplitude of the diurnal cycle. Increasing the vertical resolution to 30 levels leads to further improvements in the mean fields. The timing of the maximum and minimum radiances reveals significant model errors, however, which are sensitive to the frequency with which the radiation scheme is called. In most regions, these errors are consistent with well documented errors in the timing of convective precipitation, which peaks before noon in the model, in contrast to the observed peak in the late afternoon or evening. When the radiation scheme is called every model time step (half an hour), as opposed to every three hours in the standard version, the timing of the minimum radiance is improved for convective regions over central Africa, due to the creation of upper-level layer-cloud by detrainment from the convection scheme, which persists well after the convection itself has dissipated. However, this produces a decoupling between the timing of the diurnal cycles of precipitation and window channel radiance. The possibility is raised that a similar decoupling may occur in reality and the implications of this for the retrieval of the diurnal cycle of precipitation from infrared radiances are discussed.

Numerical simulation of baroclinic waves with a parameterized boundary layer

A dry three-dimensional baroclinic life cycle model is used to investigate the role of turbulent fluxes of heat and momentum within the boundary layer on mid-latitude cyclones. Simulations are performed of life cycles for two basic states, both with and without turbulent fluxes. The different basic states produce cyclones with contrasting frontal and mesoscale-flow structures. The analysis focuses on the generation of potential-vorticity (PV) in the boundary layer and its subsequent transport into the free troposphere. The dynamic mechanism through which friction mitigates a barotropic vortex is that of Ekman pumping. This has often been assumed to be also the dominant mechanism for baroclinic developments. The PV framework highlights an additional, baroclinic mechanism. Positive PV is generated baroclinically due to friction to the north-east of a surface low and is transported out of the boundary layer by a cyclonic conveyor belt flow. The result is an anomaly of increased static stability in the lower troposphere which restricts the growth of the baroclinic wave. The reduced coupling between lower and upper levels can be sufficient to change the character of the upper-level evolution of the mature wave. The basic features of the baroclinic damping mechanism are robust for different frontal structures, with and without turbulent heat fluxes, and for the range of surface roughness found over the oceans.

Improved simulation of water vapour and clear-sky radiation using 24 hour forecasts from ERA40

Monthly mean water vapour and clear-sky radiation extracted from the European Centre for Medium Range Weather Forecasts 40-year reanalysis (ERA40) forecasts are assessed using satellite observations and additional reanalysis data. There is a marked improvement in the interannual variability of column-integrated water vapour (CWV) over the oceans when using the 24-hour forecasts compared with the standard 6-hour forecasts products. The spatial distribution of CWV are well simulated by the 6-hour forecasts; using the 24-hour forecasts does not degrade this simulation substantially and in many cases improves on the quality. There is also an improved simulation of clear-sky radiation from the 24-hour forecasts compared with the 6-hour forecasts based on comparison with satellite observations and empirical estimates. Further work is required to assess the quality of water vapour simulation by reanalyses over land regions. Over the oceans, it is recommended that 24-hour forecasts of CWV and clear-sky radiation are used in preference to the standard 6-hour forecast products from ERA40

Stratosphere-troposphere transport in a numerical simulation of midlatitude convection

The transport of stratospheric air deep into the troposphere via convection is investigated numerically using the UK Met Office Unified Model. A convective system that formed on 27 June 2004 near southeast England, in the vicinity an upper level potential vorticity anomaly and a lowered tropopause, provides the basis for analysis. Transport is diagnosed using a stratospheric tracer that can either be passed through or withheld from the model’s convective parameterization scheme. Three simulations are performed at increasingly finer resolutions, with horizontal grid lengths of 12, 4, and 1 km. In the 12 and 4 km simulations, tracer is transported deeply into the troposphere by the parameterized convection. In the 1 km simulation, for which the convective parameterization is disengaged, deep transport is still accomplished but with a much smaller magnitude. However, the 1 km simulation resolves stirring along the tropopause that does not exist in the coarser simulations. In all three simulations, the concentration of the deeply transported tracer is small, three orders of magnitude less than that of the shallow transport near the tropopause, most likely because of the efficient dilution of parcels in the lower troposphere.

Linear viscoelasticity from molecular dynamics simulation of entangled polymers

The linear viscoelastic (LVE) spectrum is one of the primary fingerprints of polymer solutions and melts, carrying information about most relaxation processes in the system. Many single chain theories and models start with predicting the LVE spectrum to validate their assumptions. However, until now, no reliable linear stress relaxation data were available from simulations of multichain systems. In this work, we propose a new efficient way to calculate a wide variety of correlation functions and mean-square displacements during simulations without significant additional CPU cost. Using this method, we calculate stress−stress autocorrelation functions for a simple bead−spring model of polymer melt for a wide range of chain lengths, densities, temperatures, and chain stiffnesses. The obtained stress−stress autocorrelation functions were compared with the single chain slip−spring model in order to obtain entanglement related parameters, such as the plateau modulus or the molecular weight between entanglements. Then, the dependence of the plateau modulus on the packing length is discussed. We have also identified three different contributions to the stress relaxation:  bond length relaxation, colloidal and polymeric. Their dependence on the density and the temperature is demonstrated for short unentangled systems without inertia.

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.