Impacts of distributed photovoltaics on network voltages: Stochastic simulations of three Swedish low-voltage distribution grids

The continuously increasing application of distributed photovoltaics (PV-DG) in residential areas around the world calls for detailed assessment of distribution grid impacts. Both photovoltaic generation and domestic electricity demand exhibit characteristic variations on short and long time scales and are to a large extent negatively correlated, especially at high latitudes. This paper presents a stochastic methodology for simulation of PV-DG impacts on low-voltage (LV) distribution grids, using detailed generation and demand models. The methodology is applied to case studies of power flow in three existing Swedish LV grids to determine load matching, voltage levels and network losses at different PV-DG penetration levels. All studied LV grids can handle significant amounts of PV-DG, up to the highest studied level of 5 kW_p PV per household. However, the benefits of PV-DG in terms of relative improvement of on-site reduction of demand, mitigated voltage drops and reduced losses were most significant at a penetration level of 1 kW_p PV per household.     

Development of multipoint vibrational coherent anti-Stokes Raman spectroscopy for flame applications

A novel technique for coherent anti-Stokes Raman spectroscopy (CARS) measurements in multiple points is presented. In a multipass cavity the pump and Stokes laser beams are multiply reflected and refocused into a measurement volume with an adjustable number of separated points along a line. This optical arrangement was used in a vibrational CARS setup with planar BOXCARS phase-matching configuration. The CARS spectra from spatially separated points were recorded at different heights on a CCD camera. Measurements of temperature profiles were carried out in the burned gas zone of a premixed one-dimensional flame to demonstrate the applicability of this method for temperature measurements in high-temperature regions. The ability to measure in flames with strong density gradients was demonstrated by simultaneous measurements of Q-branch spectra of N2 and CO in a Wolfhard-Parker burner flame. Interference phenomena found in multipoint spectra are discussed, and possible solutions are proposed. Merits and limitations of the technique are discussed.     

A high-resolution stochastic model of domestic activity patterns and electricity demand

Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings’ indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.     

Reining China's industrial energy—Challenges of promoting expedient measures in a Chinese actor environment

This article aims to illuminate the complexities involved in efforts to influence China's energy future. It brings forth three observations. First: China's authoritarian appearance is deceptive. Second: learning about concealed but pivotal actors and their motivations is not easy but important. Third: technology diffusion is obstructed by differences in expectations. Three summarising messages conclude the presentation, noting that in order to progress one needs to (i) look beyond official consensus, (ii) address differences in technology perceptions and (iii) be watchful of the inconclusiveness of synthesised information—such as projections of the future. These findings are the result of an analytic and China-oriented exploration of three adjoining fields, i.e. of actors and their different roles in decision-making, of two recent energy futures studies, and of conceptual frameworks for understanding technology.     

Health effects of residential wood smoke particles: the importance of combustion conditions and physicochemical particle properties

Background  

Residential wood combustion is now recognized as a major particle source in many developed countries, and the number of studies investigating the negative health effects associated with wood smoke exposure is currently increasing. The combustion appliances in use today provide highly variable combustion conditions resulting in large variations in the physicochemical characteristics of the emitted particles. These differences in physicochemical properties are likely to influence the biological effects induced by the wood smoke particles.     

New Improved Tests for Cointegration with Structural Breaks

Abstract. This article proposes Lagrange multiplier‐based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to the trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also conducted to investigate the small‐sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests.     

Antagonistic effect of superplasticizer and colloidal nano-silica in the hydration of Alite and Belite pastes

The dependence on the hydration rate for Alite and Belite clinker phases in the presence of a polycarboxylate superplasticizer PC SP upon addition of colloidal nano-silica CNS were monitored by means of Diffuse Reflectance Infrared spectroscopy DR-FTIR. Spectral signatures of clinker dissolution and product formation were acquired for both materials. The rates for the build-up of product vibrational band intensities were found to depend sensitively on addition of CNS. The hydration product was proposed to be calcium-silicate-hydrate C–S–H. Details in the spectral signatures were found to differ. Quantum chemical calculations were employed and found to be consistent with the interpretation that small clusters dominate the Alite C–S–H spectrum, whereas the Belite C–S–H spectrum results from extended polymers.     

Multilevel double loop Monte Carlo and stochastic collocation methods with importance sampling for Bayesian optimal experimental design

An optimal experimental set-up maximizes the value of data for statistical inferences. The efficiency of strategies for finding optimal experimental set-ups is particularly important for experiments that are time-consuming or expensive to perform. In the situation when the experiments are modeled by partial differential equations (PDEs), multilevel methods have been proven to reduce the computational complexity of their single-level counterparts when estimating expected values. For a setting where PDEs can model experiments, we propose two multilevel methods for estimating a popular criterion known as the expected information gain (EIG) in Bayesian optimal experimental design. We propose a multilevel double loop Monte Carlo, which is a multilevel strategy with double loop Monte Carlo, and a multilevel double loop stochastic collocation, which performs a high-dimensional integration on sparse grids. For both methods, the Laplace approximation is used for importance sampling that significantly reduces the computational work of estimating inner expectations. The values of the method parameters are determined by minimizing the computational work, subject to satisfying the desired error tolerance. The efficiencies of the methods are demonstrated by estimating EIG for inference of the fiber orientation in composite laminate materials from an electrical impedance tomography experiment.     

Thorium exposure during tungsten inert gas welding with thoriated tungsten electrodes

The exposure to 232Th from TIG welding with thoriated electrodes has been determined at five different workshops. Welding with both alternating and direct current was investigated. The exposure levels of 232Th were generally below 10 mBq m(-3) in the breathing zone of the welders. Two samples from AC welding showed significant higher exposure levels, probably due to maladjustment of the TIG welding power source. Samples of the respirable fraction of 232Th from grinding thoriated electrodes were also collected showing exposure levels of 5 mBq m(-3) or lower. A dose estimate has been made for two scenarios, one realistic and one with conservative assumptions, showing that the annual committed effective dose from inhalation of 232Th, 230Th, 228Th and 228Ra, for a full-time TIG welder, in the realistic case is below 0.3 mSv and with conservative assumptions around 1 mSv or lower. The contribution from grinding electrodes was lower, 10 microSv or lower in the realistic case and 63 microSv or lower based on conservative assumptions. The study does not exclude occurrence of higher exposure levels under welding conditions different from those prevailing in this study.