Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

Impact of offshore wind power forecast error in a carbon constraint electricity market

This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

Integrating intrinsic and global kinetics as a dual kinetic model for automotive catalysis

The majority of the kinetic models employed in catalytic after-treatment of exhaust emissions use a global kinetic approach owing to the simplicity because one expression can account for all the steps in a reaction. The major drawback of this approach is the limited predictive capabilities of the models. The intrinsic kinetic approach offers much more information about the processes occurring within the catalytic converter; however, it is significantly more complex and time consuming to develop. In the present work, a methodology which allows accessing a model that combines the simplicity of the global kinetic approach and the accuracy of the intrinsic kinetic approach is reported. To assess the performance of this new approach, the oxidation of carbon monoxide in the presence of nitric oxide as well as a driving cycle was investigated. The modelling of carbon monoxide oxidation with oxygen which utilised the intrinsic kinetic approach with the global kinetic approach was used for the carbon monoxide + nitric oxide reaction (and all remaining reactions for the driving cycle). The comparison of the model results for the dual intrinsic + global kinetic approach with the experimental data obtained for both the reactor and the driving cycle indicate that the dual approach is promising with results significantly better than those obtained with only the global kinetics approach.

Detailed validation of an automotive catalysis model using spatially resolved measurements within the catalyst substrate

Many kinetic models have appeared in literature in past decades using two main approaches: the traditional global kinetics approach, or the more complex micro-kinetics approach. Whether global or micro-kinetics, kinetic models have been based on experimental data obtained at the end of the monolith. The experimental procedure using end pipe analysis may give an accurate overview of the reaction mechanisms that occur; however, the lack of information from within the catalyst can ultimately lead to inaccuracies in the kinetic model and parameters used.

Using SpaciMS, a spatially resolved experimental technique developed at the Queen's University Belfast, information from within the catalyst can be obtained. This minimally invasive technique provides detailed information of the gas concentration and temperature profile from inside the catalytic monolith. This paper presents a kinetic model and simulations validated against experimental data obtained from three positions inside the catalyst monolith at 2, 14, and 26 mm in, using data from the SpaciMS. Also, simulations of end pipe analysis, using a commercial reactor, for the CO oxidation are presented and analyzed. The simulations presented are for varying concentrations of both CO and O2 (0.5 % and 1 % CO, 0.5 % and 2 % O2) for both the global and micro-kinetic approach.

Lead in rice: Analysis of baseline lead levels in market and field collected rice grains

In a large scale survey of rice grains from markets (13 countries) and fields (6 countries), a total of 1578 rice grain samples were analysed for lead. From the market collected samples, only 0.6% of the samples exceeded the Chinese and EU limit of 0.2 μg g− 1 lead in rice (when excluding samples collected from known contaminated/mine impacted regions). When evaluating the rice grain samples against the Food and Drug Administration's (FDA) provisional total tolerable intake (PTTI) values for children and pregnant women, it was found that only people consuming large quantities of rice were at risk of exceeding the PTTI from rice alone. Furthermore, 6 field experiments were conducted to evaluate the proportion of the variation in lead concentration in rice grains due to genetics. A total of 4 of the 6 field experiments had significant differences between genotypes, but when the genotypes common across all six field sites were assessed, only 4% of the variation was explained by genotype, with 9.5% and 11% of the variation explained by the environment and genotype by environment interaction respectively. Further work is needed to identify the sources of lead contamination in rice, with detailed information obtained on the locations and environments where the rice is sampled, so that specific risk assessments can be performed.

Correlation of Static Ageing Effects on Automotive Catalysts

This study identifies and analyzes the effect that aging time and temperature have on the CO light-off activity of three-way catalyst samples, aged in a static air (oxidizing) atmosphere. The bench aging time (BAT) equation proposed by the Environmental Protection Agency (EPA), which describes aging as dependent upon time at temperature, was used to calculate a range of oven aging times and temperatures based on a RAT-A engine bench aging cycle.

CO light-off tests carried out on cores aged between 800 and 900 °C have shown that it is the aging temperature that has the greatest effect on catalyst deterioration for static aging testing, with aging time having little effect. These results were in contradiction to the BAT equation, an industry norm for the aging of catalysts. This demonstrates that static aging, whilst showing how temperature affects aging, gives little or no time effects. The results have shown that static aging is not representative of actual aging on a vehicle.

Progressive aging conducted at a temperature of 1000 °C was shown to cause a decrease in catalyst activity as the aging time increased. However, even in these extreme conditions, static aging gave a slower rate of aging with time when compared to engine aging as defined by the BAT equation. Overall, static aging in air has been shown to produce a greater increase in aging due to temperature than predicted by the BAT equation, but less aging due to aging time.

Advanced Ceramic Substrate with Ordered and Designed Micro-Structure for Applications in Automotive Catalysts

This study describes an innovative monolith structure designed for applications in automotive catalysis using an advanced manufacturing approach developed at Imperial College London. The production process combines extrusion with phase inversion of a ceramic-polymer-solvent mixture in order to design highly ordered substrate micro-structures that offer improvements in performance, including reduced PGM loading, reduced catalyst ageing and reduced backpressure.

This study compares the performance of the novel substrate for CO oxidation against commercially available 400 cpsi and 900 cpsi catalysts using gas concentrations and a flow rate equivalent to those experienced by a full catalyst brick when attached to a vehicle. Due to the novel micro-structure, no washcoat was required for the initial testing and 13 g/ft3 of Pd was deposited directly throughout the substrate structure in the absence of a washcoat.

Initial results for CO oxidation indicate that the advanced micro-structure leads to enhanced conversion efficiency. Despite an 79% reduction in metal loading and the absence of a washcoat, the novel substrate sample performs well, with a light-off temperature (LOT) only 15 °C higher than the commercial 400 cpsi sample.

To test the effects of catalyst ageing on light-off temperature, each sample was aged statically at a temperature of 1000 °C, based on the Bench Ageing Time (BAT) equation. The novel substrate performed impressively when compared to the commercial samples, with a variation in light-off temperature of only 3% after 80 equivalent hours of ageing, compared to 12% and 25% for the 400 cpsi and 900 cpsi monoliths, respectively.

Automotive waste heat recovery: Working fluid selection and related boundary conditions

This paper presents the rational for the selection of fluids for use in a model based study of sub and supercritical Waste Heat Recovery (WHR) Organic Rankine Cycle (ORC). The study focuses on multiple vehicle heat sources and the potential of WHR ORC’s for its conversion into useful work. The work presented on fluid selection is generally applicable to any waste heat recovery system, either stationary or mobile and, with careful consideration, is also applicable to single heat sources. The fluid selection process presented reduces the number of potential fluids from over one hundred to a group of under twenty fluids for further refinement in a model based WHR ORC performance study. The selection process uses engineering judgement, legislation and, where applicable, health and safety as fluid selection or de-selection criteria. This paper also investigates and discusses the properties of specific ORC fluids with regard to their impact on the theoretical potential for delivering efficient WHR ORC work output. The paper concludes by looking at potential temperature and pressure WHR ORC limits with regard to fluid properties thereby assisting with the generation of WHR ORC simulation boundary conditions.

Testing of a Market Fraction Model and Power-law Behaviour in the DAX 30

This paper tests a simple market fraction asset pricing model with heterogeneous
agents. By selecting a set of structural parameters of the model through a systematic procedure, we show that the autocorrelations (of returns, absolute returns and squared returns) of the market fraction model share the same pattern as those of the DAX 30. By conducting econometric analysis via Monte Carlo simulations, we characterize these power-law behaviours and find that estimates of the power-law decay indices, the (FI)GARCH parameters, and the tail index of the selected market fraction model closely match those of the DAX 30. The results strongly support the explanatory power of the heterogeneous agent models.

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.