Abstract

Adsorber bed is a source of driving power in the adsorption refrigeration system. Adsorber bed affects the performance of the system due to its role of initiating the refrigeration process through desorption. This paper investigates the adsorber bed’s cooling and heating performance behaviors under varying experimental conditions. Specifically, the effect of opening or closing the top and bottom part of the adsorber bed. The adsorber bed system was heated to 120 °C and then cooled to 30 °C. The average air velocity used in the experiment was 0.5 m/s to reflect the real operating environment. The short time taken to heat the system was 1362 seconds while both the top and bottom parts of the adsorber bed were closed, while 5796 seconds was the shortest time to cool the system. The average ambient temperature when experiments were carried out was 21 °C. Different temperature values were observed in the adsorber bed box during the experimental process.

Abstract

Tight oil reservoirs are mainly developed by water injection. The conventional method could not effectively characterize the sand body connectivity between oil and water wells since it only uses static geological parameters or dynamic production data to identify the connectivity between wells. In this paper, a novel machine learning evaluation method for inter-well sand body connectivity using both static geological and dynamic production data is constructed. This method is based on the CatBoost algorithm. Three types of sand body connectivity are classified by analysis of four geological factors including porosity, permeability, shale volume and net-to-gross ratio, and three dynamic production factors including oil production total (OPT), liquid production total (LPT) and water injection total (WIT). Finally, the novel method proposed in this paper is applied to predict the sand body connectivity between oil and water wells using the data from a tight oil reservoir located in the Ordos Basin, China. The results show that the proposed method can improve the forecast accuracy of inter-well sand body connectivity from 50% to 85%.

Abstract

Energy storage is a supporting technology to achieve large-scale consumption of renewable energy and smart grid. Supercritical compressed carbon dioxide energy storage (SC-CCES) system is an appealing physical energy storage thanks to its compact system structure and high round-trip efficiency. However, in previous studies, the temperature and pressure of storage chamber are traditionally set to a constant value, there is a lack of thermodynamic analysis for SC-CCES system from the perspective of storage chambers interactively varying, which results in compressor and turbine operating consistently at off-design conditions. Hence, the off-design performance of SC-CCES system is investigated. The parametric analysis is conducted to evaluate the influence of system parameters and the optimization design platform is established to explore the optimization potential. Results indicate that round-trip efficiency and energy density of SC-CCES system present opposite varying trends with increasing compressor efficiency and the initial temperature of charge in low-pressure storage chamber. The optimal round-trip efficiency of SC-CCES system is achieved as 78.14 %, along with the optimal energy density of 0.2580 kWh/m³.

Abstract

As per the 2020 UN emissions report, the average global temperature will increase by 3oC compared to pre-industrial levels if no corrective measures are taken and, with this, the frequency and intensity of heatwaves will also increase. Such a temperature rise will lead to an increased cooling demand. Although cooling provision may exist in commercial and industrial premises, this may not be the case for households. This paper presents a methodology to quantify the cooling demand of typical UK dwellings in a warming world. The commercial software IES VE was adopted, and white box modelling was carried out based on a literature review of construction standards and methodologies. Model verification was conducted to ensure compliance with building standards—allowing for a high degree of confidence in the modelling approach and methodology to understand and quantify future cooling demand.

Abstract

Solar initiatives, particularly community solar, have gained increasing traction in urban areas as a means to maximize the advantages of transitioning to clean energy sources. Accordingly, this study aims to assess the economic viability of community solar projects (CSPs) in Hong Kong by evaluating their economic feasibility, analyzing the key factors that influence their economic performance, and exploring the impact of these factors on the performance of CSPs. The findings of this research reveal that, under the current market conditions in Hong Kong, CSPs are deemed unfeasible due to the high upfront installation cost of PV systems. Furthermore, the upfront installation cost and residential payments are identified as the most sensitive variables affecting the overall costs and revenues of such projects. Specifically, a decrease in upfront installation cost or an increase in residential payments can lead to a higher IRR and an improved cumulative cashflow. These empirical findings provide valuable insights into the economic performance of CSPs within the existing market conditions in Hong Kong, as well as their potential variations under different scenarios. Consequently, this study is believed to offer significant guidance in formulating appropriate financial goals and relevant strategies to facilitate the adoption of community solar initiatives, not only in Hong Kong but also in other regions sharing similar local characteristics.

Abstract

This work evaluates future variations in wind resources in South America by considering the newest and most complex climate-change scenarios – the Shared Socioeconomic Pathways (SSPs). A multi-model ensemble of global climate models is constructed to compare wind power density values at the end of the century (2081-2100) with a baseline period (1995-2014). Three climate-change scenarios are considered, representative of high (SSP5-8.5), intermediate (SSP2-4.5) and low (SSP1-1.9) emissions pathways. The findings reveal remarkable increases in wind resources (over 100%) in regions of Brazil, Paraguay, Uruguay and Venezuela. Conversely, notable reductions (up to 50%) are predicted along the western coast of the South American continent, particularly in South Chile, Peru and Ecuador. These substantial changes must be taken into account in strategising the growth of the wind industry and its pivotal role in achieving the decarbonisation of the energy sector in South America.

Abstract

In recent years, energy consumption in universities and colleges has accounted for about 10% of the total energy consumption of Chinese society. In order to achieve the goal of carbon peaking and carbon neutrality, it is a major trend to build a new, cleaner campus power system. At the same time, fully exploiting the flexibility of campus loads is also conducive to the accommodation of renewable energy. This paper provides an optimal dispatch approach to achieve low-carbon in a campus smart grid. Firstly, a green electricity trading mechanism based on power-load matching was proposed. Secondly, flexible load models in the campus for electric vehicles, air conditioners, energy storage, and other loads were established. Thirdly, a day-ahead renewable energy power prediction method based on weather forecast data for a campus wind-solar-storage combined operation power system is proposed. Finally, by means of load regulation measures, such as flexible class schedule, an optimal dispatch approach for the low-carbon campus power system was established. The case study shows that adopting load regulation measures can effectively promote the consumption of renewable energy sources and support the development of the low-carbon campus.

Abstract

Chemical looping dry reforming of methane (CL-DRM) has emerged as a promising approach, providing a pathway to mitigate greenhouse gas emissions by simultaneously converting methane and carbon dioxide into valuable syngas. In this study, we focus on the utilization of lanthanide-based perovskite oxygen carriers to enhance the performance of CL-DRM for syngas production. We investigate the influence of various operational parameters, including temperature, reactant gas ratio, and oxygen carrier composition, on the reactivity performance. The results reveal that the LaFe0.8Al0.2O3 oxygen carrier exhibited excellent activity in promoting the CL-DRM reactivity. Furthermore, this oxygen carrier showed high selectivity towards syngas production (CO selectivity>99%, H2/CO=2). These findings suggest that LaFe0.8Al0.2O3 perovskite oxygen carriers hold great potential for sustainable syngas production, contributing to the transition to a low-carbon future.

Abstract

Liquid piston systems (LP) are an efficient, simple, and environmentally friendly way to harvest energy from relief pressurised gas flows. In this paper, we study an LP system that operates by constantly introducing gas into a piston chamber containing water. The expansion of the gas propels the water, resulting in an isothermal expansion process due to their interaction. The discharged water is used to generate electricity. A dynamic model was developed using gPROMS and the numerical results were validated against previously published experimental data. The power output predictions show a maximum relative error of 6.4% from the experimental results. The performance of the LP system was evaluated employing waste gas data obtained from a liquefaction plant utilised to supply oxygen to a metallurgical furnace located in Chile. The predicted thermal efficiencies for the case study were as high as 80%, and the produced power output was 90 kW. The cost analysis demonstrated a decrease of 5.9% in electricity consumption attributed to the LP recovery system. Furthermore, the economic analysis illustrated a payback period for the investment ranging from 1.7 to 3.8 years, followed by an annual savings generation spanning from 24 to 47 kUSD depending on the electricity cost.

Abstract

The industrial sector consumes a large amount of electricity, making it an ideal candidate for Demand response (DR) flexibility in modern power systems. However, current solutions for industrial DR are limited to individual cases, services and platforms, preventing companies from exploring their complete flexibility potential. Addressing this, we introduce the Energy synchronization platform (ESP), a digital integration platform concept to enable and streamline automated industrial DR. This paper outlines the ESP’s conceptual architecture, components, and operational interactions, highlighting the benefits and challenges faced in a small‐scale demonstrator consisting of three industrial companies.