Abstract

Non-aqueous thermally regenerative batteries (NTRBs) hold significant potential for efficiently converting low-grade waste heat into electricity, offering broad application possibilities. Nevertheless, the specific surface area of the reported electrodes restricted both the electrochemical reaction rate and electricity generation. In this work, the reduced graphene oxide modified porous carbon foam(rGO/CF) was proposed to serve as an anode electrode for NTRB to promote the electricity generation of NTRB. The maximum power density of the NTRB with rGO/CF electrodes reached its peak at 190.2 W/m², showing enhancements of 15% compared to carbon foam. The enhanced performance was primarily attributed to the abundant active sites, large specific surface area, and favorable porous electrode structure. Moreover, the stability of the rGO/CF electrodes was confirmed with a continuous operation exceeding 270 minutes and enduring through more than 8 cycles. In conclusion, NTRB-rGO/CF showed great promise for applications in converting low-grade waste heat into electricity.

Abstract

Thermal energy storage plays an important role in renewable energy utilization. Absorption thermal storage (ATS) is used to balance heat source and load due to its high stability. To investigate the charging and discharging process of ATS, a novel dynamic ATS model was proposed and validated. Based on the established model, the effects of charging temperature, discharging temperature, condenser inlet temperature, and evaporator inlet temperature on the performance of thermal storage were analyzed. The results show that the higher charging temperature increases solution glide, resulting in improved energy storage efficiency and energy storage density. The maximum energy storage efficiency is between 0.25 and 0.65, while the maximum energy storage density varies from 55.6 kWh/m³ to 143.6 kWh/m³, with discharging temperatures of 70 – 90 °C. Increasing the condenser inlet temperature and decreasing the evaporator inlet temperature significantly reduces the charging time and discharging time, respectively.

Abstract

A novel high strength clogging resistant permeable pavement (CRP, also known as Kiacrete) has been developed to prevent surface flooding by absorbing stormwater runoff. Ground source energy systems (GSES) are a sustainable method to melt ice/snow on pavements. Heat energy is deposited into the ground during the summer and extracted in the winter. In this study, a numerical model has been developed, using COMSOL Multiphysics, to investigate the thermal performance of Kiacrete that is heated with a GSES. The numerical results were validated against that of the experimental values. The experimental setup consisted of i) a Kiacrete slab (290 mm × 290 mm × 80 mm) with 144 equidistant pores (each pore was 6 mm in diameter); ii) a heating water bath that pumped 40 °C hot water into a standard High-Density Polyethylene (HDPE) pipe of 24 mm in diameter at a flow rate of 18.5 litres/minute. This pipe was placed underneath Kiacrete, at its centre, to mimic the ground source energy; iii) an aggregate layer (Thames Valley River gravel ≥ 5 mm) to simulate the ground conditions; and iv) a cooling water bath that pumped 10 °C cold water into an aluminium plate with embedded copper pipes of 8.12 mm inner diameter, spaced 18 mm apart. This cooling plate was placed underneath the aggregate layer to mimic the ground temperature conditions within the UK. K-type thermocouples were placed at different heights and locations within the Kiacrete pores and the surrounding concrete. A good agreement was observed between the numerical simulation results and the experimental values. The heat propagation inside the concrete, in lateral direction, was found to be symmetrical. Furthermore, the pores inside Kiacrete produced the effect of small chimneys supporting the convection heat transfer, with conduction heat transfer occurring inside the surrounding solid concrete. This study provides the basis for investigating the heat transfer characteristics of a new type of permeable concrete pavement, whilst providing useful insights into developing complex numerical models for simulating its efficiency in melting ice and snow.

Abstract

This study combines a novel high strength clogging resistant permeable pavement (CRP, also known as Kiacrete) with a ground source energy system GSES and numerically investigates the effect of Kiacrete’s pore diameter and number on its sensible heat storage (SHS) potential. The energy storage module consists of: i) a 290 × 290 × 80 mm Kiacrete slab that is the heat storage medium; ii) a 24 mm inner diameter standard HDPE pipe that is placed underneath Kiacrete and contains the heat transfer fluid (water), flowing at a temperature of 40 °C with volumetric flow rate of 18.5 litres/minute; iii) an aggregate layer (Thames Valley river gravel ≥ 5 mm), which is placed underneath the heating pipe, to simulate the ground conditions; and iv) a cooling plate with 8.12 mm inner diameter embedded copper pipes that has water flowing at a temperature of 10 °C, and is placed at the bottom of the aggregate layer, to mimic the ground temperature conditions within the UK. Four different Kiacrete pore diameters (4 mm, 6 mm, 8 mm and 10 mm) and two different equidistant pore numbers (144 and 121) were investigated for a 12-hour heating cycle. The results showed that the lower pore number and smaller pore diameter provided more energy storage media (concrete), resulting in high sensible energy storage within the Kiacrete slab. Conversely, the effect of pore number and diameter was relatively small on the heat transfer rates inside the Kiacrete slabs.

Abstract

The demonstration of proton exchange membrane fuel cell (PEMFC) technology for commercial vehicles has shown increasing success, but comprehensive commercialization remains limited by the service life of the cells. Timely prediction of fuel cell lifetime can enhance state assessment in advance, enabling precise control for performance recovery operations, thus reducing use and maintenance costs and avoiding predictable risks. Commonly used lifetime prediction models are categorized into mechanistic models, data-driven models and hybrid models. However, data-driven prediction methods often overlook degradation mechanisms, while mechanistic models lack real-time data integration. Additionally, the incomplete exploration of mathematical degradation mechanisms poses challenges for mechanistic models. The frequent start-stop cycles result in significant voltage recovery phenomena, complicating the accuracy of remaining lifetime predictions. This paper presents accelerated stress tests conducted on a 15kW fuel cell stack under idle, rated, and dynamic load conditions, discussing performance recovery following shutdown periods under various operating conditions. The experimental results indicate significant voltage recovery at all current conditions, with the most pronounced recovery occurring at high current conditions. Voltage recovery increases with longer downtime durations. Additionally, a data-driven model utilizing complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and long-short term memory network (LSTM) was proposed. The model first decomposed raw voltage data into modal sequences with distinct characteristic time scales, which were then input into the LSTM for voltage prediction. The prediction results demonstrate that the CEEMDAN-LSTM hybrid model reduces RMSE by 30.41% and 18.21% compared to the LSTM and GRU models under idle conditions, by 28.37% and 16.87% under rated conditions, and by 17.02% and 16.14% under variable load conditions, respectively.

Abstract

Thermostat settings in residential buildings impact both energy bills and health. While residents can only control indoor temperature through thermostats, there is a lack of understanding about the impacts of adjusting thermostat settings on energy consumption and thermal comfort. This knowledge gap makes it challenging to balance cost-effective and thermally comfortable behaviors, which could ultimately exacerbate disparities in dwelling conditions. This study presents a framework to optimize adaptive temperature setpoint schedules through parametric building energy modeling and explore energy usage strategies that reconcile energy reduction with thermal comfort for residents. The study consists of 1) defining simulation scenarios, 2) optimizing adaptive setpoint schedules in building energy models, and 3) developing energy usage strategies. By providing expected utility fees and thermal sensation levels for each strategy, this study assists residents in making informed decisions regarding adaptive thermostat settings for balancing economic and health challenges. This study promotes a sustainable and equitable built environment by equipping all populations, especially low-income households, with adaptable and actionable approaches.

Abstract

Energy storage technology can significantly enhance energy efficiency and conserve energy. Thermochemical adsorption heat storage based on salt hydrate is a crucial technology for long-term energy storage owing to its significant advantages of excellent energy storage density and minimal heat loss. K2CO3 is regarded as a prospective thermochemical heat storage material. In this work, a numerical model of the K2CO3 heat storage process is established using COMSOL based on the conservation of mass, momentum and energy, considering the variation of porosity with conversion degree and the flow of water vapor. Literature results confirm the validity of this model. The heat storage process is investigated, and the transient evolution of parameters such as temperature and concentration during the desorption process is described, elucidating the fundamental principles of the thermochemical heat storage process. The influence of various parameters on system performance is explored. The simulation results show that the porosity of the heat storage material shows obvious inhomogeneity in time and space. The porosity increases continuously with the progress of the reaction, which effectively promotes the progress of the reaction. Raising the heat flux and reducing heat loss can effectively decrease the reaction start-up time. This work offers insights into designing and optimizing thermochemical heat storage material and system.

Abstract

The storage of CO₂ in geological reservoirs is considered one of the most promising solutions to achieve net zero emissions and address the current climate change crisis by 2050. Based on planning CO₂ storage activities, it is necessary to design accurate on-site characteristics and monitoring during the injection and post injection stages to determine reliable and sustainable geological storage. This study involves the evaluation of surface gravity measurements for monitoring CO₂ plumes in the Johansen deep saline aquifer, which is a potential offshore location for CO₂ geological storage. Use available benchmark models and geological information to simulate injection and post injection stages. The gravity response of the surface was calculated based on the estimation model of reservoir density and saturation at different time intervals and injection rates. Forward calculation is achieved by assuming discretization of tetrahedral grids to ensure accurate and detailed reconstruction of complex reservoirs. The results indicate that the gravity anomaly extends radially around the well site, reaching a peak of approximately -15 μ Gal at an injection rate of 60 kg/s. During the post injection period, the gravity map clearly shows that the saturation of saline water around the injection well increases, and the CO₂ plume migrates towards the shallower part of the reservoir.

Abstract

CO2 injection technology is a widely used extraction method for conventional and unconventional oil reservoirs. This technology can further achieve carbon sequestration and carbon neutrality on the basis of improving recovery efficiency. Under the guidance of the above ideas, firstly, theoretical methods are used to analyze the feasibility of various CO2 injection technologies. Among the composite CO2 technologies, CO2 flooding after CO2 huff-n-puff has better applicability compared to other technologies. Secondly, numerical simulation methods are used to optimize the technical scheme design of the block. After optimizing the parameters of single factor gas injection, conventional gas injection, mixed gas injection, water gas alternation and other injection methods are optimized. The results show that the optimal single factor CO2 injection scheme can increase the final recovery rate by 13 percentage points compared to water drive; The water to CO2 ratio is 1:1, and injecting water to air circulation in a 3-month cycle can achieve optimal results. In the current context of carbon neutrality, the scale of CO2 injection applications will continue to expand, and this research will also provide technical support for the promotion and application of CO2 injection technology.

Abstract

In the context of decarbonization against climate change, energy management measures including Distributed Energy Resource (DER) is gaining significant social attention. The Ministry of the Environment, Government of Japan, advocates for regional decarbonization and promotes community-wide efforts to increase renewable energy usage. Recent advancement of technologies such as smart metering and blockchain make the implementation of the Peer-to-Peer(P2P) energy trading system, that enables individual buildings to buy and sell energy generated by renewable sources like photovoltaic (PV) and stored in batteries, much easier. Against these backdrops, we expect that energy sharing communities which share the benefits of renewable energy and decarbonization measures will be formed to in the future society. The existing researches which are focusing on the energy trading or energy sharing system mainly aim to evaluate economic benefit for communities through simulation regarding participants in the trading market as agents. However, we point out little consideration has been given whether the results calculated by simulation are truly aligning with participant’s behavior and benefit that participants expect in the real world. While simulations can estimate economic benefit, it is crucial to observe actual participant behavior to ensure these results are consistent with the reality. This study will examine how participants behave in the community which shares the benefit from energy management measures through observation of playing the energy sharing game. The results showed that shared funds were distributed equally to players, but players tended to perceive the distribution was equitable. Our findings will be helpful for considering how the energy sharing community will be designed, and how prosumers/consumers behave in a society where the energy sharing is implemented.