Abstract

A deep understanding of the two-phase and multi-species transport coupled with photoelectrochemical oxygen reduction reaction is crucial for boosting a photocatalytic fuel cell with a photoanode and an air-breathing photocathode. Herein, a pore network model is developed for the air-breathing CuO photocathode employed in photocatalytic fuel cell to describe the two-phase percolation and multi-species transport as well as their effect on the photocathode performance. The performance of the air-breathing photocathode is found to be greatly affected by the wettability-dependent liquid invasion into the gas diffusion layer. Increasing the proportion of hydrophilic pores/throats in the gas diffusion layer greatly lowers the photocathode performance because of more severe liquid invasion. Besides, the transport of active species, including the dissolved oxygen and photo-excited electron and hole, has a significant effect on the photocathode performance. The present work also provides a guidance for the optimal design of the air-breathing photocathode.

Abstract

In order to study the effect of nickel powder morphology on the hydrogen evolution performance of prepared aligned porous electrodes, both spherical and flake nickel powder are used in the electrode preparation. Experimental results show that the aligned porous electrode prepared by spherical nickel powder exhibit a larger electrochemically active surface area, demonstrating superior hydrogen evolution performance at low current density. Conversely, the aligned porous electrode prepared by flake nickel powder demonstrates higher bubble transfer efficiency and better hydrogen evolution performance at high current density. Furthermore, the influence of electrode thickness on the hydrogen evolution performance are studied. For the aligned porous electrode prepared using spherical nickel powder, increasing the thickness to 600 μm initially enhances electrode performance, but it subsequently decreases with further increases in current density. On the other hand, the aligned porous electrode prepared using flake nickel powder exhibits improved performance within the tested range as the electrode thickness is increased to 600 μm.

Abstract

Driven by the dual carbon target, renewable energy will be connected to the grid in a large-scale distributed way, and will be mainly concentrated in wind, photovoltaic and land resource-rich distribution network end areas. However, the weak distribution network architecture in these regions and the limited carrying and governance capacity of renewable energy make it difficult to effectively absorb the renewable energy output in peak periods, resulting in large-scale wind and light abandonment.
In response to this problem, this paper adopts a governance idea of using hydrogen energy storage to participate in the renewable energy consumption of the distribution network and meet the demand of users. The use of hydrogen energy storage can not only directly improve the absorption capacity of the distribution network, but also exchange energy with the outside world through the hydrogen network, reduce the dependence of electricity demand side on the distribution network, achieve the “soft off-grid” state, so as to reduce the burden of renewable energy governance of the distribution network, and improve the low-carbon operation economy of the end area of the distribution network.

Abstract

This paper mainly studies the configuration issues of the wind solar off-grid hydrogen production system. The system consists of a WT, PV array, energy storage batteries, an alkaline electrolyser, and a proton exchange membrane (PEM) electrolyser. The addition of PEM electrolyzer aims to reduce wind and solar power curtailment and improve the energy utilization efficiency of the system.Firstly, the study establishes simplified mathematical models for each device, designs a power-flow strategy, and develops an economically optimal objective function. The model is solved using the optimized sparrow optimization algorithm to obtain the system configuration and other important indicators such as annual energy output power and H2 production.For a scenario with a 1 MW WT and a 1 MW PV panel hydrogen production, the system configuration is determined as follows: EES with a capacity of 244 kWh, alkaline electrolyser with a power of 863 kW, PEM electrolyser with a power of 198 kW, and hydrogen storage tank capacity of 3060 kg. The energy utilization efficiency is 51% and the investment cost is approximately 2.38 million$.

Abstract

The energy dispatch of wind-solar-hydrogen storage systems is an effective technique for mitigating the intermittency of renewable energy sources. Addressing issues such as power fluctuations in off-grid hydrogen production systems and substantial tracking errors, we present a two-stage optimization scheduling strategy based on Model Predictive Control (MPC). During the first stage, a day-ahead scheduling approach is developed by comprehensively considering the stochastic behavior of renewable energy and the operational lifespan of energy storage, with the objective of optimizing the economic performance of the system. In the second stage, a day-ahead rolling optimization and correction strategy based on MPC is proposed to handle power fluctuations stemming from forecast errors in renewable energy generation, while concurrently ensuring the stable operation of the system. To tackle the inadequacies of conventional MPC in dealing with sudden disturbances, we devise an adaptive temporal parameter controller capable of determining optimal predictive and control temporal parameters. This controller design enhances the control precision and stability of MPC when confronted with abrupt changes in renewable energy generation due to sudden increases or decreases. The effectiveness of the proposed model and algorithm is validated through a case study using a microgrid as an illustrative example.

Abstract

The harsh operating environment and non-fixed foundation pose a challenge to the power output of the floating wind turbine, so a floating platform for motion within a safe range is required. The paper analyzes the influence of wind-wave coupling, wave direction angle and rotor degree of freedom on the platform movement. It is found that the stability of the floating platform is very sensitive to the key parameters of the mooring system. The mooring system dynamic model is established, and the simulation analysis is carried out by resetting the key parameters of the mooring system. The effects of variables such as the position of the fairlead, the tensile stiffness of the anchor chain, and the mass per unit length of the anchor chain on the platform’s motion stability and output power fluctuation are analyzed. It is also of great significance to balance the relationship between the platform’s dynamic response and power generation.

Abstract

Using effective vehicle-to-grid (V2G) strategies, the onboard batteries in grid-connected electric vehicles (GEVs) can be leveraged to alleviate the impact of solar photovoltaic (PV) systems and provide grid support. Nevertheless, the abuse of batteries during V2G is inevitable owing to balancing the fluctuation of solar power while ensuring charging effectiveness, resulting in risks on battery rapid degradation and thermal safety. Regarding this, a multi-physics-constrained charging scheduling strategy is proposed in this study, enabled by a novel deep reinforcement learning (DRL) technique to mitigate solar PV impact while minimize the expected customer’s charging cost, including energy cost and battery aging cost as well as satisfying the customer service quality and battery operation safety constraints. The proposed strategy is further performed within a cyber physical system-based framework, where the complicated training is carried out in the cloud, while the trained low-complexity policy is executed in the onboard controller to mitigate high computing burden. The effectiveness of the proposed strategy is verified by hardware-in-Loop tests and practical battery charging/discharging experiments combined by a real distribution system in Australia.

Abstract

The lack of clarity and uncertainty about hydrogen’s roles, demand, applications, and economics has hindered hydrogen development. This paper presents an integrated whole energy system (IWES) model to optimise the planning and operation of an energy system; the model is used to identify the role of hydrogen technologies in decarbonising energy systems, improving system flexibility and enhancing energy system security and resilience against extreme weather. The studies were conducted on the future (year 2050) Great Britain’s energy system to understand the hydrogen infrastructure capacity needed and their utilisation from the production, transport, storage, and demand under different scenarios. In the models, hydrogen technologies will compete against other alternative technologies, and the optimisation models will determine the least-cost solution. The studies demonstrate that hydrogen is essential for providing flexibility, energy system security and resilience against extreme weather. Synergy across hydrogen assets reduces the cost of hydrogen heating, which can be cost-competitive against the heat electrification approach.

Abstract

A series of three-dimensional numerical simulations of Poiseuille-Rayleigh-Benard (P-R-B) convection of cold water with different aspect ratios were carried out by using the finite volume method. The results indicate that the flow weakens gradually as the density inversion parameter increases, indicating that the density inversion parameter has a suppression effect on secondary flow. The average Nusselt number in the fully developed region increases with the increasing Rayleigh number and aspect ratio and the decreasing density inversion parameter. Based on the calculation results, a heat transfer correlation for the fully developed region of P-R-B convection was obtained.

Abstract

To explore the effect of different container geometry and interface curvature on water evaporation at low pressure, a two-side mathematical model is established, and a series of numerical simulations are carried out. According to the calculation results, the surface curvature has distinct effects on the development of thermocapillary convection, and thus affects the flow and temperature distribution in the liquid phase. The difference in the dominant convection will lead to the difference in the energy transmission mode. In addition to thermal conduction, the roles of thermocapillary convection and buoyancy flow should be considered.