Abstract

Ensuring a timely and appropriate supply of reactants is paramount for optimizing fuel cell performance. However, achieving precise reactant control depends on accurately determining the system’s internal state. In this paper, the challenge of directly measuring the internal state of vehicular PEMFCs is addressed by proposing an adaptive internal state observer. Firstly, an air subsystem model with five state variables is established based on experimental data. This model effectively describes the critical dynamic features of air flow in the fuel cell system. Secondly, a cubature Kalman filtering algorithm is used to estimate the internal state of the cathode side of the PEMFC. To improve the algorithm’s flexibility and minimize estimation errors caused by variations of model parameters, a forgetting factor is introduced, which dynamically adjusts the algorithm’s parameters based on the changing conditions of the model. Finally, the simulation comparison demonstrates that the ACKF effectively mitigates the degradation of estimation accuracy with strong robustness as the variation of key structural parameters increases. The ACKF reduces the IAE to 15.05% and 10.92% of the CKF when the selected structural parameters vary by 5%, and to 9.82% and 4.87% respectively when the variation is 10%.

Abstract

The electrochemically mediated amine regeneration (EMAR) for CO2 capture presents a promising CO2 capture approach. The EMAR process relies on the competitive binding between Cu2+ and CO2 to solvent, and employs an externally powered electrochemical cell to the desorption of the absorbed CO2. This study focuses on the simulation of the EMAR process in the EDA-Cu system. Firstly, a chemical reaction equilibrium model for the Cu(II)-EDA-CO2-H2O system is established, and the concentration changes of each component in the electrolyte under different copper loads are obtained, providing a basis for simplifying the loaded EMAR process. Next, a multiphysics model is constructed using COMSOL software to simulate the EMAR process in a simple flat-plate reactor, employing the three-dimensional Nernst-Planck model and bubble flow model. The results show that the distribution of reactive ions in the electrolyte during operation conforms to ion liquid-phase mass transfer theory. The presence of CO2 bubbles during the electrolysis process enhances the electrode reactions to some extent. The co-current flow in the anode and cathode chambers exhibits better system stability and desorption performance compared to counter-current flow. The findings of this study provide valuable guidance for the design and application of EMAR system reactors.

Abstract

Traditional research focuses on the quantity of energy while overlooking energy quality. Exergy-potential, as a critical state parameter for the energy quality of integrated energy system(IES), reflects the transport capability of effective energy. Based on the Exergy flow mechanism model of IES, this paper establishes an IES station-network joint planning model considering Exergy-potential constraints. The objective function is the minimization of the equivalent annual total cost, with Exergy-potential at IES nodes as new constraint conditions. The decision variables include the selection of energy pipelines and the 24-hour heat output of energy station equipment. Simultaneously, the accuracy and validity of the proposed method were validated in typical IES case studies. The results indicate that Exergy-potential constraints have an impact on the selection of energy pipelines and the capacity configuration of energy station equipment. Different Exergy-potential constraint conditions correspond to varying costs, and exergy loss for the planning scenarios.

Abstract

In-situ combustion (ISC) has excellent potential in the development of unconventional resources such as heavy oil and tar sand. However, a uniform extension process for the combustion chamber is crucial for maintaining efficient and economical oil recovery during the ISC, which should be given more attention. In this work, a dynamic control technique that is achieved by the regular implementation of production well intermittent shutdown (PWIS) with the aim to improve the uneven extension of combustion chamber is proposed. A 3D combustion model with a volume of 214962 cm3 is utilized in the ISC experiments to study the application effect of dynamic control technique. The variation of effluent gas compositions, spatial distribution of coke zone, swept area of combustion chamber, burning stability, and pressure difference are studied and analyzed. The results show that the PWIS method is able to force the combustion chamber to extend toward the low and medium permeability regions with little influence on the burning state. The volumetric sweep coefficient of combustion chamber in the low and medium permeability zones was improved and the combustion status varied slightly during the PWIS implementation. Final 3D morphology of coke zone is vividly described according to the real size, and its spatial volumes in the low and medium permeability zones enlarge noticeably after the PWIS implementation. Additionally, the cumulative oil production increased from 5586.5 g to 10426 g, and the final oil recovery ratio enhanced from 23.3% to 40.8% after implementing the dynamic control technique. This work provides a practical approach to improving the volumetric sweep coefficient of combustion chamber, which is of great significance in maintaining a higher oil production efficiency during the ISC field application.

Abstract

Short-term electricity trading on intraday markets is crucial for integrating variable renewable energy in the power system. For instance, it allows energy suppliers to adjust their market positions based on updated variable renewable energy and consumption forecasts, reducing their potential imbalances. In the case of Germany, the continuous intraday market allows trading from the day before delivery until several minutes before delivery. However, the complex market design and high price volatility make developing price forecasting models challenging. This paper lays a foundation for price forecasting by comparing baseline models used to benchmark rolling continuous intraday price forecasts. These baselines help develop price forecasting models as they serve as a reference for these models. We also adapt a price normalization approach from the literature to benchmark price forecasts in a volatile market environment. Our baselines include the generalization of two baselines used in literature and one new baseline. We benchmark our baselines throughout 2021 and 2022. Among other baselines, we find that the price average of the last four trades yields the lowest root mean squared error. Moreover, the analysis suggests that baseline errors are independent of the market price development through normalization.

Abstract

Non-aqueous thermally regenerative flow battery (TRFB) has shown great promise to convert low-grade waste heat into electricity for its high circuit voltage and high power density. Developing a reasonable porous anode electrode is essential for the fluid-solid interaction of the anolyte. In this study, a reduced-graphene-oxide-modified nickel foam (RGO/NF_T) was developed to optimize the anode electrode structure and hopefully obtain a competitive performance of TRFB. It was demonstrated that the RGO/NF_T as the anode electrode with better wettability and a larger specific area was beneficial for the electricity generation of TRFB. TRFB using relatively low-cost untreated nickel foam as anode (TRFB-NF) obtained a maximum power density of 105.7 W/m2, which was similar with that of TRFBs using RVC anode. A further 21% increase in the maximum power density was found in TRFB-RGO/NF_T (127.9 W/m2). Moreover, the discharging time was extended by 78% and the energy density was improved by 165% in TRFB-RGO/NF_T, in comparison with the TRFB-NF. The results indicated that RGO/NF_T could be a potential anode electrode for TRFBs having the competitive performance in future practical application.

Abstract

All-aqueous thermally regenerative battery (ATRB) is a promising technology for converting low-grade waste heat into electricity while the low specific surface area of electrodes limits its performance. In this study, a porous composite electrode by modifying carbon cloth with carbon nanotubes (CNT/CC) is developed to promote battery performance, and the effect of CNT loading amount is analyzed. The results indicate that the porous composite electrode has a significantly larger specific surface area, resulting in a 37.4% increase in battery performance compared to ATRB with the traditional carbon cloth (CC) electrode. In addition, ATRB performance initially rises and then declines with the increasing carbon nanotube loading. The optimal loading (4 mg) induces a peak power density of 492.6 W/m², which is competitive for future practical applications of ATRBs.

Abstract

An accurate understanding of slag cooling characteristics is essential for efficient slag heat recovery. Herein, we established multiple cases including different assumptions, such as dimensions, boundary conditions, width ratios, radiation models, and turbulence models to quantify the extent of error associated with these assumptions. An area-weight angle sampling method was adopted to evaluate the accuracy of assumptions. The results reveal the significant error attributed to dimensions and radiation, with RMSE and MAPE of 235.14 K and 41.30% for the 2D planar model, and 198.60 K and 25.66% for the model without radiation. Notably, when the width ratio exceeds 4, the influence of boundary conditions on cooling characteristics becomes negligible. This present work provides a benchmark model to quantify the error of assumptions and thus enables more accurate yet efficient modeling for phase-change cooling for molten slag at ultrahigh temperatures.

Abstract

Among the relatively mature new energy generation technologies, wind power has attracted widespread attention for rich reserves and pollution-free emissions. However, wind power generation has randomness and volatility, posing a huge challenge to power quality and stability. With the rapid development of technologies such as water electrolysis and breakthroughs in key technologies, wind energy hydrogen production technology provides new ideas for solving problems such as poor power quality and strong voltage fluctuations in wind power generation systems. This paper fully considering the electrolyzer dynamic power variation requirements and the wind turbine output power variation characteristics, designs a constant bandwidth MPPT control strategy to achieve on-demand power output of the wind turbine; at the same time, smooth the output power, achieve dynamic coordination of power between the wind turbine and the electrolyzer system. Finally, the effectiveness of the proposed coordinated control method is verified through simulation.

Abstract

Hydrogen (H2) production using a stand-alone microgrid composed of wind, photovoltaic (PV), and energy storage systems is gaining growing attention due to its environmentally pollution-free feature. However, because of the intermittent and random characteristics of renewable energy, the sizing of the system highly influences its safe, stable, and economical operation. So far, this problem hasn’t been addressed in both industry and academia. In this regard, an optimal sizing method for the electrolyzer and energy storage unit of a stand-alone microgrid with fixed wind and PV power generations is proposed. Under the constraints of the state of charge of the energy storage unit, the safe operation of the electrolyzer, and the optimal power allocation of the whole system, the best system profit and highly stable operation are achieved through optimization modeling and problem-solving. An example wind-PV-energy storage stand-alone hydrogen production system composed of 2MW wind power and 1MW PV power is developed. The electrolyzer, energy storage unit and hydrogen tank are sized following the proposed method.