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Abstract Efficient oxygen excess ratio (OER) control is of great importance for proton exchange membrane fuel cell because it is closely associated with the economic efficiency and safety. As widely investigated, OER control is challenging due to the difficulties of system nonlinearity, parametric uncertainty and load disturbances. In this paper, an underlying difficulty for OER control is addressed by pointing out the overshoot response. To this end, this paper employs active disturbance rejection control which is able to handle the various difficulties in a data-driven manner. It treats the nonlinearity, uncertainty and disturbances as a lumped term, which is then estimated online via analyzing the real-time data. The estimated lumped term is canceled timely such that the remaining dynamics behaves like an integrator without overshoot term therein. The data-driven and conventional proportional-integral controllers are tuned and compared based on the linearized transfer function model, showing the potential superiority of the proposed method in terms of the uncertainty and disturbance rejection, anti-windup and overshoot reduction. The nonlinear simulation based on the nonlinear mechanism model further demonstrates it good flexibility under different operating conditions. Moreover, it requires less compressor movement efforts, leading to a dynamic energy-saving effect and thus prolonging the durability and lifetime of the compressor.

Abstract When multiple transmission lines are not entirely parallel erected in one common corridor, the electric unbalance degree of double-circuit ultra-high voltage (UHV) AC transmission line can be affected by several factors, such as severe electromagnetic coupling between lines in parallel section, various phase sequence arrangements and transposing modes of the lines, active power of the lines changing constantly. This paper presents a detailed analysis on the electric unbalance degree of double-circuit UHV AC line in common corridor, with particular attention to the effects of the parallel section’s length, number and the active power of the lines. The causes and factors of unbalanced currents of double-circuit UHV AC line were taken into account by phase-sequence conversion of current and voltage, and the above effects were proved by an actual example. The main factors were studied by simulating in PSCAD/EMTDC. The results show that the parallel section’s length, number and the active power of lines have considerable influences on the electric unbalance degree of double-circuit UHV AC line in common corridor. Finally, some suggestions have been proposed to provide as a construction reference to confine the level of electric unbalance degree of double-circuit UHV AC line which is not entirely parallel erected with other lines in common corridor.

A continuous flow microbial fuel cell constructed wetland (MFC-CW) coupled with a biofilm electrode reactor (BER) system was constructed to remove sulfamethoxazole (SMX). The BER unit powered by the stacked MFC-CWs was used as a pretreatment unit, and effluent flowed into the MFC-CW for further degradation. The experimental results indicated that the removal rate of 2 or 4 mg/L SMX in a BER unit was nearly 90%, and the total removal rate in the coupled system was over 99%. As the hydraulic retention time (HRT) was reduced from 16 h to 4 h, the SMX removal rate in the BER decreased from 75% to 48%. However, the total removal rate in the coupled system was still over 97%. The maximum SMX removal rate in the MFC-CW, which accounted for 42%-55% of the total removal, was obtained in the anode layer. In addition, the relative abundances of sul genes detected in the systems were in the order of sulI > sulII > sulIII, and significant positive correlations of sul gene copy numbers versus SMX concentration and 16S rRNA gene copy numbers were observed. Furthermore, significant negative correlations were identified between sul genes, 16S rRNA gene copy numbers, and HRT. The abundances of the sul genes in the effluent of the MFC-CW were lower than the abundances observed in the BER effluent. High-throughput sequencing revealed that the microbial community diversity of the BER was affected by running time, power supply forms and HRT. Bio-electricity from the MFC-CW may reduce microbial community diversity and contribute to reduction of the antibiotic resistance gene (ARG) abundance in the BER. Taken together, the BER-MFC-CW coupled system is a potential tool to treat wastewater containing SMX and attenuate corresponding ARG abundance.

Abstract Operation safety and efficiency of high-speed trains are prone to strong winds. This study proposes a wind hazard warning system to predict wind speed and provide warning for safe and efficient operation of trains, and shows the implementation to the Lanzhou-Xinjiang High-Speed Railway. The system is composed of monitoring, remote and central processing, and execution modules. The system uses field monitoring data to predict wind speed and analyze responses of trains. Wind speed is predicted through integrating three models based on artificial neural networks and the predictions are incorporated into operation control for high speed trains under wind load. The results show that the proposed predictive model is capable of predicting wind speed, and the system is capable of providing reasonable warning for high-speed trains. It is anticipated that the system will improve the operation and management of high-speed trains for high safety and efficiency.

The growing abundance of wind and solar power has driven interest in utilizing this renewable energy to make chemicals. One of the most efficient and sophisticated frameworks to solar-to-chemical conversion is bioelectrochemical systems that electrochemically couple inorganic catalysts and microorganisms. In particular, microbial electrosynthesis systems and biohybrid systems have used CO2 and electricity or light, respectively, to synthesize organic acids at energy efficiencies that exceed natural photosynthesis. In parallel, new methods have been recently developed to improve the poor mechanistic understanding of these and other bioelectrochemical systems. Deeper knowledge of these underlying molecular processes and creation of new architectures for bioelectrochemical systems are needed to make these promising technologies scale to a commercially relevant level.

Thermostatically controlled loads (TCLs) have demonstrated their potentials in demand response. One of the key challenges for TCLs to be integrated into the system-level operation is building a compact aggregated model, in which the TCL primary behaviors are accurately captured. In this paper, TCLs are aggregated as a virtual generator and two batteries according to their different compressor types and control methods for smoothing out multi-time-scale variability of wind power generation. This will bring system operator great convenience to manage TCLs and conventional components when the system-level decisions are made. Accordingly, accurate parameters of virtual generator and batteries are critical to effectively coordinate TCLs with other resources in the system operation. However, it tends to be difficult to obtain such aggregated parameters as a result of insufficient data for each TCL. To address this problem, high-dimensional model representation (HDMR) is introduced to estimate the aggregated parameters of virtual generator and batteries using the probability distribution of TCL parameters. A numerical simulation study demonstrates that aggregated parameters of virtual generator and batteries can be accurately estimated by HDMR. And virtual generator and batteries are able to follow actual behaviors of TCL populations in power system operations.

In our previous experimental study, a novel multistage moving bed air reactor was proposed for chemical looping combustion; some operating mechanisms including the gas flow carrying capacity and ga...