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Role of nitrogen cycling functional genes and their key influencing factors in eutrophic aquatic ecosystems

Environmental Reviews 2025年 33卷

作者： Wang, Wenwen Li, Mengze Chen, Peng Yuan, Shengwu Wang, Kun Wang, Shuhang Jiang, Xia State Key Laboratory of Environmental Criteria and Risk Assessment National Engineering Laboratory for Lake Pollution Control and Ecological Restoration State Environment Protection Key Laboratory for Lake Pollution Control Chinese Research Academy of Environmental Science Beijing100012 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China Key Laboratory of Aquatic Botany and Watershed Ecology Wuhan Botanical Garden Chinese Academy of Sciences Wuhan430074 China

The nitrogen cycle, essential for the transformation and circulation of nitrogen, involves key processes such as nitrogen fixation, nitrification, denitrification, and ammonification. Microorganisms are crucial in these processes, influencing water quality through energy conversion and nitrogen cycling. Eutrophication, driven by human activities, increases exogenous nitrogen input, accelerating nitrogen cycling and loss, boosting greenhouse gas emissions, and impacting aquatic ecosystems. Functional genes in the nitrogen cycle, such as amoA (nitrification), nirS, nirK, nosZ (denitrification), and hzs and hzo (anaerobic ammonium oxidation), are indicators of nitrogen transformation in sediments. Environmental factors like temperature, dissolved oxygen (DO), organic matter content, nitrogen levels, pH, and salinity significantly influence these genes’ expression and regulation. For example, temperature changes can affect nitrifying and denitrifying bacteria activities, DO levels impact microbial growth and metabolism, and higher organic matter content stimulates the expression of nitrogen cycle genes. Understanding how these environmental factors affect nitrogen cycling genes is crucial for addressing eutrophication in aquatic ecosystems. This review focuses on the adaptability and responses of nitrogen-associated functional microorganisms and genes environmental changes, offering theoretical insights and practical guidance for sustainable ecosystem management. © 2025 The Authors.

关键词： Microorganisms

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Initial-stage performance evolution of solid oxide fuel cells based on polarization analysis 17

Initial-stage performance evolution of solid oxide fuel cell...

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17th International Symposium on Solid Oxide Fuel Cells, SOFC 2021

作者： Wang, Yige Lyu, Zewei Han, Minfang Sun, Zaihong Sun, Kaihua Department of Energy and Power Engineering State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing100084 China Xuzhou Huatsing Jingkun Energy Co. Ltd. Jiangsu Province Xuzhou221005 China

ISBN: (纸本)9781607685395

The performance evolution of solid oxide fuel cells (SOFCs) is more pronounced and non-linear in the initial stage, determining the output level during subsequent long-term operation. In this study, an industrial-size (10×10 cm2) cell was tested under 0.1 A cm-2 for 96 hours. I-V-P curves and EIS data under different DC bias (0, 0.05, 0.10, 0.30, 0.50, 0.70 A cm-2) were periodically recorded every 24 hours to investigate the mechanism of initialstage performance evolution. The ohmic loss was identified as the main contributor to the total overpotential, especially under large current density. The cell performance increased during 4-24 h due to the enhancement of anode gas-phase diffusion/conversion processes, while the performance degraded significantly during 48- 96 h caused by the deterioration of anode charge transfer reaction. The EIS evolution trend under different DC bias was consistent, while the evolution degree was larger under smaller current density. © 2021 Electrochemical Society Inc.. All rights reserved.

关键词： Deterioration

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power Load Forecasting Based on COA-Bi-LSTM Method 2

Power Load Forecasting Based on COA-Bi-LSTM Method

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2nd International Conference on Electrical Engineering and control Science, IC2ECS 2022

作者： Chen, Gang Zhang, Dian Xiang, Wei Guan, Zhenqi Huang, Jing Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control Nanan District Chongqing China Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing China

ISBN: (纸本)9798350399165

A power load forecasting method based on Coyote optimization Algorithm-Bidirectional Long short-Term Memory Neural Network (COA-Bi-LSTM) model was proposed in this study to solve the problem of inaccurate power load prediction. Aiming at the problem of artificial selection of neural network hyperparameters leading to inaccurate prediction, COA was used to iteratively optimize the three hyperparameters of Bi-LSTM: learning rate, iteration times and number of hidden units. Two groups of historical load data with different characteristics in January and August 2018 were selected and compared with the proposed method using BP neural network, LSTM and Bi-LSTM, respectively. The simulation results show that the optimized prediction effect is better. The Mean Absolute Percentage Error (MAPE) in the data prediction results in January is reduced by 45.46%, 28.57%, and 24.05% respectively. Meanwhile, the MAPE in the data prediction results in August are respectively reduced by 73.71%, 44.04%, 17.57%, verifying the effectiveness of the method. © 2022 IEEE.

关键词： Long short-term memory

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Ultra-Short-Term Multi-Step Prediction of Wind power Based on ModernTCN and Multi-Task Learning

Ultra-Short-Term Multi-Step Prediction of Wind Power Based o...

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IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Mao Yang Xiangyu Li Zifen Han Yong Sun Xiqiang Chang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Gansu Electric Power Company Gansu China State Grid Jilinsheng Economic And Technological Research Institute Jilin China State Grid Xinjiang Electric Power CO. LTD Xinjiang China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

The intermittent and fluctuating nature of wind energy makes it difficult to accurately predict wind power, leading to low penetration in the wind power grid. To address this problem, this paper designs ultra-short-term multi-step prediction of wind power based on ModernTCN and multi-task learning to improve the prediction accuracy. Firstly, ModernTCN's ability to have a large receptive field and capture cross-variate timing dependencies is exploited to obtain multivariate timing feature information and establish a multi-step mapping of input features to power. Then it is inputted into the MMoE multi-task learning method, and the prediction results are corrected to obtain the ultra-short-term prediction of wind power using multiple expert networks and gating units. The experimental results show that the method proposed in this paper can effectively improve the ultra-short-term prediction accuracy of wind power, and can provide a favourable reference for the scheduling centre to adjust the power generation plan in real-time response to the power demand.

关键词： Renewable energy sources Accuracy Wind energy Wind power generation Predictive models Multitasking Feature extraction Real-time systems Timing Wind forecasting

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Active Thermal control of Grid-Forming Converters Based on DC-link Voltage Synchronization

Active Thermal Control of Grid-Forming Converters Based on D...

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IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Mingqun Liu Guanming Zeng Xin He Liang Tu Peng He Yihua Zhu Electric Power Research Institute Yunnan Power Grid Co. Ltd. Kunming Yunnan State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&D Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&D Centre Guangzhou China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Grid-forming control, as a key technology for building new power systems, enables inertia and damping characteristics of converters to actively support grid frequency and voltage. However, GFM-based converters are often required to generate short-circuit currents in excess of the rated value to support grid voltage recovery during transient faults, which poses a greater challenge to their electro-thermal stresses. At the same time, the over-issuance of short-circuit current will lead to the aggravation of junction temperature fluctuation, which will shorten the lifetime of the power devices and bring new challenges to their reliability. Based on the above problems, this paper firstly establishes a corresponding electrothermal coupling model for the GFM converter synchronized based on DC voltage. Subsequently, an active thermal control technique based on the adaptive adjustment of switching frequency is proposed, which can not only reduce the junction temperature of the power device under the same short-circuit current amplitude, but also further reduce the junction temperature fluctuation of the power device. Finally, the corresponding circuit as well as thermal circuit models are established by simulation software to verify the effectiveness of the strategy.

关键词： Adaptation models Fluctuations Switching frequency Short-circuit currents control systems Temperature control Junctions Transient analysis Voltage control Grid forming

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Multi-parameter load sensing pump model simulation and flow rate characteristics research

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Chinese Journal of Aeronautics 2022年第12期35卷 296-308页

作者： ZongXia JIAO Zhenyu WANG Xiaochao LIU HuJiang WANG Pengyuan QI Weizhi QIAO School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Research Institute for Frontier Science Beihang UniversityBeijing100083China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Science and Technology on Vehicle Transmission Laboratory China North Vehicle Research InstituteBeijing 100072China Ningbo Institute of Technology Beihang UniversityNingbo 315800China

Load sensing pumps have been widely used in diverse hydraulic *** show that structural parameters have undeniable impacts on the characteristics and efficiency of the load sensing *** main purpose of this article is to study the influence of load sensing pump structure parameters on flow *** the present study,a nonlinear multi-parameter model is proposed for this type of *** this model,different parameters,including spool clearance,spool covering amount,internal leakage are considered to reflect the displacement adjustment process of the load sensing ***,a frequency sweep method is proposed to analyze the frequency domain of the nonlinear mathematical *** experiment rig was built to study the influence of key structural parameters on the dynamic follow-up characteristics of the pump *** obtained results show that the diameter of the orifice d can significantly affect the working characteristics of the *** is found that a large diameter of the orifice d can improve the phase following ability of the system,while a small diameter of the orifice d can reduce the bypass flow rate and increase the amplitude following *** paper provides a new consideration to study the dynamic follow-up characteristics of the load sensing pump.

关键词： Flow rate characteristics Frequency analysis Hydraulic Load sensing pump Nonlinear

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Non-Iterative Solution for Coordinated Optimal Dispatch via Equivalent Projection-Part I: Theory

arXiv

引用

arXiv 2023年

作者： Tan, Zhenfei Yan, Zheng Zhong, Haiwang Xia, Qing The Key Laboratory of Control of Power Transmission and Conversion Shanghai Jiao Tong University Ministry of Education Shanghai200240 China The State Key Laboratory of Power Systems the Department of Electrical Engineering Tsinghua University Beijing100084 China

Coordinated optimal dispatch is of utmost importance for the efficient and secure operation of hierarchically structured power systems. Conventional coordinated optimization methods, such as the Lagrangian relaxation and Benders decomposition, require iterative information exchange among subsystems. Iterative coordination methods have drawbacks including slow convergence, risk of oscillation and divergence, and incapability of multi-level optimization problems. To this end, this paper aims at the non-iterative coordinated optimization method for hierarchical power systems. The theory of the equivalent projection (EP) is proposed, which makes external equivalence of the optimal dispatch model of the subsystem. Based on the EP theory, a coordinated optimization framework is developed, where each subsystem submits the EP model as a substitute for its original model to participate in the cross-system coordination. The proposed coordination framework is proven to guarantee the same optimality as the joint optimization, with additional benefits of avoiding iterative information exchange, protecting privacy, compatibility with practical dispatch scheme, and capability of multi-level problems. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Non-Iterative Solution for Coordinated Optimal Dispatch via Equivalent Projection-Part II: Method and Applications

arXiv

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arXiv 2023年

This two-part paper develops a non-iterative coordinated optimal dispatch framework, i.e., free of iterative information exchange, via the innovation of the equivalent projection (EP) theory. The EP eliminates internal variables from technical and economic operation constraints of the subsystem and obtains an equivalent model with reduced scale, which is the key to the non-iterative coordinated optimization. In Part II of this paper, a novel projection algorithm with the explicit error guarantee measured by the Hausdorff distance is proposed, which characterizes the EP model by the convex hull of its vertices. This algorithm is proven to yield a conservative approximation within the prespecified error tolerance and can obtain the exact EP model if the error tolerance is set to zero, which provides flexibility to balance the computation accuracy and effort. Applications of the EP-based coordinated dispatch are demonstrated based on the multi-area coordination and transmission-distribution coordination. Case studies with a wide range of system scales verify the superiority of the proposed projection algorithm in terms of computational efficiency and scalability, and validate the effectiveness of the EP-based coordinated dispatch in comparison with the joint optimization. Copyright © 2023, The Authors. All rights reserved.

关键词： Computational efficiency

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Wind power Generation Capacity Evaluation Based on Correlation Analysis of Adjacent Wind Farms

Wind Power Generation Capacity Evaluation Based on Correlati...

引用

2021 IEEE Sustainable power and Energy Conference, iSPEC 2021

作者： Sun, Shuxin Qiao, Ying Lu, Zongxiang Ma, Yanhong Tsinghua University State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Beijing100084 China State Grid Gansu Electric Power Company Wind Power Technology Center Lanzhou730050 China

ISBN: (纸本)9781665414395

Accurate assessment of the power generation capacity of the wind farm is the key basis for incorporating it into power system scheduling and other optimizing operation activities. Traditional evaluation methods, such as benchmarking wind turbine method, have higher requirements for input data, but many wind farms in operation for many years are difficult to meet such data conditions. A new power generation capacity evaluation method based on correlation analysis of adjacent wind farms is proposed in this paper. Meteorological data and power of adjacent wind farms are used as replaced input data based on correlation analysis between the target farm with its adjacent farms. First, anticipate wind speed data and then construct the wind power curve with three different neural networks to evaluate power generation capacity. Afterwards, adjacent wind farms are used as data sources to fit the power data of the target wind farm with the application of influence radius method, inverse square distance method and bilinear interpolation method. Finally, combined with data in the actual case, investigate the advantages and disadvantages of different methods in the evaluation of power generation capacity. © 2021 IEEE.

关键词： Time delay

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Review and Reflection on New Energy Participating in Electricity Spot Market Mechanism

Review and Reflection on New Energy Participating in Electri...

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2021 IEEE Sustainable power and Energy Conference, iSPEC 2021

作者： Wang, Xiangyan Peng, Peipei Chen, Ning China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy Storage Systems Nanjing210003 China

ISBN: (纸本)9781665414395

In the context of global energy transition, China's new energy sources continue to develop rapidly, and the new round of electricity reform puts forward important requirements on how to design reasonable mechanisms to promote the consumption of new energy sources. This paper compares and summarizes the market mechanisms for promoting new energy consumption in mature foreign electricity spot markets, such as those in the United states, Australia and Northern Europe. Then it introduces the characteristics of the construction of electricity spot markets and related mechanisms for promoting new energy consumption in eight pilot provinces in China. By comparing the current situation of the development of spot markets for new energy participation at home and abroad, and combining the challenges faced by the construction of domestic electricity spot markets at present, suggestions are made to promote the construction of markets for new energy consumption in China. © 2021 IEEE.

关键词： Energy utilization

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