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Water Management optimization in Agriculture: a Digital Model Development

WATER RESOURCES MANAGEMENT 2025年第3期39卷 1261-1279页

作者： Preite, Luca Solari, Federico Vignali, Giuseppe Univ Parma Dept Engn Ind Syst & Technol Parco Area Sci 181-A I-43124 Parma Italy

Water scarcity is one of 21st century's most pressing global issues. The anthropogenic pressure and climate change will be the main drivers of freshwater depletion in the coming decades. According to the FAO, the amount of water needed to support all human activities will be 20-30% higher by 2050. A closer look reveals how agriculture is a major contributor to water scarcity, with irrigation accounting for 70% of global water use. In this framework, the development of effective water management approaches is a key solution to turn the tide and change current patterns. Despite that, there still exists a gap in the scientific literature in the development and validation of innovative water management strategies using advanced technologies. This study aims to address this gap by developing a digital model of a real irrigation network able to accurately predict the water distribution across the network at different operating conditions. A living lab was used for the experimental activities, where a low-power wide-area network was used to acquire data from the system. For modeling purposes, the integration of the 1-D and 3-D simulation was leveraged to fluid-dynamically characterize all the components involved. The numerical model resulted to be accurate in predicting both pressure and velocity patterns (determination coefficient higher than 93%). The proposed model could be considered a starting point for the implementation of a digital twin to support agricultural water management in both the design and management of an irrigation network by defining the correct network configuration and detect anomalous conditions.

关键词： Water management Agriculture 4.0 Digital twin Fluid dynamic simulation

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Power Quality Governance strategy of Active Distribution Network Based on Multi-phase Optimal Power Flow 21

Power Quality Governance Strategy of Active Distribution Net...

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21st International conference on Harmonics and Quality of Power

作者： Xie, Yuzhe Xu, Jiayu Duan, Jiaqi Song, Peiru Zhou, Xiang Wang, Yang State Grid Zhejiang Elect Power Co Ltd Ningbo Key Lab Digital Phys Hybrid Simulat New Po Ningbo Zhejiang Peoples R China Sichuan Univ Coll Elect Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9798350382570;9798350382563

In recent years, due to the large-scale integration of distributed energy sources in active distribution networks, severe over-voltage issues have emerged. A common solution is to install reactive power compensation devices, but the application scenarios of these devices are limited. With the widespread application of energy storage and electric vehicles in distribution networks, the active power output of energy storage systems and the V2G (Vehicle-to-Grid) interaction of electric vehicles not only address issues like peak shaving and valley filling, but also the reactive power and harmonic current output by their grid-connected inverters, when capacity permits, can be used to compensate the voltage quality of the distribution network. Therefore, this paper proposes a power quality management strategy for active distribution networks based on the collaborative optimization of energy storage systems and electric vehicles. This is achieved by establishing an Optimal Power Flow (OPF) model. Additionally, an Immune Comprehensive Learning Particle Swarm optimization (ICLPSO) algorithm is used to optimize and determine the reactive power output of energy storage systems and electric vehicles. Finally, taking the voltage issues of the IEEE 162-node distribution network with distributed PV as an example, the effectiveness of the proposed management strategy is verified.

关键词： Active distribution network energy storage system electric vehicle OPF ICLPSO

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Proceedings - 2024 21st International conference on Harmonics and Quality of Power, ICHQP 2024

Proceedings - 2024 21st International Conference on Harmonic...

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21st International conference on Harmonics and Quality of Power, ICHQP 2024

ISBN: (纸本)9798350382563

The proceedings contain 154 papers. The topics discussed include: a harmonic phase reshaping control strategy for minimizing secondary harmonic injection in DC microgrids;topology reconstruction of fully blind power distribution networks using natural transient disturbances;adaptive power system protective relays based on multi-agent system combined with conservative power theory for highly penetrated renewable energy resources;research on novel three-level DC/DC converter with energy transfer function and bipolar DC voltage control strategy;a harmonic level estimation method driven by accessible basic electricity data;power quality disturbance identification based on optimized VMD and CNN-BiGRU;and frequency-domain harmonic modeling of a six-pulse rectifier under various power supply conditions.

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Dynamic Gaussian Mutation Particle Swarm optimization for Accurate Adaptive Latent Factor Analysis 21

Dynamic Gaussian Mutation Particle Swarm Optimization for Ac...

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21st International conference on Networking, Sensing and Control, ICNSC 2024

作者： Ma, Ziwen Cheng, Jingna Lvu, Chao College of Computer and Information Science Southwest university Chongqing400715 China

ISBN: (纸本)9798350365221

The latent factor analysis (LF A) is an important and effective matrix decomposition model which has important applications in recommendation system. Traditional LFA models based on the stochastic gradient descent (SGD) algorithm are difficult to adjust the learning rate which is a critical parameter in the model training process. To address this problem, the particle swarm optimization (PSO) algorithm is often used to adjust the learning rate of LFA model due to its powerful global search ability. However, the standard PSO algorithm easily falls into a local optimal solution, causing accuracy loss. In this paper, the dynamic PSO based on Gaussian mutation (DG-PSO) is innovatively proposed by incorporating the elite particle selection strategy to improve its convergence speed and accuracy. Then the DG-PSO based LFA (DGPL) model is constructed by employing the DG- PSO to adaptively tune the learning rate of SGD in the training process. The proposed model is tested on dataset and compared with the state-of-the-art models. Experimental results show that the proposed DGPL is superior than existing LFA models. © 2024 IEEE.

关键词： stochastic systems

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Investigation of PDMS-CNT Nanocomposite for Flexible Interconnects 21

Investigation of PDMS-CNT Nanocomposite for Flexible Interco...

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21st International Multi-conference on systems, Signals and Devices, SSD 2024

作者： Attaoui, Ahmed Rajendran, Dhivakar Rosolen, Jose Mauricio Kanoun, Olfa University of Technology Chemnitz Germany Chemnitz University of Technology Germany University of Sao Paulo FFCLRP Department of Chemistry Ribeirao Preto Brazil

ISBN: (纸本)9798350374131

In this study, novel strategies are being explored to enhance composite material for flexible interconnects, particularly for temperature sensors in battery housing system applications. The study investigates the influence of material composition and fabrication process optimization on the electrical properties of the nanocomposites. The study aims to compare the effects of different amounts of carbon nanotubes (CNTs) in the PDMS matrix and the introduction of CB and graphene into CNT/PDMS composite. Analyzing the influence of carbonaceous material ratios on conductivity under different fabrication parameters. Composite homogeneity is assessed, and resistance is measured across a temperature range of 30°C to 70°C. In addition, stability analysis is performed to study the resistance changes over time in the nanocomposite thin film. This comprehensive investigation is aimed to improve the understanding of these materials and their suitability for various applications, including interconnects for temperature sensors in battery housing, with the goal of improving the safety, reliability and lifetime of energy storage systems. © 2024 IEEE.

关键词： optimization

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Route optimization for UAV-to-UAV Communication systems Leveraging Throughput and Energy Consumption 21

Route Optimization for UAV-to-UAV Communication Systems Leve...

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21st Mediterranean Communication and Computer Networking conference (MedComNet)

作者： Xu, Mingzhi Xu, Haowen Wu, Kuan Chen, Jianchao Jiang, Ming Sun Yat Sen Univ Sch Elect & Informat Technol Sch Microelect Guangzhou 510275 Peoples R China

ISBN: (纸本)9798350338843

In the development of fifth-generation (5G) networks, the unmanned aerial vehicle (UAV) technology has recently attracted increasing research attention, where UAV-to-UAV (U2U) communication is found to be one of the promising technical trends. In this work, we propose a U2U communication model for the so-called generalized out-of-coverage (OOC) scenario, where the conventional terrestrial cellular network infrastructure is not available and the satellite network access is highly limited. Specifically, we formulate a problem to jointly optimize the system throughput (stP) and the system propulsion energy (SPE), by taking into account the UAVs' positions and travel time durations. To solve this complicated joint optimization problem, we first build the corresponding model and then design a successive convex approximation (SCA) based joint stP and SPE optimization (SJSSO) algorithm as the solution. Simulation results show that the new SJSSO scheme outperforms its counterpart in several aspects, exhibiting a promising potential for supporting future U2U communications in OOC scenarios.

关键词： UAV-to-UAV communication air route optimization successive convex approximation.

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Multi-robot Cooperative Localization with Single UWB Error Correction 21

Multi-robot Cooperative Localization with Single UWB Error C...

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21st International conference on Ubiquitous Robots (UR)

作者： Marsim, Kevin Christiansen Choi, Junho Jeong, Myeongwoo Ryoo, Kihwan Kim, Jeewon Kim, Taehyun Myung, Hyun KAIST Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon 34141 South Korea

ISBN: (纸本)9798350361087;9798350361070

Deployment of multiple robots in real-world scenarios requires simultaneous information exchange from all platforms to ensure effective task performance. The robot's relative position to its peers is an important data needed to predict collision between robots or task distribution. This paper introduces a robust and simple method for achieving cooperative localization among multiple robots, utilizing a single ultra-wideband (UWB) sensor for each platform. Each robot uses a visual-inertial odometry (VIO) system to track its own trajectory. Given the inherent drift associated with VIO systems, we leverage UWB data to estimate and correct this drift, enhancing each robot's localization accuracy. Our approach substantially improves the result compared with other cooperative localization methods and can even correct the VIO ego-motion.

关键词： cooperative localization multi-robot sensor fusion error-based optimization ultra-wideband (UWB) drift correction

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Adaptive Channel modeling with Conditional Generative Adversarial Network for 209-GHz Fiber-Terahertz Integrated Communication system 21

Adaptive Channel Modeling with Conditional Generative Advers...

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21st International conference on Optical Communications and Networks, ICOCN 2023

作者： Wang, Chengxi Tao, Li Li, Zhongya Shi, Jianyang Chi, Nan Zhang, Junwen China Fudan University Shanghai Erc of Leo Satellite Communication and Applications Shanghai Cic of Leo Satellite Communication Technology Shanghai200433 China Stec Lab Csddc Wuhan430000 China

We propose and experimentally demonstrate an adaptive wave-to-wave level channel-modeling method based on conditional generative-adversarial-network (CGAN) for the 209-GHz fiber-THz integrated communication system, ac... 详细信息

ISBN: (纸本)9798350343502

关键词： Generative adversarial networks

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Improving Electrically Evoked Compound Action Potential based on Electrical Field Imaging and Electrode Interfaces 21

Improving Electrically Evoked Compound Action Potential base...

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IEEE 21st Biennial conference on Electromagnetic Field Computation (IEEE CEFC)

作者： Choi, Charles T. M. Ke, Chun Ting Lawrence, Jelani Wang, Alexander C. C. Natl Yang Ming Chiao Tung Univ Coll Elect & Comp Engn Dept Elect & Elect Engn Hsinchu 30010 Taiwan Natl Yang Ming Chiao Tung Univ Coll Elect & Comp Engn Inst Elect & Control Engn Hsinchu 30010 Taiwan Natl Yang Ming Chiao Tung Univ Coll Elect & Comp Engn Inst Biomed Engn Hsinchu 30010 Taiwan Natl Yang Ming Chiao Tung Univ Coll Elect & Comp Engn Elect Engn & Comp Sci Int Grad Program Hsinchu 30010 Taiwan

ISBN: (纸本)9798350348958;9798350348965

The electrically evoked compound action potential (ECAP) has been used in various clinical studies and has become a key physiological signal for cochlear implants (CI). This study used four sensing electrodes to record ECAP signals based on the alternating polarity approach. An electrical field imaging (EFI) result based on the finite element method was used to obtain the interface impedance, then ECAP simulation results were computed and compared with a patient's clinical ECAP measurements. Preliminary modeling results show that the interface impedance obtained by this EFI-based technique can improve the simulation accuracy of the ECAP model. The ECAP modeling result will be compared with clinical ECAP measurements to validate the model in the full paper.

关键词： cochlear implants auditory nerve electrical field imaging optimization electrically evoked compound action potential finite element method

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2023 21st International conference on Advanced Robotics, ICAR 2023

2023 21st International Conference on Advanced Robotics, ICA...

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21st International conference on Advanced Robotics, ICAR 2023

ISBN: (纸本)9798350342291

The proceedings contain 96 papers. The topics discussed include: early and accurate detection of tomato leaf diseases using TomFormer;evaluating visual-selective visual-inertial odometry: an end-to-end multi-modal pose estimation framework for underwater environments;path planning for autonomous inland vessels in complex harbor environments;modeling, optimization, and musculoskeletal simulation of elbow-wrist exosuit;learning complicated manipulation skills via deterministic policy with limited demonstrations;visual tracking nonlinear model predictive control method for autonomous wind turbine inspection;a deep reinforcement learning decision-making approach for adaptive cruise control in autonomous vehicles;subgoal-driven navigation in dynamic environments using attention-based deep reinforcement learning;and fast and accurate tactile object recognition using a random convolutional kernel transform.

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