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Self-Triggered Consensus-Based Strategy for Economic Dispatch in Uncertain Communication Networks

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第6期11卷 6652-6663页

作者： Ji, Lianghao Dou, Yuhe Zhang, Cuijuan Li, Huaqing Chongqing Univ Posts & Telecommun Chongqing Key Lab Image Cognit Chongqing 400065 Peoples R China Chongqing Univ Posts & Telecommun Sch Comp Sci & Technol Chongqing 400065 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

The communication networks of smart grids are often influenced by ubiquitous uncertainty. These uncertainties can directly influence the communication weights between generating units, consequently degrading the performance of economic dispatch (ED) algorithms. Despite this, much of the related work has been centered on ideal communication channels, thereby overlooking the impact of communication uncertainties. Consequently, this paper primarily delves into the economic dispatch problem (EDP) in smart grids with uncertain communication networks. Initially, we propose an adaptive algorithm grounded on an event-triggered strategy. This algorithm can effectively offset the communication uncertainties within a predefined upper limit, thereby facilitating optimal power allocation. Subsequently, we introduced a new self-triggered strategy. This strategy eliminates the need for continuous monitoring of neighboring statuses, leading to a reduction in controller updates and message transmissions, without negatively affecting the system's convergence performance. However, the effectiveness of the self-triggered strategy might be influenced by the accuracy of generator predictions. Finally, simulations demonstrate that the proposed approach effectively mitigates the impact of communication uncertainties on ED performance while reducing communication overhead.

关键词： Generators Uncertainty Costs Communication networks Smart grids Prediction algorithms Monitoring adaptive algorithm economic dispatch smart grid self-triggered control uncertain communication

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Water quality parameters inversion based on multispectral remote sensing

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JOURNAL OF WATER PROCESS ENGINEERING 2025年 73卷

作者： Yu, Yinshan Ding, Ping Bian, Haiyi Wei, Jinsong Zhang, Hui Huaiyin Inst Technol Jiangsu Engn Res Ctr Lake Environm Remote Sensing Huaian Peoples R China Huaiyin Inst Technol Fac Elect Informat Engn Huaian Peoples R China

To address the challenges of non-real-time monitoring and high manpower consumption in lake pollution management, this paper proposes an innovative framework integrating multispectral remote sensing technology with intelligent water quality prediction. Focusing on Hongze Lake, we establish inversion models for total phosphorus (TP) and total nitrogen (TN) through systematic spectral data acquisition coupled with outlier correction and standardized preprocessing. The adaptive boosting (AdaBoost) algorithm, Kepler optimization algorithm (KOA), and genetic algorithm (GA) are used to optimize the predictive ability of the random forest (RF) algorithm for total phosphorus and total nitrogen content. Experimental results demonstrate that these three improved models outperform conventional random forest models in predicting water quality. Notably, the KOARF model exhibits superior predictive performance (R2 = 0.94 +/- 0.02), followed by the A-RF model and GA-RF model. The proposed improved algorithms prove feasible for water quality prediction with promising predictive accuracy. These advancements provide critical algorithmic support for developing integrated space-air-ground lake monitoring systems.

关键词： Water quality detection Multispectral remote sensing Random forest Kepler optimization adaptive algorithm Genetic optimization

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Computer graphics processing technology based on GIS model and its application

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SYSTEMS AND SOFT COMPUTING 2024年 6卷

作者： Ji, Quanpeng Chongqing Univ Arts & Sci Sch Math & Artificial Intelligence Yongchuan 402160 Peoples R China

Image processing technology is extensively utilized in various domains of life and production and has been extensively researched. The conventional methods of image processing are incapable of reflecting image data comprehensively whilst ensuring rapid image processing. The study employs a computer graphics processing technique that combines enhanced neural network and geographic information system, aiming to enhance the swiftness and accuracy of extracting picture information. The study categorizes graphic processing into two parts: image acquisition and image information processing. It utilizes an enhanced convolutional neural network algorithm that integrates adaptive algorithms to improve precision and productivity of the image acquisition component. Subsequently, it enhances the throughput and processing speed of the information processing module through a geographic information system. The study findings demonstrate that the GIS-based computer graphics processing technology achieves complete calculation accuracy for one-dimensional images. Moreover, the calculation accuracy for two-dimensional and three-dimensional images is maintained at over 85 %. Adopting the GIS system for graphic processing work can enhance the calculation accuracy of the graphic processing technology. Improving the technology for graphics processing to maintain recognition of over 90 % can guarantee superior image processing capabilities.

关键词： Geographic information system Image processing Convolutional neural network adaptive algorithm Fexp activation function

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Improving the Energy Efficiency of the Environmental Monitoring System Through the Use of adaptive algorithms

Improving the Energy Efficiency of the Environmental Monitor...

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IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)

作者： Volkova, Elena Solodkov, Alexey Nevarov, Pavel Baskakov, Alexandr Sevryukova, Elena A. Natl Res Univ Elect Technol MIET Inst Adv Mat & Technol AMT Moscow Russia Natl Res Univ Elect Technol MIET Telecommun Syst Dept Moscow Russia Russian Univ Transport MIIT Dept Transport Infrastruct Management Syst Moscow Russia

ISBN: (纸本)9781665404761

Modern environmental monitoring systems are distributed systems, often with the integration of automated data collection and transmission processes. This approach allows to reduce the measurement error by eliminating the human factor, but sets a number of tasks to improve the efficiency of the system devices, including power consumption. The main consumer of energy in the device is the radio transmitter module. The article presents the calculations of the required energy for data transmission, depending on the selected parameters of the LoRaWAN radio module and the device operation algorithm, an estimate of the device operation time when using various transmission algorithms. With the introduced restrictions, the calculated benefit of the required energy for the transmission of one bit of information is up to 26% when choosing the optimal parameters of the transmitter and up to four times the operating time of the device from the battery with using varios depeloped algorithm of data forming and transmission.

关键词： enviroment monitoring system adaptive algorithm enegry efficiency algorithm

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An edgewise iterative scheme for the discontinuous Galerkin method with Lagrange multiplier for Poisson's equation

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NUMERICAL algorithmS 2025年 1-38页

作者： Kim, Mi-Young Shin, Dongwook Inha Univ Dept Math Inchon 22212 South Korea Ajou Univ Dept Math Suwon 16499 South Korea

An edgewise iterative scheme is developed for large systems of equations resulting from the discretization by the discontinuous Galerkin method with Lagrange multiplier for the Poisson's equation. The solution is computed element by element. Lagrange multiplier is edgewise updated, which is given as the average of the Robin type information on the elements sharing the edge. Analysis of the convergence of the scheme is given with the discrete maximum norm over all the edges. Several numerical experiments are presented.

关键词： Elliptic problem Edgewise iterative scheme Linear solver Discontinuous Galerkin method with Lagrange multiplier High order approximation adaptive algorithm

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RLS adaptive filter co-design for de-noising ECG signal

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RESULTS IN ENGINEERING 2024年 24卷

作者： Mahmood, Ahlam Fadhil Awny, Safaa N. Alameer, Ali Univ Mosul Dept Comp Engn Mosul Iraq Univ Mosul Coll Pharm Mosul Iraq Univ Salford Sch Sci Engn & Environm Salford England

Doctors diagnose various heart muscle disorders by continuously analyzing ELECTROCARDIOGRAM (ECG) signals. Obtaining a noise-free ECG recording is difficult due to various types of interference, making an effective filter essential for accurate diagnosis. This paper introduces a novel, low-complexity filter designed to enhance ECG signal quality. The proposed method involves partitioning the implementation of the Recursive Least Squares (RLS) adaptive filter between a Microblaze soft processor and hardware resources within a Field Programmable Gate Array (FPGA). The hardware component is responsible for creating a Finite Impulse Response (FIR) filter, while the adaptive processing is handled by the soft processor. This configuration makes the filter adaptable, allowing it to work with various algorithms for a wide range of applications. The co-design was tested for ECG noise removal, achieving an average Signal-to-Noise Ratio (SNR) improvement of 89.78 %. Offloading adaptive tasks to the soft processor reduced power consumption by 56.2 %, making it suitable for integration with ECG sensors in wearable body networks.

关键词： Electrocardiogram adaptive algorithm Co-design FPGA Soft processor

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Co-estimation of state-of-charge and state-of-temperature for large-format lithium-ion batteries based on a novel electrothermal model

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Green Energy and Intelligent Transportation 2024年第4期3卷 23-38页

作者： Chao Yu Jiangong Zhu Wenxue Liu Haifeng Dai Xuezhe Wei School of Automotive Studies Tongji UniversityShanghai201804China Clean Energy Automotive Engineering Center Tongji UniversityShanghai201804China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing400044China

The safe and efficient operation of the electric vehicle significantly depends on the accurate state-of-charge(SOC)and state-of-temperature(SOT)of Lithium-ion(Li-ion)*** the influence of cross-interference between the two states indicated above,this study establishs a co-estimation framework of battery SOC and *** framwork is based on an innovative electrothermal model and adaptive estimation *** first-order RC electric model and an innovative thermal model are components of the electrothermal ***,the thermal model includes two lumped-mass thermal submodels for two tabs and a two-dimensional(2-D)thermal resistance network(TRN)submodel for the main battery body,capable of capturing the detailed thermodynamics of large-format Li-ion ***,the proposed thermal model strikes an acceptable compromise between the estimation fidelity and computational complexity by representing the heat transfer processes by the thermal ***,the adaptive estimation algorithms are composed of an adaptive unscented Kalman filter(AUKF)and an adaptive Kalman filter(AKF),which adaptively update the state and noise *** the estimation results,the mean absolute errors(MAEs)of SOC and SOT estimation are controlled within 1%and 0.4°C at two temperatures,indicating that the co-estimation method yields superior prediction performance in a wide temperature range of 5–35°C.

关键词： Large-format Li-ion battery Electrothermal model SOT estimation SOC estimation adaptive algorithm

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A Novel Vector-Decomposition-Based Structure for Enhancing the Normalized Filtered-X Least Mean Square algorithm Under the High-Power Low-Frequency Noise

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JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES 2024年第2期12卷 2219-2230页

作者： Zhou, Zhengdao Chen, Shuming Zhang, Zhang Jilin Univ State Key Lab Automot Simulat & Control Changchun 130022 Peoples R China Jilin Univ Chongqing Res Inst Chongqing 401123 Peoples R China

PurposeThe normalized filtered-x least mean square (NFxLMS) algorithm adopts a normalized step size to improve the convergence and reduce the gradient noise caused by the high-power input signal. However, this normalization would introduce an even larger misadjustment than the FxLMS algorithm when this high-power noise is in a low-frequency range. To improve the performance of the NFxLMS algorithm in such an environment, a novel vector-decomposition-based structure (VDBS) is proposed in the *** this study, the filter weight vector is decomposed into two sub-vectors that are updated by different algorithms. The first sub-vector is updated by the NFxLMS algorithm, whereas the second one is updated by the FxLMS algorithm. In this way, the total misadjustment can be minimized by setting relevant parameters appropriately, while a faster convergence rate and smaller round-off errors can also be *** stability analysis proves that the proposed structure can enlarge the convergence range of the step size in the first sub-vector. The results of simulations and experiments justify that the VDBS can improve the performance of the NFxLMS algorithm for high-power low-frequency *** proposed structure can make the traditional NFxLMS algorithm perform better in a high-power low-frequency noise environment.

关键词： Active noise control adaptive algorithm Normalized step size Misadjustment Vector decomposition

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Modified LMS synchronization technique for distributed energy resources with DC-offset and harmonic elimination capabilities

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ISA TRANSACTIONS 2023年 135卷 567-574页

作者： Saxena, Hemant Singh, Alka Chittora, Prakash SRM Inst Sci & Technol Delhi NCR Campus Modinagar Uttar Pradesh India Delhi Technol Univ Dept Elect Engn Delhi India

Grid synchronization techniques are needed to improve the distribution system's power quality with the Shunt Active Power Filter (SAPF). The traditional synchronization technique or the Phase Locked Loop (PLL) works well under ideal grid conditions;however, its performance deteriorates under non -ideal grid conditions. In this paper, a new scheme has been proposed to function as PLL. The Modified Least Mean Square (MLMS)-PLL has been proposed for tracking the phase angle under non-ideal grid conditions such as phase shift, frequency deviation, harmonics in the signal, DC offset and combinations of these grid voltage issues. The proposed method has added the advantage of DC-offset estimation and perfect synchronization template generation over conventional PLL. The MLMS-PLL algorithm precisely estimates phase, amplitude and frequency information and generates a synchronizing signal under abnormal grid conditions. The designed algorithm is extensively tested and shows advantages such as least steady-state error, faster dynamics and DC-offset rejection capability. Experimental findings of the proposed synchronizing technique show the effectiveness of the proposed technique and experimental results are also compared with other modern synchronization techniques. The application of MLMS-PLL for synchronization, reactive power compensation and harmonic elimination in a grid-tied PV system has been validated in the experimental prototype.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Synchronization Phase-locked loops DC-offset adaptive algorithm

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A block-randomized stochastic method with importance sampling for CP tensor decomposition

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ADVANCES IN COMPUTATIONAL MATHEMATICS 2024年第2期50卷 22-22页

作者： Yu, Yajie Li, Hanyu Chongqing Univ Coll Math & Stat Chongqing 401331 Peoples R China

One popular way to compute the CANDECOMP/PARAFAC (CP) decomposition of a tensor is to transform the problem into a sequence of overdetermined least squares subproblems with Khatri-Rao product (KRP) structure involving factor matrices. In this work, based on choosing the factor matrix randomly, we propose a mini-batch stochastic gradient descent method with importance sampling for those special least squares subproblems. Two different sampling strategies are provided. They can avoid forming the full KRP explicitly and computing the corresponding probabilities directly. The adaptive step size version of the method is also given. For the proposed method, we present its theoretical properties and comprehensive numerical performance. The results on synthetic and real data show that our method is effective and efficient, and for unevenly distributed data, it performs better than the corresponding one in the literature.

关键词： CP decomposition Importance sampling Stochastic gradient descent Khatri-Rao product Randomized algorithm adaptive algorithm

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