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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Zexiang Guan Dongsheng Cai Olusola Bamisile Jian Li Zhenyuan Zhang Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu China

When a high proportion of renewable energy is connected to the grid, the net load fluctuation can be suppressed by configuring energy storage. However, the current cost of energy storage is high. This paper proposes a bi-level optimization model that takes into account the dynamic allocation of shared energy storage (SES) capacity in response to electric load demand. The upper-layer objective function adopts EO optimization algorithm, which is to maximize the income of the shared energy storage operator (SESO). The lower-layer multi-objective function is to minimize the sum of the operating cost and the net load mean square error of multiple microgrids, which can be classified as the mixed integer linear programming problem. Then, the solution flow of the algorithm is given. Finally, under the constraints of the hierarchical optimization-based model, solving the problem by the CPLEX solver on the MATLAB platform. The results demonstrate that the proposed method can allocate optimal capacity and reduce operating costs for microgrids. Simultaneously, this method increases the revenue of SESO and promotes the consumption of renewable energy.

关键词： Renewable energy sources Costs Fluctuations Microgrids Mean square error methods Mathematical models Classification algorithms

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Optimization of Low-carbon Dispatching for Microgrid Based on Improved Particle Swarm Optimization

Optimization of Low-carbon Dispatching for Microgrid Based o...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Huan Yang Dongsheng Cai Olusola Bamisile Jian Li Zhenyuan Zhang Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu China

In the context of carbon neutrality, the power industry is becoming the main battlefield of carbon emission reduction. However, the low-carbon transformation of energy structure is a complex long-term task, it needs to be analyzed in combination with the actual situation. This paper is based on the microgrid in the grid connection mode, considering microgrid power output and carbon emission constraints. An optimal model is proposed to reduce carbon emission cost, the optimal economic operation, and build a low-carbon scheduling model of a microgrid system. In this paper, the improved multi-objective particle swarm optimization algorithm is used to solve the problem. Finally, the simulation results verify the effectiveness of the model and the superiority of the improved algorithm.

关键词： Job shop scheduling Costs Wind energy Heuristic algorithms Optimal scheduling Microgrids System integration

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S$^{\text{4}}$TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第2期9卷 3220-3231页

作者： Xiao Wang Ke Tang Xingyuan Dai Jintao Xu Quancheng Du Rui Ai Yuxiao Wang Weihao Gu Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Haomo Technology Company Ltd. Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S $^{\text{4}}$ TP) framework. Specifically, S $^{\text{4}}$ TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV's planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S $^{\text{4}}$ TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs' trajectories as input. With the integration of SADRF, S $^{\text{4}}$ TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S $^{\text{4}}$ TP in terms of safety and rationality. S $^{\text{4}}$ TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%.

关键词： Trajectory Safety Vehicles Trajectory planning Autonomous vehicles Risk management Behavioral sciences

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A Method for Recognition of Mixed Gas Composition Based on PCA and KNN 19

A Method for Recognition of Mixed Gas Composition Based on P...

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19th International Conference on Optical communications and Networks, ICOCN 2021

作者： Xia, Wanyu Song, Tingting Yan, Zhanwei Song, Kai Chen, Deyun Chen, Yinsheng National Experimental Teaching Demonstration Center for Measurement and Control Technology and Instrumentation Harbin University of Science and Technology Harbin150080 China Postdoctoral Research Station of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781665424462

In the mining process of coal, oil, and natural gas, there are often a large number of toxic, hazardous and explosive gases, which pose a greater safety hazard. These gases usually exist in the form of mixtures. Accurately identifying the composition of the mixed gas is of great significance to the prevention of safety accidents. In order to improve the accuracy of the component recognition of the mixed gas, this paper proposes a mixed gas component recognition algorithm based on the combination of principal component analysis (PCA) and k-nearest neighbor algorithm (KNN). PCA is used to extract the characteristics of the sensor array signal to obtain the characteristic value of the gas, and then KNN is used to realize the recognition of the gas type. The results show that the recognition rate of the feature quantity after dimensionality reduction as input is higher than that before dimensionality reduction. Finally, PCA and KNN algorithm and PCA and support vector machine (SVM) algorithm are compared for the recognition rate of mixed gas. Experimental results show that the proposed method has a recognition rate of 96.88% for mixed gas components. © 2021 IEEE.

关键词： Support vector machines

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A Gas Recognition Method Based on PCA and PSO-LSSVM 19

A Gas Recognition Method Based on PCA and PSO-LSSVM

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19th International Conference on Optical communications and Networks, ICOCN 2021

作者： Song, Tingting Xia, Wanyu Yan, Zhanwei Song, Kai Chen, Deyun Chen, Yinsheng National Experimental Teaching Demonstration Center for Measurement and Control Technology and Instrumentation Harbin University of Science and Technology Harbin150080 China Postdoctoral Research Station of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781665424462

Gases in the real environment always exist in the form of mixtures, and effective identification of gas types to reduce the occurrence of safety incidents has become an important direction in the field of gas analysis research. This paper proposes a mixed gas identification method based on PCA and PSO-LSSVM. This method uses principal component analysis (PCA) to reduce the dimensionality of the sensor array output signal, and uses the Relief algorithm to select data. The particle swarm algorithm is used to iteratively optimize the relevant parameters in the least squares support vector machine model, and the PSO-LSSVM model is constructed to qualitatively analyze the composition of the mixed gas. This article uses a public data set of mixed gases of ethylene, methane and carbon monoxide to conduct experiments. The experimental results show that the method used in this paper can effectively identify the type of mixed gas, and the recognition accuracy rate reaches 91.67%. The method proposed in this paper can provide a research foundation for the follow-up analysis of the mixed gas concentration. © 2021 IEEE.

关键词： Particle swarm optimization (PSO)

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Post-Quantum Privacy-Preserving Provable Data Possession Scheme Based on Smart Contracts

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Wireless communications and Mobile Computing 2023年第1期2023卷

作者： Li, Zhengwen Zhang, Tengjiao Zhao, De Zha, Yaxing Sun, Jun School of Cyberspace Security Beijing University of Posts and Telecommunications 100876 China School of Information Engineering Beijing Institute of Graphic Communication 102600 China Research and Development Center of Transport Industry of Network Security Technologies China Communication Information Technology Group Co. Ltd 100088 China China Industrial Control Systems Cyber Emergency Response Team 100040 China

Provable data possession (PDP) is a crucial means of protecting the integrity of data in the domain of cloud storage. In the post-quantum era, the PDP scheme that uses lattices relies too heavily on the third-party auditor (TPA), which is not entirely trustworthy and is easily affected by a single point of failure. Moreover, the scheme often leads to the leakage of private user data while attempting to satisfy the demand for public verification. In response to the above problems, this paper designs a protocol for post-quantum privacy-preserving PDP and uses it to develop a scheme based on smart contracts. The proposed scheme has the characteristics of being post quantum and can satisfy the demand for public verification while preserving user privacy. The property of noninteraction of the protocol can reduce transaction fees incurred owing to the frequent operation of the blockchain, and the smart contract with a deposit mechanism can ensure fair payments to all parties. The results of a theoretical analysis and experiments show that the proposed scheme is highly secure and efficient. © 2023 Zhengwen Li et al.

关键词： Smart contract

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Two-step Phase Synchronization Algorithm for Distributed Collaborative Beamforming 6

Two-step Phase Synchronization Algorithm for Distributed Col...

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6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Xu, Jianwen Yang, Yi Yang, Yang Zhang, Ling Wang, Jian Zhuang, Jie School of Information and Communication Engineering Chengdu611731 China State Grid Xin Jiang Company Limited Electric Power Research Institute China Precision Measurement Radar System Technology Key Laboratory of Sichuan Province Chengdu611731 China

ISBN: (纸本)9780738133737

Beamforming technology is mainly applied to increase the energy utilization efficiency in wireless communication, and to enlarge signal transmission range via multiantenna technology. The beamforming technology presented in this paper is distributed collaborative beamforming (DCBF) technology, which is a branch of cooperative communication. In this paper, we propose a phase synchronization algorithm to achieve DCBF in a distributed array. The proposed algorithm consists of two steps. First, in order to improve the convergent speed of the phase alignment, we traverse all N possible initial phases of each node to determine a local optimum iteration point. Then we perform two-bit feedback iteration to ensure that the normalized received signal strength (NRSS) reaches the threshold of cooperative beamforming. Numerical results demonstrate that proposed algorithm offers better phase synchronization performance compared with the classical one-bit feedback method and two-bit feedback method. © 2021 IEEE.

关键词： Beamforming

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How Regulatory Orders and Public Fear Affect Vehicle Mobility Under Covid-19: A Global Perspective from Urban Overall Vehicles Using Multisource Data

SSRN

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SSRN 2024年

作者： Tang, Li Tang, Chuanli Luo, Hao He, Zhengbing Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province Xihua University Chengdu China Engineering Research Center of Ministry of Education for Intelligent Air-Ground Fusion Vehicles and Control Xihua University Chengdu China School of Automobile and Transportation Xihua University Chengdu China Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States

As one of the largest pandemics in human history, COVID-19 has dealt a heavy blow to the global economy and social life. Although the pandemic situations in most countries have been stable, lessons are highly needed to learn to get more prepared for the future. In the field of transportation, the impact of COVID-19 on public transit and shared travel has been extensively studied with a relatively consistent conclusion. However, how and why the overall vehicle travel demand (including public and private) changes have not been fully addressed. This paper investigates the impact of COVID-19 on urban overall vehicle mobility as to the magnitude, duration, and driving factors. To this end, the Prophet time series model was introduced to predict vehicle mobility without COVID-19. By comparing the predicted with the real value, the mobility loss was obtained. The causes of the loss were deeply explored by applying multiple linear regression, especially focusing on the interaction effects of the strictness of regulatory orders and public fear. A large-scale dataset with more than 4 billion raw data was built for the empirical analysis from different sources, including a three-year city-level Automatic Number Plate Recognition data and data crawled from websites relating to explanatory variables. Results show that urban vehicle mobility loss almost all occurs during the national outbreak period, which is 29.66%. The factor that represents nationwide confirmed cases has a positive lagging effect on travel mobility loss, and the lag time is around seven days. Loss of urban motorized travel demand is largely caused by the interaction of perceived risks and control policy. The marginal effects of the factors work differently, indicating strong evidence of the existence of caution fatigue and shedding light on the impact mechanism. © 2024, The Authors. All rights reserved.

关键词： Multiple linear regression

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Preface: Security and safety in artificial intelligence

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Security and Safety 2024年第4期3卷 4-5页

作者： Hao Zhang Yu-Gang Jiang Claudio Melchiorri Gerhard Rigoll Department of Control Science and Engineering Tongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Shanghai 201210China School of Computer Science Fudan UniversityShanghai 200433China Department of Electrical Electronic and Information EngineeringUniversity of BolognaBologna 40136Italy Institute for Human-Machine Communication Technical University of MunichMunich 80539Germany

This special topic centers on cutting-edge advancements in the security and safety of artificial intelligence(AI),with a focus on critical applications across domains such as autonomous systems,federated learning,and network *** rapid evolution of AI algorithms,enabled by advances in hardware and software,has led to transformative applications but also revealed significant vulnerabilities and security risks.

关键词： artificial hardware autonomous

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A Novel Edge Computing Based Area Navigation Scheme

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Computers, Materials & Continua 2020年第12期65卷 2385-2396页

作者： Jianzhong Qi Qingping Song Jim Feng School of Information Science and Technology North China University of TechnologyBeijing100144China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Science and Technology on Information Systems Engineering Laboratory Beijing Institute of Control and Electronic TechnologyBeijing100038China Amphenol Global Interconnect Systems San JoseCA 95131USA

The area navigation system,discussed in this paper,is composed of ground responders and a navigation terminal and can position a high-velocity aircraft and measure its *** navigation system is silent at ordinary *** sends out a request signal when positioning is required for an aircraft,and then the ground responders send a signal for resolving the *** the direct sequence spread spectrum and frequency hopping,the concealed communication mode is used in the whole communication process,with short communication pulses as much as possible,so the system has strong concealment and anti-interference *** the transmission delay is apparent in the response communication mode,there is a big error where the common navigation algorithm is used for the positioning and velocity measurement of a high-velocity *** this paper,a new algorithm is proposed,which can eliminate the influence of response communication delay on the positioning of a high-velocity moving target to realize the precise positioning and velocity measurement of a high-velocity aircraft.

关键词： Navigation pseudo-noise code ranging positioning velocity measurement edge computing

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