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Research on Indirect Air-Cooled Cold-End optimization System Based on ICS Platform

Research on Indirect Air-Cooled Cold-End Optimization System...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International conference on

作者： Haibin Liu Lin Gao Peng Chang Jiachen Cai Mengyao Sun Qiang Ma Dongming Li Zhongxi Huang Lei Dang Xi’an Thermal Power Research Institute Co. Ltd Xi’an China Shaanxi Yanchang Petroleum Fuxian Power Generation Co. Ltd Yan'an China

The cooling performance of an indirect aircooled system heavily depends on the environmental wind speed and temperature. Manual adjustment of shutters by operators significantly impacts the safety, stability, and cost-effectiveness of unit operations. In this paper, a large number of sensors are used to monitor environmental information, and the BP neural network algorithm improved by quantum genetic algorithm is introduced based on the ICS platform to predict the circulating water temperature at the outlet of the cooling tower. According to the historical data and environmental variables, the optimal values of the outlet water temperature is accurately predicted, which as the main parameter to adjust PID for the shutter opening adjustment, so as to automatically control the lowest stable value of the outlet water temperature and obtain the optimal back pressure value. The operation data of the case unit shows that the system can automatically control the parameters of the cooling tower to the optimal level, reduce the labor intensity of the operators, reduce the energy consumption of the unit, and improve the economy and operation stability of the unit.

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Research on Distributed optimization and Dispatch Strategy for Grid-Connected Microgrid Cluster Based on Alternating Direction Method of Multipliers

Research on Distributed Optimization and Dispatch Strategy f...

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Energy, Power and Electrical Technology (ICEPET), International conference on

作者： Qingzhu Wan Chenlu Shi College of Electrical and Control Engineering North China University of Technology Beijing China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

The coordinated optimization of microgrid clusters is an effective way to ensure the reliable operation of microgrid group system. Aiming at the minimum total operation cost of microgrid group, a distributed optimal scheduling strategy based on alternating direction multiplier method is proposed for grid-connected microgrid group. First, a total operating cost model of a microgrid group is established, which includes battery storage operating cost, inter-microgrid power transaction cost, power transaction cost of each microgrid and distribution network, and interactive power fluctuation penalty cost of a common coupling point. Then, the total operating cost model is equivalent to the sub-target of each microgrid by taking advantage of the mutual offset of power transaction costs among microgrids. Taking the interactive power of microgrid as the coupling variable, a distributed solution method based on alternating direction multiplier method is presented. Finally, an example shows that the proposed distributed scheduling method can reach convergence after about 22 iterations, which has good feasibility.

关键词： Couplings Privacy Costs Fluctuations Microgrids Optimal scheduling Carbon dioxide

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Organic-inorganic perovskite-based solar cell designs for high conversion efficiency: A comparative study by SCAPS simulation

Organic-inorganic perovskite-based solar cell designs for hi...

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3rd National conference on Functional Materials (NCFM) - Emerging Technologies and Applications in Materials Science

作者： Kumar, Manish Kumar, Arvind Raj, Abhishek Sati, Prakash Chandra Sahni, Mohit Anshul, Avneesh Univ Delhi ARSD Coll Dept Phys Expt Res Lab New Delhi 110021 India CSIR Natl Environm Engn Res Inst NEERI Nagpur 440020 Maharashtra India Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India Rajiv Gandhi Govt PG Coll Dept Phys Mandsaur 458001 Madhya Pradesh India Sharda Univ SBSR Greater Noida Uttar Pradesh India

Solar energy is the centre of attention and major need of the world. The advancement in the photovoltaic devices plays the key role in the path of solar energy applications. The progress in the perovskite solar cell technologies in the direction of their theoretical power conversion efficiency necessitates elusive control above the carrier dynamics all over the whole device. In the present investigation, a comparative study via SCAPS simulation has been done for the optimization of the device in the light of high power conver-sion efficiency of organic-inorganic perovskite-based photovoltaic solar cells. Perovskite absorber layers CH3NH3PbI3 and CH3NH3SnI3 are sandwiched in between the TiO2 as electron transport layer (ETL) and spiro-OMeTAD as hole transport layer (HTL) to design the hetrostructures for the simulation. We have achieved enhancement in the power conversion efficiencies of both the devices as compared to the reported experimental and theoretical studies previously. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： SCAPS simulation Organic-inorganic perovskite Solar cell Photovoltaics ETL HTL CH3NH3SnI3 CH3NH3PbI3

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A Multi-level Voltage/Var Stochastic optimization Method for Distribution networks Considering Communication Conditions

A Multi-level Voltage/Var Stochastic Optimization Method for...

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Power Systems and Electrical Technology (PSET), IEEE International conference on

作者： Yufeng Wu Songqing Xie Jinyu Chai Wang Liao Xu Wei Fei Chen Jiaming Weng Dong Liu Key Laboratory of Control of Power Transmission and Conversion Shanghai Jiao Tong University Shanghai China Merchant Ship R&D Department Marine Design & Research Institute of China Shanghai China

ISBN: (数字)9798350353204

ISBN: (纸本)9798350353211

Active distribution networks are typical cyber-physical systems, where faults in the cyber system may trigger voltage violations, and uncertainties of renewable energy in the physical system may lead to voltage fluctuations. In light of this, a multi-level voltage/var stochastic optimization method for distribution networks considering communication conditions is proposed. The proposed method achieves optimal coordination of inverters with different communication conditions under the renewable energy uncertainty. In the central level, a stochastic optimization problem is formulated by optimizing the output of inverters with normal communication, which achieves optimal coordination in mathematical form with inverters suffering communication interruption. It is noted that, at the central level, decisions are made for inverters with normal communication, which consider the local adjustment model for inverter suffering communication interruption. At the local level, local terminal decides whether to follow the decisions made at the central level or locally adjust output of inverters based on communication states and voltage violation states. The proposed method is validated in modified IEEE 33-node distribution network.

关键词： Renewable energy sources Uncertainty Voltage fluctuations Fluctuations Stochastic processes optimization methods Distribution networks Inverters Mathematical models Power systems

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Design and Application of Converged Infrastructure through Virtualization Technology in Grid Operation control Center in North Eastern Region of India 3

Design and Application of Converged Infrastructure through V...

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3rd IEEE International conference on Energy, Power and Environment - Towards Clean Energy Technologies (ICEPE)

作者： Suresh, V. Ramesh, M. K. Shadruddin, Sheikh Paul, Tapobrata Bhattacharya, Anirban Ahmad, Abrar POSOCO NERLDC Shillong Meghalaya India

ISBN: (纸本)9781665425360

Modern day grid operation requires multiple interlinked applications and many automated processes at control center for monitoring and operation of grid. Information technology integrated with operational technology plays a critical role in grid operation. Computing resource requirements of these software applications varies widely and includes high processing applications, high Input/Output (I/O) sensitive applications and applications with low resource requirements. Present day grid operation control center uses various applications for load despatch schedule management, various real-time analytics & optimization applications, post despatch analysis and reporting applications etc. These applications are integrated with Operational Technology (OT) like Data acquisition system / Energy management system (SCADA/EMS), Wide Area Measurement System (WAMS) etc. This paper discusses various design considerations and implementation of converged infrastructure through virtualization technology by consolidation of servers and storages using multi-cluster approach to meet high availability requirement of the applications and achieve desired objectives of grid control center of north eastern region in India. The process involves weighing benefits of different architecture solution, grouping of application hosts, making multiple clusters with reliability and security considerations, and designing suitable infrastructure to meet all end objectives. Reliability, enhanced resource utilization, economic factors, storage and physical node selection, integration issues with OT systems and optimization of cost are the prime design considerations. Modalities adopted to minimize downtime of critical systems for grid operation during migration from the existing infrastructure and integration with OT systems of North Eastern Regional Load Despatch Center are also elaborated in this paper.

关键词： design grid operation infrastructure HCI IT OT integration converged infrastructure Power system SCADA/EMS reliability Virtualization WAMS

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ICRACOS 2021 - 2021 3rd International conference on Research and Academic Community Services: Sustainable Innovation in Research and Community Services for Better Quality of Life towards Society 5

ICRACOS 2021 - 2021 3rd International Conference on Research...

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3rd International conference on Research and Academic Community Services, ICRACOS 2021

ISBN: (纸本)9781665443340

The proceedings contain 48 papers. The topics discussed include: investigation of the droplet properties along their trajectory in the cooling tower;schematics monitoring system temperature, PH and turbidity based on LORA (long range) to improve the quality of the harvest;implementation of the arithmetic optimization algorithm for economic load dispatch;user experience evaluation by using a user experience questionnaire (UEQ) based on an artificial neural network approach;the effect of hydraulic diameter variations and distance of rods square profile in rectangular channel;design and build of energy proportional electric folding bike according to rider needs;an investigation of visually impaired learners marginalized in an online classroom environment;and applying decision tree for utility control system on patient room using eye activity command.

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Congestion control of Multi-layer Cellular networks based on Modeling of Transmit Power 3

Congestion Control of Multi-layer Cellular Networks based on...

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2020 3rd International conference on Modeling, Simulation and optimization Technologies and Applications, MSOTA 2020

作者： Dai, Jiahao Chen, Yongqun Chen, Yucheng Meng, Aodong Science and Technology on Communication Information Security Control Laboratory China China Electronic Group Corporation NO.36 Institute Zhejiang Jiaxing China

The explosive growth of network traffic and the limited storage node resources make the existing network architecture bear great pressure, and network congestion appears in work and life from time to time. In order to ensure the timeliness and effectiveness of the network, we propose a congestion control method based on transmission power. Different from previous work, we built a multi-layer cellular network consisting of multiple macro stations, small base stations and mobile terminals. On this basis, we establish a congestion control model based on the mixed queuing model of service window and calculate the input/output rate and congestion. Finally, we use simulation to verify the effectiveness of the congestion model. The network builder can use our model to set the appropriate power of macro stations and small base stations to ensure network stability. © Published under licence by IOP Publishing Ltd.

关键词： Base stations

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Research on Bi-Directional Collaborative Multi-Step Ant Colony optimization for Path Planning

Research on Bi-Directional Collaborative Multi-Step Ant Colo...

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Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR), International conference on

作者： Xufei Chen Yaowei Hu Junhao Li Pingping Tang Hongzhu Xi Xiaoming Liu Linyun Yang Physics and Electronic Information Anhui Normal University Wuhu China Anhui Huadong Photoelectric Technology Research Institute Co. Ltd. Wuhu China

ISBN: (数字)9798331534035

ISBN: (纸本)9798331534042

In swarm intelligence, the ant colony optimization, known for its unique characteristics, e.g., self-organization, distributed nature, and positive feedback, has demonstrated outstanding performance in various fields like path planning, scheduling optimization, and network routing. However, in practical applications, several issues remain, including slow convergence speed, poor flexibility of ants, and susceptibility to local optima. To address these problems, this paper proposes a bi-directional collaborative multi-step ant colony optimization (BC-MSACO) algorithm. Firstly, a forward and reverse dual-population is established using bi-directional ant colony exploration, and an adaptive step-size strategy is employed to overcome the algorithm's local optima and improve the flexibility of ants. Secondly, the algorithm is optimized by using an adaptive ant colony quantity strategy and an improved heuristic function, where the node distance index of the bi-directional ant colony guides the node transfers, accelerating the algorithm's convergence speed. The proposed method is tested through simulations and compared with other path planning algorithms. Results indicate that BC-MSACO achieves fast global convergence, high stability, and shorter computation time.

关键词： Ant colony optimization Technological innovation Heuristic algorithms Simulation Stability criteria Collaboration Bidirectional control Path planning optimization Convergence

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Research on Autonomous Driving Scenario and Decision-making based on Deep Neural network

Research on Autonomous Driving Scenario and Decision-making ...

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International conference on Electronics and Information Technology (EIT)

作者： Daoyi Xiao Yulu Hu Zhiyang He School of Electronics and Control Engineering Chang'an University Xi'an China School of Transportation Engineering Chang'an University Xi'an China School of Information Engineering Chang'an University Xi'an China

ISBN: (数字)9798350369151

ISBN: (纸本)9798350369168

The foundation of autonomous driving safety is high-precision environmental perception. As a mission-critical task, object detection has attracted considerable attention in recent years. It employs a range of sensors to gather data on factors such as target position, size, and direction of movement, thereby providing a crucial foundation for driving decisions. This study employs an enhanced Deep Convolutional Neural network (CNN) to investigate decision-making processes in autonomous driving scenarios, thereby advancing the field of artificial intelligence. The introduction of a multi-scale feature extraction module and a self-attention mechanism serves to enhance the model's capacity for perception of complex traffic environments and recognition of key scenes. The model is capable of efficiently processing sensor data, thereby facilitating accurate scene understanding and real-time decision optimisation. The experimental analysis demonstrates that the enhanced model exhibits superior performance compared to the conventional approach across a spectrum of driving scenarios, thereby enhancing the precision and dependability of decision-making.

关键词： Accuracy Decision making Real-time systems Stability analysis Safety Convolutional neural networks Time factors Autonomous vehicles optimization Intelligent sensors

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Securing IoT-enabled Metaverse with Authentication and Threat Classification Framework Using DL

Securing IoT-enabled Metaverse with Authentication and Threa...

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International Symposium on Advanced Computing and Communication (ISACC)

作者： Krisha Darji Chinmay Trivedi Rajesh Gupta Fenil Ramoliya Sudeep Tanwar Smita Agrawal Dept. of Comp. Science & Engg. Institute of Tech. Nirma University Ahmedabad India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

In the current technological landscape, the rise of Web 3.0 is notable. Alongside this, immersive technologies like Virtual Reality (VR) and Augmented Reality (AR) are gaining increased popularity. This is due to idea like the Metaverse, which is a spatial computing platform that offers virtual experiences replicating real environments. However, Metaverse also faces security vulnerabilities, such as the risk of identity theft, financial fraud, and the damage of virtual assets due to the public openness of the platform. To mitigate these paramount concerns, there has to be a robust user authentication and verification approach before granting access to these domains. We propose a Convolutional Neural networks (CNN)-based approach, i.e., MetaSec, which focuses on analyzing incoming user traffic patterns to identify any anomaly in the Internet of Things (IoT)-enabled Metaverse environment. The performance evaluation of MetaSec has been done using various optimization algorithms such as Stochastic Gradient Descent (SGD), Adam, RMSprop, and Adagrad. The main goal of rigorous assessment is to identify the most effective optimization approach for enhancing virtual network security. Thus, MetaSec proactively uncovers potential susceptibility and minimises the risk of intrusion and harm to critical resources. These hardware and software plug-in ranges from computer systems, networks, databases, websites, and other network-based applications and services applied in the virtual domain.

关键词： Semantic Web Accuracy Metaverse Software algorithms Authentication Traffic control Software Spatial computing Convolutional neural networks optimization

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