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Method for controlling phytoplankton distribution in fresh open water

International Journal of Environmental Studies 2024年第5期81卷 2130-2147页

作者： Moldasheva, Raushan Ismailova, Aisulu Turmukhanova, Gulnur Mailybayeva, Aiman Yelezhanova, Shynar Zhanuzakova, Zulfiya Zhamangara, Aizhan Department of Information Systems Faculty of Computer Systems and Vocational Education S. Seifullin Kazakh Agrotechnical University Astana Kazakhstan Department of Software Engineering Faculty of Physics Mathematics and Information Technology Atyrau University named after Kh. Dosmukhamedov Atyrau Kazakhstan Department of Computer Science Faculty of Physics Mathematics and Information Technology Atyrau University named after Kh. Dosmukhamedov Atyrau Kazakhstan Laboratory of Palaeobotany Astana Botanical Garden branch of the Institute of Botany and Phytointroduction Astana Kazakhstan

This paper presents a processed phytoplankton dataset from Lake Zerendi and other Kokshetau Upland lakes, Kazakhstan. The study aimed to develop an automated method for controlling the distribution of phytoplankton in fresh open water using a gradient descent approach with the search for a starting point for research. The paper also presents the reconstructed biomass indicators for changes in water temperature, with model calibration based on results from 5 years of surface sampling. A special feature of the proposed computer data processing is the cubic spline interpolation, which allows a higher calculation accuracy. This method reduces the sample size required, providing a comprehensive picture of the condition of the infrastructure and allowing for a more efficient response to emerging ecosystem issues. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Phytoplankton

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Cyber-HIL Autonomous Inverter-Based Microgrid Framework: Control System Performance and Communication Network Quality of Service

Cyber-HIL Autonomous Inverter-Based Microgrid Framework: Con...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

The integration of communication networks within modern power systems enhances the control of modern power systems; however, it increases the system's complexity. This interdependence raises the need to analyze power systems as cyber-physical systems (CPS). Microgrids (MGs) play a vital role in modern power systems, facilitating sustainable operation while decreasing the reliance on the main grid. Different distributed energy resources can be integrated by utilizing power electronics inverters working under grid-forming mode; this configuration forms the inverter-based autonomous AC microgrids. Droop control as a primary control layer is a wellknown technique that enables power-sharing among the various resources within the inverter-based MG. However, it has a limitation in keeping the system voltage and frequency constant. Thus, a secondary control layer is introduced to compensate for the droop limitations. This paper presents an innovative study that considers the communication network performance while studying the control of MGs through a cyber hardware-in-theloop (Cyber-HIL) autonomous inverter-based MG framework that integrates Opal-rt, network simulator ns-3, and docker containers. The effectiveness of the designed MG system equipped with its primary and the developed centralized secondary control system, in addition to the quality of service (QoS) of the designed communication network emulation, are presented in the experimental results.

关键词： Emulation Microgrids Quality of service Containers Control systems Power systems Communication networks Voltage control Frequency control Load modeling

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Communication Networks-Based Control of Cyber-Physical Microgrids

Communication Networks-Based Control of Cyber-Physical Micro...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

This paper surveys the communication networksbased control of cyber-physical microgrids (MGs), including the different architectures of MGs, the control system, and the communication networks within the MGs. The proposed work introduces an overview of the AC, DC, and hybrid AC/DC architectures, highlighting the challenges in the control systems used for each architecture. Focusing on the hierarchical control structure of MGs, we demonstrate the vital role of communication infrastructure in the resilient control of MGs to coordinate between the primary, secondary, and tertiary layers for achieving the control objective. The requirements for communication networks and their influence on MGs' reliable and secure operation are also presented. We have investigated the impact of communication delays, failures, and packet loss on the control system's performance. This survey offers insights into the effects of communication infrastructure on efficient and robust control of cyber-physical MGs in dynamic energy environments.

关键词： Surveys Robust control System performance Packet loss Microgrids Control systems Delays Communication networks Reliability Resilience

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Container-based Platform for Edge-Computing in Energy System Applications

Container-based Platform for Edge-Computing in Energy System...

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IEEE General Meeting Power& Energy Society

作者： Mahmoud S. Abdelrahman Hossam Hussein Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The design of power systems is growing more complex due to the large-scale building of microgrids and the ongoing advancement of renewable energy technologies. Several management approaches are applied to overcome these issues using cloud computing and the Internet of Things (IoT). However, the security and time delay for long-distance transferring to cloud communication are crucial concerns. Edge computing is a promising technology to address these challenges. Emerging smart energy systems are frequently deployed at the Edge of the power grid to meet the needs of smart grid users and achieve secure, efficient, and low-latency data processing. This paper proposes a container-based platform for Edge computing emulation based on a co-simulation model to implement, test, and validate Edge computing-based energy system applications. In addition, the feasibility of the proposed model is demonstrated by a case study of a consensus control technique based on an Edge computing framework for multi-microgrids.

关键词： Cloud computing Computational modeling Emulation Microgrids Containers Consensus control Smart grids Internet of Things Security Edge computing

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Hydrogen Supply Infrastructure Planning Method Considering Indirect Network Effects

Hydrogen Supply Infrastructure Planning Method Considering I...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Deng, Haoran Yang, Bo Zhu, Dafeng Yao, Gang Guan, Xinping Srinivasan, Dipti Shanghai Jiao Tong University Department of Automation Shanghai China Kth Royal Institute of Technology Electric Power and Energy Systems Division Stockholm Sweden Shanghai Jiao Tong University Department of Electrical Engineering Shanghai China National University of Singapore Department of Electrical & Computer Engineering Singapore

ISBN: (纸本)9798350376067

At the early commercialization stage of hydrogen fuel cell vehicles (HFCVs), there is a strong causal relationship between HFCV parc and hydrogen refueling stations (HRSs) planning, also known as indirect network effects. This is a crucial factor that hasn't been considered and cannot be ignored in the hydrogen supply infrastructure planning (HSIP) problem. To model the indirect network effects, we quantify the effect of HRS planning on HFCV parc in detail by proposing the calculation method of drivers' fuel buffer, defining hydrogen refueling convenience, and incorporating coupled constraints between the hydrogen network and transportation network. Further, we characterize the effect of HFCVs on HRS planning by constructing a decision-dependent distributionally robust optimization problem considering the HFCV parc uncertainty. We innovatively quantify the upper bound of the ambiguity set of Wasserstein associated with both the endogenous and exogenous factors. We propose effective linearization methods to deal with the nonlinear constraints in the indirect network effects model and transform the two-stage optimization problem into a solvable MILP problem. The simulation results show that the proposed method can obtain more economical investment decisions and achieve higher energy utilization efficiency. More importantly, in this planning framework, investors can set model parameters more flexibly according to the situation of the HFCV market, thereby promoting the popularization of HFCVs. © 2024 IEEE.

关键词： Hydrogen fuels

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Geometric-Spectral Reconstruction Learning for Multi-Source Open-Set Classification With Hyperspectral and LiDAR Data

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1892-1895页

作者： Leyuan Fang Dingshun Zhu Jun Yue Bob Zhang Min He IEEE the College of Electrical and Information Engineering Hunan University the Peng Cheng Laboratory the Department of Geomatics Engineering Changsha University of Science and Technology the PAMI Research Group the Department of Computer and Information ScienceUniversity of Macao

Dear editor,This letter presents an open-set classification method of remote sensing images(RSIs)based on geometric-spectral reconstruction *** specifically,in order to improve the ability of RSI classification model to adapt to the open-set environment,an openset classification method based on geometric and spectral feature fusion is proposed.

关键词： editor letter Open

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Facial recognition system based on the Haar cascade classifier method 24

Facial recognition system based on the Haar cascade classifi...

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24th International Conference on Computational Problems of electrical engineering, CPEE 2023

作者： Karpiuk, Nazar Klym, Halyna Vasylchychyn, Ivanna Lviv Polytechnic National University Department of Specialized Computer Systems Lviv Ukraine Lviv Polytechnic National University Department of Theoretical and General Electrical Engineering Lviv Ukraine

ISBN: (纸本)9798350330342

This scientific research is devoted to the analysis and testing of the Haar cascade classifier method for face recognition. The paper also justifies the choice of algorithm and provides a description of the implementation of the system on which the analysis was conducted. During the research, the developed system was tested on a sample of facial photographs that included images at different distances from the camera, different lighting conditions, and with different facial positions in the camera's plane of view. An analysis of the test results was conducted, and conclusions were drawn regarding the factors that should be considered when designing and using a facial recognition system to achieve high accuracy. © 2023 IEEE.

关键词： Face recognition

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Coordinated EMS for Stability Enhancement of NMGs During Disturbance and Fault Conditions

Coordinated EMS for Stability Enhancement of NMGs During Dis...

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Annual Conference of Industrial Electronics Society

作者： Hossam M. Hussein Mahmoud S. Abdelrahman Ibtissam Kharchouf S M Sajjad Hossain Rafin Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Power systems are evolving from centralized power grid structures to networks of intelligent microgrids (MGs) that can share power more independently. The interconnection between these MGs, forming the networked MGs (NMGs), will increase the power system’s stability and expand its capabilities. However, a critical concern that necessitates sophisticated management strategies for voltage stabilization across the microgrids is the optimal and effective power sharing between renewable resources and energy storage devices. Effective power sharing between AC and DC sides is critical, necessitating robust control mechanisms for interlink converters (ILC). This paper presents a coordinated energy management strategy for hybrid networked MGs (NMGs) to enhance stability during contingencies and fault instances. The proposed Energy Management System (EMS) operates in two distinct modes: grid-connected and islanded. The system takes specific actions to maintain stability depending on the current mode. In grid-connected mode, the grid supplies the load demand while one of the microgrids (MGs) serves as a backup to ensure system stability. Several scenarios were created using MATLAB/Simulink to test and validate the EMS. These scenarios included varying load demands, pulsed power loads, uncertainties in photovoltaic (PV) system generation, disconnection from the AC side, and fault conditions. The proposed EMS has proven its efficiency while maintaining the system stability within the standard limits and fulfilling the load demands.

关键词： Robust control Renewable energy sources Contingency management Microgrids Power system stability Stability analysis MATLAB Energy management systems Thermal stability Energy storage

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Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors 7

Using Deep Reinforcement Learning in Optimal Energy Manageme...

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7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Lin, Yujun Yan, Linfang Hui, Hongxun Chen, Yin Chen, Xia Wen, Jinyu School of Electrical and Electronic Engineering Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology Wuhan China City & Energy Research Institute Suzhou China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China University of Strathclyde Department of Electronic and Electrical Engineering Glasgow United Kingdom

ISBN: (纸本)9798350366945

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods. © 2024 IEEE.

关键词： Deep reinforcement learning

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Graph Models of Electric Power Transmission Networks Using Synchrophasor Data

Graph Models of Electric Power Transmission Networks Using S...

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IEEE Southeastcon

作者： Ganesh K. Venayagamoorthy Dulip Madurasinghe Rajan Ratnakumar Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University SC USA

The electric power transmission network (EPTN) is a connected, geographically distributed network, which can be represented with a graph model with nodes and edges. The graph represents the physical connectivity of the EPTN. Deriving the graph model of the EPTN solely based on continually measured data is important for reliable power system operational situation awareness and decreasing uncertainties driven by weather, electrification, and interconnections. In this paper, an exhaustive search algorithm is presented to derive the EPTN graph model (TNGM) solely based on synchrophasor measurements retrieved from the substations without prior knowledge of the connectivity. Furthermore, an evaluation metric for any data-driven TNGM is introduced. The transmission network of the two-area, four-machine power system is used as the test system, and typical TNGMs for different power plant operating conditions are presented. Typical graphs obtained for network impedance and power flows are shown to be accurate, on average within 2% error margin.

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