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Research on optimization Algorithm and Decision System for Autonomous Operation of New Power System

Research on Optimization Algorithm and Decision System for A...

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Data Analytics, Computing and Artificial Intelligence (ICDACAI), International conference on

作者： Jiameng Gao Ziwei Chen Li Xiang China Electric Power Research Institute State Grid Corporation of China Beijing China Northeast Electric Power University School Jilin China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

This paper focuses on the autonomous operation optimization algorithm and decision-making system of new power system (NPS), and proposes an optimization algorithm framework based on reinforcement learning (RL) to improve the operation efficiency and security of power system. In this paper, the framework of autonomous operation optimization algorithm based on RL is constructed, the power system is abstracted as markov decision processes (MDP), and an agent is constructed through deep neural network (DNN) to learn the optimal strategy. The algorithm framework can sense the state of power system in real time, realize the optimal control decision through the learning of agents, and comprehensively consider economy, safety and new energy consumption ability. In the simulation experiment, this paper uses MATLAB/Simulink platform to build NPS model, which verifies the remarkable advantages of RL algorithm in reducing system operation cost and improving decision efficiency. Compared with traditional linear programming and dynamic programming algorithms, RL algorithm performs better in cost reduction rate and decision-making time, with the cost reduction rate as high as 15.24% and the distribution of decision-making time more centralized and stable. In addition, this paper also discusses the evaluation and analysis method of key technologies based on patent indicators, identifies the "stuck-neck" technology in the power industry, and designs a decision support system (DSS) architecture for NPS. DSS architecture includes four core modules: data acquisition and processing, RL algorithm, decision analysis and user interaction. Through modular design, information can be transmitted and shared efficiently, which provides a strong guarantee for intelligent optimization and decision support of power system. The research results of this paper provide new ideas and technical support for the autonomous operation optimization of NPS, which is of great significance to promoting energy t

关键词： Decision support systems Patents Costs Heuristic algorithms Optimal control Computer architecture Power systems Safety Decision analysis optimization

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Research on Key Technologies of SNOP Suitable for Distribution network 3

Research on Key Technologies of SNOP Suitable for Distributi...

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3rd IEEE International conference on Circuits and Systems, ICCS 2021

作者： Gong, Jianfeng Dang, Dongsheng Li, Yan Chi, Yongning Dong, XiaoJing Jin, Panlong State Grid Ningxia Electric Power Co.ltd Eco-Tech Research Instttute Yinchuan China Institute of Technology and International Standard Conformity Assessment Department Beijing China

ISBN: (纸本)9781665412346

To ensure power quality and power supply reliability, the architecture and mode of the power distribution system are undergoing major changes. In order to further solve these problems and ensure the power quality and power supply reliability of the distribution network, active distribution network technology and various distribution network-oriented power electronic equipment have attracted the attention of scholars from all over the world. Among them, SNOP has gradually become a field of distribution network. New research hotspots. In recent years, scholars in the world have begun to pay close attention to the impact of SNOP on the distribution network and its application of key technologies. SNOP is a new type of flexible primary equipment that can replace traditional tie switches at several key nodes in the distribution network. Compared with the traditional tandem switch, it not only has two states of on and off, but also has no limitation of the number of actions of traditional mechanical switches. It increases the continuous controllable state of power, and has the characteristics of flexible switching of operating modes and flexible and diverse control methods. With the gradual maturity of operation control technology, SNOP's continuous power adjustment ability has become more prominent and no longer has the obvious 'normally open' feature, so it is more called SOP (soft open point) in subsequent research. SOP technology aims to replace traditional circuit breaker-based feeder tie switches with controllable power electronic converters, thereby realizing normalized flexible 'soft connections' between feeders, and can provide flexible, fast and accurate power exchange control and power flow optimization capabilities. At present, the research on SNOP at home and abroad has just started, and the problems related to SNOP's device research and development, control technology, and system access need to be solved urgently. © 2021 IEEE.

关键词： Electric load flow

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Enhancing the Channel Quality in Cognitive network by Traffic Reduction Method

Enhancing the Channel Quality in Cognitive network by Traffi...

引用

Intelligent Technologies (CONIT), International conference on

作者： Sanjay Singh Urmila Pilania Manoj Kumar Satya Prakash Awasthi Leema Nelson Dept. of Computer Science & Technology Manav Rachna University Faridabad India Faculty of Computer Engineering Poornima University Jaipur India Department of Computer Science & Engineering Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

Cognitive radio (CR) has some specific unique characteristics like flexibility, interoperability and adaptability. Optimal technological candidate is particularly contributed which reduces the challenges towards spectrum scarceness sin multimedia communications. Moreover, this communication over CR networks produces few severe issues like delay-sensitive, bandwidth-hungry, and loss-tolerant service and particularly ensuring quality of service (QoS). Improved Dynamic optimization Algorithm (IDOA) is proposed for spectrum sensing in cognitive radio networks (CRN) where for the Secondary User (SU), data traffic is considered. From the comparison of several works in the literature, it is assumed that SU have no packets to transmit always; but actually data sent per second is considered instead of channel capacity as the possible throughput with which the problem of sensing-throughput tradeoff is reformulated. The parameters such as probability of availability, Signal to Interference Noise Ratio (SINR), Processing time and transmission time are considered to analyze the efficiency of the IDOA approach proposed which is compared with two state of methods namely Medium Access control (MAC) and Dijikstra Algorithm (DA).

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Automatic Finite Deterministic Algorithm and PSO Based Secured Energy Efficient Routing in Wireless Sensor network 3

Automatic Finite Deterministic Algorithm and PSO Based Secur...

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3rd International conference on Advances in Computing, Communication control and networking, ICAC3N 2021

作者： Shah, Priyanka Kasbe, Tanmay Oriental University Department of Computer Science Madhya Pradesh Indore India

ISBN: (纸本)9781665438117

Economic sensor networks have always been a boon to disaster management applications due to their ease of setup. Communication is difficult for them due of their vulnerability to a variety of security dangers. This study presents a new routing strategy those guards against both external and internal threats such as hello flooding, eavesdropping, and wormhole attacks. To limit energy dissipation, this method employs a one-way hash chain. Event-driven clustering at the level also saves energy. The suggested technique extends network longevity even when the cluster-based wireless sensor network is under attack, according to simulated results. A 5G wireless sensor network (WSN) is a collection of self-contained nodes that monitor the environment. WSN design goals like as energy efficiency or secure data transmission are primarily measured. With the increasing difficulties of workstation networks, network-based attacks have drawn the attention of various academics from various domains. As a result, multiple intrusion detection systems (IDS) have been built to address various areas of complicated security, such as denial-of-service attacks, worms, viruses, malware, and so on. IDS automation has been designed to safely restore the realization of energy-efficient routing in wireless sensor networks. Intrusion detection and data transmission performed in a secure manner using automatic finite deterministic and particle swarm optimization (PSO) algorithms that determine and follow an optimum path. Routing along the optimal path can restore the overall appearance of a sensor network in wireless technology, and it can be managed using a variety of indicators (such as power expenditure, capacity, network life, active nodes and dead nodes). The threat model and safety objectives for secure routing in wireless networks are discussed in this paper. The simulation was carried out using the MATLAB simulation software. © 2021 IEEE.

关键词： Intrusion detection

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A Data Driven, Convex optimization Approach to Learning Koopman Operators 3

A Data Driven, Convex Optimization Approach to Learning Koop...

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3rd Annual conference on Learning for Dynamics and control (L4DC)

作者： Sznaier, M.

Koopman operators provide tractable means of learning linear approximations of non-linear dynamics. Many approaches have been proposed to find these operators, typically based upon approximations using an a-priori fixed class of models. However, choosing appropriate models and bounding the approximation error is far from trivial. Motivated by these difficulties, in this paper we propose an optimization based approach to learning Koopman operators from data. Our results show that the Koopman operator, the associated Hilbert space of observables and a suitable dictionary can be obtained by solving two rank-constrained semi-definite programs (SDP). While in principle these problems are NP-hard, the use of standard relaxations of rank leads to convex SDPs.

关键词： Koopman Operators Learning Nonlinear Dynamics Nonlinear Identification

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Artificial Intelligence Method for V2G oriented Power Distribution network control Strategy and Capacity Analysis

Artificial Intelligence Method for V2G oriented Power Distri...

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Data Analytics, Computing and Artificial Intelligence (ICDACAI), International conference on

作者： Li Tao Wang Bo Su Yongbin Li Cheng State Grid Hubei Electric Power Co. Ltd. Jingzhou Power Supply Company Jingzhou China State Grid Jingzhou Power Supply Company Economic and Technological Research Institute Jingzhou China State Grid Hubei Electric Power Co. Ltd. Tianmen Power Supply Company Tianmen China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

With the popularization of electric vehicle (EV), Vehicle-to-Grid (V2G) technology has become an important means to balance the supply and demand of power grid and improve the flexibility of power grid. This article aims to explore a V2G-oriented power distribution network (PDN) regulation strategy and artificial intelligence (AI) method for carrying capacity analysis, so as to realize the efficient and stable operation of the power grid. In this article, a data fusion method based on modified mind evolutionary algorithm (MMEA) is proposed to deal with complex data in PDN. Then, based on the data fusion results, a V2G control strategy is designed. Finally, MMEA algorithm is used to analyze the V2G carrying capacity of PDN. The results show that this method has achieved remarkable results in data fusion, control strategy optimization and carrying capacity analysis, and improved the operation efficiency and stability of PDN. To sum up, the V2G-oriented PDN control strategy and AI method for carrying capacity analysis proposed in this article provide strong support for the practical application of V2G technology and the intelligent development of power grid.

关键词： Vehicle-to-grid Supply and demand Data integration Power system stability Power grids Regulation Stability analysis PD control Artificial intelligence Capacity planning

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Traffic optimization in IoT networks 3

Traffic optimization in IoT networks

引用

3rd International conference of Computer Science and Renewable Energies, ICCSRE 2020

作者： Ouahi, Hassan Mazoul, Abdenbi Laboratory Computing Systems and Vision LabSiv University Ibn Zohr of Agadir Faculty of Science BP 28/S Agadir80000 Morocco

Since the 2000s, the idea that the Internet could be used for machine-to-machine communication and process automation has emerged. Together with the development of electronic objects capable of communicating with IP protocols, this idea led to the concept of the Internet of Things (IoT Internet of Things). Nowadays, the evolution of networks is very intense. New networks are appearing, "all-optical"solutions in the heart of networks, "wireless"solutions to facilitate access to users or to implant sensors / actors in places difficult to access, or finally the Internet of communicating objects. In this evolution, new scientific issues and challenges are emerging. Some of the problems are related to the optimization of generated traffic as well as the improvement of the performance of tools and techniques. Often, these optimization problems lead to models using graphs. The analysis of optimization problems in networks is an important activity. IOT networks create more data traffic that is difficult to control within the operator's network. The method given in this paper will help network operators optimize their networks and assist developers in improving hardware and software interactions to reduce data traffic in the network. © The Authors, published by EDP Sciences, 2021.

关键词： Internet of things

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Android Malware Detection via Hybrid Lion-Bee optimization with Bi-Directional Recurrent Neural network

Android Malware Detection via Hybrid Lion-Bee Optimization w...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International conference on

作者： Sivaram Rajeyyagari Mohamed Ahmed Elfaki Khan Asif Rashid B Kiran Bala Omar Reyad Department of Computer Science College of Computing and Information Technology Shaqra University Shaqra Saudi Arabia Department of AI and DS K.Ramakrishnan college of Engineering Trichy India College of Computing and Information Technology Shaqra University Shaqra Saudi Arabia Faculty of Computers and Artificial Intelligence Sohag University Sohag Egypt

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

The number of malicious programs that target the Android OS has significantly expanded with the rise in mobile device usage. It is crucial to identify, prevent, and defeat Android malware assaults since they have long presented a severe threat to Android apps. The emergence of secure Android app ecosystem depends on recognizing and classifying harmful applications into groups are similar to another. Malware families can be categorized in order to recognize harmful activity and to systematically spot dangerous-patterns. Thus, the study suggests a hybrid strategy that combines the attributes discovered from doing static and dynamic malware assessment for enhanced identification and categorization of Android malware. This method more effectively addresses the issue of studying, identifying Android malware. The feature extracted from image sections utilizing the hybrid lion and artificial bee colony (HL-ABC) optimization. RNN were used to classify the retrieved features. Each segment of a malware image file served as a test case for the categorization performance. This is contrasted with other current ways to show the effectiveness of the suggested strategy. Comparing the suggested model to other approaches, the study's findings demonstrate its effectiveness in identifying and classifying Android malware.

关键词： Image segmentation Recurrent neural networks Communication systems Ecosystems Bidirectional control Feature extraction Malware Mobile handsets Integrated circuit modeling optimization

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optimization of Point-to-Point Trading with Multiple Microgrids Based on the Stackelberg Game

Optimization of Point-to-Point Trading with Multiple Microgr...

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Energy Engineering and Power Systems (EEPS), International conference on

作者： Fangsheng Wang Dapeng Li Dawei Dou Li Bao Yang Cao Wenxin Zhang Xiaotong Zhou Yijun Fan East Inner Mongolia Power Exchange Center Company Ltd. Hohhot China School of Economics and Management North China Electric Power University Beijing China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

A microgrid cluster composed of multiple microgrids can improve system stability and economic efficiency through energy mutualization. However, multi-microgrid transaction involves all parties in the game, how to balance the interests of various market players is an important topic in the current multi-microgrid research. In this regard, it is proposed to adopt Stackelberg game to study the point-to-point transaction strategy of multi-microgrid. The operation and revenue model of each unit within the micro-network is established, and the multi-micro-network transaction model is constructed. Under this game framework, with the goal of maximizing the revenue of multi-micro-networks, cooperative trading among micro-networks is incentivized by deciding the optimal transaction price. The micro-network control center as a follower gives the trading strategy under the premise of guaranteeing its own revenue. A microgrid cluster consisting of four microgrids is analyzed as an example, and the iterative search method is applied to solve the Nash equilibrium. The simulation results show that this method can improve the distributed energy utilization and reduce the system operation cost compared with the independent operation of each microgrid off-grid.

关键词： Analytical models Costs Uncertainty Supply and demand Search methods Systems operation Simulation Microgrids Games Stability analysis

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optimization and application of primary frequency system for real-time communication using PMU data 3

Optimization and application of primary frequency system for...

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3rd International conference on Electrical, Communication and Computer Engineering, ICECCE 2021

作者： Ding, Yuming Zhang, Li Zhang, Fang Wei, Yu Huadian Electric Power Research Institute Co. Ltd. Hangzhou China

By integrating the network-related parameters of the electrical and thermal control specialty in the network-related system, communicating with the Pi real-time database in the power plant Area II, and further realizing the Web application function in the Production Information Area III. Secondly, using these real-time big data, it analyzes the operation of primary frequency regulation and optimizes it accordingly, establishes the standard table, carries out monthly analysis and daily index supervision, so as to make the pass rate of primary frequency regulation close to or reach 100%, and increase the compensation cost, so that the unit is not only in energy-saving operation but also not assessed by the power grid. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Temperature control

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