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检索条件"主题词=improved particle swarm algorithm"

共 64 条记录，以下是41-50 订阅

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Research of the Maintenance Scheduling Optimization Considering the Grid Risk

Research of the Maintenance Scheduling Optimization Consider...

引用

2nd International Conference on Energy, Environment and Sustainable Development (EESD 2012)

作者： Dong, Lei Wu, Jun Pu, Tianjiao Zhou, Haiming North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China China Elect Power Res Inst Beijing 100192 Peoples R China

ISBN: (纸本)9783037855515

At present the research of power grid maintenance scheduling is mostly focused on reducing the maintenance costs or improving the reliability, which ignores the potential risk of power grid during repairing to a certain extent. Considering the potential risks of power grid and users fully, a new optimization model is built here. The model's objective function is the minimum of the comprehensive risk cost caused by maintenance, the constraint conditions are list as synchronous overhaul, mutually exclusive overhaul, security checking and resource requirement and so on. The improved particle swarm algorithm is chosen to achieve a better convergence here. The analysis of the RBTS system example verifys the effectiveness of the model and algorithm.

关键词： optimization of maintenance schedule risk of power grid load transfer improved particle swarm algorithm

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A Cell Outage Compensation Mechanism Based on IPSO for 5G Ultra-dense Small Cell Networks 26

A Cell Outage Compensation Mechanism Based on IPSO for 5G Ul...

引用

IEEE 26th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

作者： Chen, Cheng Yu, Peng Feng, Lei Zhou, Fanqin Li, Wenjing Lin, Wei Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Inspur Grp Co Ltd Jinan Shandong Peoples R China

ISBN: (纸本)9781665417792

To cope with the increment of mobile communication in 5G networks, Internet Service Providers are planning to adopt base stations with less power and smaller coverage in a more intensive manner. We call such networks multi-tier heterogeneous small cell networks, which put forward more stringent requirements on network security and stability. Self-Organizing Network (SON) is expected to be a potential solution. However, the issue of cell outage compensation (COC) is important for SON. This paper proposes a cell outage compensation mechanism based on an improved particle swarm algorithm (IPSO). Specifically, the neighboring base stations of the failed base station are selected as the compensation base stations according to the topology structure, and then the problem model is constructed to maximize the transmission rate. This model considers the priority of the quality of service (QoS) for different users. It adopts IPSO based on adaptive weights to comprehensively adjust the downtilt, horizontal azimuth, and user power allocation of the base station to ensure the transmission rate. The simulation results show the algorithm converges fast, can quickly approach the target value, and can effectively guarantee the quality of service for users.

关键词： multi-tier ultra-dense heterogeneous small cell networks self-organizing network improved particle swarm algorithm cell outage compensation

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Research on Urban Intelligent Transportation Planning Based on Storm 18

Research on Urban Intelligent Transportation Planning Based ...

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18th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

作者： Liu, Chun-Yan Zou, Cheng-Ming Wuhan Univ Technol HuaXia Coll Dept Informat Engn Wuhan Hubei Peoples R China Hunan Vocat Coll Railway Technol Hunan Engn Technol Res Ctr Highspeed Railway Oper Zhuzhou Hunan Peoples R China

ISBN: (纸本)9781728128658

This paper aims at the problem of dynamic target path planning for vehicles in urban. Firstly,design an urban real-time dynamic path planning model(UR-MODE) based on the Storm framework;then, proposes an improved particle swarm optimization algorithm(Adaptive Partner-particle swarm optimization,AP-PSO) which introduce the adaptive inertia weight and small scale perturbation strategy to ensure the efficiency of our proposed model. Finally,we implement the improved algorithm on the Storm real-time processing system and realize the mass real-time traffic data processing. Compared with the existing path planning algorithms, the experiment proves that the UR-MODE based method can reduce the travel time by 15%-20% on average and increase the traffic resource utilization by 50%. It proves the efficiency of the method.

关键词： improved particle swarm algorithm multi-objective optimization optimal path storm frame

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Application of particle swarm algorithm in Train-Set Circulation Problem of China

Application of Particle Swarm Algorithm in Train-Set Circula...

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2nd International Conference on Civil Engineering and Transportation (ICCET 2012)

作者： Li, Hua Han, Baoming Lu, Fang Li, Xiaojuan Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China

ISBN: (纸本)9783037855645

Train-set circulation problem is an important issue in operations of high-speed passenger trains in the world. On the basis of characteristics of the train-set circulation problem in China, an integer programming model is presented without considering distinct train-set types. With redefinitions of some basic mathematical objects and operations, an improved particle swarm optimization algorithm is proposed to solve the model. The algorithm is applied in a real-life case study based on the timetable of the Wuhan-Guangzhou High-speed Railway Line. The results show that the proposed algorithm is effective to find the optimized train-set circulation plan.

关键词： train-set circulation integer programming model improved particle swarm algorithm

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Diesel generator sensor fault diagnosis model based on LMD-SVM algorithm 8

Diesel generator sensor fault diagnosis model based on LMD-S...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Cao, Wenjing Wang, Jiabiao Chen, Jiajie Xu, Jing Jiangsu University of Science and Technology School of Mechanical Engineering Jiangsu Zhenjiang China Shanghai Marine Equipment Research Institute Shanghai China Jiangsu University of Science and Technology School of Economics and Management Jiangsu Zhenjiang China Jiangsu University of Science and Technology Marine Equipment and Technology Institute Jiangsu Zhenjiang China

ISBN: (纸本)9798350328813

For the fault diagnosis of a diesel generator sensor system, a fault diagnosis model of diesel generator sensor based on the coupling of LMD and SVM algorithm is proposed, firstly, the fault signal is collected and the fault features are extracted by using LMD demarcation, then it is combined with SVM model, and the SVM classifier parameters are optimized by using the modified particle swarm algorithm (MPSO) to further improve the accuracy of fault diagnosis. The experimental results show that the accuracy of fault diagnosis of diesel generator sensor system (vibration sensor, temperature sensor, voltage sensor, and current sensor) using LMD-SVM model can reach 96.9%, 95.3%, 95.8%, and 94.8%, which has better diagnosis effect. © 2023 IEEE.

关键词： fault diagnosis improved particle swarm algorithm LMD-SVM sensor

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Multi-Objective Optimal Scheduling of Virtual Power Plants Considering Cloud-Edge Collaboration 3

Multi-Objective Optimal Scheduling of Virtual Power Plants C...

引用

3rd IEEE International Conference on Electrical Engineering, Big Data and algorithms, EEBDA 2024

作者： Chen, Kun Sun, Kaiyuan Chen, Haifeng Guan, Zhe Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Csg Guangzhou510000 China

ISBN: (纸本)9798350380989

In order to effectively improve the operating economy and reliability of virtual power plants, this paper constructs a multi-objective optimal scheduling with dual consideration of energy and information. In the energy aspect, the economy of a single virtual power plant is considered, and the scheduling model is constructed with the goal of minimizing the power generation cost. In the information aspect, the cloud-edge synergy of computing resources in the scheduling process of multi-virtual power plant is taken into account, and the scheduling model is constructed with the goal of minimizing the delay of the cloud-edge system. Finally, the improved particle swarm algorithm is used to solve the model, and the examples verify that the algorithm is adapted to the scheduling problem in the virtual power plant scenario, so that it has the ability to solve the scheduling problem quickly. © 2024 IEEE.

关键词： Cloud-edge collaboration improved particle swarm algorithm Multi-objective optimal scheduling Virtual power plants

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Demand Side Response Market Clearing Strategy Based on Virtual Power Plants 3

Demand Side Response Market Clearing Strategy Based on Virtu...

引用

3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Wang, Yan Zhang, Chunmeng Sun, Jiaqi Zhao, Ying Lu, Yue State Grid Shenyang Electric Power Supply Company Shenyang China Capital Intensive Center of State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (纸本)9798350382426

To investigate the participation of virtual power plants (VPPs) in the comprehensive demand response market mechanism and clearing strategies, a comprehensive demand response market mechanism and clearing strategy that takes into consideration the adjustable capacity of virtual power plants has been proposed. Firstly, the mechanism of VPPs' participation in the comprehensive demand response market is analyzed, and a comprehensive demand response resource model that considers the internal resources of VPPs is established. Subsequently, a mathematical model for the adjustable capacity of VPPs is introduced, and it is solved using an improved particle swarm optimization algorithm. Finally, a clearing strategy for the comprehensive demand response market that considers the adjustable capacity of VPPs is proposed, along with an interactive clearing method that incorporates optimization strategies for both the upper-level distribution network and VPP operators. The computational results demonstrate that the clearing strategy presented in this study can reduce overall costs while ensuring the interests of VPP operators, thereby achieving peak shaving, valley filling, and the integration of renewable energy sources. © 2023 IEEE.

关键词： Adjustable Capacity Comprehensive Demand Response Electric/Thermal Coupling improved particle swarm algorithm Market Clearing Virtual Power Plant (VPP)

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Research on Shared Energy Storage Cooperative Voltage Regulation Strategy Based on Energy Interconnection Mode

Research on Shared Energy Storage Cooperative Voltage Regula...

引用

第43届中国控制会议

作者： Li Jiaman Xu Chang Wang Qingyi School of automation China University of Geosciences

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aiming at the node voltage overrun problem caused by the high proportion of new energy sources connected to the power system, this paper uses shared energy storage to carry out charging and discharging operations according to the demand to realize the voltage regulation control of the node loads as well as the balance and optimization of the system. This paper proposes a collaborative scheduling optimization strategy for shared energy storage based on the energy interconnection model,establishes a mathematical model of voltage overrun with economic efficiency as the core objective, and determines the optimal energy storage output size and time sequence using an improved particle swarm algorithm to achieve collaborative control of different devices. It promotes the establishment of an energy information sharing model for energy storage equipment, realizes capacity sharing, resource integration, system reliability improvement, and promotes the popularization and sustainable development of clean energy.

关键词： Power system shared energy storage voltage control cooperative scheduling improved particle swarm algorithm

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Design of Energy Dispatch Strategy of Active Distribution Network Using Chance-constrained Programming

Design of Energy Dispatch Strategy of Active Distribution Ne...

引用

IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Xie Hua Chen Yuxi Wang Jian Agelidis, Vassilios Beijing Jiaotong Univ Natl Act Distribut Network Technol Res Ctr Collaborat Innovat Ctr Vehicles Beijing Beijing Peoples R China Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

ISBN: (纸本)9781467381321

Active distribution network plays an important role in increasing the utilization level of the renewable energy and realizing the flexible intelligent distribution network management. In this paper, aiming to improve the economy and reliability of the active distribution network, the energy dispatch strategy is designed by the method of the chance-constrained programming. Considering the uncertainty of the photovoltaic power generation and wind power generation, the random simulation technique and the penalty function method are selected to build the energy scheduling mathematical model. The operation constraints are set for wind turbines, photovoltaic power generation unit, the active power energy storage devices and the exchange power between the superior power system and the active distribution network. The energy dispatch strategy is given by the improved particle swarm algorithm. An actual system in a certain area is chosen to verify the effectiveness of the proposed method in this paper.

关键词： active distribution network chance-constrained programming random simulation technique improved particle swarm algorithm

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Research on Temperature Control System Based on IPSO Optimized Fuzzy PID

Research on Temperature Control System Based on IPSO Optimiz...

引用

39th Chinese Control Conference (CCC)

作者： Gao Long Yang Yi Ren Xiaolin Gu Haiqin Han Qingqing Yu Jingya Nantong Univ Coll Elect Engn Nantong 226019 Jiangsu Peoples R China

ISBN: (数字)9789881563903

ISBN: (纸本)9789881563903

The air source heat pump heat collection control system is a system with strong nonlinearity and large time delay. It is difficult to achieve the expected control effect on the outlet water temperature by using conventional control algorithms. In view of this problem, this paper makes up for the shortcomings of fuzzy control and PID control, and proposes an improved particle swarm optimization (IPSO) fuzzy PID control strategy to control the temperature of the effluent of the air source heat pump heat collection control system. First of all, the particle swarm optimization algorithm is easy to fall into the problem of local optimization. By increasing the vector, the optimal position of individual particles is stored to increase the range of particle search. Then use the improved particle swarm algorithm to optimize the fuzzy PID scale factor and quantization factor to modify the PID parameters in real time to improve the control accuracy of the heat pump system. Finally, a MATLAB / Simulink simulation model for the heat collection temperature control of the heat pump is established and an improved particle swarm optimization algorithm program is written, and compared with the fuzzy PID and conventional PID control algorithms. Simulation results show that the heat-collection control system based on IPSO has strong adaptability, robustness and anti-interference.

关键词： Air source heat pump fuzzy PID improved particle swarm algorithm temperature control

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