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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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Credibility Evaluation of Web Big Data Information Based on particle swarm Optimization

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JOURNAL OF WEB ENGINEERING 2022年第2期21卷 405-423页

作者： Zhao, Nannan Guangdong Ocean Univ Yangjiang Sch Comp Sci & Engn Yangjiang Peoples R China

In order to improve the credibility evaluation effectiveness of web big data information, the improved particle swarm optimization is established. Firstly, framework of web big data is designed to include web big data source, data storage, data processing and data analysis. The global credibility calculation formula of whole web is established. Secondly, the improved particle swarm algorithm is constructed through updating weight and training factor, introducing cross and mutation operations into the algorithm, and improving population diversification based on mountain climbing algorithm. Finally, ten sample industries and one hundred sample stocks are selected to carry out experiment analysis, and the results show that the proposed algorithm can effectively distinguish trusted and untrustworthy records. And the proposed algorithm of calculating credibility of web big data has high reasonableness.

关键词： Credibility evaluation web big data improved particle swarm algorithm

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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...

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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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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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Reactive Power Optimization for Power System With Wind Farm Based on improved particle swarm algorithm

Reactive Power Optimization for Power System With Wind Farm ...

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第30届全国化学与物理电源学术年会

作者： ZHANG Han-ping Computer Department Wuhan Polytechnic

The problem of power system reactive power optimization is a mathematical problem with multiple variables and constraints,which is complex and *** control variables include continuous variables and discrete variables,it's difficult to get the optimal solution.A solution in power flow calculation is put forward after the mathematical model of wind farm is built in this *** on this,taking the WSCC 9 nodes system as an example,use the particle swarm algorithm to solve the reactive power optimization *** result shows that this algorithm has an apparent positive effect on reducing system power loss and improving system voltages.

关键词： improved particle swarm algorithm wind farm reactive power optimization

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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...

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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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Impact of Energy System Optimization Based on Different Ground Source Heat Pump Models

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ENERGIES 2024年第23期17卷 6023页

作者： Lai, Yingjun Gao, Yan Gao, Yaping Beijing Univ Civil Engn & Architecture Beijing Key Lab Heating Gas Supply Ventilating & A Beijing 100044 Peoples R China Beijing Univ Civil Engn & Architecture Sch Architecture & Urban Planning Beijing 100044 Peoples R China

With rapidly developing new energy technologies, rational energy planning has become an important area of research. Ground source heat pumps (GSHPs) have shown themselves to be highly efficient. effective in reducing building or district energy consumption and operating costs. However, when optimizing integrated energy systems, most studies simplify the GSHP model by using the rated coefficient of performance (COP) of the GSHP unit, neglecting factors such as soil, buried piping, and actual operating conditions. This simplification leads to a deviation from the actual operation of GSHPs, creating a gap between the derived operational guidelines and real-world performance. Therefore, this paper examines a hotel equipped with photovoltaic panels, a GSHP, and a hybrid energy storage unit. By constructing models of the underground pipes, GSHP units, and pumps, this paper considers the thermal exchanger between the underground pipes and the soil, the thermal pump, and the operating status of the unit. The purpose is to optimize the running expenses using an enhanced mote swarm optimization (PSO) algorithm to calculate the optimal operating strategy of system equipment. Compared to the simplified energy system optimization model, the detailed GSHP unit model shows a 21.36% increase in energy consumption, a 13.64% decrease in the mean COP of the GSHP unit, and a 44.4% rise in system running expenses. The differences in the GSHP model affect the energy consumption results of the unit by changing the relationship between the power consumption of the PV system and the GSHP at different times, which in turn affects the operation of the energy storage unit. The final discussion highlights significant differences in the calculated system operating results derived from the two models, suggesting that these may profoundly affect the architectural and enhancement processes of more complex GSHP configurations.

关键词： ground source heat pump improved particle swarm algorithm day-ahead optimization buried pipe

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Research on Multi-Objective Energy Management of Renewable Energy Power Plant with Electrolytic Hydrogen Production

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PROCESSES 2024年第3期12卷 541页

作者： Shi, Tao Gu, Libo Xu, Zeyan Sheng, Jialin Nanjing Univ Posts & Telecommun Coll Automat Nanjing 210023 Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Carbon Neutral Nanjing 210023 Peoples R China

This study focuses on a renewable energy power plant equipped with electrolytic hydrogen production system, aiming to optimize energy management to smooth renewable energy generation fluctuations, participate in peak shaving auxiliary services, and increase the absorption space for renewable energy. A multi-objective energy management model and corresponding algorithms were developed, incorporating considerations of cost, pricing, and the operational constraints of a renewable energy generating unit and electrolytic hydrogen production system. By introducing uncertain programming, the uncertainty issues associated with renewable energy output were successfully addressed and an improved particle swarm optimization algorithm was employed for solving. A simulation system established on the Matlab platform verified the effectiveness of the model and algorithms, demonstrating that this approach can effectively meet the demands of the electricity market while enhancing the utilization rate of renewable energies.

关键词： electrolytic hydrogen power fluctuation smoothing peak shaving auxiliary services fuzzy chance constraints improved particle swarm algorithm

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Optimization of shared energy storage configuration for village-level photovoltaic systems considering vehicle charging management

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ENERGY 2024年 311卷

作者： Wang, Haifeng Liao, Yate Zhang, Jiarui Cai, Ziwen Zhao, Yun Wang, Weijun North China Elect Power Univ Dept Econ & Management Baoding 071003 Hebei Peoples R China China Southern Power Grid Co Ltd Guangzhou 510663 Guangdong Peoples R China

Distributed renewable energy is more abundant in rural areas, and a large amount of distributed photovoltaic grid-connected power brings challenges to the stable of the power grid. How to promote the self-generation and self-consumption of distributed renewable energy has become an urgent problem. In this paper, a village-level distributed photovoltaic power generation system including energy storage and electric vehicles is constructed. With the goal of minimizing the photovoltaic grid-connected power and maximizing the annual comprehensive revenue, the planning model of energy storage capacity allocation for village-level distributed power generation system is constructed. Considering the charging management for different numbers of electric vehicles, the optimal energy storage capacity allocation strategy is solved using the improved particle swarm *** scenarios are set up as examples to be *** conclusions are:(1)After the configuration of a reasonable energy storage,the grid-connected generation of the system is significantly reduced,and the annual comprehensive revenue of the system is significantly increased.(2)After considering charging management for different numbers of electric vehicles, the capacity and power of the energy storage configuration can be significantly reduced, thus reducing the energy storage investment cost and operation and maintenance cost, and further significantly improving the annual comprehensive revenue of this system.

关键词： Village-level distributed photovoltaic systems Energy storage configuration planning improved particle swarm algorithm Electric vehicle Charge management Nomenclature

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A Rotating Tidal Current Controller and Energy Router Siting and Capacitation Method Considering Spatio-Temporal Distribution

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ENERGIES 2024年第23期17卷 5919页

作者： Jia, Junqing Zhou, Jia Gao, Yuan Shao, Chen Lu, Junda Jia, Jiaoxin Key Lab Intelligent Power Grid Simulat Enterprise Hohhot 010020 Peoples R China Inner Mongolia Elect Power Grp Co Ltd Inner Mongolia Elect Power Res Inst Hohhot 010020 Peoples R China Inner Mongolia Power Grp Co Ltd Nav Inspect Branch Hohhot 010020 Peoples R China Inner Mongolia Elect Power Grp Co Ltd Ordos Power Supply Branch Ordos 017000 Peoples R China North China Elect Power Univ Hebei Key Lab Distributed Energy Storage & Microgr Baoding 071003 Peoples R China

As the proportion of new energy access increases year by year, the resulting energy imbalance and voltage/trend distribution complexity of the distribution network system in the spatio-temporal dimension become more and more prominent. The joint introduction of electromagnetic rotary power flow controller (RPFC) and energy router (ER) can improve the high proportion of new active distribution network (ADN) consumption and power supply reliability from both spatial and temporal dimensions. To this end, the paper proposes an ADN expansion planning method considering RPFC and ER access. A two-layer planning model for RPFC and ER based on spatio-temporal characteristics is established, with the upper model being the siting and capacity-setting layer, which takes the investment and construction cost of RPFC and ER as the optimization objective, and the lower model being the optimal operation layer, which takes the lowest operating cost of the distribution network as the objective. The planning model is solved by a hybrid optimization algorithm with improved particle swarm and second-order cone planning. The proposed planning model and solving algorithm are validated with the IEEE33 node example, and the results show that the joint access of RPFC and ER can effectively improve the spatial-temporal distribution of voltage in the distribution network and has the lowest equivalent annual value investment and operation cost.

关键词： active distribution network expansion planning rotating current controller energy router improved particle swarm algorithm second order cone planning

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