2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)最新文献_第2页

A Multi-dimensional Copula Wind Speed Correction Method for Ultra-Short-Term Wind Power Prediction 一种用于超短期风电预测的多维联结风速校正方法

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759563

Chuanqi Wang, Ming Yang, Yixiao Yu, Menglin Li, Zhiyuan Si, Yating Liu, Fangqing Yan

{"title":"A Multi-dimensional Copula Wind Speed Correction Method for Ultra-Short-Term Wind Power Prediction","authors":"Chuanqi Wang, Ming Yang, Yixiao Yu, Menglin Li, Zhiyuan Si, Yating Liu, Fangqing Yan","doi":"10.1109/AEEES54426.2022.9759563","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759563","url":null,"abstract":"The focus of this paper is how to make comprehensive use of numerical weather prediction (NWP) and real power data to correct the forecasted wind speed, to improve the accuracy of ultra-short-term wind power prediction. Firstly, the multi-dimensional Copula model is built by 3 time series: current wind speed, previous wind speed error and current wind speed error. Determinate the first two values, and the current wind speed error can be obtained by gradually solving the conditional probability. Then, use the current wind speed error to correct and replace forecasted wind speed in NWP. Finally, take corrected NWP as the input of Long Short-Term Memory (LSTM), and take real power as the output. After selecting appropriate parameters to train the LSTM model, this hybrid model can be used to predict the ultra-short-term wind power. Compared with Autoregressive Integrated Moving Average (ARIMA), which only considers the time-series characteristics of wind speed error, this hybrid model can bring 2.3% reduction of mean absolute percentage error in prediction.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132213200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Study on the Pyrolysis Characterization of Rice Husk Var in CO2/N2 Atmosphere 稻壳Var在CO2/N2气氛下的热解特性研究

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759811

Bingyan Hou, Zeguo Liu, Jian Zhao, Chunliang Li

引用次数: 0

A Data-Driven MPC Energy Optimization Management Strategy for Fuel Cell Distributed Electric Propulsion UAV 数据驱动的燃料电池分布式电力推进无人机MPC能量优化管理策略

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759649

Zhihao Min, Tao Lei, Xingyu Zhang, Q. Gao, Xiaobin Zhang

{"title":"A Data-Driven MPC Energy Optimization Management Strategy for Fuel Cell Distributed Electric Propulsion UAV","authors":"Zhihao Min, Tao Lei, Xingyu Zhang, Q. Gao, Xiaobin Zhang","doi":"10.1109/AEEES54426.2022.9759649","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759649","url":null,"abstract":"With the development of green aviation technology, distributed electric propulsion aircraft has been the focus of research topic in the field of aviation technology due to its high flight efficiency, low pollutant emissions, high energy efficiency, and diverse aerodynamic layouts design. Compared with gas oil fuel, hydrogen-based fuel cell has the advantages such as zero emissions, low noise and high energy density. In order to improve the overall performance of the fuel-cell distributed electric propulsion UAV, Research on adaptive energy management strategies was conducted in this paper to improve the dynamic response of power system according to variation of propulsion power load. In order to deal with the uncertainty of the electric power load changes during different flight conditions of the UAV, the propulsion power demanding prediction method is presented under different flight conditions based on the flight data obtained from the real electric propulsion UAV flight testing. Based on the data-driven neural network, a distributed electric propulsion power load forecasting model was established. Based on the modeling of the distributed hybrid electric propulsion power system, three energy management strategies are proposed for comparison and verification in this paper. In view of the problem that the uncertainty of propulsion power demand under different flight conditions of UAV affects the performance of distributed electric propulsion system, an energy optimization management strategy based on deep neural network propulsion power demand forecasting combined with model predictive control is proposed. The performance evaluation of the proposed EMS is conducted via digital simulation studies using the data obtained from real-world UAV flighting experiments and its performance is compared with two benchmark schemes","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132531260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Reactive Power Regulation Capacity Assessment of DFIG Wind Farms DFIG风电场实时无功调节能力评估

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759755

Guixing Yang, Yaoxiang Wang, Yuan Jia, Guoyi Xu

{"title":"Real-Time Reactive Power Regulation Capacity Assessment of DFIG Wind Farms","authors":"Guixing Yang, Yaoxiang Wang, Yuan Jia, Guoyi Xu","doi":"10.1109/AEEES54426.2022.9759755","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759755","url":null,"abstract":"The output power of wind farms fluctuates with the wind speeds, which result in unstable voltage at the point of common coupling. The fast reactive power regulation capability of the variable speed wind turbine generators is an effective solution to suppress voltage fluctuation at the point of common coupling. The reactive power regulation capability of the variable speed wind turbine generators varies with their operation status. In order to design an effective voltage control method for the wind farms, it is of great significance to evaluate real time reactive power regulation range of the wind farms. In this paper, a doubly-fed wind turbine generator model is established, the reactive power limit of the wind turbine generator is derived. Then, the wind farm reactive power loss and reactive power compensation equipment capacity are considered to establish the wind farm reactive power capacity estimation model. Finally, the wind turbine equivalent model is used to simulate natural wind speed to obtain the real-time reactive power capacity range of the wind farm under random fluctuating wind speed, and the simulation results verify the reliability of the proposed method.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134091112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Parametric Average-Value Modeling of Diode Rectifier Systems Based on Neural Network 基于神经网络的二极管整流系统参数平均值建模

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759625

Kangkang Wang, Wei Wei, Shilin Gao, Shaowei Huang, Xinwei Sun, Bo Zhou

引用次数: 1

Stochastic Optimal Dispatching of Electrothermal Integrated Energy System Considering Uncertainty of Heat Load 考虑热负荷不确定性的电热综合能源系统随机优化调度

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759616

Lin Song, Haotian Wu, D. Ke, Jian Xu, Jing-Jing Zheng, Zaixun Ling, Yibo Cui

引用次数: 0

Optimal Sizing of Standalone Hybrid Microgrid Using Artificial Jellyfish Search 基于人工水母搜索的独立混合微电网优化规模

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759665

Ashraf Fathy Ali, E. Gouda, Mohamed Adel Elsayes, Di Cao, Weihao Hu, S. Abulanwar

引用次数: 1

Analysis on Influencing Factors of Repair Order of Power Supply Station based on Grey Correlation Analysis 基于灰色关联分析的供电站检修顺序影响因素分析

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759700

Jiyang Lu, Jun Ji, Xiangwei Xu

引用次数: 1

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759712

Qiuyang Ma, Jing Liu, Zhongyang Chen, Bin Han, Zhi Cai

引用次数: 0

Analysis of Container Expansion Method in New Generation of Dispatch Automation System 新一代调度自动化系统中集装箱扩展方法分析

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759722

Zhou Wan, Gao Jie, He Ming, Luo Rongsen, He Rui, Li Yi

引用次数: 0