2022 12th International Conference on Power and Energy Systems (ICPES)最新文献_第4页

Economic Assessment of Energy Storage System Frequency Regulation in Thermal Generation Station 热电站储能系统调频的经济性评价

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072912

Tianyu You, Huaye Huang, Ziming He, Sixian Yu, Haiyun Zhu, Weike Mo

引用次数: 0

Broadband Measurement Scheme Based on Positive Sequence Instantaneous Power Algorithm 基于正序瞬时功率算法的宽带测量方案

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10073063

Lai Zihan, Dai Yuhan, Wen Fuguang

引用次数: 0

Research on New Energy Probability Prediction Technology Based on Ensemble Weather Forecast 基于集合天气预报的新型能源概率预测技术研究

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072489

Han Wu, Yang Yuan, W. Yu, Chao Wu, Hao Huang, Annan Dong

引用次数: 1

Economic Analysis of Hydrogen Production from Electrolytic Water Considering Carbon Emissions 考虑碳排放的电解水制氢的经济分析

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072301

Qin Fang, Zhoubin Liu, Yuqing Pan, Danlu Xu, Tieyi Chen, Zhiliang Zhang, Bin Li

引用次数: 0

A K-NN Clustering Based Method to Generate PV Power Series for Power System Analysis under Typhoon 基于K-NN聚类的台风下光伏功率序列生成方法

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10073260

Xun Lu, Yuxuan Tang, Zhifei Guo, Zhihua Gao, Xinmiao Liu, Qihang Zhou

{"title":"A K-NN Clustering Based Method to Generate PV Power Series for Power System Analysis under Typhoon","authors":"Xun Lu, Yuxuan Tang, Zhifei Guo, Zhihua Gao, Xinmiao Liu, Qihang Zhou","doi":"10.1109/ICPES56491.2022.10073260","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10073260","url":null,"abstract":"With the increasing proportion of renewable energy, today's power system become highly sensitive to the weather condition, especially the extreme meteorological events. In order to evaluate the reliability of the power system under extreme meteorological conditions, it is necessary to accurately simulate the power curves of wind farms and PV stations. In this paper, a K-Nearest Neighbors (KNN) clustering based scheme is proposed to generate the multiday power curve of PV stations during typhoon. A two-layer modeling scheme is designed to set up the weather-mode related PV daily curve libraries and the typhoon-related multiple-day curve-mode code libraries according to historical data analysis. In application of the model, an inverse procedure can be carried out to generate the multi-day PV curves of different PV stations under any specified typhoon with retaining of the randomness and diversity. Historical data from the Guangdong power system is applied to verify the model. Results show that the multiday PV power sequences generated by the proposed method well reflect the statistical and time-domain characteristics of the PV stations during the typhoon event.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129942463","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

A HVRT Control Strategy for DFIG Considering Dynamic Changes of Stator Flux and Dynamic Reactive Power Compensation 考虑定子磁链动态变化和动态无功补偿的DFIG HVRT控制策略

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072439

Jing Chen, Jiandong Duan, Zhenghao Qi, Tong Gao, Yang Zhang

引用次数: 0

Prediction of Distributed Photovoltaic Users' Electric Energy Data Based on BP Neural Network Algorithm 基于BP神经网络算法的分布式光伏用户电量数据预测

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072679

Yu Xiao, Xing He, Rui Huang, Yuping Su, Suihan Zhang, Mouhai Liu, Wenwei Zeng, Ruixian Wang

{"title":"Prediction of Distributed Photovoltaic Users' Electric Energy Data Based on BP Neural Network Algorithm","authors":"Yu Xiao, Xing He, Rui Huang, Yuping Su, Suihan Zhang, Mouhai Liu, Wenwei Zeng, Ruixian Wang","doi":"10.1109/ICPES56491.2022.10072679","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072679","url":null,"abstract":"In this paper, a BP neural network (BPN) algorithm model is utilized to forecast the electric energy data of distributed photovoltaic (PV) users. One month's forward active power and voltage data of PV users are collected. The data was collected every hour. So, 24 data were collected every day. Then a BPN algorithm training model are established, First 20 of the days were considered for training data and final 10 days were considered for testing data. Through simulation experiment, the graph of predicted value and actual value of the forward active power and voltage of distributed PV users are obtained. It is concluded that the BPN algorithm model is an accurate model in predicting PV users' data, and the model is more accurate in predicting voltage than in predicting forward active power. The BPN algorithm model could be an effective model for a short-term forecasting of local small distributed PV station output, and has certain significance for the power management department to formulate energy management and dispatching schemes for stability and safekeeping on large grid after PV grid connection.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130907841","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

Research on the Automatic Control of Grid Peak Regulation Units to Improve the New Energy Consumption Level 电网调峰机组自动控制提高新能源消费水平的研究

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072656

Kaihui Feng, Chenhui Song, B. Huang, Jing Hu, Hu Yan, Zihan Meng

引用次数: 0

Research on Reactive Power Planning for Power Grid with the Integration of UHV AC System 特高压交流一体化电网无功规划研究

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10072580

Tao Luo, Dezheng Zhang, Kui Wang, Zhenchuan Ma, Wenbo Xuan, Haozhong Cheng

引用次数: 0

Transient Stability Analysis of AC-DC Hybrid Power Grid under Topology Changes Based on Deep Learning 基于深度学习的交直流混合电网拓扑变化暂态稳定性分析

2022 12th International Conference on Power and Energy Systems (ICPES) Pub Date : 2022-12-23 DOI: 10.1109/ICPES56491.2022.10073461

Hanxing Lin, Zihan Chen, Jinyu Chen, Wenxin Chen

{"title":"Transient Stability Analysis of AC-DC Hybrid Power Grid under Topology Changes Based on Deep Learning","authors":"Hanxing Lin, Zihan Chen, Jinyu Chen, Wenxin Chen","doi":"10.1109/ICPES56491.2022.10073461","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10073461","url":null,"abstract":"Methods based on physical models are difficult to adapt to the current complex power grids, while methods based on traditional deep learning models have insufficient generalization ability to topologically changing scenarios. The development of graph deep learning provides a new idea for transient stability analysis and control under topology changes. Based on the graph convolution aggregation (GraphSAGE) network, this paper proposes a transient stability assessment method for AC-DC hybrid power grids. According to the principle of the graph neural network, the input features are selected and the graph data processing method is designed, and multiple evaluation indicators are established. Based on GraphSAGE network, a model that can effectively learn the topology information of the power system is constructed. Simultaneous evaluation of power angle stability and voltage stability by the model. Example analysis shows that the proposed method has better performance in the face of running scene datasets with frequent topology changes, and has a stronger generalization ability to new unlearned topologies.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127769387","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