2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)最新文献_第7页

Influence Mechanism and Law of Source-Side Factors on Voltage Unbalance in Wind Power Gathering Network 风电集网源侧因素对电压不平衡的影响机理及规律

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759674

Wu Linlin, Liang Yunhong, Wang Xiao, Chen Can, Xu Man, Sun Dawei

引用次数: 0

A Decision-Making Model for Monthly or Ten-Day Time-Sharing Transactions 每月或10天分时交易的决策模型

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759656

Xiaojiang Guo, Xuhui Shen, Jinliang Kong, N. Li, Litao Song, Zheng Zhang, Hao Chen

{"title":"A Decision-Making Model for Monthly or Ten-Day Time-Sharing Transactions","authors":"Xiaojiang Guo, Xuhui Shen, Jinliang Kong, N. Li, Litao Song, Zheng Zhang, Hao Chen","doi":"10.1109/AEEES54426.2022.9759656","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759656","url":null,"abstract":"With the acceleration of the national electric power reform process, the domestic electric energy market is further improved. Among them, in order to realize time-sharing price of full electricity, the medium and long-term time-sharing trading mechanism of electricity market has been gradually carried out. From this, this paper proposes a method and system for assisting decision making of monthly or ten-day timeshare trading. Firstly, the historical data and the data of the medium and long-term contracts are preprocessed by statistical analysis. Secondly, an auxiliary decision model is established with the goal of maximizing day-ahead settlement income. Then, according to the transaction probability of the model, the valuation of the declared electricity quantity is carried out, and the model is constrained by the monthly or ten-day timeshare trading market rules. Finally, combined with operational research method and genetic algorithm, the monthly or ten-day trading assisted decision model is solved. Assist power generation side users to complete monthly or ten-day Bidding on time-sharing and monthly or ten-day Rolling time-sharing trading declaration decision. Through the method proposed in this paper, using the data of a power plant in Shanxi Province, the rolling matching transaction in August and the centralized bidding transaction in the early August are respectively used to make auxiliary decisions. For the rolling matching trading in August, the model's daily income increased by RMB30,700 compared with that reported by the power plant based on manual experience. At the same time, compared with the results of centralized bidding in early August, the estimated earnings increased by RMB53,800. Therefore, it can be seen that the method proposed in this paper is scientific and effective, which can greatly help power plants to improve revenue, maximize economic benefits and liberate human resources.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"25 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":"116756095","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 Flexible Control Strategy Model for Energy Storage System 储能系统柔性控制策略模型

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759586

Shaohua Zhang, Rong Zhang, Xinming Wei, Yunshan Wang, Zhi Cai, Rong Kang

{"title":"A Flexible Control Strategy Model for Energy Storage System","authors":"Shaohua Zhang, Rong Zhang, Xinming Wei, Yunshan Wang, Zhi Cai, Rong Kang","doi":"10.1109/AEEES54426.2022.9759586","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759586","url":null,"abstract":"As the share of wind power participating in the electricity market grows, it is becoming increasingly important to control energy storage systems in order to increase the profitability of wind farms. This paper presents a flexible control model of energy storage system that may be utilized to assist wind farms in controlling energy storage system efficiently in real time, hence improving wind farm controllability and economic benefits. Based on the rolling forecast of ultra-short-term power and real-time electricity prices, the model in this paper can adjust the control strategy of the energy storage system in real time according to actual application scenarios, so as to help wind farms avoid deviation recovery losses and obtain excess profits as much as possible. To begin, a constrained optimization model of an energy storage system is established with the maximization of income generated by energy storage system as the objective function. Then, the CPLEX solver is used to solve the constrained optimization problem. Finally, data from a wind farm in Shanxi Province is used to verify the model proposed in this paper, and the result indicates the reliability and effectiveness of the model.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"51 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":"115645705","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 Transformer District Line Loss Calculation Method Based on Data Mining and Machine Learning 基于数据挖掘和机器学习的变压器区线损计算方法

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759810

Xiaowei Miao, Zhujian Ou, Ming Yang, Jian-ping Yuan, Yue Cao, Shiying Huang, Wangchun Liu

{"title":"A Transformer District Line Loss Calculation Method Based on Data Mining and Machine Learning","authors":"Xiaowei Miao, Zhujian Ou, Ming Yang, Jian-ping Yuan, Yue Cao, Shiying Huang, Wangchun Liu","doi":"10.1109/AEEES54426.2022.9759810","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759810","url":null,"abstract":"Transformer district (TD) line loss is an important economic and technical index for the economic operation of power system. The traditional TD line loss management adopts the uniform fixed interval as a reasonable interval, which is not conducive to lean management. This paper presents an accurate quantization method of TD line loss based on data mining and machine learning. Firstly, the proposed method forms the electrical characteristic index system of TD. On this basis, the proposed method combined the improved K-means method with clustering effect comprehensive evaluation index to obtain the optimal classification results of massive TDs. Then, according to the objective weight extraction method, the key impact factor set of the TD line loss are obtained, so as to obtain the feature images of each TD. Finally, the accurate quantification of TD line loss is realized by the proposed TD line loss calculation model based on the BP neural network and kernel density estimation. The effectiveness of the proposed method are verified by simulations based on the real TD data.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"4 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":"115291807","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

A Multi-dimensional Evaluation Method for Voltage Sag Risk of Regional Grid Sensitive Enterprise 区域电网敏感型企业电压暂降风险的多维评估方法

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759607

Can Wang, Zhihao Ning, Xiaoyuan Wang, Xi Huang, Bo Li

{"title":"A Multi-dimensional Evaluation Method for Voltage Sag Risk of Regional Grid Sensitive Enterprise","authors":"Can Wang, Zhihao Ning, Xiaoyuan Wang, Xi Huang, Bo Li","doi":"10.1109/AEEES54426.2022.9759607","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759607","url":null,"abstract":"Voltage sag has become one of the most serious power quality problems in modern power grid. Voltage sag risk assessment is an important prerequisite for implementing economic and efficient management of voltage sag. This paper presents a multi-dimensional evaluation method for voltage sag risk of regional grid sensitive enterprises. This method takes all of the operating sensitive enterprise as the object, from the perspective of the whole optimization of power grid service area, and gives full consideration to all the fault types of lines of different voltage levels, different ways of erection, as well as to the effects of voltage sag, balanced voltage sag electric load loss and sensitive enterprise economic losses. The multi-dimensional evaluation of voltage sag risk is implemented from the aspects of the voltage sag influence of line fault and the voltage sag risk of sensitive enterprises, which can guide the optimal operation of regional power grid, the differentiated operation and maintenance of lines and the optimal power supply of dual-power sensitive enterprises.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"44 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":"114695176","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

New Energy Converter Control Method Based on the Droop of Hyperbolic Tangent Function 基于双曲正切函数下垂的新型能量变换器控制方法

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759757

Changzhou Yu, Haizhen Xu, Long Shen, Siqi Huang, Chun Liu, Mei-mei Sun, Xing Zhang

引用次数: 1

Detection of Latent Fault in Medium Voltage Distribution Cables Based on Guiding Learning Model 基于引导学习模型的中压配电电缆潜在故障检测

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759678

Xue Chang, Yongliang Liang, J. Lou, Wenshan Zhang, Bingguang Han, J. Zhong, Kejun Li

{"title":"Detection of Latent Fault in Medium Voltage Distribution Cables Based on Guiding Learning Model","authors":"Xue Chang, Yongliang Liang, J. Lou, Wenshan Zhang, Bingguang Han, J. Zhong, Kejun Li","doi":"10.1109/AEEES54426.2022.9759678","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759678","url":null,"abstract":"The latent fault in cables cannot be identified by conventional relay protection due to its short duration and small fault current. In order to prevent it from developing into a permanent fault, it is necessary to detect and identify the latent fault of the cables. The traditional latent fault detection of cables based on the machine learning method needs to mine a large amount of data, but there are few abnormal power data samples. At the same time, this process is prone to overlearning problems. This paper introduces a guiding learning model based on the combination of domain empirical knowledge and machine learning algorithms; the overcurrent detection criterion is constructed by performing Wavelet transform on the fault current to extract the feature quantity, which is used as the empirical knowledge to combine with the Extreme Learning Machine (ELM) model to construct the knowledge function; then PSO algorithm is used to optimize the model, the improvement of the accuracy of the guided learning model proposed in this paper is verified by comparing with the ELM detection model directly optimized by the PSO algorithm.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"46 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":"125466997","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

Evaluation and Application of Energy Efficiency in Electrolytic Aluminum Industry 电解铝工业能效评价与应用

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759692

Dezhi Li, M. Zhong, Hongyin Chen, Yi Guo, Yongfeng Huo, Junjun Shu

引用次数: 1

Research on Photovoltaic Low Voltage Ride through Based on New Model Predictive Control 基于新模型预测控制的光伏低压穿越研究

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759624

Zhe Jing, Haotian Zhang, Peihao Yang, Zipeng Zhou

{"title":"Research on Photovoltaic Low Voltage Ride through Based on New Model Predictive Control","authors":"Zhe Jing, Haotian Zhang, Peihao Yang, Zipeng Zhou","doi":"10.1109/AEEES54426.2022.9759624","DOIUrl":"https://doi.org/10.1109/AEEES54426.2022.9759624","url":null,"abstract":"In order to keep the photovoltaic power generation unit from off grid, the model predictive control (MPC) is used to realize the fast tracking and large-scale regulation of the current when the grid side voltage sag accident occurs. Model predictive control (MPC), As a new control strategy, MPC has been widely concerned in the field of photovoltaic grid connected inverter control because of its strong ability of fast dynamic response, simultaneous control of multiple targets and good output characteristics. However, the control strategy has the problem of large amount of calculation, which requires a higher performance processor, which undoubtedly increases the cost and is not conducive to the promotion of the control algorithm. In order to solve the problem of system steady-state error caused by model parameter mismatching in the regulation process, an adaptive objective function is set to improve the accuracy of reactive power distribution. The above control strategy is simulated by Matlab / Simulink to verify that the proposed scheme can make the PV power station with LVRT capability and more scientific reactive power regulation.","PeriodicalId":252797,"journal":{"name":"2022 4th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"5 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":"127287221","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: 2

Optimal Configuration of Microgrids Based on Fuzzy Scenario Clustering 基于模糊场景聚类的微电网优化配置

2022 4th Asia Energy and Electrical Engineering Symposium (AEEES) Pub Date : 2022-03-25 DOI: 10.1109/AEEES54426.2022.9759806

Haipeng Li, Yang Mi, Jin Deng, Boyang Chen

引用次数: 0