Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.10058570
Kaihui Shen, Yu Cai, Mengdi Zeng
{"title":"Optimal Configuration of New Energy Grid Connected Energy Storage Capacity from the Perspective of Dual Carbon","authors":"Kaihui Shen, Yu Cai, Mengdi Zeng","doi":"10.1504/ijetp.2023.10058570","DOIUrl":"https://doi.org/10.1504/ijetp.2023.10058570","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66772868","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.10058657
Xiaoyu Yang, Xibin Yang, Baoyu Ye
{"title":"Transient security state identification of smart grid based on multi feature fusion","authors":"Xiaoyu Yang, Xibin Yang, Baoyu Ye","doi":"10.1504/ijetp.2023.10058657","DOIUrl":"https://doi.org/10.1504/ijetp.2023.10058657","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66772952","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.134166
Baoyu Ye, Xibin Yang, Xiaoyu Yang
In order to improve the power supply stability of the smart grid and accurately identify the transient safety status of the power grid, a smart grid transient safety status identification method based on multi feature fusion is proposed. Firstly, extract the transient zero sequence active energy features of the smart grid, and use the S transform to extract the transient energy features and comprehensive phase angle features. Secondly, based on the extracted multiple features, a deep belief network (DBN) is used to fuse multiple features. Finally, based on the results of multi feature fusion, the SVM algorithm is used to classify and identify the transient safety status of the power grid. The experimental results show that the transient safety state identification accuracy of this method is high, stable at 98%; and the misjudgement rate of this method has been reduced, with a maximum of no more than 3%.
{"title":"Transient security state identification of smart grid based on multi feature fusion","authors":"Baoyu Ye, Xibin Yang, Xiaoyu Yang","doi":"10.1504/ijetp.2023.134166","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134166","url":null,"abstract":"In order to improve the power supply stability of the smart grid and accurately identify the transient safety status of the power grid, a smart grid transient safety status identification method based on multi feature fusion is proposed. Firstly, extract the transient zero sequence active energy features of the smart grid, and use the S transform to extract the transient energy features and comprehensive phase angle features. Secondly, based on the extracted multiple features, a deep belief network (DBN) is used to fuse multiple features. Finally, based on the results of multi feature fusion, the SVM algorithm is used to classify and identify the transient safety status of the power grid. The experimental results show that the transient safety state identification accuracy of this method is high, stable at 98%; and the misjudgement rate of this method has been reduced, with a maximum of no more than 3%.","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136305328","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.134161
Jing Zeng
Predicting carbon emissions trading prices is of great significance for improving market transparency. Therefore, this paper proposes a carbon emissions trading price prediction method based on claim rights. Firstly, a factor analysis model to determine six factors that affect the price of carbon emission rights is constructed, including the ratio of industrial added value, coal price, maximum temperature, closing price, natural gas closing price, and policy. Then, a transfer rate matrix is constructed based on Markov functions, and a carbon emission rights option price prediction model is constructed using claim rights. Finally, the influence parameters are substituted into the prediction model, and the European call option method is used to determine the equivalent consideration expectations, achieving the transaction price solution. The results show that the prediction error of this method is only +0.0014 yuan/ton, with an accuracy of 96%, indicating that this method can improve the prediction effect of transaction prices.
{"title":"Prediction method of carbon emission trading price based on claim rights","authors":"Jing Zeng","doi":"10.1504/ijetp.2023.134161","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134161","url":null,"abstract":"Predicting carbon emissions trading prices is of great significance for improving market transparency. Therefore, this paper proposes a carbon emissions trading price prediction method based on claim rights. Firstly, a factor analysis model to determine six factors that affect the price of carbon emission rights is constructed, including the ratio of industrial added value, coal price, maximum temperature, closing price, natural gas closing price, and policy. Then, a transfer rate matrix is constructed based on Markov functions, and a carbon emission rights option price prediction model is constructed using claim rights. Finally, the influence parameters are substituted into the prediction model, and the European call option method is used to determine the equivalent consideration expectations, achieving the transaction price solution. The results show that the prediction error of this method is only +0.0014 yuan/ton, with an accuracy of 96%, indicating that this method can improve the prediction effect of transaction prices.","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136304885","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.134160
Man Li Zhao, Zi Qin You, Jing Lu Li
{"title":"Investment benefit evaluation of wind power energy storage based on improved minimum cross entropy method","authors":"Man Li Zhao, Zi Qin You, Jing Lu Li","doi":"10.1504/ijetp.2023.134160","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134160","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136305987","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.10058512
Jing Zeng
{"title":"Prediction Method of Carbon Emission Trading Price Based on Claim Rights","authors":"Jing Zeng","doi":"10.1504/ijetp.2023.10058512","DOIUrl":"https://doi.org/10.1504/ijetp.2023.10058512","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66772543","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.134168
Zeyuan Zhou, Junrong Liu, Linyan Zhou
The continuous operation of the power system generates a large amount of state data. By querying this data, the operation status of the power system can be judged, which is beneficial for improving the stability of the power system operation. Therefore, a multilevel index based big data query method for power system state monitoring is proposed. Firstly, density clustering algorithm is used to cluster the big data of power system status monitoring. Secondly, based on the clustering results, a distance sensitive hash algorithm is used to represent the mapping relationship of data points, and a multilevel index structure is constructed to complete the query of big data for power system status monitoring. The experimental results show that the proposed method reduces the response time of big data queries for power system status monitoring, improves query throughput and accuracy, and achieves a maximum query accuracy of 94.24%.
{"title":"Power system state monitoring big data query based on multilevel index","authors":"Zeyuan Zhou, Junrong Liu, Linyan Zhou","doi":"10.1504/ijetp.2023.134168","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134168","url":null,"abstract":"The continuous operation of the power system generates a large amount of state data. By querying this data, the operation status of the power system can be judged, which is beneficial for improving the stability of the power system operation. Therefore, a multilevel index based big data query method for power system state monitoring is proposed. Firstly, density clustering algorithm is used to cluster the big data of power system status monitoring. Secondly, based on the clustering results, a distance sensitive hash algorithm is used to represent the mapping relationship of data points, and a multilevel index structure is constructed to complete the query of big data for power system status monitoring. The experimental results show that the proposed method reduces the response time of big data queries for power system status monitoring, improves query throughput and accuracy, and achieves a maximum query accuracy of 94.24%.","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136304577","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}
{"title":"Evaluation method for energy saving and emission reduction effects of high energy-consuming enterprises based on K-means clustering","authors":"Liyu Huang, Miaozhuang Cai, Yin Zheng, Yuanliang Zhang","doi":"10.1504/ijetp.2023.134164","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134164","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"335 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136305752","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.10058567
Shudong He, Shuangli Wang
{"title":"Load parameter identification method of power system with time delay based on Kalman filter","authors":"Shudong He, Shuangli Wang","doi":"10.1504/ijetp.2023.10058567","DOIUrl":"https://doi.org/10.1504/ijetp.2023.10058567","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66772702","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}
Pub Date : 2023-01-01DOI: 10.1504/ijetp.2023.134165
Mengdi Zeng, Yu Cai, Kaihui Shen
{"title":"Optimal configuration of new energy grid connected energy storage capacity from the perspective of dual carbon","authors":"Mengdi Zeng, Yu Cai, Kaihui Shen","doi":"10.1504/ijetp.2023.134165","DOIUrl":"https://doi.org/10.1504/ijetp.2023.134165","url":null,"abstract":"","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136305557","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}
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