2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)最新文献_第4页

Temporal Decomposition Transformer for Probabilistic Energy Forecasting 用于概率能量预测的时间分解变压器

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175223

Jiarui Ye, Bo Zhao, Derong Liu

{"title":"Temporal Decomposition Transformer for Probabilistic Energy Forecasting","authors":"Jiarui Ye, Bo Zhao, Derong Liu","doi":"10.1109/ICCSIE55183.2023.10175223","DOIUrl":"https://doi.org/10.1109/ICCSIE55183.2023.10175223","url":null,"abstract":"To ensure the balance of power supply and demand, probabilistic energy forecasting is significant to determine the power generation and dispatch strategies. In order to solve the probabilistic forecasting problem of energy time series, we develop a novel transformer-based decomposition framework, i.e., the temporal decomposition transformer (TDT) to estimate the probability distribution of future time series. TDT achieves accurate and reliable probabilistic forecasting by predicting the mean and standard deviation of time series successively through the decomposition framework. TDT uses the tranformer decoder to capture the temporal feature in the historical time series, and then two tranformer decoders predict the mean and standard deviation of the time series at each future time instant respectively, where the standard deviation is forecasted based on the forecasting of the mean. Finally, the time series probabilistic distribution is modeled by log-likelihood regression. By accomplishing extensive experiments on two real-world energy time series datasets, we conclude that TDT achieves better forecasting accuracy in both point forecasting and probability energy forecasting than compared methods.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131543109","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

Double-layer Robust Optimal Dispatching of Microgrid with flexible resources Based on Data-driven 基于数据驱动的柔性资源微电网双层鲁棒优化调度

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175250

Jiazheng Zhu, Yilin Pan, Yue Zuo, Aodong Dong, Shuai Han, Shuo Zhang

引用次数: 0

Day-Ahead Economic Scheduling Model Considering Spatio-Temporal Flexibility of Data Center and Electric Vehicle 考虑数据中心和电动汽车时空灵活性的日前经济调度模型

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175303

Xiaobing Wang, Wei Li, Han-Chen Wang, Baotong Song, Fangmin Wang, Chunyang Liu

引用次数: 0

Resource Sharing Strategy based on Hierarchical Game in Virtual Power Plant with 5G Base Station 基于分层博弈的5G基站虚拟电厂资源共享策略

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/iccsie55183.2023.10175216

Pei Liu, Qinglai Guo

引用次数: 0

Optimal Operation of DIES Considering Demand Response under Ladder-type Carbon Trading Mechanism 阶梯型碳交易机制下考虑需求响应的die优化运行

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175208

Dongyu Liu, Jun Yang, Zhiliang Wang

{"title":"Optimal Operation of DIES Considering Demand Response under Ladder-type Carbon Trading Mechanism","authors":"Dongyu Liu, Jun Yang, Zhiliang Wang","doi":"10.1109/ICCSIE55183.2023.10175208","DOIUrl":"https://doi.org/10.1109/ICCSIE55183.2023.10175208","url":null,"abstract":"District Integrated Energy System (DIES) are characterized by multiple levels and multiple operators. This makes it difficult to optimize scheduling using traditional centralized methods. In this paper, an optimal dispatch method of DIES considering ladder-type carbon trading mechanism and demand response is proposed. This approach protects the interests and privacy of different stakeholders, smooths load fluctuations, and controls carbon emissions. Firstly, the structural characteristics of multi-energy stations are analyzed, and a demand response model is constructed on the user side of energy stations. Secondly, a two-level optimal scheduling model is constructed. A step carbon trading mechanism is added to the objective function to reduce the total carbon emissions of the system. Finally, we decouple and solve the inter-level optimization sub-problem by using the analysis target cascade (ATC). The simulation results show that the proposed scheduling method can give consideration to the interests of all subjects. It can improve the low carbon of system operation and meet the actual scheduling requirements.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127869521","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 Network Loss Allocation Calculation Based on Arbitrary Segmentation 基于任意分割的网络损耗分配计算研究

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175222

Meng Yu, Botao Zhou, Jun-Ping Gui, Chen Liang, Yao Rao, Rui Xu

引用次数: 0

Feature extraction method of wind turbine unbalance fault based on Hilbert marginal spectrum and information entropy 基于Hilbert边际谱和信息熵的风力发电机不平衡故障特征提取方法

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175266

Yeqin Shao, Zuoxia Xing, Yang Liu, Mingyang Chen, Meng Sun, Xiangdi Miao

{"title":"Feature extraction method of wind turbine unbalance fault based on Hilbert marginal spectrum and information entropy","authors":"Yeqin Shao, Zuoxia Xing, Yang Liu, Mingyang Chen, Meng Sun, Xiangdi Miao","doi":"10.1109/ICCSIE55183.2023.10175266","DOIUrl":"https://doi.org/10.1109/ICCSIE55183.2023.10175266","url":null,"abstract":"In view of the difficulty in feature extraction of wind turbine unbalance fault by traditional methods, and the difficulty in determining the proportion of fault type when a fault occurs, a method was proposed to preprocess the signal containing fault information by five-point cubic smoothing filtering, and then to extract features of wind turbine unbalance fault by combining Hilbert marginal spectrum and information entropy. Combined with wind turbine simulation software GH Bladed, the wind turbine unbalance model of 3MW wind turbine was built, and the fault types were identified by comparing the amplitude changes of 1 times turbine frequency in the marginal spectrum diagram under different working conditions, and then the proportion of each fault type was determined by the value of marginal spectrum entropy. The results show that this method is an effective feature extraction method for impeller unbalance faults, and the marginal spectrum has obvious fault type stratification. The proportion of two kinds of unbalance faults in the occurrence of faults is calculated by combining the theory of information entropy, which provides a theoretical basis for practical engineering applications.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125057553","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

Distributed Optimal Coordination of Microgrid Systems over Unbalanced Digraph 不平衡有向图上微电网系统的分布式最优协调

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175253

Zeli Zhao, Jinliang Ding, Jin‐Xi Zhang

引用次数: 0

Reconfiguration Capability Evaluation and Optimization for Distribution Network Based on Spanning Tree Metrics 基于生成树度量的配电网重构能力评价与优化

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175296

Qingxia Li, Shengjun Huang, Xueyang Zhang, Wenhua Li, Rui Wang, Tao Zhang

引用次数: 0

A Distributed Optimization Strategy for Multienergy Microgrids Considering Nash Bargaining 考虑纳什议价的多能微电网分布式优化策略

2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE) Pub Date : 2023-01-14 DOI: 10.1109/ICCSIE55183.2023.10175263

Fengyuan Sun, Jun Yang, Hanguang Su

{"title":"A Distributed Optimization Strategy for Multienergy Microgrids Considering Nash Bargaining","authors":"Fengyuan Sun, Jun Yang, Hanguang Su","doi":"10.1109/ICCSIE55183.2023.10175263","DOIUrl":"https://doi.org/10.1109/ICCSIE55183.2023.10175263","url":null,"abstract":"This paper investigates the problem of co-optimisation of Multi-energy Microgrids (ME-MGs) under the same distribution network. To this end, a distributed optimization strategy for ME-MGs based on Nash bargaining is proposed. Firstly, a multi-energy microgrid cluster model is established, and a demand response mechanism and a mobile edge computing system are introduced. Then, based on Nash bargaining theory, a distributed optimisation model of the multi-energy microgrid cluster is established. With the objective of maximising the benefits of the alliance between each multi-energy microgrid (ME-MG), the power trading volume between Microgrid operator (MGO) and Distribution network operator (DNO) and it between MGO are solved to obtain the power trading volume. With the objective of maximising the benefits of each ME-MG, the trading electrovalence between MGO is obtained. And the optimisation model is equated into two sub-problems of maximising social benefits and maximising payment benefits. to ensure that the cooperative benefits of the ME-MGs alliance can be fairly distributed among the alliance members. Finally, the alternating direction multiplier method (ADMM) is used to solve the constructed model. The results show that the proposed strategy can effectively improve the operational efficiency of each player.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619805","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