Pub Date : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050339
Hongsheng Li, Kun Li, Yang Wang, Fei Liao, F. Gao, Bowu Cai
Loads of smart grids include traditional load and flexible load. The flexible load on the side of China's distribution network mainly consists of electric vehicles and air conditioning load, and the power demand changes with the price of electricity is one of its important features. One of its essential features is the power demand changes with the electricity price. This paper analyzes the characteristics of electric vehicles and air conditioning loads based on the assumption of a complete electricity market. It proposes a hierarchical zonal scheduling architecture and market interaction mechanism for controllable loads based on this. The model treats agents and controllable loads as a non-cooperative game relationship and establishes a two-layer optimization model to coordinate the interests of both parties based on the master-slave game model. The upper-layer model formulates retail electricity prices and power purchase and sales strategies in the real-time market through agents. The lower-layer model uses electric vehicles and air conditioning systems as controllable load research objects to optimize available power strategies by combining dispatchable periods and thermal inertia. Finally, simulation analysis is performed to verify that the proposed master-slave game model guarantees a win-win situation for both users and agents, and results in a 13.5% increase in agency revenue.
{"title":"Hierarchical and Zonal Economic Dispatching Strategy for Flexible Load Considering Electric Vehicles","authors":"Hongsheng Li, Kun Li, Yang Wang, Fei Liao, F. Gao, Bowu Cai","doi":"10.1109/ICPEE56418.2022.10050339","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050339","url":null,"abstract":"Loads of smart grids include traditional load and flexible load. The flexible load on the side of China's distribution network mainly consists of electric vehicles and air conditioning load, and the power demand changes with the price of electricity is one of its important features. One of its essential features is the power demand changes with the electricity price. This paper analyzes the characteristics of electric vehicles and air conditioning loads based on the assumption of a complete electricity market. It proposes a hierarchical zonal scheduling architecture and market interaction mechanism for controllable loads based on this. The model treats agents and controllable loads as a non-cooperative game relationship and establishes a two-layer optimization model to coordinate the interests of both parties based on the master-slave game model. The upper-layer model formulates retail electricity prices and power purchase and sales strategies in the real-time market through agents. The lower-layer model uses electric vehicles and air conditioning systems as controllable load research objects to optimize available power strategies by combining dispatchable periods and thermal inertia. Finally, simulation analysis is performed to verify that the proposed master-slave game model guarantees a win-win situation for both users and agents, and results in a 13.5% increase in agency revenue.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115710073","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050299
Long Chen, Danhong Tang, Lin Chen, Zhongping Liu, Zhongyu Yan, Hui Dong, Ying Ye
At present, photovoltaic power prediction has problems of low prediction accuracy and weak correlation between meteorological factors and power fluctuation process, so a photovoltaic power prediction method based on fluctuating weather identification is proposed in the paper. First, the weather process is initially divided into five types based on PV power fluctuation characteristics, and then the clarity index Kt is introduced to perform weather type cross-segmentation to decompose the full time PV power into smooth process and fluctuation process. Finally, a PV power prediction model is established. The model fully considers the specificity of the deep learning algorithm to classify the fluctuating process and the smooth process, and the simulation results show that the proposed method can effectively improve the prediction accuracy.
{"title":"Photovoltaic Power Prediction Method Based on Fluctuating Weather Identification","authors":"Long Chen, Danhong Tang, Lin Chen, Zhongping Liu, Zhongyu Yan, Hui Dong, Ying Ye","doi":"10.1109/ICPEE56418.2022.10050299","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050299","url":null,"abstract":"At present, photovoltaic power prediction has problems of low prediction accuracy and weak correlation between meteorological factors and power fluctuation process, so a photovoltaic power prediction method based on fluctuating weather identification is proposed in the paper. First, the weather process is initially divided into five types based on PV power fluctuation characteristics, and then the clarity index Kt is introduced to perform weather type cross-segmentation to decompose the full time PV power into smooth process and fluctuation process. Finally, a PV power prediction model is established. The model fully considers the specificity of the deep learning algorithm to classify the fluctuating process and the smooth process, and the simulation results show that the proposed method can effectively improve the prediction accuracy.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122485750","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050315
H Zhao, Zhanlong Zhang, Yongye Wu, Yu Yang, Zijian Dong
The thermal analysis of the power cable in the tunnel is important to evaluate ampacity, improve service life and ensure operation safety. However, the existing research mainly focuses on the influence of installation mode and installation position on the hottest cable and is less concerned about other cables. This paper establishes the temperature calculation model based on Ohm's law and thermal-flow coupling field, considering power cables laid in free air and closed space. The variation rules and influence factors of cable temperature under rated load conditions and different laying conditions are analyzed. The results show that the operation temperature is related to the proximity effect, heat radiation effect, and heat convection effect between cables and other facilities. When the cable is close to other facilities, the maximum temperature deviation is more than 7.0 K. With the increase in distance, the interaction between cables and other facilities gradually attenuates, and the temperature tends to be the condition of the single cable laid in free air. The research results provide suggestions for the modeling method selection of numerical analysis of cable temperature.
{"title":"Thermal Analysis of Power Cable in Tunnel Considering Different Laying Conditions","authors":"H Zhao, Zhanlong Zhang, Yongye Wu, Yu Yang, Zijian Dong","doi":"10.1109/ICPEE56418.2022.10050315","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050315","url":null,"abstract":"The thermal analysis of the power cable in the tunnel is important to evaluate ampacity, improve service life and ensure operation safety. However, the existing research mainly focuses on the influence of installation mode and installation position on the hottest cable and is less concerned about other cables. This paper establishes the temperature calculation model based on Ohm's law and thermal-flow coupling field, considering power cables laid in free air and closed space. The variation rules and influence factors of cable temperature under rated load conditions and different laying conditions are analyzed. The results show that the operation temperature is related to the proximity effect, heat radiation effect, and heat convection effect between cables and other facilities. When the cable is close to other facilities, the maximum temperature deviation is more than 7.0 K. With the increase in distance, the interaction between cables and other facilities gradually attenuates, and the temperature tends to be the condition of the single cable laid in free air. The research results provide suggestions for the modeling method selection of numerical analysis of cable temperature.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128374500","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}
In order to reduce the torque ripple of the tangential magnetizing parallel structure hybrid excitation synchronous motor (TMPS-HESM) and improve the efficiency of the motor. The TMPS-HESM torque ripple model was established by analyzing the stator and rotor magnetic force. Then, using Maxwell & Workbench & optiSLong co-simulation tool, particle swarm optimization (PSO) algorithm was used to optimize the length of the air gap and the width and length of permanent magnet. The optimal solution is screened by sensitivity analysis. The results show that the optimized motor torque ripple and cogging torque are reduced, and the average torque is improved. Meanwhile, the optimization saves the use of permanent magnets, reduces the loss of the motor, and improves the maximum efficiency of the motor to 93%.
{"title":"Research on Electromagnetic Performance Optimization of Tangential Magnetizing Parallel Structure Hybrid Excitation Synchronous Motor Based on Particle Swarm Optimization Algorithm","authors":"Wendong Zhang, Liang Pang, Qingliang Yang, Chaohui Zhao","doi":"10.1109/ICPEE56418.2022.10050269","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050269","url":null,"abstract":"In order to reduce the torque ripple of the tangential magnetizing parallel structure hybrid excitation synchronous motor (TMPS-HESM) and improve the efficiency of the motor. The TMPS-HESM torque ripple model was established by analyzing the stator and rotor magnetic force. Then, using Maxwell & Workbench & optiSLong co-simulation tool, particle swarm optimization (PSO) algorithm was used to optimize the length of the air gap and the width and length of permanent magnet. The optimal solution is screened by sensitivity analysis. The results show that the optimized motor torque ripple and cogging torque are reduced, and the average torque is improved. Meanwhile, the optimization saves the use of permanent magnets, reduces the loss of the motor, and improves the maximum efficiency of the motor to 93%.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124740161","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050275
Jianjun Zhu, X. Zhu, Yanru Zhang, Xiaolei Qi, Zhenjiang Wang, Junjie Zhou, Minghao Li, Chao Jiang, C. Yi
Trap induced non-radiative recombination is thought to be responsible for hysteresis and voltage loss in perovskite solar cells. Compared with interface or surface, bulk perovskite crystal has higher tolerance with trap state. Hence, interface engineering to enhance perovskite based device performance is particularly important to reach theory limitation. Here, we found that the modification of mesoporous TiO2 with KI is an effective way to reduce trap density at the interface between electron transporting layer and perovskite layer. The introduction of KI has no effect on perovskite morphology or charge carrier extraction, but the photo-voltage of devices is increased after KI treatment.
{"title":"Surface Modification of Mesoporous TiO2 with Potassium ion Enhances Photo-Voltage in Perovskite Solar Cell","authors":"Jianjun Zhu, X. Zhu, Yanru Zhang, Xiaolei Qi, Zhenjiang Wang, Junjie Zhou, Minghao Li, Chao Jiang, C. Yi","doi":"10.1109/ICPEE56418.2022.10050275","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050275","url":null,"abstract":"Trap induced non-radiative recombination is thought to be responsible for hysteresis and voltage loss in perovskite solar cells. Compared with interface or surface, bulk perovskite crystal has higher tolerance with trap state. Hence, interface engineering to enhance perovskite based device performance is particularly important to reach theory limitation. Here, we found that the modification of mesoporous TiO2 with KI is an effective way to reduce trap density at the interface between electron transporting layer and perovskite layer. The introduction of KI has no effect on perovskite morphology or charge carrier extraction, but the photo-voltage of devices is increased after KI treatment.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126383184","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050338
Nan Zhang, Jinhua Du
High altitude nuclear electromagnetic pulse (HEMP) can induce a steep pulse voltage with a peak value of up to thousands of kilovolts on an overhead power line, and the frequency is up to 100MHz, which is far beyond the amplitude and frequency range of traditional steep pulse voltage. Therefore, it is necessary to establish a ultrawide band model of the transformer to evaluate its insulation ability to HEMP. Firstly, a frequency-dependent distribution parameter model is established based on the skin effect of conductor and dielectric properties of oiled paper. Secondly, the ultra-wide band fractional multi-conductor transmission line model is established considering frequency-dependent distribution parameter model, and solved through the finite difference time domain (FDTD). Then, a simple model is taken as an example to compare the results of the electromagnetic simulation software with the model to verify the feasibility of the model. Finally, an oil-immersed transformer is modeled and calculated to obtain the law of voltage distribution. The current research on HEMP does not consider enough frequency-varying characteristics, the model can produce a more accurate database for the design of the transformer anti-HEMP system.
{"title":"Ultra-wide Band Modeling and Over-voltage Analysis of High Altitude Nuclear Electromagnetic Pulse on Transformer","authors":"Nan Zhang, Jinhua Du","doi":"10.1109/ICPEE56418.2022.10050338","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050338","url":null,"abstract":"High altitude nuclear electromagnetic pulse (HEMP) can induce a steep pulse voltage with a peak value of up to thousands of kilovolts on an overhead power line, and the frequency is up to 100MHz, which is far beyond the amplitude and frequency range of traditional steep pulse voltage. Therefore, it is necessary to establish a ultrawide band model of the transformer to evaluate its insulation ability to HEMP. Firstly, a frequency-dependent distribution parameter model is established based on the skin effect of conductor and dielectric properties of oiled paper. Secondly, the ultra-wide band fractional multi-conductor transmission line model is established considering frequency-dependent distribution parameter model, and solved through the finite difference time domain (FDTD). Then, a simple model is taken as an example to compare the results of the electromagnetic simulation software with the model to verify the feasibility of the model. Finally, an oil-immersed transformer is modeled and calculated to obtain the law of voltage distribution. The current research on HEMP does not consider enough frequency-varying characteristics, the model can produce a more accurate database for the design of the transformer anti-HEMP system.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133946247","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050331
Thamer A. H. Alghamdi, Fatih Anayi
Practically, it is difficult to estimate the real harmonic emissions of a grid-connected solar Photovoltaic (PV) power inverter using conventional metering systems. As a result, the authors have recently suggested a strategy that uses an Artificial Neural Network (ANN) system and incorporates location-specific data. This paper compares the performance and computational requirements of various neural networks, including Multilayer Perceptron (MLP), Recurrent Neural Networks (RNN), Echo State Networks (ESN), Linear Auto-Regressive eXogenous (NARX), and Adaptive Wavelet Neural Network (AWNN) systems, to assess the effectiveness of various neural network structures for this application. It has been shown that compared to the NARX and AWNN, the MLP, RNN, and ESN have superior prediction accuracy and require less training and prediction time with a comparatively fewer number of neurons.
{"title":"Performance of Different Structures of Artificial Neural Network Systems for Harmonic Estimation of Grid-Tied Power Conversion Systems","authors":"Thamer A. H. Alghamdi, Fatih Anayi","doi":"10.1109/ICPEE56418.2022.10050331","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050331","url":null,"abstract":"Practically, it is difficult to estimate the real harmonic emissions of a grid-connected solar Photovoltaic (PV) power inverter using conventional metering systems. As a result, the authors have recently suggested a strategy that uses an Artificial Neural Network (ANN) system and incorporates location-specific data. This paper compares the performance and computational requirements of various neural networks, including Multilayer Perceptron (MLP), Recurrent Neural Networks (RNN), Echo State Networks (ESN), Linear Auto-Regressive eXogenous (NARX), and Adaptive Wavelet Neural Network (AWNN) systems, to assess the effectiveness of various neural network structures for this application. It has been shown that compared to the NARX and AWNN, the MLP, RNN, and ESN have superior prediction accuracy and require less training and prediction time with a comparatively fewer number of neurons.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124388410","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050284
Liu Zhuangzhuang, Wang Xiang, Chen Guofu, Mu Xiaobin
The composite load model parameters can be identified using the small disturbance signals in PMU (Phasor Measurement Unit, PMU) measurements, and the quality of PMU measurement data greatly influences load parameter identification results. In this paper, we propose a PMU measurement data processing method that applies to the two-stage identification algorithm of the integrated load model parameters. The PMU measurement data are firstly screened, pre-processed, coarsely screened, and denoised to obtain a better quality PMU data set. Subsequently, feasibility analysis and spectral analysis are performed on the measured data. Further, the wavelet denoising algorithm is used to reduce the influence of Gaussian noise on parameter identification. Finally, the effectiveness of the proposed method is verified by the measured data of the Tongxin and Quan Tang substations of the Hunan Power Grid. The proposed method can improve the quality of PMU data and, thus, the accuracy of the two-stage parameter identification algorithm.
PMU(相量测量单元，Phasor Measurement Unit, PMU)测量中的小扰动信号可用于复合负荷模型参数辨识，而PMU测量数据的质量对负荷参数辨识结果影响很大。本文提出了一种适用于综合负荷模型参数两阶段辨识算法的PMU测量数据处理方法。首先对PMU测量数据进行筛选、预处理、粗筛选和去噪，得到质量较好的PMU数据集。随后，对实测数据进行了可行性分析和光谱分析。在此基础上，利用小波去噪算法降低高斯噪声对参数识别的影响。最后，通过湖南电网同心和泉塘变电站的实测数据验证了所提方法的有效性。该方法可以提高PMU数据的质量，从而提高两阶段参数识别算法的准确性。
{"title":"Phasor Measurement Unit Measurement Data Processing Method Applied to a Two-Stage Identification Algorithm for Load Model Parameters","authors":"Liu Zhuangzhuang, Wang Xiang, Chen Guofu, Mu Xiaobin","doi":"10.1109/ICPEE56418.2022.10050284","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050284","url":null,"abstract":"The composite load model parameters can be identified using the small disturbance signals in PMU (Phasor Measurement Unit, PMU) measurements, and the quality of PMU measurement data greatly influences load parameter identification results. In this paper, we propose a PMU measurement data processing method that applies to the two-stage identification algorithm of the integrated load model parameters. The PMU measurement data are firstly screened, pre-processed, coarsely screened, and denoised to obtain a better quality PMU data set. Subsequently, feasibility analysis and spectral analysis are performed on the measured data. Further, the wavelet denoising algorithm is used to reduce the influence of Gaussian noise on parameter identification. Finally, the effectiveness of the proposed method is verified by the measured data of the Tongxin and Quan Tang substations of the Hunan Power Grid. The proposed method can improve the quality of PMU data and, thus, the accuracy of the two-stage parameter identification algorithm.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123893218","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}
Severe wind turbine outage events due to the triggering of low-temperature protections greatly threatened the power supply safety. However, little is known on the occurrence pattern of such rare but extreme events, which is, however, important information for reserve planning to system operators. Focusing on annual maximum outage capacity (AMOC), this paper introduces return level and return period as key indicators to depict the consequence and the frequency respectively. A probabilistic model is necessary for calculating return level. However, the limited records challenge the distribution modeling. This paper proposes a generalized extreme value (GEV) distribution model with augmented samples as inputs. Augmented samples are obtained by combining the low-temperature protection settings of wind turbines with the spatially interpolated temperature sequences covering decades via Thiessen polygon division. The parameters of GEV distribution are inferred by Markov Chain Monte Carlo (MCMC)-based Bayes estimation method. Abundant parameter samples can be derived to facilitate the confidence interval evaluation of return levels of the AMOC, and the uncertainty in the parameter inference by small-size samples can be accounted for. Case studies based on actual data of China validate the effectiveness of the proposed method, and the findings fill the present knowledge gap.
{"title":"Evaluation of Annual Maximum Wind Power Outage Capacity Induced by Extremely Low Temperature Using Generalized Extreme Value Distribution","authors":"Yisha Lin, Ying Qiao, Zongxiang Lu, Jian Yang, Ziniu Xiao, Zhenyu Li","doi":"10.1109/ICPEE56418.2022.10050278","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050278","url":null,"abstract":"Severe wind turbine outage events due to the triggering of low-temperature protections greatly threatened the power supply safety. However, little is known on the occurrence pattern of such rare but extreme events, which is, however, important information for reserve planning to system operators. Focusing on annual maximum outage capacity (AMOC), this paper introduces return level and return period as key indicators to depict the consequence and the frequency respectively. A probabilistic model is necessary for calculating return level. However, the limited records challenge the distribution modeling. This paper proposes a generalized extreme value (GEV) distribution model with augmented samples as inputs. Augmented samples are obtained by combining the low-temperature protection settings of wind turbines with the spatially interpolated temperature sequences covering decades via Thiessen polygon division. The parameters of GEV distribution are inferred by Markov Chain Monte Carlo (MCMC)-based Bayes estimation method. Abundant parameter samples can be derived to facilitate the confidence interval evaluation of return levels of the AMOC, and the uncertainty in the parameter inference by small-size samples can be accounted for. Case studies based on actual data of China validate the effectiveness of the proposed method, and the findings fill the present knowledge gap.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127775434","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 : 2022-11-25DOI: 10.1109/ICPEE56418.2022.10050328
Xingdong Wang, Lei Ma, Jincheng Yang, Xi Yang
The demand response (DR) equipment with limited resources on the user side uses the OpenADR protocol based on HTTP / XML to carry the DRservice, which will cause problems of large overhead and high delay. In order to solve this problem, the lightweight protocol constrained application protocol (CoAP) is used to replace HTTP protocol to complete the process of demand response information interaction, and a DR communication architecture based on CoAP is designed. At the same time, aiming at the problems that the congestion control mode of CoAP protocol is too simple and facing high concurrent DR services may cause network congestion and long response delay, an adaptive congestion control method based on network state is proposed. Simulation results show that CoAP protocol can effectively improve DR real-time response ability and reduce overhead. The proposed congestion control algorithm can alleviate the problem of network congestion, so as to improve the performance of DR service carried by CoAP protocol.
{"title":"Optimization of Interactive Demand Response Information Model for Adjustable Load Platform","authors":"Xingdong Wang, Lei Ma, Jincheng Yang, Xi Yang","doi":"10.1109/ICPEE56418.2022.10050328","DOIUrl":"https://doi.org/10.1109/ICPEE56418.2022.10050328","url":null,"abstract":"The demand response (DR) equipment with limited resources on the user side uses the OpenADR protocol based on HTTP / XML to carry the DRservice, which will cause problems of large overhead and high delay. In order to solve this problem, the lightweight protocol constrained application protocol (CoAP) is used to replace HTTP protocol to complete the process of demand response information interaction, and a DR communication architecture based on CoAP is designed. At the same time, aiming at the problems that the congestion control mode of CoAP protocol is too simple and facing high concurrent DR services may cause network congestion and long response delay, an adaptive congestion control method based on network state is proposed. Simulation results show that CoAP protocol can effectively improve DR real-time response ability and reduce overhead. The proposed congestion control algorithm can alleviate the problem of network congestion, so as to improve the performance of DR service carried by CoAP protocol.","PeriodicalId":404319,"journal":{"name":"2022 6th International Conference on Power and Energy Engineering (ICPEE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133928380","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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