Frequency control of power grids has become a relevant research topic due to the massive integration of renewable generation in power systems. Frequency control of traditional thermal generating units with relatively slow ramp rate cannot meet the frequency regulation requirements of power grid. Thus, the inclusion of energy storage system (ESS) at the thermal generation frequency control output can be used to improve the speed of load following and increase the profiles of ancillary service. In this paper, the economic assessment of energy storage system investments in thermal generation station is studied. A methodology has been presented here for the financial calculations of the ESS providing frequency regulation. A numerical case study based on frequency profiles of Yunnan power grid is simulated.
{"title":"Economic Assessment of Energy Storage System Frequency Regulation in Thermal Generation Station","authors":"Tianyu You, Huaye Huang, Ziming He, Sixian Yu, Haiyun Zhu, Weike Mo","doi":"10.1109/ICPES56491.2022.10072912","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072912","url":null,"abstract":"Frequency control of power grids has become a relevant research topic due to the massive integration of renewable generation in power systems. Frequency control of traditional thermal generating units with relatively slow ramp rate cannot meet the frequency regulation requirements of power grid. Thus, the inclusion of energy storage system (ESS) at the thermal generation frequency control output can be used to improve the speed of load following and increase the profiles of ancillary service. In this paper, the economic assessment of energy storage system investments in thermal generation station is studied. A methodology has been presented here for the financial calculations of the ESS providing frequency regulation. A numerical case study based on frequency profiles of Yunnan power grid is simulated.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"5 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":"134589226","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10073063
Lai Zihan, Dai Yuhan, Wen Fuguang
Modern power system shows the characteristics of high proportion of renewable energy and power electronic equipment (referred to as “double high”). Affected by the “double high” characteristics, in addition to power frequency signals, large amount of harmonic and interharmonic signals exist in the system. Resulting in the effect of broadband oscillation by the interaction between those signals of different frequencies and power frequency in the system, which may severely threaten the safe and stable operation of power system. At the current stage, the occurrence of broadband oscillation is mainly determined by measurement of the three-phase instantaneous power. However, the result might be confusing when three-phase imbalance occurs in the system. To solve this, the paper provides a broadband measurement method based on the algorithm of positive sequence instantaneous power, which significantly increases the accuracy of the measurement. This feasibility of the proposed method is verified by implementation results presented in the paper.
{"title":"Broadband Measurement Scheme Based on Positive Sequence Instantaneous Power Algorithm","authors":"Lai Zihan, Dai Yuhan, Wen Fuguang","doi":"10.1109/ICPES56491.2022.10073063","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10073063","url":null,"abstract":"Modern power system shows the characteristics of high proportion of renewable energy and power electronic equipment (referred to as “double high”). Affected by the “double high” characteristics, in addition to power frequency signals, large amount of harmonic and interharmonic signals exist in the system. Resulting in the effect of broadband oscillation by the interaction between those signals of different frequencies and power frequency in the system, which may severely threaten the safe and stable operation of power system. At the current stage, the occurrence of broadband oscillation is mainly determined by measurement of the three-phase instantaneous power. However, the result might be confusing when three-phase imbalance occurs in the system. To solve this, the paper provides a broadband measurement method based on the algorithm of positive sequence instantaneous power, which significantly increases the accuracy of the measurement. This feasibility of the proposed method is verified by implementation results presented in the paper.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"72 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":"117331783","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072489
Han Wu, Yang Yuan, W. Yu, Chao Wu, Hao Huang, Annan Dong
In this paper, a ensemble weather forecasting method based on multi-initial value, multi-mode and multi-physical process, with multiple algorithm perturbations, and BMA+EMOS statistical modeling is proposed. Based on the ensemble weather forecasting method, a new energy probabilistic power prediction method combining taboo algorithm and BP neural network algorithm is proposed. Through the design example analysis, the proposed method can effectively reduce the prediction bias, reduce the upper and lower limit bandwidth of probability prediction by 25%, and overcome the power distribution fat tail and multimodal anomalies, making the power prediction results more stable and accurate.
{"title":"Research on New Energy Probability Prediction Technology Based on Ensemble Weather Forecast","authors":"Han Wu, Yang Yuan, W. Yu, Chao Wu, Hao Huang, Annan Dong","doi":"10.1109/ICPES56491.2022.10072489","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072489","url":null,"abstract":"In this paper, a ensemble weather forecasting method based on multi-initial value, multi-mode and multi-physical process, with multiple algorithm perturbations, and BMA+EMOS statistical modeling is proposed. Based on the ensemble weather forecasting method, a new energy probabilistic power prediction method combining taboo algorithm and BP neural network algorithm is proposed. Through the design example analysis, the proposed method can effectively reduce the prediction bias, reduce the upper and lower limit bandwidth of probability prediction by 25%, and overcome the power distribution fat tail and multimodal anomalies, making the power prediction results more stable and accurate.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"51 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":"116254651","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072301
Qin Fang, Zhoubin Liu, Yuqing Pan, Danlu Xu, Tieyi Chen, Zhiliang Zhang, Bin Li
Hydrogen production from electrolytic water can realize the absorption of new energy, and hydrogen production from new energy electricity has no direct carbon emissions, but the electricity production process will produce different degrees of indirect carbon emissions to hydrogen production from electrolytic water according to different power generation sources. Therefore, this paper takes the carbon price into account in the cost of hydrogen production from electric water, and analyzes the levelized cost of hydrogen production from electrolytic water under different power sources, It is concluded that the total cost of hydrogen production in the low valley electricity electrolysis water hydrogen production process is most sensitive to the carbon price, and the cost of hydrogen production under each power source increases with the carbon price, and gradually slows down.
{"title":"Economic Analysis of Hydrogen Production from Electrolytic Water Considering Carbon Emissions","authors":"Qin Fang, Zhoubin Liu, Yuqing Pan, Danlu Xu, Tieyi Chen, Zhiliang Zhang, Bin Li","doi":"10.1109/ICPES56491.2022.10072301","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072301","url":null,"abstract":"Hydrogen production from electrolytic water can realize the absorption of new energy, and hydrogen production from new energy electricity has no direct carbon emissions, but the electricity production process will produce different degrees of indirect carbon emissions to hydrogen production from electrolytic water according to different power generation sources. Therefore, this paper takes the carbon price into account in the cost of hydrogen production from electric water, and analyzes the levelized cost of hydrogen production from electrolytic water under different power sources, It is concluded that the total cost of hydrogen production in the low valley electricity electrolysis water hydrogen production process is most sensitive to the carbon price, and the cost of hydrogen production under each power source increases with the carbon price, and gradually slows down.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"14 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":"115368059","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}
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.
{"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}
Pub Date : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072439
Jing Chen, Jiandong Duan, Zhenghao Qi, Tong Gao, Yang Zhang
In recent years, the proportion of wind power generation in the grid has become higher and higher. Doubly-fed induction generator (DFIG) has become the mainstream wind turbine of distributed wind farms. For DFIG, large rotor currents and DC bus voltages will be generated when the grid voltage swells. Without protection, the converter may be damaged. It is essential to enhance the fault ride through capability of DFIG and reduce the impact on the stable operation of power grid. Therefore, a high voltage ride-through (HVRT) control strategy considering dynamic reactive power compensation is investigated to address this problem. Firstly, the original control strategy is described. Secondly, variation of the stator flux is considered during the grid fault. Thirdly, the grid-side converter (GSC) and the rotor-side converter (RSC) output reactive current to provide reactive power compensation. Finally, simulation results analyses are conducted by MATLAB/Simulink to evaluate the effectiveness of the proposed strategy.
{"title":"A HVRT Control Strategy for DFIG Considering Dynamic Changes of Stator Flux and Dynamic Reactive Power Compensation","authors":"Jing Chen, Jiandong Duan, Zhenghao Qi, Tong Gao, Yang Zhang","doi":"10.1109/ICPES56491.2022.10072439","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072439","url":null,"abstract":"In recent years, the proportion of wind power generation in the grid has become higher and higher. Doubly-fed induction generator (DFIG) has become the mainstream wind turbine of distributed wind farms. For DFIG, large rotor currents and DC bus voltages will be generated when the grid voltage swells. Without protection, the converter may be damaged. It is essential to enhance the fault ride through capability of DFIG and reduce the impact on the stable operation of power grid. Therefore, a high voltage ride-through (HVRT) control strategy considering dynamic reactive power compensation is investigated to address this problem. Firstly, the original control strategy is described. Secondly, variation of the stator flux is considered during the grid fault. Thirdly, the grid-side converter (GSC) and the rotor-side converter (RSC) output reactive current to provide reactive power compensation. Finally, simulation results analyses are conducted by MATLAB/Simulink to evaluate the effectiveness of the proposed strategy.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"41 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":"124500153","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072679
Yu Xiao, Xing He, Rui Huang, Yuping Su, Suihan Zhang, Mouhai Liu, Wenwei Zeng, Ruixian Wang
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.
{"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}
Pub Date : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072656
Kaihui Feng, Chenhui Song, B. Huang, Jing Hu, Hu Yan, Zihan Meng
While China's new energy maintains a rapid development momentum, grid consumption capacity is facing great challenges. In-depth peak regulation of grid peak regulation units represents a powerful measure for raising the new energy consumption level. This paper proposes an automatic control method for grid peak regulation units to improve the consumption level of new energy power generation. In this method, the relationship between new energy consumption and grid power regulation units is constructed. On this basis, considering the new energy consumption and related costs of various factors involved in grid power regulation unit control, the grid peak regulation unit control method and model are established and a multi-objective particle swarm optimization algorithm is adopted. The simulation results show that the proposed method can refine the control of the output of grid peak regulation units, effectively increase new energy consumption, and urge the grid toward a high security margin.
{"title":"Research on the Automatic Control of Grid Peak Regulation Units to Improve the New Energy Consumption Level","authors":"Kaihui Feng, Chenhui Song, B. Huang, Jing Hu, Hu Yan, Zihan Meng","doi":"10.1109/ICPES56491.2022.10072656","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072656","url":null,"abstract":"While China's new energy maintains a rapid development momentum, grid consumption capacity is facing great challenges. In-depth peak regulation of grid peak regulation units represents a powerful measure for raising the new energy consumption level. This paper proposes an automatic control method for grid peak regulation units to improve the consumption level of new energy power generation. In this method, the relationship between new energy consumption and grid power regulation units is constructed. On this basis, considering the new energy consumption and related costs of various factors involved in grid power regulation unit control, the grid peak regulation unit control method and model are established and a multi-objective particle swarm optimization algorithm is adopted. The simulation results show that the proposed method can refine the control of the output of grid peak regulation units, effectively increase new energy consumption, and urge the grid toward a high security margin.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"5 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":"116430191","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10072580
Tao Luo, Dezheng Zhang, Kui Wang, Zhenchuan Ma, Wenbo Xuan, Haozhong Cheng
URV AC transmission has the characteristics of large capacity, long distance, low loss and effective utilization of transmission corridor. It is an inevitable choice for the development of power grid in China. The operation of UHV AC system will have a considerable impact on the operation economy and stability of power grid, and also put forward new requirements for reactive power planning. In this paper, a two-stage reactive power planning model is proposed, in which the first-stage reactive power planning model aims at the minimization of system operation cost, active power loss and traversing reactive power under normal conditions. The second-stage model is to obtain the optimal reactive power planning scheme with the goal of minimizing the investment cost and the constraint of voltage stability margin under severe faults based on the first-stage planning scheme. Finally, the effectiveness of this model is verified through numerical results.
{"title":"Research on Reactive Power Planning for Power Grid with the Integration of UHV AC System","authors":"Tao Luo, Dezheng Zhang, Kui Wang, Zhenchuan Ma, Wenbo Xuan, Haozhong Cheng","doi":"10.1109/ICPES56491.2022.10072580","DOIUrl":"https://doi.org/10.1109/ICPES56491.2022.10072580","url":null,"abstract":"URV AC transmission has the characteristics of large capacity, long distance, low loss and effective utilization of transmission corridor. It is an inevitable choice for the development of power grid in China. The operation of UHV AC system will have a considerable impact on the operation economy and stability of power grid, and also put forward new requirements for reactive power planning. In this paper, a two-stage reactive power planning model is proposed, in which the first-stage reactive power planning model aims at the minimization of system operation cost, active power loss and traversing reactive power under normal conditions. The second-stage model is to obtain the optimal reactive power planning scheme with the goal of minimizing the investment cost and the constraint of voltage stability margin under severe faults based on the first-stage planning scheme. Finally, the effectiveness of this model is verified through numerical results.","PeriodicalId":425438,"journal":{"name":"2022 12th International Conference on Power and Energy Systems (ICPES)","volume":"191 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":"125344529","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 : 2022-12-23DOI: 10.1109/ICPES56491.2022.10073461
Hanxing Lin, Zihan Chen, Jinyu Chen, Wenxin Chen
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.
{"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}
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