Pub Date : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033004
Dian Chen, Runzhao Lu, Xi Wang, Yongcan Wang
For power system calculation and analysis, the accuracy and rationality of operation mode selection is the key to determine the calculation quality. With the access of a high proportion of renewable energy, the traditional manual selection method is not applicable. How to automatically extract the typical operation mode form the data set obtained from production simulation is an urgent scientific and technical problem to be solved. This paper firstly carries out the demand analysis of operation mode extraction of high proportion renewable energy power system. Secondly, an automatic mode extraction algorithm based on K-means++ algorithm and improved cluster validity index is proposed. Then this paper designed a mode extraction approach with joint manual processing and automatic algorithm. Finally, based on the practical data of a region power grid in China, the numerical experiments demonstrate the effectiveness and rationality of the proposed algorithm based on the comparison with the manually selected operation mode from two aspects of mode characteristics and security check. The contribution of the algorithm in improving the level of power system planning was proved.
{"title":"Power System Operation Mode Identification Method Based on Improved Clustering Algorithm","authors":"Dian Chen, Runzhao Lu, Xi Wang, Yongcan Wang","doi":"10.1109/iSPEC54162.2022.10033004","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033004","url":null,"abstract":"For power system calculation and analysis, the accuracy and rationality of operation mode selection is the key to determine the calculation quality. With the access of a high proportion of renewable energy, the traditional manual selection method is not applicable. How to automatically extract the typical operation mode form the data set obtained from production simulation is an urgent scientific and technical problem to be solved. This paper firstly carries out the demand analysis of operation mode extraction of high proportion renewable energy power system. Secondly, an automatic mode extraction algorithm based on K-means++ algorithm and improved cluster validity index is proposed. Then this paper designed a mode extraction approach with joint manual processing and automatic algorithm. Finally, based on the practical data of a region power grid in China, the numerical experiments demonstrate the effectiveness and rationality of the proposed algorithm based on the comparison with the manually selected operation mode from two aspects of mode characteristics and security check. The contribution of the algorithm in improving the level of power system planning was proved.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132227427","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033074
M. Zulfiqar, M. B. Rasheed
In the routine operation of a smart grid (SG), accurate short-term load forecasting (STLF) is paramount. To predict short-term load more effectively, this paper proposes an integrated evolutionary deep learning strategy based on navel feature engineering (FE), long short-term memory (LSTM) network, and Genetic algorithm (GA). First, FE eradicates repetitious and irrelevant attributes to guarantee high computational efficiency. The GA is then used to optimize the parameters (ReLU, MAPE, RMSprop batch size, Number of neurons, and Epoch) of LSTM. The optimized LSTM is used to get the actual STLF results. Furthermore, most literature studies focus on accuracy improvement. At the same time, the importance and productivity of the devised model are confined equally by its convergence rate. Historical load data from the independent system operator (ISO) New England (ISO-NE) energy sector is analyzed to validate the developed hybrid model. The MAPE of the proposed model has a small error value of 0.6710 and the shortest processing time of 159 seconds. The devised model outperforms benchmark models such as the LSTM, LSTM-PSO, LSTM-NSGA-II, and LSTM-GA in aspects of convergence rate and accuracy. In other words, the LSTM errors are effectively decreased by the GA hyperparameter optimization. These results may be helpful as a procedure to shorten the time-consuming process of hyperparameter setting.
{"title":"Short-Term Load Forecasting using Long Short Term Memory Optimized by Genetic Algorithm","authors":"M. Zulfiqar, M. B. Rasheed","doi":"10.1109/iSPEC54162.2022.10033074","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033074","url":null,"abstract":"In the routine operation of a smart grid (SG), accurate short-term load forecasting (STLF) is paramount. To predict short-term load more effectively, this paper proposes an integrated evolutionary deep learning strategy based on navel feature engineering (FE), long short-term memory (LSTM) network, and Genetic algorithm (GA). First, FE eradicates repetitious and irrelevant attributes to guarantee high computational efficiency. The GA is then used to optimize the parameters (ReLU, MAPE, RMSprop batch size, Number of neurons, and Epoch) of LSTM. The optimized LSTM is used to get the actual STLF results. Furthermore, most literature studies focus on accuracy improvement. At the same time, the importance and productivity of the devised model are confined equally by its convergence rate. Historical load data from the independent system operator (ISO) New England (ISO-NE) energy sector is analyzed to validate the developed hybrid model. The MAPE of the proposed model has a small error value of 0.6710 and the shortest processing time of 159 seconds. The devised model outperforms benchmark models such as the LSTM, LSTM-PSO, LSTM-NSGA-II, and LSTM-GA in aspects of convergence rate and accuracy. In other words, the LSTM errors are effectively decreased by the GA hyperparameter optimization. These results may be helpful as a procedure to shorten the time-consuming process of hyperparameter setting.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134070239","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033049
Song Yue, W. Ji, Jiangbo Xu, Junjun Zhang, Shenglong Wang
The use of photovoltaic generation as black-start power supply is of great significance for the black-start in areas with more photovoltaic and less water. However, photovoltaic generation’s ability of black start is limited due to the extreme weather and unstable generation. For the high-proportion renewable energy system based on the solar-storage operation, this paper proposes a black-start method using grid-forming energy storage as the black-start power supply. The grid-forming energy storage can establish the reliable bus voltage for the photovoltaic generation access. Then the solar-storage system can realize the smooth start of the auxiliary equipment for the traditional power plant to restore the supply of significant loads. This process has been verified in a simulation system established in MATLAB/Simulink. During the whole restart process of the auxiliary equipment, frequency varies within 0.2Hz and can be restored to a stable state. It shows that the grid-forming energy storage is a suitable black-start supply for the high-proportion renewable energy system, capable of starting non-self-starting units in the system and providing reliable power for loads.
{"title":"Research on Black Start of High-Proportion Renewable Energy System Based on Solar-Storage Generation System","authors":"Song Yue, W. Ji, Jiangbo Xu, Junjun Zhang, Shenglong Wang","doi":"10.1109/iSPEC54162.2022.10033049","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033049","url":null,"abstract":"The use of photovoltaic generation as black-start power supply is of great significance for the black-start in areas with more photovoltaic and less water. However, photovoltaic generation’s ability of black start is limited due to the extreme weather and unstable generation. For the high-proportion renewable energy system based on the solar-storage operation, this paper proposes a black-start method using grid-forming energy storage as the black-start power supply. The grid-forming energy storage can establish the reliable bus voltage for the photovoltaic generation access. Then the solar-storage system can realize the smooth start of the auxiliary equipment for the traditional power plant to restore the supply of significant loads. This process has been verified in a simulation system established in MATLAB/Simulink. During the whole restart process of the auxiliary equipment, frequency varies within 0.2Hz and can be restored to a stable state. It shows that the grid-forming energy storage is a suitable black-start supply for the high-proportion renewable energy system, capable of starting non-self-starting units in the system and providing reliable power for loads.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115931763","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033066
Shumin Chen, Junda Li, Lingfang Li
Reasonable and scientific charging stations location planning is the prerequisite for electric vehicles application. There are many factors affecting the location of charging stations. Not only the spatial and temporal characteristics of charging load, but also the cost and interests of each market entity should be considered. Based on the prediction of electric vehicle charging load in the temporal dimension, this paper distributes the charging demand spatially. Then the interests of electric vehicle owners, charging station operators and power grid companies is comprehensively considered in the optimization location model. The optimization location model is established with the objective of minimum cost in the whole society and with the constraint to meet the charging demand. At last, a study case is taken to verify the accuracy of the optimization location model.
{"title":"Research on The Method for Optimal Location of Charging Stations Based on The Spatial and Temporal Characteristics of Electric Vehicle Charging Demand","authors":"Shumin Chen, Junda Li, Lingfang Li","doi":"10.1109/iSPEC54162.2022.10033066","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033066","url":null,"abstract":"Reasonable and scientific charging stations location planning is the prerequisite for electric vehicles application. There are many factors affecting the location of charging stations. Not only the spatial and temporal characteristics of charging load, but also the cost and interests of each market entity should be considered. Based on the prediction of electric vehicle charging load in the temporal dimension, this paper distributes the charging demand spatially. Then the interests of electric vehicle owners, charging station operators and power grid companies is comprehensively considered in the optimization location model. The optimization location model is established with the objective of minimum cost in the whole society and with the constraint to meet the charging demand. At last, a study case is taken to verify the accuracy of the optimization location model.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116151072","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033044
Zehua Zhao, F. Luo, Jiajia Yang, G. Ranzi
Widespread deployment of distributed renewable energy sources drives the emergence of the Peer-to-Peer (P2P) energy trading paradigm, which refers to the scenario that energy entities in low-voltage distribution networks trade energy with each other. This paper presents a new system that facilitates P2P energy trading based on both the economic profit/cost and non-economic considerations of the participants. The latter includes the social relationships among the participants and their multi-class energy trading preferences, which are represented by a social network model. Based on this, bidding strategies and market operation mechanisms are developed to support the formation of P2P energy trading transactions. Simulation based on the real-world social media data is conducted to validate the effectiveness of the proposed system.
{"title":"A Peer-to-Peer Energy Trading System Considering Participants’ Social Relationships and Multi-class Preferences","authors":"Zehua Zhao, F. Luo, Jiajia Yang, G. Ranzi","doi":"10.1109/iSPEC54162.2022.10033044","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033044","url":null,"abstract":"Widespread deployment of distributed renewable energy sources drives the emergence of the Peer-to-Peer (P2P) energy trading paradigm, which refers to the scenario that energy entities in low-voltage distribution networks trade energy with each other. This paper presents a new system that facilitates P2P energy trading based on both the economic profit/cost and non-economic considerations of the participants. The latter includes the social relationships among the participants and their multi-class energy trading preferences, which are represented by a social network model. Based on this, bidding strategies and market operation mechanisms are developed to support the formation of P2P energy trading transactions. Simulation based on the real-world social media data is conducted to validate the effectiveness of the proposed system.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116228501","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033047
Liu Haitao, Ma Bingtai, Hao Sipeng, Zhang Kuangyi, Huang Cheng, Lu Heng
In the photovoltaic hybrid energy storage microgrid system, in order to reduce the unreasonable value of decomposition mode number (K) and secondary penalty factor (a) in VMD affect the accuracy of system reconstruction power. A new intelligent algorithm called sooty tern optimization algorithm(STOA) is proposed for the K and a optimization analysis. The parameters of VMD are optimized by STOA to obtain the [K, a] optimal combination quickly and stably, and then the result is applied in VMD to decompose the residual power of microgrid system. So as to improve the coincidence degree between the reconstructed power and the original residual power signal and can allocate the residual power to hybrid energy storage system reasonably, which will be beneficial to optimize the initial power allocation and capacity allocation of hybrid energy storage. This paper analyzes the algorithm and compares it with the results of particle swarm optimization and gray wolf algorithm to verify the effectiveness and superiority of the method.
{"title":"Research on Residual Power Reconfiguration of Hybrid Energy Storage System Based on Microgrid","authors":"Liu Haitao, Ma Bingtai, Hao Sipeng, Zhang Kuangyi, Huang Cheng, Lu Heng","doi":"10.1109/iSPEC54162.2022.10033047","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033047","url":null,"abstract":"In the photovoltaic hybrid energy storage microgrid system, in order to reduce the unreasonable value of decomposition mode number (K) and secondary penalty factor (a) in VMD affect the accuracy of system reconstruction power. A new intelligent algorithm called sooty tern optimization algorithm(STOA) is proposed for the K and a optimization analysis. The parameters of VMD are optimized by STOA to obtain the [K, a] optimal combination quickly and stably, and then the result is applied in VMD to decompose the residual power of microgrid system. So as to improve the coincidence degree between the reconstructed power and the original residual power signal and can allocate the residual power to hybrid energy storage system reasonably, which will be beneficial to optimize the initial power allocation and capacity allocation of hybrid energy storage. This paper analyzes the algorithm and compares it with the results of particle swarm optimization and gray wolf algorithm to verify the effectiveness and superiority of the method.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115127433","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033008
Gaoyang Mou, Jiaqi Huang, Chenye Wu
To achieve the ambitious carbon neutrality goal, it is important to trace the carbon flow in different sectors, especially in the electricity sector, as it is one of the major carbon emitters. Most of the existing literature focuses on carbon accounting in the power generation and delivery processes. Carbon accounting for the demand side is often overlooked because it is rather challenging to handle a large number of consumers in the system. Also, it is commonly believed that consumers with low serving costs are often carbon friendly, implying that there is not much need to conduct carbon accounting on the demand side. In this paper, we propose a new metric to measure the carbon intensity of each consumer based on its load profile and then examine if the common belief holds in practice. Through extensive comparative study, we conclude the conditions under which consumer’s system serving cost and carbon intensity are positively correlated and further exploit the possible reasons for these conditions.
{"title":"Are Consumers with Low Serving Costs Necessarily Carbon Friendly?","authors":"Gaoyang Mou, Jiaqi Huang, Chenye Wu","doi":"10.1109/iSPEC54162.2022.10033008","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033008","url":null,"abstract":"To achieve the ambitious carbon neutrality goal, it is important to trace the carbon flow in different sectors, especially in the electricity sector, as it is one of the major carbon emitters. Most of the existing literature focuses on carbon accounting in the power generation and delivery processes. Carbon accounting for the demand side is often overlooked because it is rather challenging to handle a large number of consumers in the system. Also, it is commonly believed that consumers with low serving costs are often carbon friendly, implying that there is not much need to conduct carbon accounting on the demand side. In this paper, we propose a new metric to measure the carbon intensity of each consumer based on its load profile and then examine if the common belief holds in practice. Through extensive comparative study, we conclude the conditions under which consumer’s system serving cost and carbon intensity are positively correlated and further exploit the possible reasons for these conditions.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123902565","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 : 2022-12-04DOI: 10.1109/iSPEC54162.2022.10033011
Suad S. Al Mattar, S. Alnaser, Sereen Z. Althaher
The increasing dependence on renewable energy particularly solar Photovoltaic (PV) to supply energy consumption needs in Jordan has placed operational challenges on the power system operator to cope with the significant drop in the system’s net-demand and the reduction in synchronous inertia. These challenges were not expected to become critical until the penetration of renewables increases to meet future national energy targets in the forthcoming years. However, the adoption of lockdowns to restrict the outbreak of COVID-19 combined with PV injections reduced the system’s net-demand particularly during daytime in spring 2020 like expected levels in the future with high PV penetration. Thus, the implications of future significant penetration of renewables on system security could be better understood based on the operating conditions during lockdowns. In particular, it is important to assess the system’s frequency adequacy during emergency events that might be occurred whilst running a low-inertia power system. To do so, this paper provides a detailed dynamic frequency analysis of the Jordanian power system during lockdowns using Power Factory software. The results highlight the importance of energy curtailment of renewables to maintain adequate level of synchronous inertia to maintain security when the system is islanded without interconnections to neighboring countries. However, deciding the proper level of curtailment requires performing dynamic analysis to ensure that both the Rate of Change of Frequency (RoCoF) and the minimum frequency level during generation contingency events will not trigger the Under Frequency Load Shedding (UFLS) relays.
{"title":"Dynamic Frequency Analysis of the Jordanian Power System with Significant Penetration of Renewables: Lessons Learnt from the COVID-19 Lockdowns","authors":"Suad S. Al Mattar, S. Alnaser, Sereen Z. Althaher","doi":"10.1109/iSPEC54162.2022.10033011","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033011","url":null,"abstract":"The increasing dependence on renewable energy particularly solar Photovoltaic (PV) to supply energy consumption needs in Jordan has placed operational challenges on the power system operator to cope with the significant drop in the system’s net-demand and the reduction in synchronous inertia. These challenges were not expected to become critical until the penetration of renewables increases to meet future national energy targets in the forthcoming years. However, the adoption of lockdowns to restrict the outbreak of COVID-19 combined with PV injections reduced the system’s net-demand particularly during daytime in spring 2020 like expected levels in the future with high PV penetration. Thus, the implications of future significant penetration of renewables on system security could be better understood based on the operating conditions during lockdowns. In particular, it is important to assess the system’s frequency adequacy during emergency events that might be occurred whilst running a low-inertia power system. To do so, this paper provides a detailed dynamic frequency analysis of the Jordanian power system during lockdowns using Power Factory software. The results highlight the importance of energy curtailment of renewables to maintain adequate level of synchronous inertia to maintain security when the system is islanded without interconnections to neighboring countries. However, deciding the proper level of curtailment requires performing dynamic analysis to ensure that both the Rate of Change of Frequency (RoCoF) and the minimum frequency level during generation contingency events will not trigger the Under Frequency Load Shedding (UFLS) relays.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128636013","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 consumption of traditional energy, renewable energy has gradually become the main force of energy production. To avoid the wind turbines tripping-off caused by the fault of power grid, the renewable energy transmission system usually needs to be equipped with a variety of reactive power compensation devices. To improve the reliability of LVRT (low voltage ride through) of wind turbines under the failure of the sending-end system, a LVRT method for wind turbines based on the cooperative control strategy of multiple reactive power sources is proposed in this paper. Firstly, this paper analyzes the reactive power output capability of the DFIG (doubly fed induction generator) and PMSG (permanent magnetic synchronous generator); and the reactive power output capability of typical reactive compensation devices i.e., SVG (static var generator) and synchronous condenser, is introduced. Secondly, based on the remaining reactive power compensation capacity and response speed of each reactive power source, the voltage regulation participation index defined as VRPI is introduced. Consequently, the cooperative control strategy of multiple reactive power sources is proposed based on the introduced index. Finally, case study of typical fault of the sending-end system integrated with wind turbines is performed, the simulation results show the effectiveness of the proposed cooperative control strategy of multiple reactive power sources.
{"title":"Low Voltage Ride Through Method for Wind Turbines Based on Cooperative Control Strategy of Multiple Reactive Power Sources","authors":"Baoyu Zhai, Guanchu Chen, Shakenbieke Alimasibieke, Shuchao Liang, Z. Cao, Bingtuan Gao","doi":"10.1109/iSPEC54162.2022.10033017","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033017","url":null,"abstract":"With the consumption of traditional energy, renewable energy has gradually become the main force of energy production. To avoid the wind turbines tripping-off caused by the fault of power grid, the renewable energy transmission system usually needs to be equipped with a variety of reactive power compensation devices. To improve the reliability of LVRT (low voltage ride through) of wind turbines under the failure of the sending-end system, a LVRT method for wind turbines based on the cooperative control strategy of multiple reactive power sources is proposed in this paper. Firstly, this paper analyzes the reactive power output capability of the DFIG (doubly fed induction generator) and PMSG (permanent magnetic synchronous generator); and the reactive power output capability of typical reactive compensation devices i.e., SVG (static var generator) and synchronous condenser, is introduced. Secondly, based on the remaining reactive power compensation capacity and response speed of each reactive power source, the voltage regulation participation index defined as VRPI is introduced. Consequently, the cooperative control strategy of multiple reactive power sources is proposed based on the introduced index. Finally, case study of typical fault of the sending-end system integrated with wind turbines is performed, the simulation results show the effectiveness of the proposed cooperative control strategy of multiple reactive power sources.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122617906","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}
During the recovery process of commutation failure, the current command repeatedly enters and exits the voltage dependent current order limiter (VDCOL) control because of the interaction between the DC regulation speed and the AC voltage recovery rate, causing the DC power to oscillate continuously. Concerning this problem, a transient stability analysis method of VDCOL control based on energy variation rate is proposed. Firstly, the paper analyzes the VDCOL control during the recovery process of commutation failure and constructs the voltage recovery equation of the receiving-end power grid. Secondly, according to the model of receiving-end power grid and voltage recovery equation, the energy function is established, and the transient stability of the system during the recovery process of commutation failure is revealed based on the analysis of energy variation rate of DC terminal (in VDCOL control) and other components. Finally, the transient energy trend of the receiving-end power grid is analyzed by building a commutation failure and recovery simulation, and the simulation results illustrate the effectiveness of the proposed transient stability analysis method.
{"title":"Energy Variation Rate-Based Transient Stability Analysis Method for VDCOL Control of HVDC Transmission System","authors":"Z. Cao, Bingtuan Gao, Xiaolin Liu, Xingang Wang, Zhuan Zhou, Feng Zhang","doi":"10.1109/iSPEC54162.2022.10033023","DOIUrl":"https://doi.org/10.1109/iSPEC54162.2022.10033023","url":null,"abstract":"During the recovery process of commutation failure, the current command repeatedly enters and exits the voltage dependent current order limiter (VDCOL) control because of the interaction between the DC regulation speed and the AC voltage recovery rate, causing the DC power to oscillate continuously. Concerning this problem, a transient stability analysis method of VDCOL control based on energy variation rate is proposed. Firstly, the paper analyzes the VDCOL control during the recovery process of commutation failure and constructs the voltage recovery equation of the receiving-end power grid. Secondly, according to the model of receiving-end power grid and voltage recovery equation, the energy function is established, and the transient stability of the system during the recovery process of commutation failure is revealed based on the analysis of energy variation rate of DC terminal (in VDCOL control) and other components. Finally, the transient energy trend of the receiving-end power grid is analyzed by building a commutation failure and recovery simulation, and the simulation results illustrate the effectiveness of the proposed transient stability analysis method.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121543718","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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