Pub Date : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952266
Ying Li, Hui Peng, Fan Yang, Shaowei Liang
The problem of voltage sag can be alleviated to some extent by building energy storage power station(ESPS). Therefore, it is necessary to consider the voltage sag level of sensitive users to conduct site selection and capacity allocation of ESPSs. Firstly, the voltage sag severity of sensitive users is evaluated, the sensitive users are graded and quantified, and the comprehensive location coefficient of each node is determined according to the annual economic loss of sensitive users. Secondly, the energy storage cost optimization model, which considers the cost of ESPS itself and the cost of voltage sag detection equipment, is constructed. Thirdly, based on the comprehensive location coefficient of each node, the improved particle swarm optimization algorithm(MPSO) is used to obtain the capacity optimal allocation scheme of ESPS. Finally, the simulation results of IEEE33-bus distribution system show that the method in this paper has good applicability in optimal configuration of ESPS considering voltage sag.
{"title":"Optimal Configuration of Energy Storage Power Station Considering Voltage Sag","authors":"Ying Li, Hui Peng, Fan Yang, Shaowei Liang","doi":"10.1109/ACFPE56003.2022.9952266","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952266","url":null,"abstract":"The problem of voltage sag can be alleviated to some extent by building energy storage power station(ESPS). Therefore, it is necessary to consider the voltage sag level of sensitive users to conduct site selection and capacity allocation of ESPSs. Firstly, the voltage sag severity of sensitive users is evaluated, the sensitive users are graded and quantified, and the comprehensive location coefficient of each node is determined according to the annual economic loss of sensitive users. Secondly, the energy storage cost optimization model, which considers the cost of ESPS itself and the cost of voltage sag detection equipment, is constructed. Thirdly, based on the comprehensive location coefficient of each node, the improved particle swarm optimization algorithm(MPSO) is used to obtain the capacity optimal allocation scheme of ESPS. Finally, the simulation results of IEEE33-bus distribution system show that the method in this paper has good applicability in optimal configuration of ESPS considering voltage sag.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122327888","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952344
Yuan-Yuan Zhang, Shu Xia, Fan Yang
With the signing of the , countries around the world have paid special attention to the construction of green energy, green economy, carbon governance and other aspects and invested a lot of energy in it. China, as one of the important signatories, has made a commitment to the international community to “carbon peak and carbon neutrality”. By drawing on the theoretical methods of carbon emission reduction and carbon emission measurement in supply chains both domestic and abroad, this paper forms a calculation method which is suitable for checking the carbon emissions of the supply chain of power grid enterprises in China. The method is able to calculate and grasp the real carbon emissions of the supply chain of power grid enterprises, so as to enhance the basic ability of power grid enterprises in green transformation, to formulate green carbon emission reduction directions, to help the green transformation of energy supply chains, and to ultimately serve the national double carbon strategy.
{"title":"Research on Carbon Emission Measurement Method Based on Carbon Emission Reduction of Power Grid Supply Chain","authors":"Yuan-Yuan Zhang, Shu Xia, Fan Yang","doi":"10.1109/ACFPE56003.2022.9952344","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952344","url":null,"abstract":"With the signing of the , countries around the world have paid special attention to the construction of green energy, green economy, carbon governance and other aspects and invested a lot of energy in it. China, as one of the important signatories, has made a commitment to the international community to “carbon peak and carbon neutrality”. By drawing on the theoretical methods of carbon emission reduction and carbon emission measurement in supply chains both domestic and abroad, this paper forms a calculation method which is suitable for checking the carbon emissions of the supply chain of power grid enterprises in China. The method is able to calculate and grasp the real carbon emissions of the supply chain of power grid enterprises, so as to enhance the basic ability of power grid enterprises in green transformation, to formulate green carbon emission reduction directions, to help the green transformation of energy supply chains, and to ultimately serve the national double carbon strategy.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115015845","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952286
Junhang Wu, Zhi Tang, Yi Gao, Lianbin Wei, Jin Zhou, Fujia Han, Junyong Liu
Accurate and reliable photovoltaic short term power prediction is of great significance to the improvement of photovoltaic consumption capacity, the day ahead scheduling and the safe and stable operation of the power grid. To ensure an accurate prediction, in this paper, a regional distributed photovoltaic short term power prediction method based on stacking ensemble learning and cluster analysis is proposed. In the proposed method, several weather patterns are firstly identified by using the K-means++ algorithm based on the historical data. Then, for each weather pattern, all the photovoltaic panels are clustered into several groups based on the k-Shape algorithm, where a prediction model for each photovoltaic cluster is established by employing the Stacking ensemble learning algorithm. Finally, based on the numerical weather forecast (NWP) of the forecast day, we select the best suited weather pattern and obtain the final prediction result by employing the trained prediction model under this weather pattern. The effectiveness of the proposed strategy is verified by the actual dataset.
{"title":"Regional Distributed Photovoltaic Short Term Power Prediction Method Based on Cluster Analysis and Stacking Ensemble Learning","authors":"Junhang Wu, Zhi Tang, Yi Gao, Lianbin Wei, Jin Zhou, Fujia Han, Junyong Liu","doi":"10.1109/ACFPE56003.2022.9952286","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952286","url":null,"abstract":"Accurate and reliable photovoltaic short term power prediction is of great significance to the improvement of photovoltaic consumption capacity, the day ahead scheduling and the safe and stable operation of the power grid. To ensure an accurate prediction, in this paper, a regional distributed photovoltaic short term power prediction method based on stacking ensemble learning and cluster analysis is proposed. In the proposed method, several weather patterns are firstly identified by using the K-means++ algorithm based on the historical data. Then, for each weather pattern, all the photovoltaic panels are clustered into several groups based on the k-Shape algorithm, where a prediction model for each photovoltaic cluster is established by employing the Stacking ensemble learning algorithm. Finally, based on the numerical weather forecast (NWP) of the forecast day, we select the best suited weather pattern and obtain the final prediction result by employing the trained prediction model under this weather pattern. The effectiveness of the proposed strategy is verified by the actual dataset.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130758362","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952313
Panlong Jin, Zongchuan Zhou, Xue Feng, Zhiyuan Wang
The carbon peaking and carbon neutrality goals makes the distribution network develop towards low carbon in China, environmental protection and economy, and the demand for new energy power generation resources with zero carbon emission is more urgent. However, how to balance the low-carbon cost and economic cost and realize the scientific planning and access of multiple flexible resource forms such as “source”, “storage” and “load” to the active distribution network (ADN) remains to be solved. Therefore, a bi-level planning model of the ADN was developed, which aims at carbon cost and economy, considering multiple flexible resource access. In the upper level planning, the distributed generations (DGs) and energy storage systems (ESSs) are located and rated with the objective of economy. In the lower level planning, the DG, interruptible load, and ESS are co-optimized with the objective of reducing network loss, and the modified particle swarm optimization algorithm is proposed for solution. The case study results show that the improved solution model can reduce carbon emissions obviously, and ensure the lowest comprehensive cost and realize ADN low-carbon economic operation.
{"title":"The Coordinated Planning of “Source-Load-Storage” Active Distribution Network under Low-carbon Economy","authors":"Panlong Jin, Zongchuan Zhou, Xue Feng, Zhiyuan Wang","doi":"10.1109/ACFPE56003.2022.9952313","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952313","url":null,"abstract":"The carbon peaking and carbon neutrality goals makes the distribution network develop towards low carbon in China, environmental protection and economy, and the demand for new energy power generation resources with zero carbon emission is more urgent. However, how to balance the low-carbon cost and economic cost and realize the scientific planning and access of multiple flexible resource forms such as “source”, “storage” and “load” to the active distribution network (ADN) remains to be solved. Therefore, a bi-level planning model of the ADN was developed, which aims at carbon cost and economy, considering multiple flexible resource access. In the upper level planning, the distributed generations (DGs) and energy storage systems (ESSs) are located and rated with the objective of economy. In the lower level planning, the DG, interruptible load, and ESS are co-optimized with the objective of reducing network loss, and the modified particle swarm optimization algorithm is proposed for solution. The case study results show that the improved solution model can reduce carbon emissions obviously, and ensure the lowest comprehensive cost and realize ADN low-carbon economic operation.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086836","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952186
Li Yue, Fu Yu, Bai Hao, Y. Zhiyong, He Xiaomeng, Jin Qinyuan
A large number of distributed photovoltaic grids have exacerbated the problems of voltage limit, three-phase imbalance and power reversal of the low-voltage distribution network, bringing challenges to the stable operation of the distribution network. Aiming at the problem of absorbing a high proportion of distributed photovoltaics, this paper proposes a space-time coordination based on Voltage Source Converter (VSC) and energy storage by exploiting the power regulation potential of low-voltage AC and DC distribution networks and energy storage. Optimization. Firstly, the power transfer characteristics of VSC and energy storage at the spatial and temporal levels are analyzed; secondly, with the goal of minimizing PV cut-off and network loss, and energy storage and VSC power as optimization variables, a low-voltage AC-DC hybrid distribution is established. Finally, taking a typical low-voltage AC-DC hybrid distribution network as an example, the validity of the proposed method is proved by simulation, and the photovoltaic capacity of the low-voltage distribution network is improved.
{"title":"Low-voltage AC-DC hybrid distribution network for large-scale photovoltaic consumption Space-time Coordinated Optimization Method","authors":"Li Yue, Fu Yu, Bai Hao, Y. Zhiyong, He Xiaomeng, Jin Qinyuan","doi":"10.1109/ACFPE56003.2022.9952186","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952186","url":null,"abstract":"A large number of distributed photovoltaic grids have exacerbated the problems of voltage limit, three-phase imbalance and power reversal of the low-voltage distribution network, bringing challenges to the stable operation of the distribution network. Aiming at the problem of absorbing a high proportion of distributed photovoltaics, this paper proposes a space-time coordination based on Voltage Source Converter (VSC) and energy storage by exploiting the power regulation potential of low-voltage AC and DC distribution networks and energy storage. Optimization. Firstly, the power transfer characteristics of VSC and energy storage at the spatial and temporal levels are analyzed; secondly, with the goal of minimizing PV cut-off and network loss, and energy storage and VSC power as optimization variables, a low-voltage AC-DC hybrid distribution is established. Finally, taking a typical low-voltage AC-DC hybrid distribution network as an example, the validity of the proposed method is proved by simulation, and the photovoltaic capacity of the low-voltage distribution network is improved.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132237017","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952181
Guojun Xiong, Meng Zhu, Hong Fan, Haoran Hu, Zheng Cheng
Relying on the background of power grid digital drive, this paper uses the improved deep learning network model to analyze and predict the load energy consumption of complex systems. In order to provide a complete and reliable sample data set for the multi-layer network model, this paper uses normalization, mutual information and other methods to preprocess the data set, reduce the correlation among different data; At the same time, based on the error reciprocal method, the bidirectional long and short term memory network is combined with the XGboost network model to reduce the calculation error of the model. The simulation experiment is used the actual data set of a city in southern China. The result proves that the index MAPE of the Bi LSTM XGboost forecasting method is 6.15, which can realize the accurate load forecasting of the actual complex system.
{"title":"Short-term load forecasting method based on deep learning under digital driving","authors":"Guojun Xiong, Meng Zhu, Hong Fan, Haoran Hu, Zheng Cheng","doi":"10.1109/ACFPE56003.2022.9952181","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952181","url":null,"abstract":"Relying on the background of power grid digital drive, this paper uses the improved deep learning network model to analyze and predict the load energy consumption of complex systems. In order to provide a complete and reliable sample data set for the multi-layer network model, this paper uses normalization, mutual information and other methods to preprocess the data set, reduce the correlation among different data; At the same time, based on the error reciprocal method, the bidirectional long and short term memory network is combined with the XGboost network model to reduce the calculation error of the model. The simulation experiment is used the actual data set of a city in southern China. The result proves that the index MAPE of the Bi LSTM XGboost forecasting method is 6.15, which can realize the accurate load forecasting of the actual complex system.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134230264","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952256
Pei Su, Huitao Niu, Lidong Wang, Hongyan Zhang, Han Fu, Peiyi Zhang
Clarifying the user's energy demand is the first step to develop integrated energy services. This paper collects multi-dimensional energy consumption data of users and builds an energy demand model for user. Firstly, users' energy consumption data is collected by the monitoring devices, authors identify and correct the abnormal data, and fill in the missing data. Secondly, authors unify the dimensions of different energy consumption data, construct consumption curves of different energies. The demands of different energies for user can be calculated by the areas enclosed by the energy consumption curve. Thirdly, based on different energy demands, the radar map can be obtained. The demand of integrated energy can be calculated by the areas of radar map. Finally, taking 6 users in central China as an example to verify the rationality of the method proposed in this paper.
{"title":"Demand model of single energy and integrated energy for user","authors":"Pei Su, Huitao Niu, Lidong Wang, Hongyan Zhang, Han Fu, Peiyi Zhang","doi":"10.1109/ACFPE56003.2022.9952256","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952256","url":null,"abstract":"Clarifying the user's energy demand is the first step to develop integrated energy services. This paper collects multi-dimensional energy consumption data of users and builds an energy demand model for user. Firstly, users' energy consumption data is collected by the monitoring devices, authors identify and correct the abnormal data, and fill in the missing data. Secondly, authors unify the dimensions of different energy consumption data, construct consumption curves of different energies. The demands of different energies for user can be calculated by the areas enclosed by the energy consumption curve. Thirdly, based on different energy demands, the radar map can be obtained. The demand of integrated energy can be calculated by the areas of radar map. Finally, taking 6 users in central China as an example to verify the rationality of the method proposed in this paper.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133282741","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}
Aiming at the voltage fluctuation and flicker problem caused by renewable energy mass access, a flicker detection and flicker responsibility division method based on the flicker power are proposed in this paper. This method first uses probabilistic neural networks (PNN) and Hilbert-Huang transform (HHT) to get the characteristic information of fluctuation components in power system monitoring data, calculates the power of flicker to locate the flicker, and then proposes the flicker responsibility contribution degree. In addition, the dynamic time-scale calculation method is proposed to reduce the amount of calculation. Finally, the performance of the presented method is validated through Simulink simulation examples.
{"title":"Flicker Source Location and Responsibility Division Method Considering Flicker Power Fluctuation Characteristics","authors":"Ruize Sun, Yuanyuan Sun, Shulin Yin, Shukang Zhao, Guangze Meng, Xiaolei Hou","doi":"10.1109/ACFPE56003.2022.9952315","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952315","url":null,"abstract":"Aiming at the voltage fluctuation and flicker problem caused by renewable energy mass access, a flicker detection and flicker responsibility division method based on the flicker power are proposed in this paper. This method first uses probabilistic neural networks (PNN) and Hilbert-Huang transform (HHT) to get the characteristic information of fluctuation components in power system monitoring data, calculates the power of flicker to locate the flicker, and then proposes the flicker responsibility contribution degree. In addition, the dynamic time-scale calculation method is proposed to reduce the amount of calculation. Finally, the performance of the presented method is validated through Simulink simulation examples.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122011634","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 : 2022-10-01DOI: 10.1109/ACFPE56003.2022.9952246
Wang Shiyu
Green energy has been an attractive and developing area for the whole world, the researchers are trying to tackle its drawbacks like uncertainty and effectiveness. This paper analyzes when the low voltage ride through and anti-islanding protection happened and why they can not coexist. By studying the reasons of voltage drop, the specific design was given in this paper, in which the detection of voltage and frequency can be done. A certain example also shown latter to prove the reliability and quality of the design, this paper also shows more possibilities of the design and its operating mode in other field.
{"title":"A Technical Design for Smart-grid to Realize both Low Voltage Ride Through and Anti-islanding Protection","authors":"Wang Shiyu","doi":"10.1109/ACFPE56003.2022.9952246","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952246","url":null,"abstract":"Green energy has been an attractive and developing area for the whole world, the researchers are trying to tackle its drawbacks like uncertainty and effectiveness. This paper analyzes when the low voltage ride through and anti-islanding protection happened and why they can not coexist. By studying the reasons of voltage drop, the specific design was given in this paper, in which the detection of voltage and frequency can be done. A certain example also shown latter to prove the reliability and quality of the design, this paper also shows more possibilities of the design and its operating mode in other field.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125578415","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 overcome the disadvantages of long regulation time and large overshoot in the traditional marine diesel power main network under complex operating conditions, a hybrid energy storage system is added to the main diesel power network in this paper, the charge and discharge power of the battery and the supercapacitor are changed by the power optimization control strategy. Using MATLAB/Simulink to build the simulation model of marine diesel-storage main network system, the analysis and simulation results show that the overshoot and regulation time of marine diesel-storage main network are obviously reduced after adopting the power optimal control strategy of hybrid energy storage system, at the same time, the charging and discharging power of battery and supercapacitor can be adjusted automatically according to different working conditions.
{"title":"Research on Power Optimal Control Strategy of Marine Diesel-storage","authors":"Jianbao Liu, Shuaijie Shan, Jia-Kun Gao, Zhongtian Zhang","doi":"10.1109/ACFPE56003.2022.9952311","DOIUrl":"https://doi.org/10.1109/ACFPE56003.2022.9952311","url":null,"abstract":"In order to overcome the disadvantages of long regulation time and large overshoot in the traditional marine diesel power main network under complex operating conditions, a hybrid energy storage system is added to the main diesel power network in this paper, the charge and discharge power of the battery and the supercapacitor are changed by the power optimization control strategy. Using MATLAB/Simulink to build the simulation model of marine diesel-storage main network system, the analysis and simulation results show that the overshoot and regulation time of marine diesel-storage main network are obviously reduced after adopting the power optimal control strategy of hybrid energy storage system, at the same time, the charging and discharging power of battery and supercapacitor can be adjusted automatically according to different working conditions.","PeriodicalId":198086,"journal":{"name":"2022 Asian Conference on Frontiers of Power and Energy (ACFPE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126175909","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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