Pub Date : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621391
Encheng Dong, W. Cong, Jian Chen, Ming Chen, Tianyou Yang, Zhen Wei
Aiming at the optimal utilization problem of integrated energy for commercial users, the stepped utilization of energy was firstly analyzed in typical combined cooling, heating and power(CCHP) systems. Secondly, considering the coupling structure of the system and energy utilization characteristics of commercial users, a physical framework of integrated energy system(IES) was set up for multi-energy optimal utilization. Devices of energy production, conversion and storage was modelled on the source side, and meanwhile, on end-user side, load models were built according to space cooling, space heating, hot water and electric. Then, taking into account the time-of-use and costs of operation and maintenance, a mathematical model of IES optimal utilization was established, which was solved by YALMIP/Gurobi. Finally, Case study proves the economy and effectiveness of the proposed optimization strategy.
{"title":"Optimal Utilization Strategy of Integrated Energy for Commercial Users Based on CCHP Coupling","authors":"Encheng Dong, W. Cong, Jian Chen, Ming Chen, Tianyou Yang, Zhen Wei","doi":"10.1109/ICPSAsia52756.2021.9621391","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621391","url":null,"abstract":"Aiming at the optimal utilization problem of integrated energy for commercial users, the stepped utilization of energy was firstly analyzed in typical combined cooling, heating and power(CCHP) systems. Secondly, considering the coupling structure of the system and energy utilization characteristics of commercial users, a physical framework of integrated energy system(IES) was set up for multi-energy optimal utilization. Devices of energy production, conversion and storage was modelled on the source side, and meanwhile, on end-user side, load models were built according to space cooling, space heating, hot water and electric. Then, taking into account the time-of-use and costs of operation and maintenance, a mathematical model of IES optimal utilization was established, which was solved by YALMIP/Gurobi. Finally, Case study proves the economy and effectiveness of the proposed optimization strategy.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125524812","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621659
Zheng Lin, Fei Jiang, Chunming Tu, Zekun Xiao
The construction of a high-proportion new energy power system is conducive to the realization of renewable energy utilization and the achievement of dual-carbon goals. Aiming at the voltage overrun problem caused by large-scale photovoltaic grid-connected in new energy power generation, this paper proposes a distributed coordinated voltage control strategy for photovoltaic and energy storage system based on a dynamic consensus algorithm. The voltage control method of low-voltage distribution network is analyzed, and the distributed control model of photovoltaic and energy storage system is established, which realizes the coordinated control of photovoltaic and energy storage system. The results of the calculation example show that the proposed strategy can effectively coordinate the reactive power control of PV with the active power control of energy storage system, and suppress the voltage overrun problem in the low-voltage distribution network.
{"title":"Distributed Coordinated Voltage Control of Photovoltaic and Energy Storage System Based on Dynamic Consensus Algorithm","authors":"Zheng Lin, Fei Jiang, Chunming Tu, Zekun Xiao","doi":"10.1109/ICPSAsia52756.2021.9621659","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621659","url":null,"abstract":"The construction of a high-proportion new energy power system is conducive to the realization of renewable energy utilization and the achievement of dual-carbon goals. Aiming at the voltage overrun problem caused by large-scale photovoltaic grid-connected in new energy power generation, this paper proposes a distributed coordinated voltage control strategy for photovoltaic and energy storage system based on a dynamic consensus algorithm. The voltage control method of low-voltage distribution network is analyzed, and the distributed control model of photovoltaic and energy storage system is established, which realizes the coordinated control of photovoltaic and energy storage system. The results of the calculation example show that the proposed strategy can effectively coordinate the reactive power control of PV with the active power control of energy storage system, and suppress the voltage overrun problem in the low-voltage distribution network.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134250733","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621549
Shaobo Yang, Liang Meng, C. Su, Jing Tian, Lei Wang, Li Guo
The penetration rate of distributed power sources in the distribution network continues to increase, and the problem of voltage limit violations in the distribution network has gradually become prominent. This paper combines the linearization method and the voltage sensitivity to propose a two-stage linearization voltage regulation strategy. In the first stage, the optimal voltage regulation model is established. Aiming at the problem that the traditional model is difficult to solve by non-convex and nonlinearity, this paper analyzes the influence of transformer taps and distributed power reactive power on network loss and node voltage, and constructs linearized voltage regulation. The model effectively reduces the calculation complexity and calculation time of the optimization problem. In the second stage, in view of the uncertain factors in actual operation, an in-situ compensation based on droop characteristics and a comprehensive voltage adjustment strategy based on voltage sensitivity are proposed. Based on the linearized scheduling results of the first stage, the output of photovoltaic power is reproduced. The regulation ensures the robustness of the voltage regulation algorithm, and the effectiveness of the method proposed in this paper is verified through case analysis.
{"title":"Research on Double-Layer Coupling Voltage Regulation Strategy for Distribution Network Containing High Permeability Distributed Generation","authors":"Shaobo Yang, Liang Meng, C. Su, Jing Tian, Lei Wang, Li Guo","doi":"10.1109/ICPSAsia52756.2021.9621549","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621549","url":null,"abstract":"The penetration rate of distributed power sources in the distribution network continues to increase, and the problem of voltage limit violations in the distribution network has gradually become prominent. This paper combines the linearization method and the voltage sensitivity to propose a two-stage linearization voltage regulation strategy. In the first stage, the optimal voltage regulation model is established. Aiming at the problem that the traditional model is difficult to solve by non-convex and nonlinearity, this paper analyzes the influence of transformer taps and distributed power reactive power on network loss and node voltage, and constructs linearized voltage regulation. The model effectively reduces the calculation complexity and calculation time of the optimization problem. In the second stage, in view of the uncertain factors in actual operation, an in-situ compensation based on droop characteristics and a comprehensive voltage adjustment strategy based on voltage sensitivity are proposed. Based on the linearized scheduling results of the first stage, the output of photovoltaic power is reproduced. The regulation ensures the robustness of the voltage regulation algorithm, and the effectiveness of the method proposed in this paper is verified through case analysis.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133828632","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621550
Haiyang Liu, Xiaobo Ling, Yifan Zhu, Qiyu Tu, Piao Gao, Chenxu Chao, Yaxin Xie, Xiaodong Zheng, N. Tai
Large-scale distributed photovoltaics (DPs) are connected to the distribution network. when a fault happens in the distribution network, the bus voltage at the fault location cannot immediately decrease to zero due to the existence of DPs, which invalidates the criteria of non-voltage detection and synchronism check and impedes the automatic switching of backup power. Therefore, considering the influence of DPs, this paper puts forward a configuration optimization scheme of backup power automatic switching (BPAS) strategy, which allows the BPAS devices in the distribution network with DPs to conduct non-voltage detection and synchronism check. The example analysis shows that the optimized BPAS strategy can effectively improve the load transfer capacity and reduce the cost of BPAS devices.
{"title":"Optimization of Backup Power Automatic Switching Strategy in the Distribution Network with Distributed Photovoltaics","authors":"Haiyang Liu, Xiaobo Ling, Yifan Zhu, Qiyu Tu, Piao Gao, Chenxu Chao, Yaxin Xie, Xiaodong Zheng, N. Tai","doi":"10.1109/ICPSAsia52756.2021.9621550","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621550","url":null,"abstract":"Large-scale distributed photovoltaics (DPs) are connected to the distribution network. when a fault happens in the distribution network, the bus voltage at the fault location cannot immediately decrease to zero due to the existence of DPs, which invalidates the criteria of non-voltage detection and synchronism check and impedes the automatic switching of backup power. Therefore, considering the influence of DPs, this paper puts forward a configuration optimization scheme of backup power automatic switching (BPAS) strategy, which allows the BPAS devices in the distribution network with DPs to conduct non-voltage detection and synchronism check. The example analysis shows that the optimized BPAS strategy can effectively improve the load transfer capacity and reduce the cost of BPAS devices.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"72 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133587094","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}
The power load characteristic index is an industry index that describes the characteristics of the load and the law of load change, and is an important reference basis for the decision-making of the power grid dispatching and planning department. However, the medium and long-term load characteristic index data points are sparse, and the forecasting method that only analyzes the data trend has great limitations. Therefore, it is necessary to consider the external influence factors of the load in the forecasting model to improve the effectiveness and accuracy of the forecast. First, the weight-improved gray correlation analysis method is used in the article to evaluate the degree of influence of external factors such as weather, economy, and society on the load characteristic indicators. The factors with low correlation are removed, and then t-SNE is used. Reduce the dimensions of multiple influencing factors to reduce data redundancy. Then build multiple linear and nonlinear regression models of mid and long term load indicators through generalized regression neural network, and determination of optimal super parameters by one dimensional optimization to achieve mid and long term load characteristic indicators prediction. Finally, the feasibility of the method is verified by using relevant data such as load in a certain area of southwest.
{"title":"Load Index Forecasting Method Based on Nonlinear Dimensionality Reduction of Correlated Factors and Generalized Regression Neural Network Fitting","authors":"Weiting Xu, Yuhong Zhang, Hui Liu, Xuna Liu, Fang Liu, Wei Yang, Shu Zhang","doi":"10.1109/ICPSAsia52756.2021.9621507","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621507","url":null,"abstract":"The power load characteristic index is an industry index that describes the characteristics of the load and the law of load change, and is an important reference basis for the decision-making of the power grid dispatching and planning department. However, the medium and long-term load characteristic index data points are sparse, and the forecasting method that only analyzes the data trend has great limitations. Therefore, it is necessary to consider the external influence factors of the load in the forecasting model to improve the effectiveness and accuracy of the forecast. First, the weight-improved gray correlation analysis method is used in the article to evaluate the degree of influence of external factors such as weather, economy, and society on the load characteristic indicators. The factors with low correlation are removed, and then t-SNE is used. Reduce the dimensions of multiple influencing factors to reduce data redundancy. Then build multiple linear and nonlinear regression models of mid and long term load indicators through generalized regression neural network, and determination of optimal super parameters by one dimensional optimization to achieve mid and long term load characteristic indicators prediction. Finally, the feasibility of the method is verified by using relevant data such as load in a certain area of southwest.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121801416","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621522
Yuanfan Ji, Guangchao Geng, Q. Jiang
Concept drift refers to the relation between input and target envolves over time in an online supervised learning scenario. With the development of smart grid and smart meter, mass data accessibility poses a huge challenge to learning model adaptability. To address such issue, this paper proposed a model adaptability enhancement approaches based on concept drift detection for short-term forecast model. It exploits canonical correlation analysis to measure mapping relation between input and output of the forecast model. Then the correlation coefficient vector sequence will be monitored over an adaptive window to detect concept drift. Model is updated on data over the sliding window only when a concept drift happens. Experimental results shows this method reduces memory assumption and computing resources remarkably meanwhile guarantees the forecast accuracy.
{"title":"Enhancing Model Adaptability Using Concept Drift Detection for Short-Term Load Forecast","authors":"Yuanfan Ji, Guangchao Geng, Q. Jiang","doi":"10.1109/ICPSAsia52756.2021.9621522","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621522","url":null,"abstract":"Concept drift refers to the relation between input and target envolves over time in an online supervised learning scenario. With the development of smart grid and smart meter, mass data accessibility poses a huge challenge to learning model adaptability. To address such issue, this paper proposed a model adaptability enhancement approaches based on concept drift detection for short-term forecast model. It exploits canonical correlation analysis to measure mapping relation between input and output of the forecast model. Then the correlation coefficient vector sequence will be monitored over an adaptive window to detect concept drift. Model is updated on data over the sliding window only when a concept drift happens. Experimental results shows this method reduces memory assumption and computing resources remarkably meanwhile guarantees the forecast accuracy.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116644352","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621742
Hanghang Liu, Juncheng Si, Yuanyuan Wang, W. Song, Yanbin Cai, Qi Liu, Xiaoyi Ma
Photovoltaic power generation is fluctuation and intermittent, and the grid-connected operation of large-scale photovoltaic power plants may have an impact on the safe and stable economic operation of the power system. An effective way to solve the problem is to make scientific forecasts of the output power of PV power plants. In this paper, Back Propagation (BP) and Radial Basis Function (RBF) neural network prediction models are established by using the historical values of actual power generation of Guhe Runneng Photovoltaic Power Station in Gaotang County of Liaocheng City in 2017. According to the characteristics of photovoltaic power fluctuation, the output power is treated as a set of digital signals for short-term PV power prediction, and a prediction model based on the Hilbert Huang Transform (HHT) power data decomposition is proposed. Through the analysis of an example, it can be concluded that after HHT, the prediction effect is significantly improved, and the accuracy of PV power prediction is improved. Moreover, compared with BP neural network, RBF neural network has smaller prediction error.
{"title":"Performance Improvement of Photovoltaic Power Forecasting Model Based on Hilbert Huang Transforsm","authors":"Hanghang Liu, Juncheng Si, Yuanyuan Wang, W. Song, Yanbin Cai, Qi Liu, Xiaoyi Ma","doi":"10.1109/ICPSAsia52756.2021.9621742","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621742","url":null,"abstract":"Photovoltaic power generation is fluctuation and intermittent, and the grid-connected operation of large-scale photovoltaic power plants may have an impact on the safe and stable economic operation of the power system. An effective way to solve the problem is to make scientific forecasts of the output power of PV power plants. In this paper, Back Propagation (BP) and Radial Basis Function (RBF) neural network prediction models are established by using the historical values of actual power generation of Guhe Runneng Photovoltaic Power Station in Gaotang County of Liaocheng City in 2017. According to the characteristics of photovoltaic power fluctuation, the output power is treated as a set of digital signals for short-term PV power prediction, and a prediction model based on the Hilbert Huang Transform (HHT) power data decomposition is proposed. Through the analysis of an example, it can be concluded that after HHT, the prediction effect is significantly improved, and the accuracy of PV power prediction is improved. Moreover, compared with BP neural network, RBF neural network has smaller prediction error.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116729233","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 wide application of distributed generation and advanced power electronic technology, AC / DC hybrid distribution network provides a new idea for the development of distribution network. Therefore, the AC-DC hybrid distribution network planning is of great significance. This paper presents a bi-level programming model of AC / DC distribution network considering the randomness of DC type of bus and connecting line. The model uses Monte Carlo method to simulate the uncertain output curve of load demand and photovoltaic distributed generation, and divides the planning scheme into upper planning model and lower optimization model: the upper planning model uses genetic membrane algorithm, with the lowest grid construction cost and operation cost as the objective function; the lower optimization model uses interior point method, with the lowest operation cost as the objective function. The upper and lower layer models are solved alternately to obtain the optimal network configuration.
{"title":"Bi-level Programming of AC / DC Hybrid Distribution System","authors":"Chunyi Wang, Zijia Ding, Xingyou Zhang, Zhaohui He, Huali Liu, Zhendong Xu","doi":"10.1109/ICPSAsia52756.2021.9621429","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621429","url":null,"abstract":"With the wide application of distributed generation and advanced power electronic technology, AC / DC hybrid distribution network provides a new idea for the development of distribution network. Therefore, the AC-DC hybrid distribution network planning is of great significance. This paper presents a bi-level programming model of AC / DC distribution network considering the randomness of DC type of bus and connecting line. The model uses Monte Carlo method to simulate the uncertain output curve of load demand and photovoltaic distributed generation, and divides the planning scheme into upper planning model and lower optimization model: the upper planning model uses genetic membrane algorithm, with the lowest grid construction cost and operation cost as the objective function; the lower optimization model uses interior point method, with the lowest operation cost as the objective function. The upper and lower layer models are solved alternately to obtain the optimal network configuration.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123764563","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621679
Zhang Xingyou, Wang Yuejiao, Chen Jian, Yu Peng
Based on common characteristic that liquid hydrogen storage system(LHSS) and superconducting magnetic energy storage(SMES) has similar requirement for refrigeration, This paper analyzes advantages of joint operation of LHSS combined SMES system based on their common characteristics. Consider current situation of renewable energy utilization difficulties in recent years, this paper studies the optimal capacity configuration of LHSS combined SMES hybrid energy storage system to maximum use renewable energy. Based on above scene, a time series based method is proposed to simulate the operation scenario of a high penetration renewable energy system, and a capacity optimization method which objects to maximize the economic benefit of hybrid energy storage system is also proposed in this paper. Also, the effectiveness of the proposed strategy is verified by a simple case.
{"title":"The Utility Analysis of LHSS Combined SMES System Considering Capacity Configuration","authors":"Zhang Xingyou, Wang Yuejiao, Chen Jian, Yu Peng","doi":"10.1109/ICPSAsia52756.2021.9621679","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621679","url":null,"abstract":"Based on common characteristic that liquid hydrogen storage system(LHSS) and superconducting magnetic energy storage(SMES) has similar requirement for refrigeration, This paper analyzes advantages of joint operation of LHSS combined SMES system based on their common characteristics. Consider current situation of renewable energy utilization difficulties in recent years, this paper studies the optimal capacity configuration of LHSS combined SMES hybrid energy storage system to maximum use renewable energy. Based on above scene, a time series based method is proposed to simulate the operation scenario of a high penetration renewable energy system, and a capacity optimization method which objects to maximize the economic benefit of hybrid energy storage system is also proposed in this paper. Also, the effectiveness of the proposed strategy is verified by a simple case.","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121940398","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 : 2021-07-18DOI: 10.1109/ICPSAsia52756.2021.9621727
Ye Zhang, Pengfei Li, Xialin Li, Zhiwang Li
Grid-connected dc systems with high penetration of renewable power generations (RPGs) are prone to dc voltage impact and stability issues, especially when connected to a weak ac grid. In order to address these problems, a novel cascaded power and dc voltage control loops based power smoothing control for energy storage system (ESS) has been proposed in this paper. With this method, transient power fluctuations can be compensated, then transmission power of the grid-connected converter (GCC) from dc system to ac grid and dc voltage can be both smoothed. After transient power supporting, the output of ESS can be recovered according to the pre-scheduled power instruction. Moreover, a detailed small signal model of a dc system based on state-space equations has been derived for dynamic and stability analysis. Finally, the effectiveness of the proposed control method is verified by PSCAD/EMPTC based simulation results in a weak grid-connected dc system with GCC, ESS and constant power load (CPL, to simulate RPG or real loads).
{"title":"Power Smoothing Control of Energy Storage System for DC Systems Connected to Weak Grids","authors":"Ye Zhang, Pengfei Li, Xialin Li, Zhiwang Li","doi":"10.1109/ICPSAsia52756.2021.9621727","DOIUrl":"https://doi.org/10.1109/ICPSAsia52756.2021.9621727","url":null,"abstract":"Grid-connected dc systems with high penetration of renewable power generations (RPGs) are prone to dc voltage impact and stability issues, especially when connected to a weak ac grid. In order to address these problems, a novel cascaded power and dc voltage control loops based power smoothing control for energy storage system (ESS) has been proposed in this paper. With this method, transient power fluctuations can be compensated, then transmission power of the grid-connected converter (GCC) from dc system to ac grid and dc voltage can be both smoothed. After transient power supporting, the output of ESS can be recovered according to the pre-scheduled power instruction. Moreover, a detailed small signal model of a dc system based on state-space equations has been derived for dynamic and stability analysis. Finally, the effectiveness of the proposed control method is verified by PSCAD/EMPTC based simulation results in a weak grid-connected dc system with GCC, ESS and constant power load (CPL, to simulate RPG or real loads).","PeriodicalId":296085,"journal":{"name":"2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117196147","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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