In coal-fired power generation industry, parameters such as particle size affect combustion efficiency. Especially in the application of two-phase flow clean energy, the parameters such as particle velocity, particle ...In coal-fired power generation industry, parameters such as particle size affect combustion efficiency. Especially in the application of two-phase flow clean energy, the parameters such as particle velocity, particle size distribution and concentration are very important, because the coal particle velocity, concentration or size range have an impact on the whole combustion process. This paper introduces an optical measurement setup based on the transmission fluctuation correlation spectrum measurement technique, which realizes the simultaneous measurement of particle velocity, particle size distribution and concentration. Compared with image method, ultrasonic spectrum method and other methods, the experimental device is simple and low-cost.展开更多
The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of secur...The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.展开更多
研究多馈入直流电网多重故障集的机理有助于电网安全分析与控制,为此提出考虑发电机调速及负荷电压特性的基于BPA动态潮流连锁故障模式搜索法。基于多馈入有效短路比(multi-infeed effective short circuit ratio,MIESCR)来衡量直流之...研究多馈入直流电网多重故障集的机理有助于电网安全分析与控制,为此提出考虑发电机调速及负荷电压特性的基于BPA动态潮流连锁故障模式搜索法。基于多馈入有效短路比(multi-infeed effective short circuit ratio,MIESCR)来衡量直流之间的相互作用,进而来选择多重故障集的第一层故障。在第一层故障的基础上断开一条输电线路进行动态潮流计算,提出基于平均传输距离、线路功率比和节点电压变化比的加权综合脆弱度指标,用于电网重要交流线路的识别,之后把重要的交流线路作为多重故障集的第二层故障。最后考虑输电线路和发电机保护、直流换相失败甚至闭锁的后续故障,进行连锁故障大停电故障集的构建。对上海电网的仿真表明,所提重要线路的识别方法更为全面;连锁故障大停电多重故障集的构建方法具有的实用性。展开更多
文摘In coal-fired power generation industry, parameters such as particle size affect combustion efficiency. Especially in the application of two-phase flow clean energy, the parameters such as particle velocity, particle size distribution and concentration are very important, because the coal particle velocity, concentration or size range have an impact on the whole combustion process. This paper introduces an optical measurement setup based on the transmission fluctuation correlation spectrum measurement technique, which realizes the simultaneous measurement of particle velocity, particle size distribution and concentration. Compared with image method, ultrasonic spectrum method and other methods, the experimental device is simple and low-cost.
基金supported in part by Science and Technology Projects of Electric Power Research Institute of State Grid Jiangsu Electric Power Co.,Ltd.(J2021171).
文摘The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.
文摘研究多馈入直流电网多重故障集的机理有助于电网安全分析与控制,为此提出考虑发电机调速及负荷电压特性的基于BPA动态潮流连锁故障模式搜索法。基于多馈入有效短路比(multi-infeed effective short circuit ratio,MIESCR)来衡量直流之间的相互作用,进而来选择多重故障集的第一层故障。在第一层故障的基础上断开一条输电线路进行动态潮流计算,提出基于平均传输距离、线路功率比和节点电压变化比的加权综合脆弱度指标,用于电网重要交流线路的识别,之后把重要的交流线路作为多重故障集的第二层故障。最后考虑输电线路和发电机保护、直流换相失败甚至闭锁的后续故障,进行连锁故障大停电故障集的构建。对上海电网的仿真表明,所提重要线路的识别方法更为全面;连锁故障大停电多重故障集的构建方法具有的实用性。
