Wind energy （WE） has become immensely popular for distributed generation （DG）. This case presents the monitoring, modeling, control, and analysis of the two-level three-phase WE based DG system where the electric ...Wind energy （WE） has become immensely popular for distributed generation （DG）. This case presents the monitoring, modeling, control, and analysis of the two-level three-phase WE based DG system where the electric grid interfacing custom power device （CPD） is controlled to perform the smart exchanging of electric power as per the Indian grid code. WE is connected to DC link of CPD for the grid integration purpose. The CPD based distributed static compensator, i.e. the distributed static synchronous compensator （DSTATCOM）, is utilized for injecting the wind power to the point of common coupling （PCC） and also acts against the reactive power demand. The novel indirect current control scheme of DSTATCOM regulates the power import and export between the WE and the electric grid system. It also acts as a compensator and performs both the key features simultaneously. Hence, the penetration of additional generated WE power to the grid is increased by 20% to 25%. The burden of reactive power compensation from grid is reduced by DSTATCOM. The modeling and simulation are done in MATLAB. The results are validated and verified.展开更多
As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing custom...As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing customer service pressure,and reducing operating costs.Currently,the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions,and complex user expressions are difficult to understand.To solve the problem of low accuracy of multi-round dialogue semantic understanding,this paper proposes a semantic understanding model based on the fusion of a convolutional neural network(CNN)and attention.The model builds an“intention-slot”joint model based on the“encoding–decoding”framework and uses hidden semantic information that combines intent recognition and slot filling,avoiding the problem of information loss in traditional isolated tasks,and achieving end-to-end semantic understanding.Additionally,an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text,thereby increasing the accuracy of semantic understanding.Finally,by applying the model to electric power intelligent customer service,we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.展开更多
The power system infrastructure, operations and market have gone through radical changes for the last couple of decades. The society has become more dependent to the continuous electric power supply and hence the conc...The power system infrastructure, operations and market have gone through radical changes for the last couple of decades. The society has become more dependent to the continuous electric power supply and hence the concept of electric power reliability has become more significant. At this point, understanding the economic outcomes of power outages is vital and imperative for both utilities and the customers. There are certain methodologies to understand the costs of power interruptions. This paper suggests a novel hybrid method that comprises of customer surveys and direct analytical methods to reach customer specific, objective and reliable results for the industry sector customers. The paper also brings a statistical approach to censor the zero and extreme responses given via the surveys.展开更多
To forecast exactly the key components＇ quantities needed for the mass customization in complex machine manufac-turing,a weighted acyclic networks directed model is constructed,and the power-law distribution of the t...To forecast exactly the key components＇ quantities needed for the mass customization in complex machine manufac-turing,a weighted acyclic networks directed model is constructed,and the power-law distribution of the topological properties for the networks is mined,which makes the relationship between the sum quantities of products and components as well as the relationship between the sum quantities of products and key components clear. The conclusion is that it is an equilibrium network if the time-scale is short and it is a non-equilibrium network if the time-scale is long. As for the evolution law for the components in the mass customiza-tion process,the exponent for equilibrium networks is 0.99 and the exponent for non-equilibrium networks is 1.36.展开更多
文摘Wind energy （WE） has become immensely popular for distributed generation （DG）. This case presents the monitoring, modeling, control, and analysis of the two-level three-phase WE based DG system where the electric grid interfacing custom power device （CPD） is controlled to perform the smart exchanging of electric power as per the Indian grid code. WE is connected to DC link of CPD for the grid integration purpose. The CPD based distributed static compensator, i.e. the distributed static synchronous compensator （DSTATCOM）, is utilized for injecting the wind power to the point of common coupling （PCC） and also acts against the reactive power demand. The novel indirect current control scheme of DSTATCOM regulates the power import and export between the WE and the electric grid system. It also acts as a compensator and performs both the key features simultaneously. Hence, the penetration of additional generated WE power to the grid is increased by 20% to 25%. The burden of reactive power compensation from grid is reduced by DSTATCOM. The modeling and simulation are done in MATLAB. The results are validated and verified.
基金supported by National Natural Science Foundation of China(No.2018YFB0905000).
文摘As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing customer service pressure,and reducing operating costs.Currently,the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions,and complex user expressions are difficult to understand.To solve the problem of low accuracy of multi-round dialogue semantic understanding,this paper proposes a semantic understanding model based on the fusion of a convolutional neural network(CNN)and attention.The model builds an“intention-slot”joint model based on the“encoding–decoding”framework and uses hidden semantic information that combines intent recognition and slot filling,avoiding the problem of information loss in traditional isolated tasks,and achieving end-to-end semantic understanding.Additionally,an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text,thereby increasing the accuracy of semantic understanding.Finally,by applying the model to electric power intelligent customer service,we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.
文摘The power system infrastructure, operations and market have gone through radical changes for the last couple of decades. The society has become more dependent to the continuous electric power supply and hence the concept of electric power reliability has become more significant. At this point, understanding the economic outcomes of power outages is vital and imperative for both utilities and the customers. There are certain methodologies to understand the costs of power interruptions. This paper suggests a novel hybrid method that comprises of customer surveys and direct analytical methods to reach customer specific, objective and reliable results for the industry sector customers. The paper also brings a statistical approach to censor the zero and extreme responses given via the surveys.
文摘To forecast exactly the key components＇ quantities needed for the mass customization in complex machine manufac-turing,a weighted acyclic networks directed model is constructed,and the power-law distribution of the topological properties for the networks is mined,which makes the relationship between the sum quantities of products and components as well as the relationship between the sum quantities of products and key components clear. The conclusion is that it is an equilibrium network if the time-scale is short and it is a non-equilibrium network if the time-scale is long. As for the evolution law for the components in the mass customiza-tion process,the exponent for equilibrium networks is 0.99 and the exponent for non-equilibrium networks is 1.36.
