The paper deals with analysis and synthesis of non-harmonic and non-linear sources and appliances, and their interaction with harmonic power supply network. Basic idea is based on knowledge of harmonic spectrum of the...The paper deals with analysis and synthesis of non-harmonic and non-linear sources and appliances, and their interaction with harmonic power supply network. Basic idea is based on knowledge of harmonic spectrum of the sources and/or appliances, respectively. Obviously, one need to know voltage harmonic components of voltage sources （renewable with inverters,...）, and current harmonic components generated by non-linear appliances （rectifiers,...）. Method of investigation lies on decomposition of real electric circuit into n-harmonic separated equivalent schemes for each harmonic component. Then transient analysis will be done for each scheme separately using ＂impedance harmonic matrices＂. The important fact is that each equivalent scheme is now linearized and therefore easily calculated. Finally, the effects of each investigated schemes arc summed into resulting quantities of real non-linear electric circuit.展开更多
This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a predict...This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a prediction model of multi-source information fusion for large data is established, the fusion prediction of various parameters of the same object is realized. A combined algorithm of Map Reduce and neural network is used in this paper. Using clustering and nonlinear mapping ability of neural network, it can effectively solve the problem of nonlinear objective function approximation, and neural network is applied to the prediction of fusion. In this paper, neural network model using multi layer feed forward network--BP neural network. Simultaneously, to achieve large-scale data sets in parallel computing, the parallelism and real-time property of the algorithm should be considered, further combined with Reduce Map model, to realize the parallel processing of the algorithm, making it more suitable for the study of the fusion of large data. And finally, through simulation, it verifies the feasibility of the proposed model and algorithm.展开更多
文摘The paper deals with analysis and synthesis of non-harmonic and non-linear sources and appliances, and their interaction with harmonic power supply network. Basic idea is based on knowledge of harmonic spectrum of the sources and/or appliances, respectively. Obviously, one need to know voltage harmonic components of voltage sources （renewable with inverters,...）, and current harmonic components generated by non-linear appliances （rectifiers,...）. Method of investigation lies on decomposition of real electric circuit into n-harmonic separated equivalent schemes for each harmonic component. Then transient analysis will be done for each scheme separately using ＂impedance harmonic matrices＂. The important fact is that each equivalent scheme is now linearized and therefore easily calculated. Finally, the effects of each investigated schemes arc summed into resulting quantities of real non-linear electric circuit.
文摘This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a prediction model of multi-source information fusion for large data is established, the fusion prediction of various parameters of the same object is realized. A combined algorithm of Map Reduce and neural network is used in this paper. Using clustering and nonlinear mapping ability of neural network, it can effectively solve the problem of nonlinear objective function approximation, and neural network is applied to the prediction of fusion. In this paper, neural network model using multi layer feed forward network--BP neural network. Simultaneously, to achieve large-scale data sets in parallel computing, the parallelism and real-time property of the algorithm should be considered, further combined with Reduce Map model, to realize the parallel processing of the algorithm, making it more suitable for the study of the fusion of large data. And finally, through simulation, it verifies the feasibility of the proposed model and algorithm.
