Because multiple wind farms are connected to the grid at the same time and the total amount of energy in the same wind zone is limited, there is a strong correlation between wind farms with similar geographical locations. Neglecting this correlation can lead to a large difference between wind power analysis and actual operation, which in turn leads to a series of adverse consequences. In this paper, we use nuclear density estimation to establish the edge distribution of wind power output, compare and analyze various Copula functions based on correlation parameters and entropy weight optimization theory. The simulation analysis results show that the Clayton-Copula function is the best correlation function, which can describe the tail part of the random time series more accurately.
This paper attempts to present an optimal design strategy and characteristics of multipolar permanent magnet synchronous motor(MPMSM) with wide power for fully electric drive system(EDS). The structures of stator lamination, rotor lamination and stator winding are analyzed. And how temperature influences the performance of the motor is presented. Moreover, how to calculate air-gap length and the size of permanent magnet of MPMSM are discussed.
The study of regionally integrated energy system optimization problems is of great significance and usefulness for the development of the energy Internet. Regional integrated energy system planning and optimization modeling is the basis for rational system configuration and economical operation. It is one of the key issues in the development of integrated regional energy systems. The optimization of a regionally integrated energy system is studied in this paper. The uncertainty of wind power generation and photovoltaic power generation and the characteristic of CHP is considered. Were established. On this basis, Considering the uncertainty of new energy, a GSHP optimal allocation model based on two-layer optimization is established. A two-level optimization model is introduced. A genetic algorithm is applied to the upper layer, and a genetic algorithm is applied to the lower layer to analyze the nonlinear programming problem. Finally, different system configuration schemes are proposed and computationally solved, combined with examples for case studies to verify the feasibility of the established regional integrated energy system optimization model.
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