Copula theory based energy storage configuration selection method for electric vehicle photovoltaic charging station

A technology for electric vehicles and configuration selection, which is applied in combustion engines, data processing applications, internal combustion piston engines, etc., and can solve problems such as optimal configuration of energy storage systems that do not consider correlation

Active Publication Date: 2016-11-23
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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AI Technical Summary

Problems solved by technology

At present, the traditional energy storage allocation methods do not consider the impact of correlation on the optimal allocation of energy storage systems.

Method used

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  • Copula theory based energy storage configuration selection method for electric vehicle photovoltaic charging station
  • Copula theory based energy storage configuration selection method for electric vehicle photovoltaic charging station
  • Copula theory based energy storage configuration selection method for electric vehicle photovoltaic charging station

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Embodiment Construction

[0022] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0023] In this example, the electric vehicle charging station is equipped with 120 charging piles, and the rated power of a single charging pile is 10kW; the rated capacity of the photovoltaic power generation unit is 800kW; the energy storage unit is composed of lead-acid batteries and supercapacitors.

[0024] Table 1 Energy storage device parameters

[0025]

[0026] 1) Select the output rate of photovoltaic unit and electric vehicle charging load as a random variable, and normalize the measured data. From the frequency histogram, figure 2 , image 3 It can be seen that the sample data is not normally distributed, and non-parametric tests are used to estimate the marginal distribution. This paper uses the kernel density estimation method. Let x1, x2, ..., xn be samples of random variable X, and the calculation formula of pro...

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Abstract

The invention discloses a copula theory based energy storage configuration selection method for an electric vehicle photovoltaic charging station. The method includes steps of selecting photovoltaic units and an electric vehicle charging load capacity as random variables, normalizing measured data and constructing edge distribution of the variables; based on the Copula theory, selecting Gumbel-Copula and Clayton-Copula for constructing a mixed Copula function for describing the relevance of non-symmetric rear molding features among the variables; sampling an annual net load capacity of the photovoltaic charging station on the basis of a joint capacity probability density function; establishing an energy storage optimization configuration model taking the minimization of annual operation cost of the photovoltaic electric vehicle charging state as a target function under the constrains of fluctuation rate, confidence coefficient and the like; performing Matlab programming for optimization computation on the optimal energy storage capacity. Through overall consideration of operation performance and economy, analysis of correctness and practicability of the integrated system energy storage configuration model considering relevance is performed and the optical configuration scheme can be selected, so that the optical energy utilization rate and the system economic benefit can be improved.

Description

technical field [0001] The present invention relates to the field of energy storage configuration selection, and more specifically relates to a Copula theory-based energy storage configuration selection method for electric vehicle photovoltaic charging stations. Background technique [0002] The energy crisis and environmental problems are becoming more and more serious, and the utilization of renewable energy and electric vehicles (Electric Vehicles, EVs) shows great potential in energy saving and emission reduction. The volatility and intermittent characteristics of photovoltaic power generation make it difficult to consume large-scale. The random charging of a large number of electric vehicles will increase the burden on the grid, and the indirect carbon emissions are still not dominant, and the improvement of energy and environmental problems is not obvious. In the urban environment, the typical integration method of building electric vehicle photovoltaic charging stati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06
CPCY02E40/70Y02T10/40Y04S10/50
Inventor 卢锦玲杨月王阳
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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