Probabilistic power flow calculation method considering distributed power supply and electric vehicle access

Abstract

The invention discloses a probabilistic power flow calculation method considering distributed power supply and electric vehicle access. The method comprises steps: a probability model of a distributedpower supply node and an electric vehicle node is established; according to conventional power flow calculation, a power grid connection topology, line impedance, node injection power and other powergrid basic data are obtained; a Latin hypercube sampling method based on a random walk theory is adopted to sample input variables to obtain a sample matrix; according to the relationship between thesample matrix and semi-invariants and an origin matrix, the each-order semi-invariant of the input variable is calculated; a cumulative distribution function of a state variable and a branch power flow is solved through series expansion; and a semi-invariant method is used to calculate the probabilistic power flow. Uncertain power injection of photovoltaic and wind power in the distribution network is considered, random load with the electric vehicle as an example is also considered, the result is more accurate, the calculation precision is high, the sampling speed is quick, and the new energy acceptance ability of the power system is enhanced.

Description

Technical field [0001] The invention belongs to the field of probabilistic power flow calculation methods, and relates to a probabilistic power flow calculation method that takes into account the access of distributed power sources and electric vehicles. Background technique [0002] my country is the third largest country in energy consumption in the world. With the rapid development of productivity, energy consumption is also increasing, among which oil and coal consumption account for a large proportion. However, with the gradual warming of the global climate in recent years and the depletion of petroleum resources, the development of new energy sources is extremely urgent. Since domestic wind power and photovoltaics implemented the Benchmark electricity price system in 2009 and 2013 respectively, the domestic new energy industry has developed rapidly. In 2017, the national installed photovoltaic power generation capacity reached 130,000MW, and the national wind power install...

AI Technical Summary

Problems solved by technology

Among them, the Monte Carlo method uses sampling technology to generate relevant samples, and then performs multiple deterministic power flow calculations to obtain the statistical distribution characteristics of output variables. However, this method has a relatively complicated calculation amount and requires large-scale sampling, which consumes time and cost.

The point estimation method is a probability statistical method to obtain the moments of each order of the output random variable according to the probability distribution of the known input random variable, but this method cannot obtain the cumulative distribution function of the output variable and the accuracy of the moments of each order of the output random variable varies with Decrease with increasing order

The convolution method is to perform convolution calculation according to the probability distribution function of the input random variable, and obtain the probability distribution characteristics of the output random variable, but this method needs to use the convolution formula for calculation, and the mathematical calculation is complicated

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