A Day-Ahead Output Optimization Method of Photovoltaic Distributed Power Sources

Abstract

The invention discloses a photovoltaic distributed type power supply day-ahead output optimization method. A linear auto-regression moving average model capable of predicting parameters in different time frames is designed to obtain a day-ahead environment temperature, day-ahead illumination intensity and day-ahead electrical load; mathematical modeling is performed to obtain the photovoltaic distributed type power supply day-ahead output; the photovoltaic distributed type power supply day-ahead output and the day-ahead electrical load are introduced into power distribution network load flow calculation; a transmission loss approximate quadratic term computational formula is obtained by simplifying the transmission loss calculation in the power distribution network load flow calculation; and a sequence quadratic optimization method is introduced according to the transmission loss approximate quadratic term computational formula so as to fulfill the purpose of optimizing the photovoltaic distributed type power supply day-ahead output at the minimum transmission loss of the power distribution network. According to the optimization method, the prediction precision is improved; due to the prediction on the environment temperature, the illumination intensity and the electrical load, the photovoltaic distributed type power supply output can be adjusted dynamically according to changes of weather factors and electrical load; the derived transmission loss approximate quadratic term computational formula is combined with the sequence quadratic optimization method, so that the transmission loss calculation efficiency is improved; and therefore, engineering practice of the optimization method can be realized easily.

Description

technical field [0001] The invention belongs to the technical field of new energy control, and relates to a method for optimizing the day-ahead output of a photovoltaic distributed power source, in particular to a method for optimizing the day-ahead output of a photovoltaic distributed power source based on a time-sharing prediction parameter linear autoregressive sliding average model. Background technique [0002] In recent years, the rapid development of my country's economy has brought about the rapid growth of electricity load, and the rapid growth of electricity load urgently needs a large amount of electric energy to meet. Traditional centralized power generation mainly relies on coal fossil fuels to generate electricity, and this centralized power generation method has occupied a considerable proportion of electricity production for a long time. However, the global shortage of fossil energy and environmental climate change have put great pressure on the existing cent...

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Problems solved by technology

[0003] The focus of existing research on photovoltaic distributed power is to optimize its access location and access capacity to minimize the distribution network. However, for the uncertainty of photovoltaic distributed Time variation is rarely involved

Therefore, the existing photovoltaic distributed power output optimization method is aimed at the static output and power load scenarios, and it is difficult to meet the random changes of photovoltaic distributed power output and power load distribution network.

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