On-line control method of big climbing rate event of battery energy storage stabilized photovoltaic power generation

Abstract

The invention discloses an on-line control method of a big climbing rate event of battery energy storage stabilized photovoltaic power generation. The on-line control method of the big climbing rate event of battery energy storage stabilized photovoltaic power generation comprises the following steps: confirming MPC control variables based on the statistical results of the duration of climbing events throughout a year, wherein the MPC control variables comprise control period, control time domain and optimizing time domain; confirming charging and discharging rules according to the energy storage capacity of the energy storage system and the photovoltaic climbing rate in the MPC control time domain; confirming the action state of the energy storage system at the next moment; establishing aMPC optimizing control model; and executing the calculation results by the energy storage system according to the idea of rolling optimization. According to the invention, the stabilizing is performed only aiming at the big climbing rate events that the photovoltaic output fluctuation exceeds a certain range, therefore, the configuration capacity and charging and discharging times of the energy storage system can be reduced; and the control error for the energy storage system is reduced through continuous rolling optimization, therefore, photovoltaic power generation can be effectively stabilized.

Description

technical field [0001] The invention relates to an online control method for battery energy storage to stabilize a large ramp-up event of photovoltaic power generation. Background technique [0002] With environmental pollution and energy crisis, photovoltaic power generation has been favored more and more. Since my country's vigorous development of photovoltaic power generation began in 2011, by the end of 2016, the cumulative installed capacity of photovoltaic power generation had reached 77.42 million kilowatts, ranking first in the world. However, since the power of photovoltaic power generation is affected by various factors such as weather, solar radiation, and temperature, it has strong volatility and randomness. As the penetration rate increases, large-scale photovoltaic grid integration will have adverse effects on the grid. Therefore, how to improve the power quality of photovoltaic power generation and reduce the harm of photovoltaic grid-connected to the power ...

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Problems solved by technology

[0004] However, the above-mentioned literatures are all based on the premise that the photovoltaic prediction model has no error, and the effective regulation of photovoltaic grid-connected power can be realized.

At present, the average prediction error of photovoltaic power generation within 30 minutes through clustering or physical prediction model methods is about 15%, and it is impossible to achieve accurate online control of energy storage with conventional methods

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