A control method and system for adaptive dynamic programming of a large-scale energy storage power station

Abstract

The present invention provides a control method and system for adaptive dynamic programming of large-scale energy storage power stations. The method includes the following steps: setting the structure and control target parameters of the adaptive dynamic programming control system; initializing parameters and importing the initial parameters of the controlled object State; calculate the original wind power fluctuation rate at the current moment t, and smooth the original wind power according to the change rate control method; calculate the smoothed wind storage power fluctuation rate, energy storage system power, and SOC of the energy storage system; initialization Training evaluation module and execution module; calculate the control strategy at each moment, the smoothed wind storage power fluctuation rate, energy storage power and energy storage system state of charge SOC, and save it; output the control strategy at each moment, smooth The final wind storage power fluctuation rate, energy storage power and state of charge SOC of the energy storage system. The system includes a parameter initialization module, a data collection and calculation module, an execution module, an evaluation module, an output module and the like. The invention realizes the optimal control of the large-scale energy storage system, and improves the technical economy of the energy storage system.

Description

technical field [0001] The invention belongs to the technical fields of smart grid, energy internet and energy storage, and in particular relates to a control method and system for adaptive dynamic programming of a large-scale energy storage power station. Background technique [0002] With the continuous development of wind power and photovoltaic power generation technology, the large-scale grid connection of wind power and photovoltaic power generation and other new energy power generation, the fluctuation of its output is becoming more and more serious. After wind power, photovoltaic power generation and other new energy power generation are connected to the power grid on a large scale, their volatility and intermittency will adversely affect the safety, stability and power quality of power grid operation. Therefore, in current practical applications, the grid connection of wind power and photovoltaic power generation is greatly restricted, which is not conducive to the d...

AI Technical Summary

Problems solved by technology

[0006] When smoothing large-scale new energy generation output fluctuations in large-scale battery energy storage power stations, the traditional first-order low-pass filtering or output filtering method with variable time constant (T) is used, which sometimes leads to control sensitivity due to the time lag of the method itself. bad

The energy storage output target value output by the general moving average filtering algorithm is also largely limited by the input of new energy generation power such as wind power and photovoltaic power generation. These traditional methods encounter sudden changes in the output of new energy power generation. The performance is degraded and affects the subsequent filtering effect

On the other hand, when improving the output control of energy storage power stations that are friendly to new energy power generation, the traditional control method needs to be further improved in the aspect of adaptive control of the overall output of energy storage power stations based on self-learning intelligent optimization control

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