Intelligent power generation control method for island microgrid based on correlation equilibrium reinforcement learning

Abstract

The invention discloses a method for controlling intelligent power generation of an island micro grid based on correlated equilibrium reinforcement learning. The method comprises the steps of 1, determining a state discrete set and a joint control motion set of the micro grid, 2, conducting initialization according to state motion value functions and equilibrium strategies of units, 3, collecting the real-time frequency deviation of the micro grid and power deviation values of the units, 4, determining immediate reward values of the units in the current control period, 5, updating the state motion value functions of the units under the current control period, 6, solving the linear planning of correlated equilibrium reinforcement learning, obtaining the optimum equilibrium strategy of the correlated equilibrium combined motions under the current control period, 7, selecting the collaborative motions of the units, controlling the units to work in the next control period according to the collaborative motions, executing the next control period, and returning to the step 3. The optimum equilibrium strategy is obtained under the linear planning of correlated equilibrium reinforcement learning, the method can better adapt to the complex working condition of the micro grid system under the island running mode, and the method has the advantage of being rapid in convergence.

Description

technical field [0001] The invention relates to the technical field of micro-grid operation and control, in particular to an island micro-grid intelligent power generation control method based on correlation equilibrium reinforcement learning. This method is suitable for active power-frequency control of island microgrids under a variety of new energy combinations. Background technique [0002] With the rapid development of the world's industry and economy, traditional energy sources are difficult to meet the load growth, coupled with the increasingly serious pollution of the environment by fossil energy sources, the micro-grid composed of distributed new energy photovoltaic cells, fuel cells, gas turbines, wind power generation devices, etc. Its flexible and intelligent control not only solves the problem of large-scale grid connection of DG (Distributed Generation, distributed generation technology), but also improves the reliability of power supply, and the energy consume...

AI Technical Summary

Problems solved by technology

The control system breaks through the traditional PI control, and realizes the load frequency control (Load Frequency Control, LFC) of the microgrid through the AGC controller based on reinforcement learning. The scheduling instruction is not necessarily the optimal instruction, and there is still a large room for optimization in terms of the number of adjustments of the AGC unit and the convergence speed of the algorithm

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