Integrated energy system scheduling model construction method and device, medium and electronic equipment

Abstract

The embodiment of the invention discloses a scheduling method and device of an integrated energy system, a medium and electronic equipment. The method comprises the following steps: collecting historical data of new energy power generation power, an electric load and a natural gas load as training samples; setting an optimization target of the integrated energy system; constructing elements of the deep reinforcement learning model, wherein the elements comprise a state variable, an action variable, a return function, a discount factor and a memory library capacity; wherein the deep reinforcement learning model comprises an action device, an online strategy network, a target strategy network of the online strategy network, an evaluator, an online network and a target network of the online network; and carrying out iteration on a training sample based on the deep reinforcement learning model, and determining a scheduling strategy in a scheduling period. According to the technical scheme, the source-load probability distribution is automatically and adaptively learned through the deep neural network, and the trained model can quickly and online give an optimal scheduling strategy in a second level.

Description

technical field [0001] The embodiments of the present application relate to the field of optimized operation of energy Internet integrated energy systems, and in particular to a method, device, medium, and electronic equipment for constructing an integrated energy system scheduling model. Background technique [0002] With the continuous development of science and technology, the contradiction between the growing demand for energy worldwide and the protection of environmental ecology is prominent. Improving energy utilization efficiency and seeking alternative new energy sources have become the only way for energy transformation in countries all over the world. The flexible gas turbine unit provides a guarantee for stabilizing intermittent new energy output; for new energy output that is difficult for the grid to absorb, it can be converted into natural gas / hydrogen through power-to-gas (P2G) technology and stored in natural gas pipelines on a large scale. The power system a...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a construction method, device, medium and electronic equipment for an integrated energy system scheduling model, which overcomes the problems of slow convergence speed, long decision-making time, inability to adapt to source-load randomness scenarios, and the need for a large number of simplified assumptions in traditional methods. Through in-depth The neural network automatically and adaptively learns the probability distribution of source loads, and quickly and online provides optimal scheduling strategies within seconds

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