Scheduling method and device for multi-type energy storage in micro-grid based on deep Q learning
The invention discloses a deep Q learning-based scheduling method and device for multi-type energy storage in a micro-grid, the micro-grid comprises a power supply, a long-period energy storage device and a short-period energy storage device, the scheduling problem of the multi-type energy storage i...
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Format: | Patent |
Sprache: | chi ; eng |
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Zusammenfassung: | The invention discloses a deep Q learning-based scheduling method and device for multi-type energy storage in a micro-grid, the micro-grid comprises a power supply, a long-period energy storage device and a short-period energy storage device, the scheduling problem of the multi-type energy storage in the micro-grid is described as a Markov decision process, a neural network model of deep Q learning is constructed and trained, and the deep Q learning-based multi-type energy storage in the micro-grid is obtained. And adopting the trained deep Q learning neural network model, inputting the current state of the micro-grid, outputting a corresponding action, and scheduling according to the output action. The optimal energy storage scheduling strategy is obtained through continuous interaction of the intelligent agent and the micro-grid scheduling environment, the influence caused by model inaccuracy is avoided, the method is suitable for the micro-grid comprising multiple types of energy storage technologies, supp |
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