Microgrid cooperative scheduling optimization based on quality of service constraint and deep Q-network algorithm

Jie Zhou and Rong Lu

International Journal of Low-Carbon Technologies, 2025, vol. 20, 47-57

Abstract: This paper proposes a quality of service Cloud Workflow Firefly Algorithm (CWFA), which considers dynamic priorities. Whenever the algorithm experiences a new state–action pair, this experience is recorded as part of the training data. Genetic algorithm (GA) is introduced to optimize the initial parameters of deep Q-network (DQN). Through GA, a better initial weight can be found, so as to improve the estimation of Q-value, making the overall workflow scheduling more efficient. The simulation results show that, compared with other methods, CWFA–GA–DQN can effectively improve the efficiency of microgrid cooperative scheduling.

Keywords: microgrid; cooperative scheduling optimization; genetic algorithm–deep Q-network; quality of service; firefly algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:47-57.

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