Optimal Operation of a Hydrogen-based Building Multi-Energy System under Uncertainties

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Abstract

This paper investigates an optimal operation problem of a hydrogen-based building multi-energy system (HBMES). Specifically, we first formulate an operational cost minimization problem of HBMES. Since there are uncertain parameters, inexplicit building thermal dynamics model, temporally coupled operational constraints, as well as the coupling between electricity and heat, solving the minimization problem is nontrivial. To overcome the challenge, we reformulate the problem as a Markov decision process (MDP). Then, we design an algorithm to solve the MDP based on deep deterministic policy gradients and prioritized experience replay. The designed algorithm supports real-time decision without any process of searching optimal solution. Performance evaluation verifies the effectiveness and robustness of the designed algorithm.

Original languageEnglish
Title of host publicationProceeding - 2021 China Automation Congress, CAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1583-1588
Number of pages6
ISBN (Electronic)9781665426473
DOIs
StatePublished - 2021
Event2021 China Automation Congress, CAC 2021 - Beijing, China
Duration: 22 Oct 202124 Oct 2021

Publication series

NameProceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference2021 China Automation Congress, CAC 2021
Country/TerritoryChina
CityBeijing
Period22/10/2124/10/21

Keywords

  • deep reinforcement learning
  • hydrogen-based multi-energy systems
  • operational cost

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