FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308903698> ?p ?o ?g. }

• W4308903698 endingPage "120215" @default.
• W4308903698 startingPage "120215" @default.
• W4308903698 abstract "In commercial buildings, Heat, Ventilation, and Air Conditioning (HVAC) systems account for about 40–50 % of total electricity usage, contributing to an economic burden on building operators. Furthermore, increasing amounts of distributed generation can bring challenges and opportunities for voltage regulation in low voltage distribution networks. In this paper, we tend to develop intelligent management to save the electricity bills of HVAC systems in multiple multi-zone buildings while relieving the stress of voltage regulation across the network. However, it is challenging to achieve the above aims due to the existence of parameter uncertainties (e.g., electricity load, outdoor temperature, photovoltaic generation, etc.), a sizeable continuous decision space, unknown thermal dynamics model, and distribution network topology, and a non-convex multi-objective function. In this context, a novel model-free multi-agent deep reinforcement learning (MADRL)-based multi-building control algorithm is proposed to achieve building-side and grid-level objectives. The proposed method adopts a centralized training and decentralized execution framework while integrating an attention mechanism to ease training and preserve privacy. This also enables the agent to achieve control purposes based only on local measurements, reducing communication cost. Simulation results based on real-world data verify that the proposed method can achieve real-time physical-model-free control of multi-buildings to tackle fast fluctuations of voltage and temperature caused by the uncertain external factors while being advantageous over other two MADRL methods. Additionally, comparison analysis on untouched datasets illustrates that the proposed method achieves similar results and better computation performance with the perfect physical-model-based approach." @default.
• W4308903698 created "2022-11-19" @default.
• W4308903698 creator A5046881277 @default.
• W4308903698 creator A5058169961 @default.
• W4308903698 creator A5065546196 @default.
• W4308903698 creator A5082636856 @default.
• W4308903698 creator A5087631945 @default.
• W4308903698 date "2022-12-01" @default.
• W4308903698 modified "2023-10-14" @default.
• W4308903698 title "Multi-agent deep reinforcement learning-based coordination control for grid-aware multi-buildings" @default.
• W4308903698 cites W1965882001 @default.
• W4308903698 cites W2035678547 @default.
• W4308903698 cites W2255511049 @default.
• W4308903698 cites W2277615321 @default.
• W4308903698 cites W2677961683 @default.
• W4308903698 cites W2735561395 @default.
• W4308903698 cites W2740655068 @default.
• W4308903698 cites W2748109868 @default.
• W4308903698 cites W2753767989 @default.
• W4308903698 cites W2766636687 @default.
• W4308903698 cites W2886617354 @default.
• W4308903698 cites W2921672886 @default.
• W4308903698 cites W2954693707 @default.
• W4308903698 cites W3037631072 @default.
• W4308903698 cites W3038624044 @default.
• W4308903698 cites W3043475934 @default.
• W4308903698 cites W3122800106 @default.
• W4308903698 cites W3123856535 @default.
• W4308903698 cites W3174511347 @default.
• W4308903698 cites W3184866585 @default.
• W4308903698 cites W3200357735 @default.
• W4308903698 cites W3207726175 @default.
• W4308903698 cites W3209381781 @default.
• W4308903698 cites W4210539565 @default.
• W4308903698 doi "https://doi.org/10.1016/j.apenergy.2022.120215" @default.
• W4308903698 hasPublicationYear "2022" @default.
• W4308903698 type Work @default.
• W4308903698 citedByCount "6" @default.
• W4308903698 countsByYear W43089036982022 @default.
• W4308903698 countsByYear W43089036982023 @default.
• W4308903698 crossrefType "journal-article" @default.
• W4308903698 hasAuthorship W4308903698A5046881277 @default.
• W4308903698 hasAuthorship W4308903698A5058169961 @default.
• W4308903698 hasAuthorship W4308903698A5065546196 @default.
• W4308903698 hasAuthorship W4308903698A5082636856 @default.
• W4308903698 hasAuthorship W4308903698A5087631945 @default.
• W4308903698 hasConcept C103742991 @default.
• W4308903698 hasConcept C119599485 @default.
• W4308903698 hasConcept C120314980 @default.
• W4308903698 hasConcept C122346748 @default.
• W4308903698 hasConcept C127413603 @default.
• W4308903698 hasConcept C133731056 @default.
• W4308903698 hasConcept C151730666 @default.
• W4308903698 hasConcept C154945302 @default.
• W4308903698 hasConcept C187691185 @default.
• W4308903698 hasConcept C2524010 @default.
• W4308903698 hasConcept C2775924081 @default.
• W4308903698 hasConcept C2776784348 @default.
• W4308903698 hasConcept C2779343474 @default.
• W4308903698 hasConcept C33923547 @default.
• W4308903698 hasConcept C41008148 @default.
• W4308903698 hasConcept C41291067 @default.
• W4308903698 hasConcept C78519656 @default.
• W4308903698 hasConcept C86803240 @default.
• W4308903698 hasConcept C97541855 @default.
• W4308903698 hasConceptScore W4308903698C103742991 @default.
• W4308903698 hasConceptScore W4308903698C119599485 @default.
• W4308903698 hasConceptScore W4308903698C120314980 @default.
• W4308903698 hasConceptScore W4308903698C122346748 @default.
• W4308903698 hasConceptScore W4308903698C127413603 @default.
• W4308903698 hasConceptScore W4308903698C133731056 @default.
• W4308903698 hasConceptScore W4308903698C151730666 @default.
• W4308903698 hasConceptScore W4308903698C154945302 @default.
• W4308903698 hasConceptScore W4308903698C187691185 @default.
• W4308903698 hasConceptScore W4308903698C2524010 @default.
• W4308903698 hasConceptScore W4308903698C2775924081 @default.
• W4308903698 hasConceptScore W4308903698C2776784348 @default.
• W4308903698 hasConceptScore W4308903698C2779343474 @default.
• W4308903698 hasConceptScore W4308903698C33923547 @default.
• W4308903698 hasConceptScore W4308903698C41008148 @default.
• W4308903698 hasConceptScore W4308903698C41291067 @default.
• W4308903698 hasConceptScore W4308903698C78519656 @default.
• W4308903698 hasConceptScore W4308903698C86803240 @default.
• W4308903698 hasConceptScore W4308903698C97541855 @default.
• W4308903698 hasLocation W43089036981 @default.
• W4308903698 hasOpenAccess W4308903698 @default.
• W4308903698 hasPrimaryLocation W43089036981 @default.
• W4308903698 hasRelatedWork W1574359403 @default.
• W4308903698 hasRelatedWork W2057975886 @default.
• W4308903698 hasRelatedWork W2356033827 @default.
• W4308903698 hasRelatedWork W2391138633 @default.
• W4308903698 hasRelatedWork W2907234787 @default.
• W4308903698 hasRelatedWork W4206134051 @default.
• W4308903698 hasRelatedWork W4210780382 @default.
• W4308903698 hasRelatedWork W4285503559 @default.
• W4308903698 hasRelatedWork W4308700935 @default.
• W4308903698 hasRelatedWork W4383747562 @default.
• W4308903698 hasVolume "328" @default.

• next