Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366994674> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W4366994674 endingPage "97" @default.
- W4366994674 startingPage "88" @default.
- W4366994674 abstract "Model predictive control is an effective approach for microgrid energy management. However, the main downside of such method is its expensive online computational cost, which is not amenable to most practical microgrid implementations. To address this issue, we propose a deep neural network assisted column generation approach that can accelerate the solution procedure of model predictive control. In each iteration, our approach leverages different deep neural networks to predict the optimal solutions of all the subproblems in column generation, which can accelerate the computation of all the subproblems and the entire process of column generation. The pre-existing knowledge of the microgrid is also exploited to guarantee the feasibility of the neural network outputs using multi-parametric programming theory. The numerical results show that our approach leads to a reduction in computational time of approximately 50% in a medium-sized microgrid compared with the full mixed integer solution based on traditional branch and bound method, while the optimality loss is only 0.02% in terms of operating costs." @default.
- W4366994674 created "2023-04-27" @default.
- W4366994674 creator A5006096734 @default.
- W4366994674 creator A5018591499 @default.
- W4366994674 creator A5054164968 @default.
- W4366994674 creator A5075390180 @default.
- W4366994674 date "2023-09-01" @default.
- W4366994674 modified "2023-10-14" @default.
- W4366994674 title "Learning assisted column generation for model predictive control based energy management in microgrids" @default.
- W4366994674 cites W2294561737 @default.
- W4366994674 cites W2555838481 @default.
- W4366994674 cites W2603921561 @default.
- W4366994674 cites W2624981577 @default.
- W4366994674 cites W2638230244 @default.
- W4366994674 cites W2810195925 @default.
- W4366994674 cites W2888818189 @default.
- W4366994674 cites W2891115142 @default.
- W4366994674 cites W2923965088 @default.
- W4366994674 cites W2963317745 @default.
- W4366994674 cites W3000723039 @default.
- W4366994674 cites W3011455949 @default.
- W4366994674 doi "https://doi.org/10.1016/j.egyr.2023.04.330" @default.
- W4366994674 hasPublicationYear "2023" @default.
- W4366994674 type Work @default.
- W4366994674 citedByCount "0" @default.
- W4366994674 crossrefType "journal-article" @default.
- W4366994674 hasAuthorship W4366994674A5006096734 @default.
- W4366994674 hasAuthorship W4366994674A5018591499 @default.
- W4366994674 hasAuthorship W4366994674A5054164968 @default.
- W4366994674 hasAuthorship W4366994674A5075390180 @default.
- W4366994674 hasBestOaLocation W43669946741 @default.
- W4366994674 hasConcept C105795698 @default.
- W4366994674 hasConcept C111335779 @default.
- W4366994674 hasConcept C111919701 @default.
- W4366994674 hasConcept C11413529 @default.
- W4366994674 hasConcept C117251300 @default.
- W4366994674 hasConcept C126042441 @default.
- W4366994674 hasConcept C126255220 @default.
- W4366994674 hasConcept C154945302 @default.
- W4366994674 hasConcept C168956720 @default.
- W4366994674 hasConcept C172205157 @default.
- W4366994674 hasConcept C186370098 @default.
- W4366994674 hasConcept C2524010 @default.
- W4366994674 hasConcept C2775924081 @default.
- W4366994674 hasConcept C2776045410 @default.
- W4366994674 hasConcept C2776784348 @default.
- W4366994674 hasConcept C2780551164 @default.
- W4366994674 hasConcept C33923547 @default.
- W4366994674 hasConcept C41008148 @default.
- W4366994674 hasConcept C45374587 @default.
- W4366994674 hasConcept C50644808 @default.
- W4366994674 hasConcept C56086750 @default.
- W4366994674 hasConcept C76155785 @default.
- W4366994674 hasConcept C7817414 @default.
- W4366994674 hasConcept C98045186 @default.
- W4366994674 hasConceptScore W4366994674C105795698 @default.
- W4366994674 hasConceptScore W4366994674C111335779 @default.
- W4366994674 hasConceptScore W4366994674C111919701 @default.
- W4366994674 hasConceptScore W4366994674C11413529 @default.
- W4366994674 hasConceptScore W4366994674C117251300 @default.
- W4366994674 hasConceptScore W4366994674C126042441 @default.
- W4366994674 hasConceptScore W4366994674C126255220 @default.
- W4366994674 hasConceptScore W4366994674C154945302 @default.
- W4366994674 hasConceptScore W4366994674C168956720 @default.
- W4366994674 hasConceptScore W4366994674C172205157 @default.
- W4366994674 hasConceptScore W4366994674C186370098 @default.
- W4366994674 hasConceptScore W4366994674C2524010 @default.
- W4366994674 hasConceptScore W4366994674C2775924081 @default.
- W4366994674 hasConceptScore W4366994674C2776045410 @default.
- W4366994674 hasConceptScore W4366994674C2776784348 @default.
- W4366994674 hasConceptScore W4366994674C2780551164 @default.
- W4366994674 hasConceptScore W4366994674C33923547 @default.
- W4366994674 hasConceptScore W4366994674C41008148 @default.
- W4366994674 hasConceptScore W4366994674C45374587 @default.
- W4366994674 hasConceptScore W4366994674C50644808 @default.
- W4366994674 hasConceptScore W4366994674C56086750 @default.
- W4366994674 hasConceptScore W4366994674C76155785 @default.
- W4366994674 hasConceptScore W4366994674C7817414 @default.
- W4366994674 hasConceptScore W4366994674C98045186 @default.
- W4366994674 hasLocation W43669946741 @default.
- W4366994674 hasOpenAccess W4366994674 @default.
- W4366994674 hasPrimaryLocation W43669946741 @default.
- W4366994674 hasRelatedWork W2049971005 @default.
- W4366994674 hasRelatedWork W2087693625 @default.
- W4366994674 hasRelatedWork W2145082692 @default.
- W4366994674 hasRelatedWork W2163563729 @default.
- W4366994674 hasRelatedWork W2616127505 @default.
- W4366994674 hasRelatedWork W2795935220 @default.
- W4366994674 hasRelatedWork W2801942988 @default.
- W4366994674 hasRelatedWork W2807131660 @default.
- W4366994674 hasRelatedWork W2921003940 @default.
- W4366994674 hasRelatedWork W4252560726 @default.
- W4366994674 hasVolume "9" @default.
- W4366994674 isParatext "false" @default.
- W4366994674 isRetracted "false" @default.
- W4366994674 workType "article" @default.