Matches in SemOpenAlex for { <https://semopenalex.org/work/W2924269685> ?p ?o ?g. }
- W2924269685 endingPage "1124" @default.
- W2924269685 startingPage "1124" @default.
- W2924269685 abstract "Optimal operation scheduling of energy storage systems (ESSs) has been considered as an effective way to cope with uncertainties arising in modern grid operation such as the inherent intermittency of the renewable energy sources (RESs) and load variations. This paper proposes a scheduling algorithm where ESS power inputs are optimally determined to minimize the microgrid (MG) operation cost. The proposed algorithm consists of two stages. In the first stage, hourly schedules during a day are optimized one day in advance with the objective of minimizing the operating cost. In the second stage, the optimal schedule obtained from the first stage is repeatedly updated every 5 min during the day of operation to compensate for the uncertainties in load demand and RES output power. The ESS model is developed considering operating efficiencies and then incorporated in mixed integer linear programming (MILP). Penalty functions are also considered to acquire feasible optimal solutions even under large forecasting errors in RES generation and load variation. The proposed algorithm is verified in a campus MG, implemented using ESSs and photovoltaic (PV) arrays. The field test results are obtained using open-source software and then compared with those acquired using commercial software." @default.
- W2924269685 created "2019-04-01" @default.
- W2924269685 creator A5019085537 @default.
- W2924269685 creator A5028944769 @default.
- W2924269685 creator A5065194371 @default.
- W2924269685 creator A5075668408 @default.
- W2924269685 creator A5075894873 @default.
- W2924269685 date "2019-03-22" @default.
- W2924269685 modified "2023-10-16" @default.
- W2924269685 title "Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid" @default.
- W2924269685 cites W106711868 @default.
- W2924269685 cites W1873571028 @default.
- W2924269685 cites W1965988806 @default.
- W2924269685 cites W1980364886 @default.
- W2924269685 cites W1991971024 @default.
- W2924269685 cites W1992970170 @default.
- W2924269685 cites W2005621669 @default.
- W2924269685 cites W2007501244 @default.
- W2924269685 cites W2012035739 @default.
- W2924269685 cites W2023594033 @default.
- W2924269685 cites W2023870905 @default.
- W2924269685 cites W2048015660 @default.
- W2924269685 cites W2049713484 @default.
- W2924269685 cites W2065680350 @default.
- W2924269685 cites W2070052642 @default.
- W2924269685 cites W2074817043 @default.
- W2924269685 cites W2121362791 @default.
- W2924269685 cites W2222845742 @default.
- W2924269685 cites W2273721420 @default.
- W2924269685 cites W2290410061 @default.
- W2924269685 cites W2296221482 @default.
- W2924269685 cites W2303389336 @default.
- W2924269685 cites W2314548687 @default.
- W2924269685 cites W2317466700 @default.
- W2924269685 cites W2410270974 @default.
- W2924269685 cites W2422154338 @default.
- W2924269685 cites W2530583702 @default.
- W2924269685 cites W2553716752 @default.
- W2924269685 cites W2555838481 @default.
- W2924269685 cites W2563490605 @default.
- W2924269685 cites W2593513685 @default.
- W2924269685 cites W2604871931 @default.
- W2924269685 cites W2614034933 @default.
- W2924269685 cites W2738379986 @default.
- W2924269685 cites W2745166643 @default.
- W2924269685 cites W2753070488 @default.
- W2924269685 cites W2760815103 @default.
- W2924269685 cites W2772228086 @default.
- W2924269685 cites W2790228887 @default.
- W2924269685 cites W2802339474 @default.
- W2924269685 cites W2889578848 @default.
- W2924269685 cites W2912896555 @default.
- W2924269685 doi "https://doi.org/10.3390/en12061124" @default.
- W2924269685 hasPublicationYear "2019" @default.
- W2924269685 type Work @default.
- W2924269685 sameAs 2924269685 @default.
- W2924269685 citedByCount "22" @default.
- W2924269685 countsByYear W29242696852019 @default.
- W2924269685 countsByYear W29242696852020 @default.
- W2924269685 countsByYear W29242696852021 @default.
- W2924269685 countsByYear W29242696852022 @default.
- W2924269685 countsByYear W29242696852023 @default.
- W2924269685 crossrefType "journal-article" @default.
- W2924269685 hasAuthorship W2924269685A5019085537 @default.
- W2924269685 hasAuthorship W2924269685A5028944769 @default.
- W2924269685 hasAuthorship W2924269685A5065194371 @default.
- W2924269685 hasAuthorship W2924269685A5075668408 @default.
- W2924269685 hasAuthorship W2924269685A5075894873 @default.
- W2924269685 hasBestOaLocation W29242696851 @default.
- W2924269685 hasConcept C111919701 @default.
- W2924269685 hasConcept C11413529 @default.
- W2924269685 hasConcept C119599485 @default.
- W2924269685 hasConcept C121332964 @default.
- W2924269685 hasConcept C126255220 @default.
- W2924269685 hasConcept C127413603 @default.
- W2924269685 hasConcept C163258240 @default.
- W2924269685 hasConcept C188573790 @default.
- W2924269685 hasConcept C196558001 @default.
- W2924269685 hasConcept C199360897 @default.
- W2924269685 hasConcept C200601418 @default.
- W2924269685 hasConcept C206729178 @default.
- W2924269685 hasConcept C2776784348 @default.
- W2924269685 hasConcept C2777904410 @default.
- W2924269685 hasConcept C2780388094 @default.
- W2924269685 hasConcept C33923547 @default.
- W2924269685 hasConcept C41008148 @default.
- W2924269685 hasConcept C41291067 @default.
- W2924269685 hasConcept C56086750 @default.
- W2924269685 hasConcept C62520636 @default.
- W2924269685 hasConcept C68387754 @default.
- W2924269685 hasConcept C73916439 @default.
- W2924269685 hasConcept C79403827 @default.
- W2924269685 hasConcept C97355855 @default.
- W2924269685 hasConceptScore W2924269685C111919701 @default.
- W2924269685 hasConceptScore W2924269685C11413529 @default.
- W2924269685 hasConceptScore W2924269685C119599485 @default.
- W2924269685 hasConceptScore W2924269685C121332964 @default.
- W2924269685 hasConceptScore W2924269685C126255220 @default.