FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3092156689> ?p ?o ?g. }

• W3092156689 endingPage "101935" @default.
• W3092156689 startingPage "101935" @default.
• W3092156689 abstract "• The optimal charging/discharging strategy of EV and state of charge of EV (SoE) in the forms of V2G, V2L and G2V using robust approach based on bender limit decomposition and Lagrange method. • Transforming the complex problem to the linear mixed integer problem using bender decomposition and applying GAMS and Simulink for optimization. • Considering EV-scheduling based on V2G, V2L and G2V in addition to the DR program to maximize the profit profile of the MG. • Analysis of the uncertainties of DGs, EVs, DR and load and their effects on the cost function and profit profile. • Analysis of the effect of profit profile maximization on the reduction of green-house gases emission. Electric Vehicle (EV)-based microgrid (MG) has an opportunity of using of mobile energy storage units where EV can help the MG in supporting load demands and maintaining the quality of voltage and power profile. However, in EV traffic time, MG suffers from high demands of EVs and loads. EV power scheduling can overcome the challenges of profit profile, demand support and cost profile in the MG. Two strategies as power flow from EV to the main grid (V2G) and from EV to load (V2L) can be used to reduce the cost and prevent buying energy from main grid. In high-demand times, the MG should buy energy from main grid which consequently increases the cost profile. To overcome the high-demand supporting problem, demand response program is also employed to reduce the loads in on-peak time durations or shift them to off-peak times. Applying the EV scheduling and demand response program helps MG to reduce the cost and improve the profit profile. Bender decomposition and Lagrange method provide a robust approach in this paper for optimization of MG in terms of EV scheduling and demand response program to obtain desirable cost and profit profile. As shown in simulation results, using the proposed approach, the cost profile is reduced by 14.67% compared to applying no optimized EV scheduling and no demand response program in the MG." @default.
• W3092156689 created "2020-10-15" @default.
• W3092156689 creator A5057691571 @default.
• W3092156689 date "2020-12-01" @default.
• W3092156689 modified "2023-10-16" @default.
• W3092156689 title "Vehicle-to-Grid and vehicle-to-load strategies and demand response program with bender decomposition approach in electrical vehicle-based microgrid for profit profile improvement" @default.
• W3092156689 cites W1968962169 @default.
• W3092156689 cites W1973799593 @default.
• W3092156689 cites W2036367660 @default.
• W3092156689 cites W2044121814 @default.
• W3092156689 cites W2063996928 @default.
• W3092156689 cites W2080064039 @default.
• W3092156689 cites W2196845260 @default.
• W3092156689 cites W2212485538 @default.
• W3092156689 cites W2250624617 @default.
• W3092156689 cites W2278572372 @default.
• W3092156689 cites W235576719 @default.
• W3092156689 cites W2551804397 @default.
• W3092156689 cites W2564397272 @default.
• W3092156689 cites W2573624245 @default.
• W3092156689 cites W2740184383 @default.
• W3092156689 cites W2740883036 @default.
• W3092156689 cites W2789789676 @default.
• W3092156689 cites W2805482844 @default.
• W3092156689 cites W2880673324 @default.
• W3092156689 cites W2888833478 @default.
• W3092156689 cites W2895447565 @default.
• W3092156689 cites W2898199288 @default.
• W3092156689 cites W2901537089 @default.
• W3092156689 cites W2921800668 @default.
• W3092156689 cites W2931464100 @default.
• W3092156689 cites W2978472846 @default.
• W3092156689 cites W2983350278 @default.
• W3092156689 cites W3014698992 @default.
• W3092156689 cites W3020983427 @default.
• W3092156689 cites W3046262654 @default.
• W3092156689 cites W3099561736 @default.
• W3092156689 doi "https://doi.org/10.1016/j.est.2020.101935" @default.
• W3092156689 hasPublicationYear "2020" @default.
• W3092156689 type Work @default.
• W3092156689 sameAs 3092156689 @default.
• W3092156689 citedByCount "13" @default.
• W3092156689 countsByYear W30921566892021 @default.
• W3092156689 countsByYear W30921566892022 @default.
• W3092156689 countsByYear W30921566892023 @default.
• W3092156689 crossrefType "journal-article" @default.
• W3092156689 hasAuthorship W3092156689A5057691571 @default.
• W3092156689 hasConcept C119599485 @default.
• W3092156689 hasConcept C121332964 @default.
• W3092156689 hasConcept C126255220 @default.
• W3092156689 hasConcept C127413603 @default.
• W3092156689 hasConcept C163258240 @default.
• W3092156689 hasConcept C171146098 @default.
• W3092156689 hasConcept C187691185 @default.
• W3092156689 hasConcept C188573790 @default.
• W3092156689 hasConcept C206658404 @default.
• W3092156689 hasConcept C2524010 @default.
• W3092156689 hasConcept C2776422217 @default.
• W3092156689 hasConcept C2776582896 @default.
• W3092156689 hasConcept C2776784348 @default.
• W3092156689 hasConcept C2777908891 @default.
• W3092156689 hasConcept C2779438525 @default.
• W3092156689 hasConcept C33923547 @default.
• W3092156689 hasConcept C41008148 @default.
• W3092156689 hasConcept C555008776 @default.
• W3092156689 hasConcept C62520636 @default.
• W3092156689 hasConcept C73916439 @default.
• W3092156689 hasConceptScore W3092156689C119599485 @default.
• W3092156689 hasConceptScore W3092156689C121332964 @default.
• W3092156689 hasConceptScore W3092156689C126255220 @default.
• W3092156689 hasConceptScore W3092156689C127413603 @default.
• W3092156689 hasConceptScore W3092156689C163258240 @default.
• W3092156689 hasConceptScore W3092156689C171146098 @default.
• W3092156689 hasConceptScore W3092156689C187691185 @default.
• W3092156689 hasConceptScore W3092156689C188573790 @default.
• W3092156689 hasConceptScore W3092156689C206658404 @default.
• W3092156689 hasConceptScore W3092156689C2524010 @default.
• W3092156689 hasConceptScore W3092156689C2776422217 @default.
• W3092156689 hasConceptScore W3092156689C2776582896 @default.
• W3092156689 hasConceptScore W3092156689C2776784348 @default.
• W3092156689 hasConceptScore W3092156689C2777908891 @default.
• W3092156689 hasConceptScore W3092156689C2779438525 @default.
• W3092156689 hasConceptScore W3092156689C33923547 @default.
• W3092156689 hasConceptScore W3092156689C41008148 @default.
• W3092156689 hasConceptScore W3092156689C555008776 @default.
• W3092156689 hasConceptScore W3092156689C62520636 @default.
• W3092156689 hasConceptScore W3092156689C73916439 @default.
• W3092156689 hasLocation W30921566891 @default.
• W3092156689 hasOpenAccess W3092156689 @default.
• W3092156689 hasPrimaryLocation W30921566891 @default.
• W3092156689 hasRelatedWork W2163297865 @default.
• W3092156689 hasRelatedWork W2613113841 @default.
• W3092156689 hasRelatedWork W2793190505 @default.
• W3092156689 hasRelatedWork W3023335632 @default.
• W3092156689 hasRelatedWork W3092156689 @default.
• W3092156689 hasRelatedWork W3097725212 @default.
• W3092156689 hasRelatedWork W3187349546 @default.
• W3092156689 hasRelatedWork W4220757008 @default.

• next