FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285105364> ?p ?o ?g. }

• W4285105364 endingPage "54028" @default.
• W4285105364 startingPage "54018" @default.
• W4285105364 abstract "Demand Response (DR) programs show great promise for energy saving and load profile flattening. They bring about an opportunity for indirect control of end-users’ demand based on different price policies. However, the difficulty in characterizing the price-responsive behavior of customers is a significant challenge towards an optimal selection of these policies. This paper proposes a Demand Response Aggregator (DRA) for transactive policy generation by combining a Reinforcement Learning (RL) technique on the aggregator side with a convex optimization problem on the customer side. The proposed DRA can maintain users’ privacy by exploiting the DR as the only source of information. In addition, it can avoid mistakenly penalizing users by offering price discounts as an incentive to realize a satisfying multi-agent environment. With an ensured convergence, the resultant DRA is capable of learning adaptive Time-of-Use (ToU) tariffs and generating near-to-optimal price policies. Moreover, this study suggests an off-line training procedure that can deal with issues related to the convergence time of RL algorithms. The suggested process can notably expedite the DRA convergence and, in turn, enable online applications. The developed method is applied to a set of residential agents in order to benefit them by regulating their thermal loads according to generated price policies. The efficiency of the proposed approach is thoroughly evaluated from the standpoint of the aggregator and customers in terms of load shifting and comfort maintenance, respectively. Besides, the superior performance of the selected RL method is represented through a comparative study. An additional assessment is also conducted by use of a coordination algorithm to validate the competitiveness of the recommended DR program. The multifaceted evaluation demonstrates that the designed scheme can significantly improve the quality of the aggregated load profile with a low reduction in the aggregator’s income." @default.
• W4285105364 created "2022-07-14" @default.
• W4285105364 creator A5008090389 @default.
• W4285105364 creator A5017643875 @default.
• W4285105364 creator A5021017219 @default.
• W4285105364 creator A5032893120 @default.
• W4285105364 creator A5043426685 @default.
• W4285105364 creator A5069925575 @default.
• W4285105364 date "2022-01-01" @default.
• W4285105364 modified "2023-09-30" @default.
• W4285105364 title "A Discount-Based Time-of-Use Electricity Pricing Strategy for Demand Response With Minimum Information Using Reinforcement Learning" @default.
• W4285105364 cites W1999643482 @default.
• W4285105364 cites W2010668661 @default.
• W4285105364 cites W2023409181 @default.
• W4285105364 cites W2042454807 @default.
• W4285105364 cites W2052394609 @default.
• W4285105364 cites W2070042835 @default.
• W4285105364 cites W2072230340 @default.
• W4285105364 cites W2419591819 @default.
• W4285105364 cites W2480680748 @default.
• W4285105364 cites W2617778626 @default.
• W4285105364 cites W2621259510 @default.
• W4285105364 cites W2741458426 @default.
• W4285105364 cites W2755412030 @default.
• W4285105364 cites W2765349520 @default.
• W4285105364 cites W2795276745 @default.
• W4285105364 cites W2796857734 @default.
• W4285105364 cites W2883300051 @default.
• W4285105364 cites W2883899184 @default.
• W4285105364 cites W2891284509 @default.
• W4285105364 cites W2898025312 @default.
• W4285105364 cites W2901621510 @default.
• W4285105364 cites W2904635416 @default.
• W4285105364 cites W2907011345 @default.
• W4285105364 cites W2922450265 @default.
• W4285105364 cites W2962980800 @default.
• W4285105364 cites W2963382853 @default.
• W4285105364 cites W2963723202 @default.
• W4285105364 cites W2998170450 @default.
• W4285105364 cites W3038624044 @default.
• W4285105364 cites W3046697705 @default.
• W4285105364 cites W3047508891 @default.
• W4285105364 cites W3048447665 @default.
• W4285105364 cites W3089354771 @default.
• W4285105364 cites W3089368496 @default.
• W4285105364 cites W3098389716 @default.
• W4285105364 cites W3108288031 @default.
• W4285105364 cites W3109005681 @default.
• W4285105364 cites W3126442977 @default.
• W4285105364 cites W3138355836 @default.
• W4285105364 cites W3158649951 @default.
• W4285105364 cites W3160525100 @default.
• W4285105364 cites W3189694631 @default.
• W4285105364 doi "https://doi.org/10.1109/access.2022.3175839" @default.
• W4285105364 hasPublicationYear "2022" @default.
• W4285105364 type Work @default.
• W4285105364 citedByCount "7" @default.
• W4285105364 countsByYear W42851053642022 @default.
• W4285105364 countsByYear W42851053642023 @default.
• W4285105364 crossrefType "journal-article" @default.
• W4285105364 hasAuthorship W4285105364A5008090389 @default.
• W4285105364 hasAuthorship W4285105364A5017643875 @default.
• W4285105364 hasAuthorship W4285105364A5021017219 @default.
• W4285105364 hasAuthorship W4285105364A5032893120 @default.
• W4285105364 hasAuthorship W4285105364A5043426685 @default.
• W4285105364 hasAuthorship W4285105364A5069925575 @default.
• W4285105364 hasBestOaLocation W42851053641 @default.
• W4285105364 hasConcept C111919701 @default.
• W4285105364 hasConcept C119599485 @default.
• W4285105364 hasConcept C126255220 @default.
• W4285105364 hasConcept C127413603 @default.
• W4285105364 hasConcept C154945302 @default.
• W4285105364 hasConcept C162324750 @default.
• W4285105364 hasConcept C175444787 @default.
• W4285105364 hasConcept C180505990 @default.
• W4285105364 hasConcept C206658404 @default.
• W4285105364 hasConcept C2777303404 @default.
• W4285105364 hasConcept C2779438525 @default.
• W4285105364 hasConcept C29122968 @default.
• W4285105364 hasConcept C33923547 @default.
• W4285105364 hasConcept C41008148 @default.
• W4285105364 hasConcept C42475967 @default.
• W4285105364 hasConcept C50522688 @default.
• W4285105364 hasConcept C97541855 @default.
• W4285105364 hasConcept C98045186 @default.
• W4285105364 hasConceptScore W4285105364C111919701 @default.
• W4285105364 hasConceptScore W4285105364C119599485 @default.
• W4285105364 hasConceptScore W4285105364C126255220 @default.
• W4285105364 hasConceptScore W4285105364C127413603 @default.
• W4285105364 hasConceptScore W4285105364C154945302 @default.
• W4285105364 hasConceptScore W4285105364C162324750 @default.
• W4285105364 hasConceptScore W4285105364C175444787 @default.
• W4285105364 hasConceptScore W4285105364C180505990 @default.
• W4285105364 hasConceptScore W4285105364C206658404 @default.
• W4285105364 hasConceptScore W4285105364C2777303404 @default.
• W4285105364 hasConceptScore W4285105364C2779438525 @default.
• W4285105364 hasConceptScore W4285105364C29122968 @default.
• W4285105364 hasConceptScore W4285105364C33923547 @default.

• next