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Optimal Scheduling of DR for load balancing and User Comfort Management in Smart Grid /

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dc.contributor.author Malik, Muhammad Mahad
dc.date.accessioned 2020-12-23T05:25:24Z
dc.date.available 2020-12-23T05:25:24Z
dc.date.issued 2020-09
dc.identifier.other 206675
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/19466
dc.description Supervisor : Dr. Syed Ali Abbas Kazmi en_US
dc.description.abstract Smart community setups nowadays are subjected to complicated issues such as instability, intermittent integration of the load at the demand side and lack of intelligent two-way communication process. These issues need to be addressed in terms of a balanced power demand dispatch (DD) in the real-time or day-ahead duplex signal regime under multi-microgrids. This paper offers an intelligent multi-agent-based approach that works between different levels of communication and their respective layers for a community-based system to optimize the power in community-based multi-microgrids model. This will further enhance user personal comfort. Constraints relative to cost minimization also have a relation with this model. A three-level structure with various layers of autonomous agents take intelligent decisions based on prioritized particle swarm optimization (P-PSO), prioritized plug and play (PPnP), and knapsack; considering DD as the main driver of the system to handle price and power consumption uncertainties. Distinct smart home models, depending upon their living habits, are keenly observed providing their power infrastructure and personal comfort. Load appliances considered as load agents are individually contemplated for maximum proficiency. Furthermore, two-way communication between utility and consumers lower downs the risk of inefficiency of the system where anyone seems unsatisfied with the other. en_US
dc.language.iso en_US en_US
dc.publisher U.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), NUST en_US
dc.relation.ispartofseries TH-227
dc.subject Demand dispatch en_US
dc.subject Demand response en_US
dc.subject Multi-agent system en_US
dc.subject Multi-microgrid en_US
dc.subject Python agent development en_US
dc.subject Prioritized plug-and-play en_US
dc.subject Prioritized particle swarm optimization en_US
dc.subject Real-time pricing and usage en_US
dc.title Optimal Scheduling of DR for load balancing and User Comfort Management in Smart Grid / en_US
dc.type Thesis en_US


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