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http://hdl.handle.net/10603/522330
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Energy efficient algorithms for demand response in smart grid | |
dc.date.accessioned | 2023-11-01T09:36:04Z | - |
dc.date.available | 2023-11-01T09:36:04Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/522330 | - |
dc.description.abstract | The ever-increasing demand for electricity, and environmental concerns in using traditional non renewable energy sources like coal insist the need for alternative Renewable Energy Sources (RESs). The traditional electric power grid system that has been serving the energy needs for nearly two decades, is rigid. The prominent inefficiencies with traditional power system are, lack of monitoring which leads to frequent failures, interoperability issues in adopting to latest Information and Communication Technologies (ICTs), absence of communication infrastructure and inflexibility in integrating renewable sources of power into the existing grid system. Smart grid is the key enabler for effectively generating, distributing and consuming electricity in a sustainable manner. The household energy demands contribute to the major part of electricity consumption around the globe. The optimal energy management strategies implemented at consumer level will have a greater impact on energy saving. The major challenges in implementing energy management methods at consumer level are; the dynamic nature of load demand, communication aspects between consumers and service providers and maintaining user comfort after scheduling. Smart grid provides an efficient Demand Side Management (DSM) framework for consumption analysis and this optimizes the energy usage pattern of the consumer. The methodologies, and the algorithms to achieve the DSM initiatives are called, Demand Response (DR) programs. newline | |
dc.format.extent | xix, 134 | |
dc.language | English | |
dc.relation | p. 122-133 | |
dc.rights | university | |
dc.title | Energy efficient algorithms for demand response in smart grid | |
dc.title.alternative | ||
dc.creator.researcher | Geetha S | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Information Systems | |
dc.subject.keyword | Demand Response | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Information and Communication Technologies | |
dc.subject.keyword | Renewable Energy Sources | |
dc.description.note | ||
dc.contributor.guide | Srivatsun G | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | 21 cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 55.37 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 1.72 MB | Adobe PDF | View/Open | |
03_content.pdf | 466.66 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 875.32 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 3.45 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 5.16 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 4.72 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 5.25 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 6 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 4.87 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 1.29 MB | Adobe PDF | View/Open |
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