Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market
Buildings; Commerce; Electric industry; Electric power transmission networks; Intelligent buildings; Scheduling; Smart power grids; Algebraic modeling; Consumption patterns; Demand response; Demand response resources; Negawatt; Network reliability; Spinning reserves; Triangulum; Power markets
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-244692023-05-29T15:23:46Z Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market Safari A. Tahmasebi M. Pasupuleti J. 55921938000 55945605900 11340187300 Buildings; Commerce; Electric industry; Electric power transmission networks; Intelligent buildings; Scheduling; Smart power grids; Algebraic modeling; Consumption patterns; Demand response; Demand response resources; Negawatt; Network reliability; Spinning reserves; Triangulum; Power markets Demand response resources are one of the possible solutions for solving the network and market problems. Demand response refers to end-users shifts in electricity usage from their usual consumption pattern while network reliability is jeopardized or changes to market prices. The smart building contains 'the use of coordinates innovative building frameworks, communications, and controls to form a building and its infrastructure which gives the proprietor, administrator, and occupant with an environment which is adaptable, viable, comfortable and secure'. Smart buildings ready to be interconnected with smart grids and Triangulum smart cities project should comply with the following demand response capabilities. In this paper, we have proposed a new bidding strategy for the smart buildings aggregator as a 'Negawatt Demand Response Resources' in the electricity market based on self-scheduling method. The self-scheduling framework is formulated as a linear model. This model is optimized under the General Algebraic Modeling System (GAMS) software. The results of case studies are discussed in detail. � 2019 IEEE. Final 2023-05-29T07:23:46Z 2023-05-29T07:23:46Z 2019 Conference Paper 10.1109/ISGTEurope.2019.8905471 2-s2.0-85075869520 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075869520&doi=10.1109%2fISGTEurope.2019.8905471&partnerID=40&md5=f052f059819c16291da808fac02310cc https://irepository.uniten.edu.my/handle/123456789/24469 8905471 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Buildings; Commerce; Electric industry; Electric power transmission networks; Intelligent buildings; Scheduling; Smart power grids; Algebraic modeling; Consumption patterns; Demand response; Demand response resources; Negawatt; Network reliability; Spinning reserves; Triangulum; Power markets |
| author2 |
55921938000 |
| author_facet |
55921938000 Safari A. Tahmasebi M. Pasupuleti J. |
| format |
Conference Paper |
| author |
Safari A. Tahmasebi M. Pasupuleti J. |
| spellingShingle |
Safari A. Tahmasebi M. Pasupuleti J. Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| author_sort |
Safari A. |
| title |
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| title_short |
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| title_full |
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| title_fullStr |
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| title_full_unstemmed |
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market |
| title_sort |
smart buildings aggregator bidding strategy as a negawatt demand response resources in the spinning reserve electricity market |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806426175296241664 |
| score |
13.214268 |