Typification of load curves for DSM in Brazil for a smart grid environment
•This study discusses the use of DSM in a smart grid environment in Brazil.•We present the simulation for creating load curve patterns using the k-means technique.•The creation of the load curve patterns is for selecting the policies of DSM. The deployment of a smart grid environment is a worldwide...
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| Veröffentlicht in: | International journal of electrical power & energy systems 2015-05, Vol.67, p.216-221 |
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| container_title | International journal of electrical power & energy systems |
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| creator | Macedo, Maria N.Q. Galo, Joaquim J.M. Almeida, Luiz A.L. Lima, Antonio C.C. |
| description | •This study discusses the use of DSM in a smart grid environment in Brazil.•We present the simulation for creating load curve patterns using the k-means technique.•The creation of the load curve patterns is for selecting the policies of DSM.
The deployment of a smart grid environment is a worldwide trend and generates of a large volume of data. The load curve for each consumer in real time is an example of this. The challenge is the transformation of these data into useful information that may help to improve efficiency in the management, planning and operation of the power grid. The implementation of demand side management (DSM) requires an analysis of the data generated in a smart grid environment to determine which policies are most appropriate for each type of consumer. Because of the large number of customers, the application of these policies involves the selection of patterns for the load curve.
This study discusses the use of DSM in a smart grid environment in Brazil and presents the simulation for creating load curve patterns using the k-means technique from the consumer data of a concessionaire for the Brazilian electric system. The result obtained in this research is the creation of the load curve patterns for selecting the policies of DSM. |
| doi_str_mv | 10.1016/j.ijepes.2014.11.029 |
| format | Article |
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The deployment of a smart grid environment is a worldwide trend and generates of a large volume of data. The load curve for each consumer in real time is an example of this. The challenge is the transformation of these data into useful information that may help to improve efficiency in the management, planning and operation of the power grid. The implementation of demand side management (DSM) requires an analysis of the data generated in a smart grid environment to determine which policies are most appropriate for each type of consumer. Because of the large number of customers, the application of these policies involves the selection of patterns for the load curve.
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The deployment of a smart grid environment is a worldwide trend and generates of a large volume of data. The load curve for each consumer in real time is an example of this. The challenge is the transformation of these data into useful information that may help to improve efficiency in the management, planning and operation of the power grid. The implementation of demand side management (DSM) requires an analysis of the data generated in a smart grid environment to determine which policies are most appropriate for each type of consumer. Because of the large number of customers, the application of these policies involves the selection of patterns for the load curve.
This study discusses the use of DSM in a smart grid environment in Brazil and presents the simulation for creating load curve patterns using the k-means technique from the consumer data of a concessionaire for the Brazilian electric system. The result obtained in this research is the creation of the load curve patterns for selecting the policies of DSM.</description><subject>Brazil</subject><subject>Consumers</subject><subject>Customers</subject><subject>Demand side management</subject><subject>Distributed memory</subject><subject>Electric power generation</subject><subject>Load curve</subject><subject>Policies</subject><subject>Simulation</subject><subject>Smart grid</subject><subject>Transformations</subject><issn>0142-0615</issn><issn>1879-3517</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkEtPwzAQhC0EEqXwDzj4yCXBmzhOfEHi_VARB3q3XGeNHKVxsNNK5deTEs6I00q734x2hpBzYCkwEJdN6hrsMaYZA54CpCyTB2QGVSmTvIDykMzGQ5YwAcUxOYmxYYyVkmcz8rLc9c46owfnO-otbb2uqdmELUZqfaB376_UdfQm6C_X_mw0jWsdBvoRXE2x27rguzV2wyk5srqNePY752T5cL-8fUoWb4_Pt9eLxORlNiTacKaxMkxqLlcMmbC1lSUA51zmzIh9CF3YjK2qknOLEvJqJbkQOs815HNyMdn2wX9uMA5q7aLBttUd-k1UIISseCGqf6EslwVUYkT5hJrgYwxoVR_cGHOngKl9yapRU8lq_58CUGPJo-xqkuEYeOswqGgcdgZrF9AMqvbub4Nv7laFiQ</recordid><startdate>20150501</startdate><enddate>20150501</enddate><creator>Macedo, Maria N.Q.</creator><creator>Galo, Joaquim J.M.</creator><creator>Almeida, Luiz A.L.</creator><creator>Lima, Antonio C.C.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20150501</creationdate><title>Typification of load curves for DSM in Brazil for a smart grid environment</title><author>Macedo, Maria N.Q. ; Galo, Joaquim J.M. ; Almeida, Luiz A.L. ; Lima, Antonio C.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-ac40ae8c09a49b0e06fdf9711444930c62014a5f20b8744fe9138b9466a33a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Brazil</topic><topic>Consumers</topic><topic>Customers</topic><topic>Demand side management</topic><topic>Distributed memory</topic><topic>Electric power generation</topic><topic>Load curve</topic><topic>Policies</topic><topic>Simulation</topic><topic>Smart grid</topic><topic>Transformations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Macedo, Maria N.Q.</creatorcontrib><creatorcontrib>Galo, Joaquim J.M.</creatorcontrib><creatorcontrib>Almeida, Luiz A.L.</creatorcontrib><creatorcontrib>Lima, Antonio C.C.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>International journal of electrical power & energy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Macedo, Maria N.Q.</au><au>Galo, Joaquim J.M.</au><au>Almeida, Luiz A.L.</au><au>Lima, Antonio C.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Typification of load curves for DSM in Brazil for a smart grid environment</atitle><jtitle>International journal of electrical power & energy systems</jtitle><date>2015-05-01</date><risdate>2015</risdate><volume>67</volume><spage>216</spage><epage>221</epage><pages>216-221</pages><issn>0142-0615</issn><eissn>1879-3517</eissn><abstract>•This study discusses the use of DSM in a smart grid environment in Brazil.•We present the simulation for creating load curve patterns using the k-means technique.•The creation of the load curve patterns is for selecting the policies of DSM.
The deployment of a smart grid environment is a worldwide trend and generates of a large volume of data. The load curve for each consumer in real time is an example of this. The challenge is the transformation of these data into useful information that may help to improve efficiency in the management, planning and operation of the power grid. The implementation of demand side management (DSM) requires an analysis of the data generated in a smart grid environment to determine which policies are most appropriate for each type of consumer. Because of the large number of customers, the application of these policies involves the selection of patterns for the load curve.
This study discusses the use of DSM in a smart grid environment in Brazil and presents the simulation for creating load curve patterns using the k-means technique from the consumer data of a concessionaire for the Brazilian electric system. The result obtained in this research is the creation of the load curve patterns for selecting the policies of DSM.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.ijepes.2014.11.029</doi><tpages>6</tpages></addata></record> |
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| language | eng |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Brazil Consumers Customers Demand side management Distributed memory Electric power generation Load curve Policies Simulation Smart grid Transformations |
| title | Typification of load curves for DSM in Brazil for a smart grid environment |
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