Customer baseline load models for residential sector in a smart-grid environment
Demand response (DR) can expand the customer participation in the electricity market and lead by changing its pattern from a simple function to an interactive relation. There are various methods to evaluate the successful implementation of DR program, the most important of which is determination of...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016-11-01
|
| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484716300130 |
| _version_ | 1818684205861699584 |
|---|---|
| author | R. Sharifi S.H. Fathi V. Vahidinasab |
| author_facet | R. Sharifi S.H. Fathi V. Vahidinasab |
| author_sort | R. Sharifi |
| collection | DOAJ |
| description | Demand response (DR) can expand the customer participation in the electricity market and lead by changing its pattern from a simple function to an interactive relation. There are various methods to evaluate the successful implementation of DR program, the most important of which is determination of customer baseline load (CBL). In fact, CBL is the expected pattern of customer consumption in the absence of DR programs. Few works have been done in the field of calculation of CBL in residential sector, while most of them have paid little attention to the impact of changes in weather conditions on these calculations.
In this paper, a new method is presented for the calculation of CBL for customers in residential sector in the context of a smart grid, considering the impact of weather changes. The results clearly show the high impact of changes in weather conditions on the calculation of CBL, and also show the extent of effect of buildings’ improved insulation on this parameter. It is also indicated that implementing DR programs can increase the willingness of customers in residential sector to improve the insulations of their buildings. |
| first_indexed | 2024-12-17T10:46:56Z |
| format | Article |
| id | doaj.art-241e8d8a921a4fa3a138f391dce2016e |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-12-17T10:46:56Z |
| publishDate | 2016-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-241e8d8a921a4fa3a138f391dce2016e2022-12-21T21:52:06ZengElsevierEnergy Reports2352-48472016-11-012C748110.1016/j.egyr.2016.04.003Customer baseline load models for residential sector in a smart-grid environmentR. Sharifi0S.H. Fathi1V. Vahidinasab2Department of Electrical Engineering, Amirkabir University of Technology, Tehran, IranDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, IranDepartment of Electrical Engineering, Shahid Beheshti University, Tehran, IranDemand response (DR) can expand the customer participation in the electricity market and lead by changing its pattern from a simple function to an interactive relation. There are various methods to evaluate the successful implementation of DR program, the most important of which is determination of customer baseline load (CBL). In fact, CBL is the expected pattern of customer consumption in the absence of DR programs. Few works have been done in the field of calculation of CBL in residential sector, while most of them have paid little attention to the impact of changes in weather conditions on these calculations. In this paper, a new method is presented for the calculation of CBL for customers in residential sector in the context of a smart grid, considering the impact of weather changes. The results clearly show the high impact of changes in weather conditions on the calculation of CBL, and also show the extent of effect of buildings’ improved insulation on this parameter. It is also indicated that implementing DR programs can increase the willingness of customers in residential sector to improve the insulations of their buildings.http://www.sciencedirect.com/science/article/pii/S2352484716300130Demand response (DR)Demand side management (DSM)Customer baseline load (CBL)Building load coefficient (BLC)Building insulationFlexible load (FL)Non-flexible load (NFL) |
| spellingShingle | R. Sharifi S.H. Fathi V. Vahidinasab Customer baseline load models for residential sector in a smart-grid environment Energy Reports Demand response (DR) Demand side management (DSM) Customer baseline load (CBL) Building load coefficient (BLC) Building insulation Flexible load (FL) Non-flexible load (NFL) |
| title | Customer baseline load models for residential sector in a smart-grid environment |
| title_full | Customer baseline load models for residential sector in a smart-grid environment |
| title_fullStr | Customer baseline load models for residential sector in a smart-grid environment |
| title_full_unstemmed | Customer baseline load models for residential sector in a smart-grid environment |
| title_short | Customer baseline load models for residential sector in a smart-grid environment |
| title_sort | customer baseline load models for residential sector in a smart grid environment |
| topic | Demand response (DR) Demand side management (DSM) Customer baseline load (CBL) Building load coefficient (BLC) Building insulation Flexible load (FL) Non-flexible load (NFL) |
| url | http://www.sciencedirect.com/science/article/pii/S2352484716300130 |
| work_keys_str_mv | AT rsharifi customerbaselineloadmodelsforresidentialsectorinasmartgridenvironment AT shfathi customerbaselineloadmodelsforresidentialsectorinasmartgridenvironment AT vvahidinasab customerbaselineloadmodelsforresidentialsectorinasmartgridenvironment |