Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations
Peak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent sys...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-03-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/9/4/570 |
| _version_ | 1797626458289471488 |
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| author | Peter Schwarz Saeed Mohajeryami Valentina Cecchi |
| author_facet | Peter Schwarz Saeed Mohajeryami Valentina Cecchi |
| author_sort | Peter Schwarz |
| collection | DOAJ |
| description | Peak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent system operators, due to factors that include heterogeneous demands and random variations. Prevailing research is limited for residential markets, which are growing rapidly with the presence of load aggregators and the availability of smart grid systems. Our research pioneers a novel method that clusters customers according to the size and predictability of their demands, substantially improving existing customer baseline calculations and other clustering methods. |
| first_indexed | 2024-03-11T10:10:40Z |
| format | Article |
| id | doaj.art-33ad9673bc434523962edec281c85e4d |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T10:10:40Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-33ad9673bc434523962edec281c85e4d2023-11-16T14:33:17ZengMDPI AGElectronics2079-92922020-03-019457010.3390/electronics9040570Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random VariationsPeter Schwarz0Saeed Mohajeryami1Valentina Cecchi2UNC Charlotte Department of Economics, 9201 University City Blvd, Charlotte, NC 28223-0001, USAAccenture Digital, 1400 16th Street, Suite 500, Denver, CO 80202, USAUNC Charlotte Department of Electrical and Computer Engineering, 9201 University City Blvd., Charlotte, NC 28223-0001, USAPeak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent system operators, due to factors that include heterogeneous demands and random variations. Prevailing research is limited for residential markets, which are growing rapidly with the presence of load aggregators and the availability of smart grid systems. Our research pioneers a novel method that clusters customers according to the size and predictability of their demands, substantially improving existing customer baseline calculations and other clustering methods.https://www.mdpi.com/2079-9292/9/4/570demand responsecustomer baseline loadresidential customersclustering |
| spellingShingle | Peter Schwarz Saeed Mohajeryami Valentina Cecchi Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations Electronics demand response customer baseline load residential customers clustering |
| title | Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations |
| title_full | Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations |
| title_fullStr | Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations |
| title_full_unstemmed | Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations |
| title_short | Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations |
| title_sort | building a better baseline for residential demand response programs mitigating the effects of customer heterogeneity and random variations |
| topic | demand response customer baseline load residential customers clustering |
| url | https://www.mdpi.com/2079-9292/9/4/570 |
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