Distributed Demand Response Management for a Virtually Connected Community With Solar Power
With the high proliferation of solar power, curtailments and higher capacity reserves are required for a reliable power system operation. However, system operators can tap into demand flexibility to maintain reliability affordably. Temperature-controlled loads (TCL) have higher flexibility in demand...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9676653/ |
| _version_ | 1818955953837441024 |
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| author | Chirath Pathiravasam Ganesh K. Venayagamoorthy |
| author_facet | Chirath Pathiravasam Ganesh K. Venayagamoorthy |
| author_sort | Chirath Pathiravasam |
| collection | DOAJ |
| description | With the high proliferation of solar power, curtailments and higher capacity reserves are required for a reliable power system operation. However, system operators can tap into demand flexibility to maintain reliability affordably. Temperature-controlled loads (TCL) have higher flexibility in demand response due to their frequency of operation, power rating, and tolerance in the desired operating region. In this study, a TCL demand flexibility quantification is presented using temperature measurements and consumer preferences, and predictions of TCL demand flexibility and solar power generation are used to improve demand response (DR) reliability. The utility can leverage predictions to issue DR requests considering resource adequacy and operational costs. Consumers are formed as a virtually connected community, and an aggregator facilitates the utility in providing situational intelligence and distributing DR requests among consumers. A distributed DR management framework is proposed based on demand flexibility to (a) simplify the optimization and (b) improve optimality. Typical results show power consumption reduction during peak reduction and emergency DR requests and power consumption with low variability during capacity firming requests compared to individual thermostat controls. Two indices to measure DR reliability and consumer comfort are defined, and results are presented for different DR requests. |
| first_indexed | 2024-12-20T10:46:15Z |
| format | Article |
| id | doaj.art-e2202c5703be4611a30b2cb35b7d2f8a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T10:46:15Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e2202c5703be4611a30b2cb35b7d2f8a2022-12-21T19:43:24ZengIEEEIEEE Access2169-35362022-01-01108350836210.1109/ACCESS.2022.31417729676653Distributed Demand Response Management for a Virtually Connected Community With Solar PowerChirath Pathiravasam0https://orcid.org/0000-0001-5660-2076Ganesh K. Venayagamoorthy1https://orcid.org/0000-0003-3154-8119Holcombe Department of Electrical and Computer Engineering, Real-Time Power and Intelligent Systems Laboratory, Clemson University, Clemson, SC, USAHolcombe Department of Electrical and Computer Engineering, Real-Time Power and Intelligent Systems Laboratory, Clemson University, Clemson, SC, USAWith the high proliferation of solar power, curtailments and higher capacity reserves are required for a reliable power system operation. However, system operators can tap into demand flexibility to maintain reliability affordably. Temperature-controlled loads (TCL) have higher flexibility in demand response due to their frequency of operation, power rating, and tolerance in the desired operating region. In this study, a TCL demand flexibility quantification is presented using temperature measurements and consumer preferences, and predictions of TCL demand flexibility and solar power generation are used to improve demand response (DR) reliability. The utility can leverage predictions to issue DR requests considering resource adequacy and operational costs. Consumers are formed as a virtually connected community, and an aggregator facilitates the utility in providing situational intelligence and distributing DR requests among consumers. A distributed DR management framework is proposed based on demand flexibility to (a) simplify the optimization and (b) improve optimality. Typical results show power consumption reduction during peak reduction and emergency DR requests and power consumption with low variability during capacity firming requests compared to individual thermostat controls. Two indices to measure DR reliability and consumer comfort are defined, and results are presented for different DR requests.https://ieeexplore.ieee.org/document/9676653/Demand flexibilitydistributed demand responseDR reliabilitysolar PV powertemperature-controlled loadsvirtually connected community |
| spellingShingle | Chirath Pathiravasam Ganesh K. Venayagamoorthy Distributed Demand Response Management for a Virtually Connected Community With Solar Power IEEE Access Demand flexibility distributed demand response DR reliability solar PV power temperature-controlled loads virtually connected community |
| title | Distributed Demand Response Management for a Virtually Connected Community With Solar Power |
| title_full | Distributed Demand Response Management for a Virtually Connected Community With Solar Power |
| title_fullStr | Distributed Demand Response Management for a Virtually Connected Community With Solar Power |
| title_full_unstemmed | Distributed Demand Response Management for a Virtually Connected Community With Solar Power |
| title_short | Distributed Demand Response Management for a Virtually Connected Community With Solar Power |
| title_sort | distributed demand response management for a virtually connected community with solar power |
| topic | Demand flexibility distributed demand response DR reliability solar PV power temperature-controlled loads virtually connected community |
| url | https://ieeexplore.ieee.org/document/9676653/ |
| work_keys_str_mv | AT chirathpathiravasam distributeddemandresponsemanagementforavirtuallyconnectedcommunitywithsolarpower AT ganeshkvenayagamoorthy distributeddemandresponsemanagementforavirtuallyconnectedcommunitywithsolarpower |