A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model
This paper proposes a day-ahead dispatch framework of thermostatically controlled loads (TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user's indoor thermal comfort degree through the building thermal inertia modelling. Based on the therma...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | Journal of Modern Power Systems and Clean Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9158203/ |
| _version_ | 1818606050584035328 |
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| author | Yingying Chen Fengji Luo Zhaoyang Dong Ke Meng Gianluca Ranzi Kit Po Wong |
| author_facet | Yingying Chen Fengji Luo Zhaoyang Dong Ke Meng Gianluca Ranzi Kit Po Wong |
| author_sort | Yingying Chen |
| collection | DOAJ |
| description | This paper proposes a day-ahead dispatch framework of thermostatically controlled loads (TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user's indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a day-ahead TCL scheduling model is formulated, which consists of 3 stages: ① TCL aggregator estimate their maximal controllable TCL capacities at each scheduling time interval by solving a optimization model; ② the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator; and ③ the TCL aggregators schedules the ON/OFF control actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution (HDDE) algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model. |
| first_indexed | 2024-12-16T14:04:42Z |
| format | Article |
| id | doaj.art-6e46c12f3e694b6f87db6d5a21e2f603 |
| institution | Directory Open Access Journal |
| issn | 2196-5420 |
| language | English |
| last_indexed | 2024-12-16T14:04:42Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | Journal of Modern Power Systems and Clean Energy |
| spelling | doaj.art-6e46c12f3e694b6f87db6d5a21e2f6032022-12-21T22:28:57ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202019-01-017356857810.1007/s40565-018-0431-39158203A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort modelYingying Chen0Fengji Luo1https://orcid.org/0000-0003-4041-6062Zhaoyang Dong2Ke Meng3Gianluca Ranzi4Kit Po Wong5Visionstream Australia Pty Ltd,Sydney,NSW,Australia,2067School of Civil Engineering, University of Sydney,Sydney,NSW,Australia,2006School of Electrical Engineering and Telecommunications, University of New South Wales,Sydney,NSW,Australia,2052School of Electrical Engineering and Telecommunications, University of New South Wales,Sydney,NSW,Australia,2052School of Civil Engineering, University of Sydney,Sydney,NSW,Australia,2006School of Electrical, Electronics, and Computer Engineering, University of Western Australia,Crawley,WA,Australia,6009This paper proposes a day-ahead dispatch framework of thermostatically controlled loads (TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user's indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a day-ahead TCL scheduling model is formulated, which consists of 3 stages: ① TCL aggregator estimate their maximal controllable TCL capacities at each scheduling time interval by solving a optimization model; ② the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator; and ③ the TCL aggregators schedules the ON/OFF control actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution (HDDE) algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.https://ieeexplore.ieee.org/document/9158203/Thermostatically controlled loadDemand side managementThermal comfort modelDemand responseDirect load control |
| spellingShingle | Yingying Chen Fengji Luo Zhaoyang Dong Ke Meng Gianluca Ranzi Kit Po Wong A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model Journal of Modern Power Systems and Clean Energy Thermostatically controlled load Demand side management Thermal comfort model Demand response Direct load control |
| title | A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| title_full | A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| title_fullStr | A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| title_full_unstemmed | A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| title_short | A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| title_sort | day ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model |
| topic | Thermostatically controlled load Demand side management Thermal comfort model Demand response Direct load control |
| url | https://ieeexplore.ieee.org/document/9158203/ |
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