A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

Yingying Chen; Fengji Luo; Zhaoyang Dong; Ke Meng; Gianluca Ranzi; Kit Po Wong

doi:10.1007/s40565-018-0431-3

A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

Yingying Chen, Fengji Luo^*, Zhaoyang Dong, Ke Meng, Gianluca Ranzi, Kit Po Wong

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

31 Citations (Scopus)

21 Downloads (CityUHK Scholars)

Abstract

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. © 2018, The Author(s).

Original language	English
Pages (from-to)	568-578
Journal	Journal of Modern Power Systems and Clean Energy
Volume	7
Issue number	3
DOIs	https://doi.org/10.1007/s40565-018-0431-3
Publication status	Published - 1 May 2019
Externally published	Yes

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Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Demand response
Demand side management
Direct load control
Thermal comfort model
Thermostatically controlled load

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This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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title = "A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model",

abstract = "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{\textquoteright}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. {\textcopyright} 2018, The Author(s).",

keywords = "Demand response, Demand side management, Direct load control, Thermal comfort model, Thermostatically controlled load",

author = "Yingying Chen and Fengji Luo and Zhaoyang Dong and Ke Meng and Gianluca Ranzi and Wong, {Kit Po}",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].",

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A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model. / Chen, Yingying; Luo, Fengji; Dong, Zhaoyang et al.
In: Journal of Modern Power Systems and Clean Energy, Vol. 7, No. 3, 01.05.2019, p. 568-578.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

TY - JOUR

T1 - A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

AU - Chen, Yingying

AU - Luo, Fengji

AU - Dong, Zhaoyang

AU - Meng, Ke

AU - Ranzi, Gianluca

AU - Wong, Kit Po

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2019/5/1

Y1 - 2019/5/1

N2 - 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. © 2018, The Author(s).

AB - 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. © 2018, The Author(s).

KW - Demand response

KW - Demand side management

KW - Direct load control

KW - Thermal comfort model

KW - Thermostatically controlled load

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A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

Abstract

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Research Keywords

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