Optimal Dispatch Method of Thermostatically Controlled Load Based on Cerebellar Model Articulation Controller
Basic Research|更新时间:2025-06-16
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Optimal Dispatch Method of Thermostatically Controlled Load Based on Cerebellar Model Articulation Controller
Automation of Electric Power SystemsVol. 46, Issue 10, Pages: 199-208(2022)
作者机构:
燕山大学电气工程学院,河北省秦皇岛市 066004
作者简介:
基金信息:
National Natural Science Foundation of China(61973264);Hebei Provincial Natural Science Foundation of China(F2021203075);Central Government Guides Local Science and Technology Development Fund Projects(216Z1601G)
YANG Jie,LI Zehui,MA Kai,et al.Optimal Dispatch Method of Thermostatically Controlled Load Based on Cerebellar Model Articulation Controller[J].Automation of Electric Power Systems,2022,46(10):199-208.
YANG Jie,LI Zehui,MA Kai,et al.Optimal Dispatch Method of Thermostatically Controlled Load Based on Cerebellar Model Articulation Controller[J].Automation of Electric Power Systems,2022,46(10):199-208. DOI: 10.7500/AEPS20210804004.
Optimal Dispatch Method of Thermostatically Controlled Load Based on Cerebellar Model Articulation Controller
Thermostatically controlled loads can provide frequency regulation auxiliary services for power grids through demand response. Aiming at the problems of limited adjustment ability and large temperature variation on traditional control methods
a hybrid control strategy based on the cerebellar model articulation controller (CMAC) is proposed. First
the CMAC is used to optimize the power regulation quantity in real time
so as to assign the regulation task to the load clusters with different control methods. Then
the load cluster completes the assigned adjustment task and defines the energy storage index and discomfort index according to the different needs of users
respectively. Finally
the fuzzy comprehensive evaluation method is used to evaluate user satisfaction
and then the user satisfaction and root mean square error are weighed to establish a comprehensive evaluation index which is fed back to the CMAC
thereby providing a basis for the optimization of power regulation quantity. Simulation results show that the proposed strategy can not only increase the system tracking accuracy
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