Aggregate Control Strategy for Thermostatically Controlled Loads with Demand Response

The improvement of intelligent appliances provides the basis for the demand response (DR) of residential loads. Thermostatically controlled loads (TCLs) are one of the most important DR resources and are characterized by a large load and a high degree of control. Due to its distribution characteristic, the aggregation of TCLs and their control are key issues in implementing the load control for the DR. In this study, we focus on air conditioning loads as an example of TCLs and propose a simple and transferable aggregate model by establishing a virtual house model, which accurately captures the aggregate flexibility. The deviation of the aggregate model is analyzed for the model evaluation. An air conditioning DR control scheme is proposed based on the aggregate model; it has the advantage of simple implementation and convenient control for the individual units. Simulations are performed in Gridlab-D to evaluate the accuracy and effectiveness of the proposed model and control method.

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Power Retailer Air-Conditioning Load Aggregation Operation Control Method and Demand Response

IEEE Access ◽

10.1109/access.2020.3003278 ◽

2020 ◽

Vol 8 ◽

pp. 112041-112056

Author(s):

Xiangyu Kong ◽

Bowei Sun ◽

Jian Zhang ◽

Shupeng Li ◽

Qun Yang

Keyword(s):

Demand Response ◽

Air Conditioning ◽

Control Method ◽

Operation Control

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Aggregated modeling and control of air conditioning loads for demand response

2014 IEEE PES General Meeting | Conference & Exposition ◽

10.1109/pesgm.2014.6939498 ◽

2014 ◽

Cited By ~ 4

Author(s):

Wei Zhang ◽

Jianming Lian ◽

Chin-Yao Chang ◽

Karanjit Kalsi

Keyword(s):

Demand Response ◽

Air Conditioning ◽

Modeling And Control ◽

And Control

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Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

IEEE Transactions on Power Systems ◽

10.1109/tpwrs.2013.2266121 ◽

2013 ◽

Vol 28 (4) ◽

pp. 4655-4664 ◽

Cited By ~ 244

Author(s):

Wei Zhang ◽

Jianming Lian ◽

Chin-Yao Chang ◽

Karanjit Kalsi

Keyword(s):

Demand Response ◽

Air Conditioning ◽

Modeling And Control ◽

And Control

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Overview of the Load-source Duality Modeling for Demand Side

Journal of Physics Conference Series ◽

10.1088/1742-6596/2095/1/012007 ◽

2021 ◽

Vol 2095 (1) ◽

pp. 012007

Author(s):

Xueying Wang ◽

Yawei Xue ◽

Dong Peng ◽

Lang Zhao ◽

Hongyang Liu ◽

...

Keyword(s):

Power System ◽

Demand Response ◽

Control Method ◽

Development Trend ◽

Green Energy ◽

Load Response ◽

Safety And Reliability ◽

The Difference ◽

Response Modeling ◽

And Control

Abstract With the increase of load and clean-green energy connect to the power system, big challenges are brought to the traditional control method of generation-follows-load (GFL). Therefore, it is important to study the load-follows-generation (LFG) models which can achieve active demand response by changing the load temporarily to reduce the difference between maximum and minimum load. This paper introduces the concept of LFG and GFL models, summarizes the difference between them and puts forward the concept of load-source duality at first. Then, introduces load response modeling, optimization objectives, constraints, scheduling methods and control methods of six LFG models based on the recent research results in this area. Each model can alleviate the pressure in maintaining stability on the generation side, improving the safety and reliability of the power system. Finally, this paper puts forward the future development trend of LFG models based on the overviews.

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Emergent Behavior in a Population of Thermostatically Controlled Loads With Peer-to-Peer Communication

Volume 6: Energy ◽

10.1115/imece2019-10456 ◽

2019 ◽

Author(s):

Ryan Schwartz ◽

John F. Gardner

Keyword(s):

Demand Response ◽

Air Conditioning ◽

Large Scale ◽

Large Population ◽

Agent Based Modeling ◽

Emergent Behavior ◽

Peer Communication ◽

Agent Based ◽

Thermostatically Controlled Loads ◽

Residential Air Conditioning

Abstract Thermostatically controlled loads (TCLs) are often considered as a possible resource for demand response (DR) events. However, it is well understood that coordinated control of a large population of previously un-coordinated TCLs may result in load synchronization that results in higher peaks and large uncontrolled swings in aggregate load. In this paper we use agent based modeling to simulate a number of residential air conditioning loads and allow each to communicate a limited amount of information with their nearest neighbors. As a result, we document emergent behavior of this large scale, distributed and nonlinear system. Using the techniques described here, the population of TCLs experienced up to a 30% reduction in peak demand following the DR event. This behavior is shown to be beneficial to the goals of balancing the grid and integrating increasing penetration of variable generators.

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