scholarly journals Demand Response From the Control of Aggregated Inverter Air Conditioners

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 88163-88173 ◽  
Author(s):  
Yanbo Che ◽  
Jianxiong Yang ◽  
Yue Zhou ◽  
Yuancheng Zhao ◽  
Wei He ◽  
...  
Keyword(s):  
Demand Response ◽  
Air Conditioners

scholarly journals An Analytical Model for Demand Response of Variable-Speed Air Conditioners

2018 ◽  
Vol 51 (28) ◽  
pp. 426-431 ◽  
Author(s):  
Berend Jan Christiaan van Putten ◽  
Nariman Mahdavi ◽  
Julio H. Braslavsky
Keyword(s):  
Analytical Model ◽  
Demand Response ◽  
Variable Speed ◽  
Air Conditioners

Demand Response Control Technique for Smart Air Conditioners Using NB-PLC

2018 ◽  
Vol E101.B (3) ◽  
pp. 723-730 ◽  
Author(s):  
Bilal MASOOD ◽  
Waheed Aftab KHAN ◽  
Manzoor ELLAHI ◽  
Talha ARSHAD ◽  
Muhammad Farooq AMJAD ◽  
...  
Keyword(s):  
Demand Response ◽  
Control Technique ◽  
Response Control ◽  
Air Conditioners

scholarly journals Generation-Load Coordinative Scheduling considering the Demand-Response Uncertainty of Inverter Air Conditioners

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wei Hu ◽  
Jin Yang ◽  
Yi Wu ◽  
Weiguo Zhang ◽  
Xueming Li ◽  
...  
Keyword(s):  
Power System ◽  
Demand Response ◽  
Load Scheduling ◽  
Air Conditioners ◽  
Power Scheduling ◽  
Scheduling Model ◽  
Conditioning Equipment ◽  
The Cost ◽  
First Time

Inverter air conditioners (IACs) have gradually become the mainstream of resident air-conditioning equipment. Similar to traditional fixed-frequency air conditioners, IACs have the potential for demand response and load scheduling. However, the uncertainty of IACs is nonnegligible in generation-load scheduling. In this paper, the uncertain demand-response cost of IACs is studied for the first time. Meanwhile, based on the cost, a generation-load coordinative day-ahead scheduling model is proposed. In the scheduling, an IACs aggregator and traditional generators are coordinately dispatched to minimize the expected scheduling cost of the power system. The case study shows that the coordinative scheduling model can reduce the scheduling cost of the power system and encourage the IACs aggregator to improve their responsiveness or reduce their uncertainty, so as to improve the economy and reliability of power scheduling.

scholarly journals Control Strategy of Constant-Speed Air-Conditioners Based on Virtual State of Charging Priority

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yanbo Che ◽  
Zheng Li ◽  
Wei He ◽  
Yuancheng Zhao ◽  
Ruiping Zhang
Keyword(s):  
Demand Response ◽  
Control Strategy ◽  
Control Function ◽  
Constant Speed ◽  
Operating Characteristics ◽  
Air Conditioners ◽  
Energy Conversion And Storage ◽  
Control Load ◽  
Thermostatically Controlled Loads ◽  
Load Regulation

As typical thermostatically controlled loads (TCL) driven by constant-speed compressor, constant-speed air-conditioners play important roles in demand-side response for their abilities of energy conversion and storage. Their great potential for load regulation can be incorporated into power system scheduling through demand response. In view of their operating characteristics, a virtual energy storage (VES) model of thermostatically controlled loads with electrical and thermal parameters is established. This model is discretized and linearized to simplify calculation. By analyzing the control function and constraints of the VES model, the control strategy of VES of constant-speed air-conditioners load with virtual charging state priority is proposed. Example analysis shows that this strategy can solve and alleviate power shortage problem of the system by participating in demand response, which provides methodological support for constant-speed compressor temperature-control load to participate in the system operation.

scholarly journals Data-Driven Load Forecasting of Air Conditioners for Demand Response Using Levenberg–Marquardt Algorithm-Based ANN

2019 ◽  
Vol 3 (3) ◽  
pp. 36 ◽  
Author(s):  
Muhammad Waseem ◽  
Zhenzhi Lin ◽  
Li Yang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Power Systems ◽  
Demand Response ◽  
Load Forecasting ◽  
Big Data Analysis ◽  
Statistical Regression ◽  
Air Conditioners ◽  
Marquardt Algorithm ◽  
Levenberg Marquardt

Air Conditioners (AC) impact in overall electricity consumption in buildings is very high. Therefore, controlling ACs power consumption is a significant factor for demand response. With the advancement in the area of demand side management techniques implementation and smart grid, precise AC load forecasting for electrical utilities and end-users is required. In this paper, big data analysis and its applications in power systems is introduced. After this, various load forecasting categories and various techniques applied for load forecasting in context of big data analysis in power systems have been explored. Then, Levenberg–Marquardt Algorithm (LMA)-based Artificial Neural Network (ANN) for residential AC short-term load forecasting is presented. This forecasting approach utilizes past hourly temperature observations and AC load as input variables for assessment. Different performance assessment indices have also been investigated. Error formulations have shown that LMA-based ANN presents better results in comparison to Scaled Conjugate Gradient (SCG) and statistical regression approach. Furthermore, information of AC load is obtainable for different time horizons like weekly, hourly, and monthly bases due to better prediction accuracy of LMA-based ANN, which is helpful for efficient demand response (DR) implementation.

scholarly journals Control Strategy for Inverter Air Conditioners under Demand Response

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 407 ◽  
Author(s):  
Yanbo Che ◽  
Jianxiong Yang ◽  
Yuancheng Zhao ◽  
Siyuan Xue
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Control Strategy ◽  
Air Conditioning ◽  
Power Grid ◽  
Thermal Parameter ◽  
State Of Charge ◽  
Operating Characteristics ◽  
Air Conditioners ◽  
Storage Model

Air conditioning loads are important resources for demand response. With the help of thermal energy storage capacity, they can reduce peak load, improve the reliability of power grid operations, and enhance the emergency capacity of a power grid, without affecting the comfort of the users. In this paper, a virtual energy storage model for inverter air conditioning loads, which reflects their operating characteristics and is more conducive to practical application, is established. Two parts are involved in the virtual energy storage model: An electrical parameter part, based on the operating characteristics, and a thermal parameter part, based on the equivalent thermal parameter model. The control function and restrictive conditions of the virtual energy storage are analyzed and a control strategy, based on virtual state-of-charge ranking, is proposed. The strategy controls the inverter air conditioners through re-assigning indoor temperature set-points within the pre-agreed protocol interval and gives priority those with a higher virtual state of charge. As a result, electric power consumption is reduced while the temperature remains unchanged, so that a shortage in the power system can be compensated for as much as possible, while the comfort of users is guaranteed. Simulation and example analyses show that the strategy is effective in controlling air conditioning loads. Additionally, the influences of load reduction target magnitude and communication time-step on the performance of the control strategy are analyzed.

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