Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control
In recent years, demand response (DR) has played an increasingly important role in maintaining the safety, stability and economic operation of power grid. Due to the continuous running state and extremely fast speed of response, the aggregated inverter air conditioning (IAC) load is considered as th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/2/535 |
| _version_ | 1797494386527830016 |
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| author | Zexu Chen Jing Shi Zhaofang Song Wangwang Yang Zitong Zhang |
| author_facet | Zexu Chen Jing Shi Zhaofang Song Wangwang Yang Zitong Zhang |
| author_sort | Zexu Chen |
| collection | DOAJ |
| description | In recent years, demand response (DR) has played an increasingly important role in maintaining the safety, stability and economic operation of power grid. Due to the continuous running state and extremely fast speed of response, the aggregated inverter air conditioning (IAC) load is considered as the latest and most ideal object for DR. However, it is easy to cause load rebound when the aggregated IAC load participates in DR. Existing methods for controlling air conditioners to participate in DR cannot meet the following three requirements at the same time: basic DR target, load rebound suppression, and users’ comfort. Therefore, this paper has proposed a genetic algorithm based temperature-queuing control method for aggregated IAC load control, which could suppress load rebound under the premise of ensuring the DR target and take users’ comfort into account. Firstly, the model of the aggregated IAC load is established by the Monte Carlo method. Then the start and end time of DR are selected as the main solution variables. A genetic algorithm is used as the solving tool. The simulation results show that the proposed strategy shows better performance in suppressing load rebound. In the specific application scenario of adjusting the frequency fluctuation of the microgrid, the results of the case show that this strategy can effectively control the frequency fluctuation of the microgrid. The effectiveness of the strategy is verified. |
| first_indexed | 2024-03-10T01:33:32Z |
| format | Article |
| id | doaj.art-59dd741eea5047dcaffaa621ca743f51 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T01:33:32Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-59dd741eea5047dcaffaa621ca743f512023-11-23T13:37:49ZengMDPI AGEnergies1996-10732022-01-0115253510.3390/en15020535Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load ControlZexu Chen0Jing Shi1Zhaofang Song2Wangwang Yang3Zitong Zhang4State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaIn recent years, demand response (DR) has played an increasingly important role in maintaining the safety, stability and economic operation of power grid. Due to the continuous running state and extremely fast speed of response, the aggregated inverter air conditioning (IAC) load is considered as the latest and most ideal object for DR. However, it is easy to cause load rebound when the aggregated IAC load participates in DR. Existing methods for controlling air conditioners to participate in DR cannot meet the following three requirements at the same time: basic DR target, load rebound suppression, and users’ comfort. Therefore, this paper has proposed a genetic algorithm based temperature-queuing control method for aggregated IAC load control, which could suppress load rebound under the premise of ensuring the DR target and take users’ comfort into account. Firstly, the model of the aggregated IAC load is established by the Monte Carlo method. Then the start and end time of DR are selected as the main solution variables. A genetic algorithm is used as the solving tool. The simulation results show that the proposed strategy shows better performance in suppressing load rebound. In the specific application scenario of adjusting the frequency fluctuation of the microgrid, the results of the case show that this strategy can effectively control the frequency fluctuation of the microgrid. The effectiveness of the strategy is verified.https://www.mdpi.com/1996-1073/15/2/535demand responsepower systemsmart gridmicrogrid |
| spellingShingle | Zexu Chen Jing Shi Zhaofang Song Wangwang Yang Zitong Zhang Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control Energies demand response power system smart grid microgrid |
| title | Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control |
| title_full | Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control |
| title_fullStr | Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control |
| title_full_unstemmed | Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control |
| title_short | Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control |
| title_sort | genetic algorithm based temperature queuing method for aggregated iac load control |
| topic | demand response power system smart grid microgrid |
| url | https://www.mdpi.com/1996-1073/15/2/535 |
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