Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model

Ran Lv, Enqi Wu, Li Lan, Chen Fu, Mingxing Guo, Feier Chen, Min Wang () and Jie Zou
Additional contact information
Ran Lv: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Enqi Wu: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Li Lan: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Chen Fu: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Mingxing Guo: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Feier Chen: Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China
Min Wang: School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China
Jie Zou: School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China

Energies, 2024, vol. 17, issue 11, 1-19

Abstract: With the rapid development of a social economy, the yearly increase in air conditioning load in the winter and summer seasons may bring serious challenges to the safe and economic operation of the power grid during the peak period of electricity consumption. So, how we reasonably adjust the set temperature of air conditioning so as to cut down the load during peak periods is very important. In this paper, considering the thermal inertia of air-conditioned buildings and the adaptability of human thermal comfort to temperature changes, the air conditioning load is regarded as virtual energy storage, the air conditioning temperature adjustment range for different users is determined based on the adaptive thermal comfort model of different geographic locations and climatic conditions, and a compensation mechanism is set up based on air conditioning users’ level of participation. Then, an optimal scheduling strategy for a microgrid was constructed with the objectives of user satisfaction, carbon emissions, and microgrid operation benefits, as well as regulating the users’ electricity consumption behavior, and the strategy was solved by using a multi-objective JAYA algorithm. Finally, winter and summer are used as case studies to analyze the results, which demonstrate that regulating the virtual energy storage of air conditioning can effectively improve the economy and environmental friendliness of a microgrid operation and reduce the cost of electricity consumption for the users, taking into account the comfort of the users.

Keywords: virtual energy storage; multi-objective optimization; air conditioning load; optimal dispatch (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/11/2670/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/11/2670/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:11:p:2670-:d:1405973

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().