Paper
13 May 2024 Study on the potential of virtual power plants based on LEAP model: a case study of a northern city
Xiaohan Yu, Lingxiao Fu, Hongtao Liu, Peng Wang
Author Affiliations +
Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 131597R (2024) https://doi.org/10.1117/12.3024459
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China
Abstract
By aggregating decentralized resources, Virtual Power Plants (VPP) provide a reliable and flexible way to regulate power systems. Currently, the development of virtual power plants in China is in its infancy. Taking N city as an example, this paper evaluates the dispatchable resource capacity, the ability to guarantee power supply reliability, and the carbon emissions under different scenarios, and conducts a quantitative study on the development potential of virtual power plants in N city. This study uses the Long-range Energy Alternatives Planning (LEAP) framework to conduct the assessment, and sets three scenarios, namely the baseline scenario, the renewable energy development scenario, and VPP scenario. The results show that in the renewable energy development scenario, the level of renewable energy consumption and carbon reduction capacity continues to grow. In the VPP scenario, as the VPP's ability to aggregate resources increases, the utilization of renewable energy increases, resulting in the ability to better secure loads and achieving better carbon emission reduction and being able to accelerate the achievement of the power sector's carbon neutrality goal. This study has positive practical significance for the promotion of virtual power plants across the country.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaohan Yu, Lingxiao Fu, Hongtao Liu, and Peng Wang "Study on the potential of virtual power plants based on LEAP model: a case study of a northern city", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 131597R (13 May 2024); https://doi.org/10.1117/12.3024459
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KEYWORDS
Carbon

Renewable energy

Solar energy

Atmospheric modeling

Power consumption

Industry

Data modeling

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