Study on optimal scheduling model of virtual power plant with low carbon and economic benefits

Against the backdrop of China’s “dual-carbon” targets, distributed wind and solar capacity is surging, yet the vast coal-fired base still subjects the power system to multiple environmental pressures—high carbon emissions, high variability, and the resulting pollution. To break this impasse and mitigate the energy system’s ecological footprint, this paper develops a virtual power plant (VPP) operational-scheduling model that simultaneously minimizes energy-procurement costs, carbon externality costs, and O and M expenses. An empirical analysis demonstrates that the model effectively curbs the environmental externalities of coal-fired peaking units and fosters green resilience in park-level energy systems.

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Publication Details

Published
2025-09-19
DOI
https://doi.org/10.1117/12.3086720
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
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article

Study on optimal scheduling model of virtual power plant with low carbon and economic benefits

Xinsheng Lou, Yan Wang, Yu Sun, Hongwei Ma et al.
Power Systems and Renewable Energy
article

Study on optimal scheduling model of virtual power plant with low carbon and economic benefits

Xinsheng Lou, Yan Wang, Yu Sun, Hongwei Ma, Huidan Zhuo
article en

Abstract

Against the backdrop of China’s “dual-carbon” targets, distributed wind and solar capacity is surging, yet the vast coal-fired base still subjects the power system to multiple environmental pressures—high carbon emissions, high variability, and the resulting pollution. To break this impasse and mitigate the energy system’s ecological footprint, this paper develops a virtual power plant (VPP) operational-scheduling model that simultaneously minimizes energy-procurement costs, carbon externality costs, and O and M expenses. An empirical analysis demonstrates that the model effectively curbs the environmental externalities of coal-fired peaking units and fosters green resilience in park-level energy systems.

Jiangsu Yonggang Group (China) (CN)
Openalex Percentile: Top 72%
Power Systems and Renewable Energy
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