A scheduling optimization model for a gas-electricity interconnected virtual power plant considering green certificates-carbon joint trading and source-load uncertainties
Jinliang Zhang,
Ziyi Liu and
Yishuo Liu
Energy, 2025, vol. 315, issue C
Abstract:
Virtual power plant (VPP) play a positive role in enhancing the flexibility of new power systems and guaranteeing the safe and stable supply of electricity. In order to enhance the sustainability of gas-electricity interconnected virtual power plant (GVPP) operation and reduce the impact of source-load uncertainty on GVPP scheduling, a research scheme based on interval prediction of source-load data, analysis of trading mechanism, scheduling model construction and solution, and multi-scenario comparison is proposed. First, an improved hybrid interval prediction model is proposed to construct the prediction interval of source-load and portray the uncertainty through the upper and lower bounds of the interval. Second, the coupling principle between green certificate trading and carbon emission trading and the feasibility of GVPP participation in trading are analyzed. Again, the net profit and carbon emission are taken as two optimization objectives to establish a multi-objective optimal scheduling model of GVPP considering the emission reduction effect of green certificate and the source-load uncertainty. Finally, based on the considerations of the model, different scenarios are set up and the comparison of the scheduling results of each scenario is realized. The simulation results show that under the uncertainty condition, the optimal net profit of GVPP is 464,657.39¥, and the carbon emissions offset by green certificates are 246.43t. The proposed model can enhance its willingness to take the initiative to control emissions on the basis of safeguarding the benefits of the system, which improves the plannability of the scheduling scheme.
Keywords: Virtual power plant; Uncertainty; Carbon trading; Green certificate trading; Optimal dispatching (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:315:y:2025:i:c:s0360544225001124
DOI: 10.1016/j.energy.2025.134470
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