Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties
|更新时间:2025-11-23
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Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties
Vol. 62, Issue 5, (2025)
作者机构:
1. 上海电力大学
2. 上海电力大学电气工程学院
3. 新能源电力系统国家重点实验室(华北电力大学)
作者简介:
基金信息:
DOI:
CLC:
Published:2025
稿件说明:
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bian xin yi, Fan Hong, Zeng Bo. Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties[J]. 2025, 62(5).
DOI:
bian xin yi, Fan Hong, Zeng Bo. Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties[J]. 2025, 62(5).DOI:
Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties
摘要
双碳背景下,寻求可持续的能源生产与消费方式尤为重要。为进一步提升综合能源系统的经济性与低碳性,文章构造了综合能源系统(integrated energy sysytem
it is particularly important to seek sustainable energy production and consumption. In order to further improve the economy and low carbon of the integrated energy system
the paper constructs the structure of the integrated energy system (IES)
improves and adds carbon capture devices and electric-to-gas devices in the system
and considers the optimization mechanism with stepped carbon trading to further control carbon emissions. The master-slave pricing model of energy operators and load aggregators under the system is established. The operator is taken as the leader to optimize the electricity price and output planning strategy
and solve the multiple uncertainties of electricity price and scenery through robust optimization and opportunity constraints. The load aggregator is regarded as the follower to optimize the energy utilization strategy to maximize its benefits. The improved differential evolution method of double variation is used in combination with YEMIP and CPLEX tools for simulation in MATLAB
and the results verify that the model can not only better balance the interests of comprehensive energy operators and load aggregators
but also effectively reduce carbon emissions and improve the ability of the system to deal with uncertain risks.
Integrated energy microgrid scheduling considering carbon emission
Distributionally robust optimization for integrated energy distribution network considering vine Copula uncertainty of wind power, photovoltaic and demand side response
Operation optimization of micro-grid based on predictive control with consideration of carbon trade price
Load aggregator adjustable capability forecasting based on graph convolution neural network
Study of Online Detection Device Performance EvaluationMethod of Transformation Equipment Based onEmotion Objective Filtration