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在低碳电力调度框架内，如何应对新能源出力的不确定性、设计相应的低碳调度方式，进而提升新能源消纳比率是需要研究的重要问题。为此，文章首先运用自适应核密度估计法拟合了风电、光电的出力特性，利用Copula函数描述了风电、光电出力之间的相关性，结合场景分析法刻画了二者联合出力的不确定性；接着，在风光联合出力场景及其概率特征的基础上，建立了风-光-火协同优化电力调度模型；然后，在调度模型中引入了阶梯式碳价格进一步控制碳排放量，双目标优化问题也随之转化为单目标优化问题。算例分析结果表明，实施阶梯式碳价格机制后碳排放量减少了4.02%、新能源消纳比率从14.04%提高到71.06%，验证了本文模型与方法的合理性和有效性。
Abstract：To enhance the absorption rate of new energy within the power dispatching of new energy systems, the uncertainty of new energy output must be addressed, and an appropriate low-carbon management mechanism should be designed properly. In this paper, the adaptive kernel density estimation method is used to model the output characteristics of wind power and photovoltaic systems. The correlation between wind power and photovoltaic systems is described using the Copula function, and Monte Carlo simulations are integrated to illustrate wind-solar uncertainties. By obtaining the joint output scenario of wind and solar power and their probability characteristics, a collaborative optimization power dispatching model for wind-solar-thermal power systems is established. Subsequently, the ladder-type carbon price mechanism is introduced into the dispatching model to further reduce carbon emissions, transforming the dual-objective optimization problem into a single-objective optimization problem. A case study confirms that carbon emissions are reduced by 4.02% after the stepped carbon price mechanism is implemented, ultimately increasing the new energy absorption rate from 14.04% to 71.06%, validating the rationality and validity of the model and methods developed in this work.
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基本信息:
DOI：10.12194/j.ntu.20250104001
中图分类号:TM73;TM743
引用信息:
[1]周超阳,赵丽雅,李琳琳,等.基于阶梯式碳价格的风-光-火协同优化调度建模与仿真[J].南通大学学报(自然科学版),2026,25(02):53-62.DOI:10.12194/j.ntu.20250104001.
基金信息:
江苏省研究生科研与实践创新计划项目（KYCX24＿3624）; 南通市科技计划项目（MS2023001）
2025-04-09
2025-04-09
2025-04-09