摘要
在新能源出力不确定性情况下,园区综合能源系统碳交易响应新能源消纳的动态调整能力较差,存在交易非实时性、静态性问题。为更加有效地引导碳交易优化园区综合能源系统低碳调度方案,该文提出一种计及动态激励机制的分时阶梯式碳交易优化模型和两阶段非线性鲁棒优化模型的求解方法。首先,建立多能源耦合的园区综合能源系统模型,为保证电-热能源出力的灵活性,构建热电比可调的热电联产机组模型。其次,以调度前一时段新能源消纳能力实时滚动激励下一时段碳交易参数,建立动态激励机制的分时阶梯式碳交易模型和min-max-min非线性优化模型。再次,提出考虑多维0-1变量矩阵和哈达玛积的阶梯式函数线性化方法和McCormick包络收紧策略确保模型的线性化和精度。然后,提出条件法分段解耦两阶段内层模型(karush-kuhn-tucker,KKT),避免复杂非线性目标函数下传统对偶变换的不适用性,针对不同光伏场景求解最恶劣场景下新能源出力。最后,以某园区为例,算例分析验证了所提模型的正确性和有效性。相比传统非激励机制的阶梯式碳交易模型,在恶劣场景与最优场景下所提模型的经济成本分别降低5.97%和1.88%,系统碳排放分别减少1440kg和466.4kg,提高新能源消纳能力的同时保证了碳交易的实时性、动态性。
Considering the uncertainty of renewable energy output,the current carbon trading response to the consumption of new energy in the park's integrated energy system has poor dynamic adjustment capability,with issues of non-real-time trading and static nature.To more effectively facilitate carbon trading and optimize the low-carbon dispatch strategy of park-integrated energy systems,this paper proposes a time-sharing stepped carbon trading optimization model with a dynamic incentive mechanism and a solution method for a two-stage nonlinear robust optimization model.First,a park integrated energy system model with multi-energy coupling is established,and a model of combined heat and power units with adjustable heat-to-power ratios is constructed to ensure the flexibility of electricity and heat energy output.Then,by utilizing the real-time rolling incentive of renewable energy consumption capacity from the previous period to adjust the carbon trading parameters for the next period,a time-sharing stepped carbon trading model with a dynamic incentive mechanism and a min-max-min nonlinear optimization model is established.Furthermore,a linearization method is employed for step-wise functions,which considers a multidimensional 0-1 variable matrix and the Hadamard product,along with the McCormick envelope tightening strategy,to ensure the model's linearization and accuracy.Afterwards,the karush-kuhn-tucker(KKT)conditions method is proposed to transform the piecewise decoupled two-stage inner model,thereby avoiding the inapplicability of traditional dual transformations under complex nonlinear objective functions,and solving for the renewable energy output under the worst-case scenario for different photovoltaic scenarios.Finally,taking a certain park as an example,the case study analysis verifies that the proposed model,compared to the traditional stepped carbon trading model without incentive mechanisms reduce economic costs by 5.97%and 1.88%under worst-case scenarios and optimal scenarios,respectively,while decreasing system carbon emissions by 1,440 kg and 466.4 kg,thereby improving the renewable energy consumption capacity of the system while ensuring the real-time and dynamic nature of carbon trading.
作者
傅嘉琪
孙永辉
殷晨旭
圣凡
赵亮
孟雲帆
FU Jiaqi;SUN Yonghui;YIN Chenxu;SHENG Fan;ZHAO Liang;MENG Yunfan(School of Electrical and Power Engineering,Hohai University,Nanjing 210098,Jiangsu Province,China)
出处
《电网技术》
北大核心
2025年第11期4638-4648,I0065-I0068,共15页
Power System Technology
基金
国家自然科学基金项目(NO.62073121)。
关键词
园区综合能源系统
分时阶梯式碳交易
两阶段鲁棒优化
新能源动态激励机制
风光不确定性
park integrated energy system
time-sharing stepped carbon trading model
two-stage robust optimization
dynamic incentives mechanism for renewable energy
wind and photovoltaic uncertainty
