基于改进模糊均衡策略的碳循环虚拟电厂多目标鲁棒随机调度优化模型

A Multi-objective Robust Stochastic Optimal Dispatching Model for Carbon Cycle Virtual Power Plant Based on Improved Fuzzy Equilibrium Strategy

燃气碳捕集(gas-power plant carbon capture,GPPCC)设备能捕集CO_(2),电转气(power-to-gas,P2G)设备可将CO_(2)转化为甲烷,提出将GPPCC、储碳设备(carbon storage device,CS)和P2G与虚拟电厂(virtual power plant,VPP)进行连接,即C2P-VPP。首先,搭建C2P-VPP结构并构建数学模型;然后,选择最小化调度成本、最小化碳排放量、最小化出力波动作为优化目标,并利用鲁棒随机优化理论刻画风力发电厂(wind power plants,WPP)和光伏(photovoltaic,PV)发电的不确定性,建立C2P-VPP多目标随机最优调度模型。最后,选择CIGRE中压配电系统进行算例分析,结果表明所提最优决策模型能发挥C2P的电-碳-电循环优化效应,为决策者制定兼顾C2P-VPP调度方案提供有效的决策工具。

In gas-fired power plant carbon capture(GPPCC),carbon dioxide(CO2)is captured and converted to methane(CH4)via power-to-gas(P2G).This paper proposes connecting GPPCC,carbon storage device(CS),and P2G with a virtual power plant(i.e.,C2P-VPP).First,a C2P-VPP structure and a mathematical model were constructed.Subsequently,the dispatch cost,carbon emissions,and output fluctuation are minimized as the optimal objectives,and the robust stochastic optimal theory is employed to characterize the uncertainty of wind power plants(WPPs)and photovoltaic power plants,and establish a C2P-VPP multi-objective stochastic optimal dispatching model.Finally,the CIGRE mediumvoltage distribution system was selected for the analysis.The results show that the proposed optimal decision model can exert the electrocarbon–electric cycle optimal effect of C2P and provide an effective tool to aid decisionmakers in balancing the C2P-VPP dispatching scheme.