基于MVO算法的新能源接入下的最优碳流及灵敏度分析

Optimal Carbon Flow and Sensitivity Analysis under New Energy Integration Based on MVO Algorithm

  • 摘要: 随着电力系统碳排放的不断增加,电力系统的低碳化改革势在必行。提出一种在新能源接入下的最优碳流计算方法,通过调节发电出力,将发电侧的碳排放量根据负荷节点和支路网损进行合理分摊,并建立新能源降碳数学模型,对新能源机组节能减排的具体贡献进行定量评估。首先分析光伏、风电并网的影响,优化碳流计算模型;其次建立以电网发电成本为优化目标的数学模型,进行优化并将结果作为最优碳流的约束条件;然后通过节点导纳矩阵将发电出力与碳流率进行映射,建立最优碳流计算模型,通过多元宇宙优化算法(Multi-verse optimization,MVO)进行优化并进行灵敏度分析,评估最优解的稳定性和可行性;最后以IEEE 30节点系统进行仿真分析,结果表明,MVO算法较传统的优化算法,能较快地在大规模最优碳流计算模型上实现收敛,具有更好的速度和精度,并且所提出的最优碳流模型在兼顾经济的同时,量化了新能源机组在降碳过程的贡献并降低了约23.41%的碳排放。

     

    Abstract: With the continuous increase in carbon emissions from the power system, low-carbon transformation of the power system is imperative. An optimal carbon flow calculation method under the integration of new energy sources is proposed. By adjusting the power generation output, the carbon emissions on the generation side are reasonably allocated based on load nodes and branch network losses. A mathematical model for carbon reduction of new energy sources is established to quantitatively evaluate the specific contributions of energy-saving and emission reduction by new energy units. First, the impacts of photovoltaic and wind power grid integration are analyzed, and the carbon flow calculation model is optimized. Then, a mathematical model is established with the optimization objective of power grid generation cost, and the results are used as constraints for the optimal carbon flow. Subsequently, the power generation output is mapped to the carbon flow rate using node admittance matrix, and an optimal carbon flow calculation model is established. The multi-verse optimization(MVO), a multi-objective optimization algorithm, is used for optimization and sensitivity analysis to evaluate the stability and feasibility of the optimal solution. Finally, the simulation analysis of the IEEE 30-node system shows that the MVO algorithm can achieve convergence on the large-scale optimal carbon flow calculation model faster than the traditional optimization algorithm, with better speed and accuracy, and the proposed optimal carbon flow model can quantify the contribution of new energy units in the carbon reduction process and reduce carbon emissions by about 23.41% while taking into account the economy.

     

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