Life-cycle Oriented Assessment of Photovoltaic Low-Carbon Economic Carrying Capacity

To address the complex coupling relationship between the increase in installed capacity and the rise in carbon emission cost per unit of electricity production due to distributed photovoltaic (PV) output curtailment, this paper proposes a life-cycle oriented assessment method for evaluating the low-carbon economic carrying capacity of PV systems. First, to assess the optimal PV installation capacity that maximizes the low-carbon economic benefits from curtailment, a deterministic evaluation model for PV low-carbon economic carrying capacity, considering low-carbon economic benefits, is constructed. Second, to address the impact of the uncertainty of distributed PV output on the accuracy of the evaluation results, an additional inner layer “min” is incorporated into the original model to find the worst-case scenario within the Wasserstein fuzzy set, forming a min-max distributionally robust chance-constrained carrying capacity evaluation model. Third, McCormick relaxation and distributionally robust chance-constrained transformation are applied to handle the nonlinear constraints in the evaluation model, and the transformed mixed-integer linear programming model is solved using the CPLEX solver. Finally, an example analysis is conducted using the IEEE 33-bus system to validate the effectiveness of the proposed method.