Assessing the maximum carbon reduction potential of regional power grids from grid operators' perspective

The influence of reactive power on carbon emissions in power flows has been largely underestimated, limiting the assessment of grid-side carbon reduction potential and hindering effective emission accountability. To address this, this study develops an operator-oriented framework to quantify the maximum carbon reduction potential of regional power grids through optimal reactive power compensation, considering operational constraints. The framework models how reactive power affects voltage profiles, power flow distribution, and network losses, and accordingly establishes a carbon flow accounting method aligned with actual network power distribution. Carbon-reactive power sensitivity indices are introduced to identify critical buses where compensation yields the greatest emission reduction. Based on these insights, a constrained optimization model is formulated to search for the maximum boundary of system-level carbon reduction. Due to nonlinear objectives, discrete decision variables, and mixed equality-inequality constraints, conventional solvers are insufficient. To address this, an exponential-trigonometric optimization (ETO) algorithm, leveraging a two-stage exploration-exploitation mechanism, is employed to efficiently search for the theoretical boundary of carbon reduction potential. Case studies on IEEE 30-bus and 118-bus systems demonstrate emission reductions of 1.06 t/h and 8.38 t/h, respectively, while maintaining voltage stability. Results show that even limited investments in reactive power devices can achieve substantial emission reductions, providing a cost-effective pathway for grid-side decarbonization. Comparative analysis confirms that the proposed framework outperforms alternative approaches in accounting accuracy, emission reduction, and operational reliability. Overall, the framework offers grid operators a practical and precise tool for low-carbon operation under realistic operational constraints.