Optimal Scheduling of Active Distribution Considering Uncertainties in Wind and Solar Power Generation

This article aims to optimally schedule an active distribution considering uncertainties in both wind and solar power generations. In this respect, an optimal scheduling model to minimize electricity interaction and maximize the autonomous defense capability of active distribution, achieving economical and efficient operation is firstly developed; a sampling and clustering approach is then introduced to quantify the uncertainty in both wind and solar power generations; and an improved genetic algorithm is finally proposed to solve the corresponding optimal scheduling problem. The numerical results from the case study demonstrate that the proposed approach effectively manages the uncertainty in wind and solar power integration, leading to more stable and cost-efficient power system scheduling.