Dynamic Reactive Power Allocation Optimization Considering Effectiveness under High Penetration of Renewable Energy

Integrating a lot of renewable energy sources makes the power generation decisions and the need for generation highly uncertain at the same time. This, in turn, leads to a condition where there is high voltage instability, and the reactive power reserve of the existing grids is consumed. To tackle this head-on, we are introducing a strategy centered around a two-stage concealing distributionally robust optimization (DRO) procedure, which is also connected to an Automatic Voltage Control (AVC) system that redistributes reactive power through the system depending on the target voltages. This model takes a bird's-eye view, considering the unpredictable nature of renewable energy, the need to meet the N-1 contingency requirements, and how the reactive power reserves perform overall. The real key concepts here are that we've finely integrated a second-order cone relaxation for the power flow constraints and employed a column-and-constraint generation (CCG) algorithm to speed things up, especially for vast grids. We implemented this method in a real 38-node provincial grid in eastern China, and the results speak for themselves: the average voltage deviation rate dropped by 83.7%, from 76.125% to 9.336%, despite a 51.91% penetration of renewable energy sources. Moreover, the performance was consistent under the 50 N-1 contingencies we simulated. Among the other methods we compared, it did the best when it came to low percentages of renewable energy, and the reactive power adjustment frequency decreased by 65%. This approach does factually accomplish the goal of harmonizing what is low cost with the requirement of a robust system, and therefore it is a very handy way to increase the voltage stability in power systems that are increasingly reliant on renewable energy sources.