Renewable voltage control method for distribution networks based on multi-layer stochastic model prediction
"Zero-carbon electricity"is a crucial support for achieving the"dual carbon"goals,and adopting renewable energy generation is an important measure to achieve"zero-carbon electricity".The integration of a high proportion of renewable energy into distribution networks presents significant challenges for voltage control.Additionally,renewable energy such as wind farms is characterized by high randomness and intermittency,making traditional voltage control methods ineffective under scenarios with high renewable energy penetration.To address these voltage control issues,this paper proposes a voltage control method based on a dual-layer stochastic model predictive control(MPC)approach.In the proposed method,transformers and shunt capacitors are controlled at the upper layer on an hourly basis,while the lower layer controller adjusts the output of distributed generation(DG)with a 15-minute control cycle.This method combines the advantages of MPC and stochastic optimization,achieving effective voltage control and reducing carbon emissions.Simulation results based on an improved IEEE 33 bus system demonstrate that the proposed method can effectively coordinate different voltage regulation devices,achieve good voltage control effects under high randomness of renewable energy penetration,ensure the economic operation of the distribution network,and significantly reduce the carbon emissions of the distribution network.
distribution networkvoltage controlcarbon emissionstochastic model predictive controldistributed generation
万方数据
维普
