Model Predictive Driven Volt/VAr Control for Smart Grid Enabled CVR in Active Distribution Network

Abstract

Energy conservation through voltage reduction methodology is becoming popular now a days. Enabling of conservation of voltage reduction (CVR) through smart grid technologies makes informal and effective way. However, the integration of distributed energy resources (DERs) in active distribution grids are facing some operational issues. Moreover, the enabling of CVR through conventional schemes are restricted with limited voltage reduction and unable to cope up during intermittency. This paper proposes a model predictive driven Volt/VAR Control (VVC) scheme for smart grid enabled CVR operation in presence of solar photovoltaic (PV) power system. The impact of uncertainty in PV power generation and error in load forecasting are incorporated in predictive model. Scenario based Volt/VAR optimization (VVO) approach is utilized to CVR deployment. The VVO objective is to minimize the voltage deviations between load node voltage and expected CVR voltage. The VVO problem is solved through particle swarm optimization. In order to avoid the voltage violation due to cloud transients, PV inverter-based VAR has been dispatched as a local voltage control. The proposed CVR method is validated on modified IEEE 13 node feeder of radial distribution network. The simulation results revels that the remarkable energy demand and peak load power is reduced through proposed CVR scheme with suitable feeder voltage profile. © 2018 IEEE.