Chance Constraint Co-Optimization of Volt/Var and Demand Response in Distribution Networks

Proliferating solar PV generations in distribution networks poses technical challenges to system operators including voltage variations and generation variability and uncertainty. Volt/VAr Optimization (VVO) and Demand Response Program (DRP) are among the most effective techniques to overcome the aforementioned challenges. Although VVO and DRP utilize some common sources and may impact each other, they have been solved separately. Also, in the studies that combine VVO and DRP, loads have been modeled using fixed impedances, which can cause some errors. In this paper, a novel look-ahead co-optimization framework for VVO and DRP is proposed to simultaneously schedule active and reactive resources in distribution grids with high penetration of PV generations and voltage-dependent loads. A chance constraint optimization approach is used to model uncertainties of PV generation for the optimal scheduling of real and reactive power. The proposed framework is verified using the modified IEEE-37 node system with added PV systems, batteries, and flexible loads. The simulation results demonstrate the effectiveness of the proposed framework to achieve peak shaving and loss minimization.