Chance-constrained real-time volt/var optimization using simulated annealing

Solar is the fastest growing source of renewable electricity in the U.S. The anticipated PV proliferation brings integration challenges on system volt/var performance at the utility scale. One of the greatest challenges is to maintain desirable feeder voltages in utility distribution networks. The intermittent PV generation causes more frequent operation of volt/var control (VVC) devices to alleviate voltage issues. This paper proposes a real-time volt/var optimization (VVO) strategy to control voltage regulators, switched capacitors, and PV inverters for minimizing the active power loss. Chance constrained programming is used to model solar uncertainty. Simulated annealing technique is applied to solve the developed optimization problem. The proposed VVO strategy is tested in the modified IEEE 37-bus system. Simulation results demonstrate that the coordination of VVC devices and reactive power support of PV inverters can help handle solar variability and uncertainty in real-time volt/var operation.