Dynamic stochastic optimal power flow control for intelligent coordination of grid-connected energy systems

High penetration of intermittent renewable energy demands major upgrades to the existing power grid transmission infrastructure. Increasing transmission capacities and interconnections creates larger balancing areas. With a larger balancing area, more grid-connected energy systems can be coordinated to achieve one or multiple control objectives (for example, balancing intermittent renewable energy), but how to achieve such an optimal coordination has not yet been fully answered. The existing power system operation method is based on steady-state optimization that may break down when fast variation is present in the system. To provide a coordinating control solution to multiple grid-connected energy systems, an intelligent real-time power flow control method, namely the dynamic stochastic optimal power flow (DSOPF) control, is presented in this paper. The DSOPF control algorithm is based on the Adaptive Critic Designs (ACDs), which provide methods to design optimal neurocontrollers without the need of system analytical models. Studies on a 12-bus and a 70-bus test power system are presented to demonstrate the DSOPF controller.