  This paper presents an optimal control strategy for operating a solar hybrid
system consisting of solar photovoltaic (PV) and a high-power, low-storage
battery energy storage system (BESS). A state-space model of the hybrid PV
plant is first derived, based on which an adaptive model predictive controller
is designed. The controller's objective is to control the PV and BESS to follow
power setpoints sent to the the hybrid system while maintaining desired power
reserves and meeting system operational constraints. Furthermore, an extended
Kalman filter (EKF) is implemented for estimating the battery SOC, and an error
sensitivity is executed to assess its limitations. To validate the proposed
strategy, detailed EMT models of the hybrid system are developed so that losses
and control limits can be quantified accurately. Day-long simulations are
performed in an OPAL-RT real-time simulator using second-by-second actual PV
farm data as inputs. Results verify that the proposed method can follow power
setpoints while maintaining power reserves in days of high irradiance
intermittency even with a small BESS storage.
