  In this paper, a neural-network (NN)-based online optimal control method
(NN-OPT) is proposed for ultra-capacitors (UCs) energy storage system (ESS) in
hybrid AC/DC microgrids involving multiple distributed generations (e.g.,
Photovoltaic (PV) system, battery storage, diesel generator). Conventional
control strategies usually produce large disturbances to buses during charging
and discharging (C&D) processes of UCs, which significantly degrades the power
quality and system performance, especially under fast C&D modes. Therefore, the
optimal control theory is adopted to optimize the C&D profile as well as to
suppress the disturbances caused by UCs implementation. Specifically, an
NN-based intelligent algorithm is developed to learn the optimal control policy
for bidirectional-converter-interfaced UCs. The inaccuracies of system modeling
are also considered in the control design. Since the designed NN-OPT method is
decentralized that only requires the local measurements, plug & play of UCs can
be easily realized with minimal communication efforts. In addition, the PV
system is under the maximum power point tracking (MPPT) control to extract the
maximum benefit. Both islanded and grid-tied modes are considered during the
controller design. Extensive case studies have been conducted to evaluate the
effectiveness of the proposed method.
