  This paper presents a novel scheme termed Optimization-based Ramping Reserve
Allocation (ORRA) for addressing an ongoing challenge in Automatic Generation
Control (AGC) enhancement, i.e., the optimal coordination of multiple Battery
Energy Storage Systems (BESSs). While exploiting further the synergy between
BESSs and slow ramping resources, the proposed scheme offers an insight into
the energy-neutral operation, which is achieved by smoothly discontinuing the
BESS participation along with the minimization of Area Injection Error (AIE), a
variant of traditional Area Control Error (ACE). The first stage of ORRA is to
incorporate Neural Networks (NNs) with the AIE in order to ensure a zero-mean
of ramping reserves to be allocated among BESSs. These AIE signals are then
used to formulate the optimal coordination of BESS as an online optimization
problem, which is therefore feedback-driven. Finally, a distributed
optimization algorithm is developed to solve the formulated problem in
real-time, achieving a sublinear dynamic regret that quantifies the cost
difference to the trajectory computed by a centralized optimizer with perfect
global information. Consistent with the geographical distribution of BESSs, the
proposed ORRA is fully distributed such that the algorithm can be executed in
parallel at all nodes. Simulations on a modified IEEE 14-bus system are
performed to illustrate the effectiveness and important features of ORRA.
