  In this paper (Part II) we implement the prediction-updating approach
developed in Part I to address fast changes in wind power generation when
solving a complex real-time optimal power flow (RT-OPF) problem. The approach
considers essential scenarios around forecasted wind power values in a moving
prediction horizon (120 seconds). The individual optimal power flow problems
corresponding to these scenarios are solved in parallel using a multi-processor
server. Then the operation strategy is updated in a short sampling time (every
20 seconds) considering real wind power values. The RT-OPF problem is
formulated considering both technical and economic aspects simultaneously. The
RT-OPF is implemented on a 41-bus medium-voltage distribution network with two
wind stations. The results show the benefits of the proposed approach and
highlight further challenges of RT-OPF.
