  Real-time optimal power flow (RT-OPF) under wind energy penetration is highly
desired but extremely difficult to realize. This is basically due to the
conflict between the fast changes in wind power generation and the slow
response from the optimization computation. This paper (Part I) presents a
prediction-updating approach to address this challenge. We consider essential
scenarios around forecasted data of wind power that would probably happen
during the computation time required for solving a large-scale complex optimal
power flow problem. Parallel computing is used to solve the individual OPF
problems corresponding to these scenarios. This provides for the forecasted
time horizon probable reference operations in the form of a lookup-table. One
of these operations will be selected based on the actual wind power and
realized to the grid for the current time interval, thus leading to a RT-OPF
framework. The proposed approach is implemented in Part II of this paper using
a 41-bus medium-voltage distribution network as a case study.
