1 hour / Eastern Time (New York)
Judy Cardell, Picker Engineering Program and Department of Computer Science, Smith College, Smith College
Wind power forecast uncertainty raises concerns of the impact of wind power on power system and electricity market operations. This research project uses an optimal power flow (OPF) model in a Monte Carlo Simulation (MCS) framework to estimate the cost impacts from the uncertainty in wind farm output.
Using various regional load levels and assumptions on the costs for providing balancing energy, the results from the OPF and MCS analysis show that wind power forecast uncertainty, combined with load forecast uncertainty, can increase production cost for the 39-bus test system up to 350 times, though for most cases the forecast uncertainty does not introduce any significant changes from the base cases. The real and reactive power losses are shown to be higher for scenarios with low wind–high load and high wind–low load as compared to the moderate wind–load cases. The results also show minimal voltage violations across the test system.
The webinar takes place October 6 between 2pm and 3pm US Eastern Time.