Information Gap Decision Theory Based Congestion and Voltage Management in the Presence of Uncertain Wind Power

The supply of electrical energy is being increasinglysourced from renewable generation. The variability anduncertainty of renewable generation, compared to a dispatchableplant, is a significant dissimilarity of concern to the traditionallyreliable and robust power system. This change is driving thepower system towards a more flexible entity that carries greateramounts of reserve. For congestion management purposes itis of benefit to know the probable and possible renewablegeneration dispatch, but to what extent will these variations effectthe management of congestion on the system? Reactive powergeneration from wind generators and demand response flexibilityare the decision variables here in a risk averse multi-periodAC optimal power flow (OPF) seeking to manage congestionon distribution systems. Information Gap Decision Theory isused to address the variability and uncertainty of renewablegeneration. In addition, this work considers the natural benefitsto the congestion on a system from the over estimation of windforecast; providing an opportunistic schedule for both demandresponse nodes and reactive power provision from distributedgeneration.