A Riskbased Two-stage Stochastic Optimal Power Flow Considering the Impact of Multiple Operational Uncertainties

This paper shows an application of a scenario-based method for risk constrained stochastic optimal power flow (RC-SOPF) problem in electricity utilities. A two-stage stochastic programming framework is developed for dealing with various uncertainties. Customers’ demand, wind power generation, and electricity price are considered as the uncertain parameters in the proposed RC-SOPF problem. The aim is to minimize the energy procurement costs, while preserving an acceptable risk level. The energy procurement cost consists of generators active power generation costs, cost of energy procurement from external network (e.g. pool market or upstream network) and operation maintenance cost of wind farms. To control the negative impacts of the uncertainties, variance and conditional value at risk (CVAR) are used as risk measures. The proposed model is implemented on the 39-bus New England test system. The obtained results show that CVAR is suitable index for management of the risk associated with uncertain parameters in comparison with variance.