Stochastic Operation Framework for Distribution Networks Hosting High Wind Penetrations

In this paper, a stochastic framework including two hierarchical stages is presented for the operation of distribution networks with high penetrations of wind power. In the first stage termed Day Ahead Market Stage (DAMS), the power purchases from the day-ahead market and commitment of distributed generations (DGs) are determined. The DAMS model is formulated as a mixed integer linear programming optimization problem. The uncertainty in predictions of wind generation, real time prices, and load profile are included in the optimization problem according to a scenario-based stochastic programming approach. The risk encountered due to the uncertainties is also taken into account. The objective is to minimize the expected operation cost while satisfying the acceptable level of risk. In the second stage named Real Time Market Stage (RTMS), the power purchases from the real time market, dispatch of committed DGs, load curtailment invocations, and hourly reconfigurations are determined. In each hour, the RTMS problem is solved based on the information of that hour and next few hours. To prevent large numbers of switching operations during a day, the switching cost of reconfiguration is considered. The RTMS is modeled as a mixed integer conic programming problem. To analyze the proposed framework, the IEEE 33-bus DN is used as a case study.