TY - JOUR ID - 46746 TI - A Risk-based Two-stage Stochastic Optimal Power Flow Considering the Impact of Multiple Operational Uncertainties JO - Journal of Energy Management and Technology JA - JEMT LA - en SN - AU - Rabiee, Abbas AU - Mohseni-Bonab, Seyed Masoud AU - Soltani, Tahereh AU - Bayat, Leila AD - Department of Electrical Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran. AD - 2Department of Electrical Engineering, Laval University, 1065 Avenue de la Médecine, Québec, Canada AD - Department of Electrical Engineering, University of Zanjan, Zanjan, Iran Y1 - 2017 PY - 2017 VL - 1 IS - 1 SP - 30 EP - 42 KW - Risk constrained stochastic optimal power flow (RC-SOPF) KW - scenario-based modeling KW - Risk Management KW - conditional value at risk (CVAR) DO - 10.22109/jemt.2017.46746 N2 - his 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. UR - https://www.jemat.org/article_46746.html L1 - https://www.jemat.org/article_46746_e278abf7cb9e9bfcb0b3aee5f9155e04.pdf ER -