| Title | An AC-QP Optimal Power Flow Algorithm Considering Wind Forecast Uncertainty |
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Jennifer Marley, Maria Vrakopoulou, Ian Hiskens |
| Conference Name | IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia) |
| Date Published | November |
| Abstract | While renewable generation sources provide many economic and environmental benefits for the operation of power systems, their inherent stochastic nature introduces challenges from the perspective of reliability. Existing optimal power flow (OPF) methods must therefore be extended to consider forecast errors to mitigate in an economic manner the uncertainty that renewable generation introduces. This paper presents an AC-QP OPF solution algorithm that has been modified to include wind generation uncertainty. We solve the resulting stochastic optimization problem using a scenario based algorithm that is based on randomized methods that provide probabilistic guarantees of the solution. The proposed method produces an AC-feasible solution while satisfying reasonable reliability criteria. Test cases are included for the IEEE 14-bus network that has been augmented with 2 wind generators. The scalability, optimality and reliability achieved by the proposed method are then assessed. |
| URL | https://cps-vo.org/node/38483 |
| Citation Key | MarleyVrakopoulouHiskens16_ACQPOptimalPowerFlowAlgorithmConsideringWindForecast |
An AC-QP Optimal Power Flow Algorithm Considering Wind Forecast Uncertainty