Second-order cone robust AC–DC DOPF considering correlation of wind power

Abstract

Due to the increasing penetration, intermittent renewable energy sources (RESs), such as wind power, have added additional uncertainties to AC–DC power system operation. The strong correlation between wind power will bring larger computational errors. It makes generation dispatching incompatible with the current single-period optimal power flow practice. This study presents an AC–DC affinely adjustable robust dynamic optimal power flow (AARDOPF) model. Ellipsoidal uncertainty set is adopted to well fit the spatial-temporal correlated wind power. Affine policies are utilised in the re-dispatch process. To apply AC–DC AARDOPF, the base-point generation is calculated and determined to match the power with forecasted RES output. And once the uncertainty is revealed, generators reschedule its output through participation factors responding to the uncertain fluctuation of RES output to ensure a feasible solution for all realisations of RES output. Then original non-linear models are transformed into SOCP models. Finally, GUROBI is used to solve this model. Numerical results are obtained on modified AC–DC IEEE 30-bus and 118-bus system to minimise the expected operational cost. Comparing with stochastic dynamic optimal power flow (DOPF), this model is proved to be more practical and effective.

Keywords

• power generation dispatch
• stochastic processes
• load flow
• wind power plants
• ac-dc power convertors
• ac–dc power system operation
• ellipsoidal uncertainty set
• forecasted res output
• second order cone robust ac–dc dopf
• generation dispatching
• ac–dc dynamic optimal power flow model
• aardopf
• socp models
• gurobi
• ieee 30-bus system
• ieee 118-bus system
• intermittent renewable energy sources
• wind power correlation