Flexible transmission expansion planning associated with large-scale wind farms integration considering demand response

With increasing large-scale wind farms being integrated into the power grids, transmission expansion planning (TEP) increasingly requires more flexibility to account for the intermittency as well as other uncertainty factors involved in the process. In this study, a probabilistic TEP model is proposed for planners to tackle the variability and uncertainty factors associated with grid connected wind farms. Both load forecast and wind power output uncertainties are considered in the proposed model. Other factors considered in the model include the forced outage rates of transmission lines and generators, and the wind speed correlation between wind farms. Moreover, the incentive-based demand response (IBDR) program is introduced as a non-network solution instead of the conventional network expansion approaches. The utilities will pay IBDR providers for their contributions to peak demand reduction. The proposed TEP model can find the optimal trade-off between transmission investment and demand response expenses. The hierarchical Bender's decomposition algorithm integrated with Monte Carlo simulation is employed to solve the proposed model. Case studies are given using the Garver's six-bus system and the IEEE-reliability test system to show the effectiveness of the method.