Should unit commitment be endogenously included in wind power transmission planning optimisation models?

The historical time series data or Monte Carlo simulation approaches that are often used to represent wind power in transmission planning models will lead to large-scale optimisation problems. The complexity of such problems will be further compounded if advanced techniques for wind variability and wind forecast uncertainty management are also endogenously included, corresponding to a merging of the traditionally separate `real-time operations´ and `long-term planning´ analysis timeframes in power system analysis. A stochastic mixed-integer scheduling model is applied here to investigate the likely transmission planning model formulation impacts of advanced wind forecast techniques, and to determine whether any additional optimal transmission planning model precisions offered justify the associated very-large-scale computational burden. Results indicate that power-flow modelling is only significantly influenced in a small subset of the network branches associated with major interconnections and flexible/inflexible conventional generation locations. Model sensitivity analysis also suggests that even at high wind penetrations, such power-flow modelling differences may be overshadowed by the impact of general uncertainty in fuel price volatility and demand profile that is systemic to long-term planning problems. Such trade-offs have significant practical relevance to the many researchers currently investigating formulations of this class of optimisation problem.