ABSTRACT Renewable energy (RE) poses a challenge to power balances due to its inherent uncertainty. Locational directrix (LD)‐based demand response (DR) exploits flexibility in different network locations with target load profiles that facilitates RE accommodation. However, relying on optimisation with empirical parameters and forecast results, LDs are generally derived only in the day‐ahead stage for efficiency, struggling to restrain RE uncertainty. To address this, the paper proposes a rolling optimisation and analytical sensitivity‐based framework for intraday and real‐time LD formulation. First, an optimisation model is constructed to decompose the network‐unconstrained target load profile into LDs, and its relationship with system constraints is rigorously analysed through optimality conditions. Second, multiparametric programming is employed to derive analytical sensitivities of LD with respect to any of the system operation parameters, and a piecewise linear approximation method is developed to derive optimal solutions from sensitivities. Third, based on the LD model with its sensitivities, a two‐stage framework is proposed. Intraday rolling optimisation addresses RE randomness, while real‐time sensitivity‐based LD projection enables rapid adjustments responding to RE volatility. Numerical tests validate both the theoretical insights into LD formation and the framework's superior performance in RE accommodation under uncertainty.
Shen et al. (Thu,) studied this question.
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