Temporal Decomposition-Based Stochastic Economic Dispatch for Smart Grid Energy Management

This paper presents a temporal decomposition strategy to decompose security-constrained economic dispatch (SCED) over the scheduling horizon with the goal of reducing its computational burden and enhancing its scalability. A set of subproblems, each with respect to demand response, normal constraints, and $N-1$ contingency corrective actions at a subhorizon, is formulated. The proposed decomposition deals with computational complexities originated from intertemporal interdependencies of system equipment, i.e., generators’ ramp constraints and state of charge of storage devices. The concept of overlapping intervals is introduced to make SCED subproblems solvable in parallel. Intertemporal connectivity related to energy storage is also modeled in the context of temporal decomposition. Besides, reserve up and down requirements are formulated as data-driven nonparametric chance constraints to account for wind generation uncertainties. The concept of $\phi -$ divergence is used to convert nonparametric chance constraints to more conservative parametric constraints. A reduced risk level is calculated with respect to wind generation prediction errors to ensure the satisfaction of system constraints with a confidence level after the true realization of uncertainty. Auxiliary problem principle is applied to coordinate SCED subproblems in parallel. Numerical results on three test systems show the effectiveness of the proposed algorithm.