Abstract
Generation scheduling decision-making of power systems with renewable energy and energy storage (ES) is a multistage stochastic programming problem in nature, in which unit commitment (UC) decisions have to be made one day ahead before uncertainties are revealed, and hourly economic dispatch (ED) decisions are successively determined when real uncertainty realizations are observed gradually (i.e., nonanticipativity). To this end, inappropriate ED decisions at current hour may cause infeasibility of future ED decisions (i.e., robustness). Thus, how to properly schedule thermal unit outputs and ES charging/ discharging power against uncertainties becomes an important and urgent issue. In this paper, two mixed-integer linear programming (MILP) methods are proposed to solve the scheduling problem of thermal units and ESs with uncertainties while ensuring solution robustness and nonanticipativity: explicit and implicit decision methods. Specifically, explicit decision method directly assumes affine policies between decision variables and uncertainty realizations; implicit decision method explores safe ranges of thermal unit outputs and ES state-of-charge (SOC) levels to guarantees feasibility of future ED solutions. Both methods can guarantee the nonanticipativity and robustness of multistage solutions. Numerical tests illustrate effectiveness of the proposed methods.
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