Definition and Identification of Limit State Function for Low Complexity Modeling of Power System Reliability-Constrained Economic Dispatch

Incorporating reliability constraints in economic dispatch is challenging considering massive system states resulting from random component failures and renewable energy (RE) uncertainties. Traditionally, only N-1 or N-2 failures are considered to reduce complexity, and the consequence is remarkable accuracy losses. This paper aims to achieve low complexity and precise characterization of reliability constraints with fewer system states. First, the initial system state space is constructed, and the limit state function is proposed to define the boundary between reliable and unreliable domains. Then, the limit state function is converted to constraints on a particular set of system states defined as limit system states (LSS). Moreover, by revealing the distribution regulations of system states, the “worst of the best” principle is proposed to identify LSS. In the first step, a chance-constrained optimal power flow model is established to screen the better system states (BSS) considering RE uncertainties. In the second step, the worst ones among the BSS are targeted based on the capacity of failed components and the tolerance to RE uncertainties. Finally, the reliability constraint is converted to the condition that none of the LSS suffers load loss, which is convenient to formulate and incorporate in the dispatch model. Case studies have been conducted to verify the validity of the proposed methods.