Simplified Sequential Simulation of Bulk Power System Reliability Via Chronological Probability Model of Load Supplying Capability

This paper proposes a simplified sequential Monte Carlo simulation to enhance the efficiency of bulk power system reliability evaluation. The basic idea is to construct chronological system state sequence by using the chronological probability model of load supplying capability which reflects the joint chronological variation pattern of system state intrinsic properties including load supplying capability (C), system state average duration ( D), and splitting percentage (P). The chronological probability model can simplify sequential simulation procedure no matter how system load pattern changes, and avoid the time-consuming optimal load curtailment model calculations by using the above-mentioned system state intrinsic properties. Thus, the proposed method can considerably accelerate simulation, especially when evaluating system reliability for different system load conditions. Besides, as the proposed method retains the chronological property of system state transition, it can not only obtain the probability distribution of reliability indices but also incorporate time-dependent renewable generations. RBTS, RTS79, and modified RTS79 with wind farm are utilized to verify the effectiveness of the proposed method.