Power system reliability assessment technique and modeling approach based on quantum computing theory

Abstract

Aiming at the reliability assessment of power system, the state sampling process as a critical step requires to generate power system states one by one using classical computer. Due to the quantum superposition, all system states can be generated at once using the quantum computing and then assess the reliability, and thus it will improve the assessment efficiency. However, how to sample system states and assess reliability using the quantum computing theory will be very important. Therefore, this paper proposes a power system reliability assessment technique and its modeling approach based on the quantum computing theory. Firstly, this paper develops a quantum model of power system reliability (including reliability models of electrical device and system) and proposes a new system state sampling method based on the quantum computing theory, which samples all system states at once and improves the sampling efficiency. Secondly, this paper proposes a quantum computing theory based on reliability assessment technique and its modeling approach for the reliability indices: Loss of Load Probability (LOLP) and Expected Energy Not Supplied (EENS). Thirdly, this paper uses an iterative quantum amplitude estimation (IQAE) algorithm to measure the reliability indices for improving the measurement accuracy. Finally, this paper investigates both designed Case and RBTS, and results shows the correctness and effectiveness of reliability assessment of power system based on the quantum computing.