Three-parameter interval number theory and its application in power system reliability evaluation

Abstract

With the increasing integration of renewable energy in the power system, its strong volatility and randomness will greatly affect the planning and operation of the power system. In this situation, compared to the traditional point-value-based reliability assessment results, system operators prefer the results which can give the most likely recommended values and their possible ranges. To this end, in this paper, we present a novel framework to evaluate the reliability of multi-state power systems that incorporates three-parameter interval number theory and improved universal generating function method. In particular, we first improve the three-parameter interval number theory by proposing a similarity-based indicator to describe the distance (or closeness-degree) between two three-parameter interval numbers and redefine the probability that one three-parameter interval number is greater or less than another one. Secondly, we extended the traditional universal generating function to a three-parameter interval number-based universal generating function. Moreover, the three-parameter interval number-based universal generating functions of conventional generators, renewable energy generators and load demand are further established to describe their multi-state characteristics. At last, a three-parameter interval number-based loss of load expectation metric is presented for reliability evaluation. Compared with the existing methods, the proposed framework can well evaluate the reliability of multi-state power systems, and can describe the uncertainty of reliability evaluation results through the three-parameter interval number, thus providing the most likely value of the evaluation result and its fluctuation range at the same time. In the numerical simulation part, a comparison of five different scenarios is performed on an IEEE Reliability Test System. The results show that the proposed method is suitable for the reliability assessment of power systems with high penetration of renewable energy, which can describe the fluctuation range and indicate the most possible value of reliability simultaneously.