Multi-area power system reliability evaluation by application of copula theory

Evaluating the risk of capacity deficit in large interconnected power systems is an important task in planning studies in order to supply the demand in the system at a certain risk level. It makes it possible to identify in which parts of the system reinforcements are needed in terms of generating capacity and/or interconnections. In modern power systems, with tie lines interconnecting countries and continents as well as an increasing amount of intermittent renewable resources, areas become dependent on each other for generating capacity not only under rare hazardous operating conditions but also in what can be considered as normal operation. This paper presents a novel way of taking inter-area load correlation into account when calculating the risk of capacity deficit by applying Copula sampling. The Monte Carlo simulation method is applied in addition to a Cross-Entropy based importance sampling technique to reduce computation time. The resulting procedure is a computationally effective general method of evaluating the risk of capacity deficit in a large scale multi-area interconnected power system.