LAUSR

Abstract Transmission expansion solutions can be affected greatly by renewable energy resources scale-up efforts that aim at tapping a large amount of renewable generation from dispersed locations. In this paper, we study how renewable generation, wind and solar in particular, can impact the transmission expansion planning (TEP). We study the effects of correlations between variable resources, installed capacities, fluctuations, and changing the harvesting locations on transmission expansion solutions. To capture these effects accurately, especially the correlations effects, we consider hourly resolution for renewable generation and system demand when computing the operation costs. Since using hourly resolution substantially increases the computational time of the TEP solution algorithm, we use multivariate interpolation to accelerate the computations. We use the Binary Particle Swarm Optimization to solve the TEP problem. We also compare the expansion plans obtained by using the multivariate interpolation method, clustered data, and using DC versus AC optimal power flow models. We run all studies on the IEEE 24-bus test system for a planning horizon of 10 years.