Identification of Representative Operating Hours for High Renewable Grid Planning

The ongoing carbon-free transformation of the electric grid requires the improvement of existing long-term planning tools and methods. Unlike conventional approaches where only seasonal peak load conditions are considered in the planning stage, generation mix information for various levels of loading conditions becomes crucial. At the same time, analyzing the stability of a large grid is computationally challenging for 8760 operating hours a year. This article proposes a three-dimensional clustering approach to identify very few representative hours from the 8760 hours of operation in a year. Proposed algorithm is successful in identifying <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;$</tex> 1 % of the total operating hours as the representative for each year. These operating hours will help speed-up the stability analysis in the long-term planning accounting for the high resolution variations in renewable energy and net-loads.