Impact of unit commitment constraints on generation expansion planning with renewables

Abstract

Growing use of renewables pushes thermal generators against operating constraints - e.g. ramping, minimum output, and operating reserves - that are traditionally ignored in expansion planning models. We show how including such unit-commitment-derived details can significantly change energy production and optimal capacity mix. We introduce a method for efficiently combining unit commitment and generation expansion planning into a single mixed-integer optimization model. Our formulation groups generators into categories allowing integer commitment states from zero to the installed capacity. This formulation scales well, runs much faster (e.g. 5000×) than individual plant binary decisions, and makes the combined model computationally tractable for large systems (hundreds of generators) at hourly time resolutions (8760 hours) using modern solvers on a personal computer. We show that ignoring these constraints during planning can result in a sub-optimal capacity mix with significantly higher operating costs (17%) and carbon emissions (39%) and/or the inability to meet emissions targets.