Heterogeneous Unit Clustering for Efficient Operational Flexibility Modeling for Strategic Models
Name
esd-wp-2013-04.pdf
Size
1.31 MB
Format
Adobe PDF
Checksum (MD5)
1154a359e190c787716bdc599af6e44d
Author(s)
Palmintier, Bryan S.
Webster, Mort D.
Date Issued
January 2013
Publisher
Massachusetts Institute of Technology. Engineering Systems Division
Series/Report no.
ESD Working Papers;ESD-WP-2013-04
Abstract
The increasing penetration of wind generation has led to significant improvements in unit commitment models. However, long-term capacity planning methods have not been similarly modified to address the challenges of a system with a large fraction of generation from variable sources. Designing future capacity mixes with adequate flexibility requires an embedded approximation of the unit commitment problem to capture operating constraints. Here we propose a method, based on clustering units, for a simplified unit commitment model with dramatic improvements in solution time that enable its use as a submodel within a capacity expansion framework. Heterogeneous clustering speeds computation by aggregating similar but non-identical units thereby replacing large numbers of binary commitment variables with fewer integers that still capture individual unit decisions and constraints. We demonstrate the trade-off between accuracy and run-time for different levels of aggregation. A numeric example using an ERCOT-based 205-unit system illustrates that careful aggregation introduces errors of 0.05-0.9% across several metrics while providing several orders of magnitude faster solution times (400x) compared to traditional binary formulations and further aggregation increases errors slightly (~2x) with further speedup (2000x). We also compare other simplifications that can provide an additional order of magnitude speed-up for some problems.
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