An improved algorithm for single-unit commitment with ramping limits

•Two new dynamic programming algorithms for the single unit commitment problem.•Algorithm for convex generation cost that grows linear in practice.•Algorithm for convex piece-wise linear generation cost that is in O(n).•Both algorithms outperform the state-of-the-art on a large variety of instances....

Full description

Saved in:
Bibliographic Details
Published in:Electric power systems research Vol. 190; p. 106720
Main Authors: Wuijts, Rogier Hans, van den Akker, Marjan, van den Broek, Machteld
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.01.2021
Elsevier Science Ltd
Subjects:
Algorithms
Downtime
Dynamic programming
Electricity generation
Electricity pricing
Generators
Polynomial-time algorithm
Schedules
Single-unit commitment problem
Unit commitment
Single-unit commitment problem
Polynomial-time algorithm
Dynamic programming
ISSN:0378-7796, 1873-2046
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Two new dynamic programming algorithms for the single unit commitment problem.•Algorithm for convex generation cost that grows linear in practice.•Algorithm for convex piece-wise linear generation cost that is in O(n).•Both algorithms outperform the state-of-the-art on a large variety of instances. The single-unit commitment problem (1UC) is the problem of finding a cost optimal schedule for a single generator given a time series of electricity prices subject to generation limits, minimum up- and downtime and ramping limits. In this paper we present two efficient dynamic programming algorithms. For each time step we keep track of a set of functions that represent the cost of optimal schedules until that time step. We show that we can combine a subset of these functions by only considering their minimum. We can construct this minimum either implicitly or explicitly. Experiments show both methods scale linear in the amount of time steps and result in a significant speedup compared to the state-of-the-art for piece-wise linear as well as quadratic generation cost. Therefore using these methods could lead to significant improvements for solving large scale unit commitment problems with Lagrangian relaxation or related methods that use 1UC as subproblem.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2020.106720