Unit Commitment with Continuous-Time Generation and Ramping Trajectory Models

Masood Parvania, Anna Scaglione

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


There is increasing evidence of shortage of ramping resources in the real-time operation of power systems. To explain and remedy this problem systematically, in this paper we take a novel look at the way the day-ahead unit commitment (UC) problem represents the information about load, generation and ramping constraints. We specifically investigate the approximation error made in mapping of the original problem, that would decide the continuous-time generation and ramping trajectories of the committed generating units, onto the discrete-time problem that is solved in practice. We first show that current practice amounts to approximating the trajectories with linear splines. We then offer a different representation through cubic splines that provides physically feasible schedules and increases the accuracy of the continuous-time generation and ramping trajectories by capturing sub-hourly variations and ramping of load in the day-ahead power system operation. The corresponding day-ahead UC model is formulated as an instance of mixed-integer linear programming (MILP), with the same number of binary variables as the traditional UC formulation. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day-ahead and real-time operation cost, and the number of events of ramping scarcity in the real-time operations.

Original languageEnglish (US)
Article number7307230
Pages (from-to)3169-3178
Number of pages10
JournalIEEE Transactions on Power Systems
Issue number4
StatePublished - Jul 2016


  • Continuous-time function space
  • generation trajectory
  • mixed-integer linear programming
  • ramping trajectory
  • unit commitment

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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