### Abstract

In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: The binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients, thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total dayahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations.

Original language | English (US) |
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Title of host publication | Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 |

Publisher | IEEE Computer Society |

Pages | 2335-2344 |

Number of pages | 10 |

Volume | 2016-March |

ISBN (Electronic) | 9780769556703 |

DOIs | |

State | Published - Mar 7 2016 |

Event | 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 - Koloa, United States Duration: Jan 5 2016 → Jan 8 2016 |

### Other

Other | 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 |
---|---|

Country | United States |

City | Koloa |

Period | 1/5/16 → 1/8/16 |

### Fingerprint

### Keywords

- Continuous-time function space
- Generation trajectory
- Mixed-integer linear programming
- Ramping cost
- Ramping trajectory
- Unit commitment

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016*(Vol. 2016-March, pp. 2335-2344). [7427475] IEEE Computer Society. https://doi.org/10.1109/HICSS.2016.292

**Generation ramping valuation in day-ahead electricity markets.** / Parvania, Masood; Scaglione, Anna.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016.*vol. 2016-March, 7427475, IEEE Computer Society, pp. 2335-2344, 49th Annual Hawaii International Conference on System Sciences, HICSS 2016, Koloa, United States, 1/5/16. https://doi.org/10.1109/HICSS.2016.292

}

TY - GEN

T1 - Generation ramping valuation in day-ahead electricity markets

AU - Parvania, Masood

AU - Scaglione, Anna

PY - 2016/3/7

Y1 - 2016/3/7

N2 - In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: The binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients, thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total dayahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations.

AB - In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: The binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients, thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total dayahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations.

KW - Continuous-time function space

KW - Generation trajectory

KW - Mixed-integer linear programming

KW - Ramping cost

KW - Ramping trajectory

KW - Unit commitment

UR - http://www.scopus.com/inward/record.url?scp=84975506602&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84975506602&partnerID=8YFLogxK

U2 - 10.1109/HICSS.2016.292

DO - 10.1109/HICSS.2016.292

M3 - Conference contribution

AN - SCOPUS:84975506602

VL - 2016-March

SP - 2335

EP - 2344

BT - Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016

PB - IEEE Computer Society

ER -